explorers: incomes-across-distribution-comparison

This data as json

slug	isPublished	config	createdAt	updatedAt
incomes-across-distribution-comparison	1	{ "blocks": [ { "args": [], "type": "graphers", "block": [ { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income per day (after tax)", "ySlugs": "mean_day p0p100_avg_posttax_nat_day mean_dhi_pc_day", "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Mean income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income per month (after tax)", "ySlugs": "mean_month p0p100_avg_posttax_nat_month mean_dhi_pc_month", "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Mean income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income per year (after tax)", "ySlugs": "mean_year p0p100_avg_posttax_nat_year mean_dhi_pc_year", "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "defaultView": "true", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Mean income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income per day (before tax)", "ySlugs": "p0p100_avg_pretax_day mean_mi_pc_day", "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Mean income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income per month (before tax)", "ySlugs": "p0p100_avg_pretax_month mean_mi_pc_month", "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Mean income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income per year (before tax)", "ySlugs": "p0p100_avg_pretax_year mean_mi_pc_year", "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Mean income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Median income per day (after tax)", "ySlugs": "median_day median_posttax_nat_day median_dhi_pc_day", "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Median income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Median income per month (after tax)", "ySlugs": "median_month median_posttax_nat_month median_dhi_pc_month", "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Median income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Median income per year (after tax)", "ySlugs": "median_year median_posttax_nat_year median_dhi_pc_year", "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Median income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Median income per day (before tax)", "ySlugs": "median_pretax_day median_mi_pc_day", "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Median income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Median income per month (before tax)", "ySlugs": "median_pretax_month median_mi_pc_month", "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Median income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Median income per year (before tax)", "ySlugs": "median_pretax_year median_mi_pc_year", "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Indicator Dropdown": "Median income or consumption", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the poorest decile (after tax)", "ySlugs": "decile1_avg_day p0p10_avg_posttax_nat_day avg_p10_dhi_pc_day", "subtitle": "The mean income per day within the poorest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the poorest decile (after tax)", "ySlugs": "decile1_avg_month p0p10_avg_posttax_nat_month avg_p10_dhi_pc_month", "subtitle": "The mean income per month within the poorest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the poorest decile (after tax)", "ySlugs": "decile1_avg_year p0p10_avg_posttax_nat_year avg_p10_dhi_pc_year", "subtitle": "The mean income per year within the poorest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the poorest decile (before tax)", "ySlugs": "p0p10_avg_pretax_day avg_p10_mi_pc_day", "subtitle": "The mean income per day within the poorest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the poorest decile (before tax)", "ySlugs": "p0p10_avg_pretax_month avg_p10_mi_pc_month", "subtitle": "The mean income per month within the poorest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the poorest decile (before tax)", "ySlugs": "p0p10_avg_pretax_year avg_p10_mi_pc_year", "subtitle": "The mean income per year within the poorest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the poorest decile (after tax)", "ySlugs": "decile1_thr_day p10p20_thr_posttax_nat_day thr_p10_dhi_pc_day", "subtitle": "The level of income per day below which 10% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the poorest decile (after tax)", "ySlugs": "decile1_thr_month p10p20_thr_posttax_nat_month thr_p10_dhi_pc_month", "subtitle": "The level of income per month below which 10% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the poorest decile (after tax)", "ySlugs": "decile1_thr_year p10p20_thr_posttax_nat_year thr_p10_dhi_pc_year", "subtitle": "The level of income per year below which 10% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the poorest decile (before tax)", "ySlugs": "p10p20_thr_pretax_day thr_p10_mi_pc_day", "subtitle": "The level of income per day below which 10% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the poorest decile (before tax)", "ySlugs": "p10p20_thr_pretax_month thr_p10_mi_pc_month", "subtitle": "The level of income per month below which 10% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the poorest decile (before tax)", "ySlugs": "p10p20_thr_pretax_year thr_p10_mi_pc_year", "subtitle": "The level of income per year below which 10% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the poorest decile (after tax)", "ySlugs": "decile1_share p0p10_share_posttax_nat share_p10_dhi_pc", "subtitle": "The share of income received by the poorest decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the poorest decile (before tax)", "ySlugs": "p0p10_share_pretax share_p10_mi_pc", "subtitle": "The share of income received by the poorest decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "1 (poorest)", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 2nd decile (after tax)", "ySlugs": "decile2_avg_day p10p20_avg_posttax_nat_day avg_p20_dhi_pc_day", "subtitle": "The mean income per day within the 2nd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 2nd decile (after tax)", "ySlugs": "decile2_avg_month p10p20_avg_posttax_nat_month avg_p20_dhi_pc_month", "subtitle": "The mean income per month within the 2nd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 2nd decile (after tax)", "ySlugs": "decile2_avg_year p10p20_avg_posttax_nat_year avg_p20_dhi_pc_year", "subtitle": "The mean income per year within the 2nd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 2nd decile (before tax)", "ySlugs": "p10p20_avg_pretax_day avg_p20_mi_pc_day", "subtitle": "The mean income per day within the 2nd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 2nd decile (before tax)", "ySlugs": "p10p20_avg_pretax_month avg_p20_mi_pc_month", "subtitle": "The mean income per month within the 2nd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 2nd decile (before tax)", "ySlugs": "p10p20_avg_pretax_year avg_p20_mi_pc_year", "subtitle": "The mean income per year within the 2nd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 2nd decile (after tax)", "ySlugs": "decile2_thr_day p20p30_thr_posttax_nat_day thr_p20_dhi_pc_day", "subtitle": "The level of income per day below which 20% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 2nd decile (after tax)", "ySlugs": "decile2_thr_month p20p30_thr_posttax_nat_month thr_p20_dhi_pc_month", "subtitle": "The level of income per month below which 20% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 2nd decile (after tax)", "ySlugs": "decile2_thr_year p20p30_thr_posttax_nat_year thr_p20_dhi_pc_year", "subtitle": "The level of income per year below which 20% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 2nd decile (before tax)", "ySlugs": "p20p30_thr_pretax_day thr_p20_mi_pc_day", "subtitle": "The level of income per day below which 20% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 2nd decile (before tax)", "ySlugs": "p20p30_thr_pretax_month thr_p20_mi_pc_month", "subtitle": "The level of income per month below which 20% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 2nd decile (before tax)", "ySlugs": "p20p30_thr_pretax_year thr_p20_mi_pc_year", "subtitle": "The level of income per year below which 20% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the 2nd decile (after tax)", "ySlugs": "decile2_share p10p20_share_posttax_nat share_p20_dhi_pc", "subtitle": "The share of income received by the 2nd decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the 2nd decile (before tax)", "ySlugs": "p10p20_share_pretax share_p20_mi_pc", "subtitle": "The share of income received by the 2nd decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "2", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 3rd decile (after tax)", "ySlugs": "decile3_avg_day p20p30_avg_posttax_nat_day avg_p30_dhi_pc_day", "subtitle": "The mean income per day within the 3rd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 3rd decile (after tax)", "ySlugs": "decile3_avg_month p20p30_avg_posttax_nat_month avg_p30_dhi_pc_month", "subtitle": "The mean income per month within the 3rd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 3rd decile (after tax)", "ySlugs": "decile3_avg_year p20p30_avg_posttax_nat_year avg_p30_dhi_pc_year", "subtitle": "The mean income per year within the 3rd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 3rd decile (before tax)", "ySlugs": "p20p30_avg_pretax_day avg_p30_mi_pc_day", "subtitle": "The mean income per day within the 3rd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 3rd decile (before tax)", "ySlugs": "p20p30_avg_pretax_month avg_p30_mi_pc_month", "subtitle": "The mean income per month within the 3rd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 3rd decile (before tax)", "ySlugs": "p20p30_avg_pretax_year avg_p30_mi_pc_year", "subtitle": "The mean income per year within the 3rd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 3rd decile (after tax)", "ySlugs": "decile3_thr_day p30p40_thr_posttax_nat_day thr_p30_dhi_pc_day", "subtitle": "The level of income per day below which 30% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 3rd decile (after tax)", "ySlugs": "decile3_thr_month p30p40_thr_posttax_nat_month thr_p30_dhi_pc_month", "subtitle": "The level of income per month below which 30% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 3rd decile (after tax)", "ySlugs": "decile3_thr_year p30p40_thr_posttax_nat_year thr_p30_dhi_pc_year", "subtitle": "The level of income per year below which 30% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 3rd decile (before tax)", "ySlugs": "p30p40_thr_pretax_day thr_p30_mi_pc_day", "subtitle": "The level of income per day below which 30% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 3rd decile (before tax)", "ySlugs": "p30p40_thr_pretax_month thr_p30_mi_pc_month", "subtitle": "The level of income per month below which 30% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 3rd decile (before tax)", "ySlugs": "p30p40_thr_pretax_year thr_p30_mi_pc_year", "subtitle": "The level of income per year below which 30% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the 3rd decile (after tax)", "ySlugs": "decile3_share p20p30_share_posttax_nat share_p30_dhi_pc", "subtitle": "The share of income received by the 3rd decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the 3rd decile (before tax)", "ySlugs": "p20p30_share_pretax share_p30_mi_pc", "subtitle": "The share of income received by the 3rd decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "3", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 4th decile (after tax)", "ySlugs": "decile4_avg_day p30p40_avg_posttax_nat_day avg_p40_dhi_pc_day", "subtitle": "The mean income per day within the 4th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 4th decile (after tax)", "ySlugs": "decile4_avg_month p30p40_avg_posttax_nat_month avg_p40_dhi_pc_month", "subtitle": "The mean income per month within the 4th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 4th decile (after tax)", "ySlugs": "decile4_avg_year p30p40_avg_posttax_nat_year avg_p40_dhi_pc_year", "subtitle": "The mean income per year within the 4th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 4th decile (before tax)", "ySlugs": "p30p40_avg_pretax_day avg_p40_mi_pc_day", "subtitle": "The mean income per day within the 4th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 4th decile (before tax)", "ySlugs": "p30p40_avg_pretax_month avg_p40_mi_pc_month", "subtitle": "The mean income per month within the 4th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 4th decile (before tax)", "ySlugs": "p30p40_avg_pretax_year avg_p40_mi_pc_year", "subtitle": "The mean income per year within the 4th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 4th decile (after tax)", "ySlugs": "decile4_thr_day p40p50_thr_posttax_nat_day thr_p40_dhi_pc_day", "subtitle": "The level of income per day below which 40% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 4th decile (after tax)", "ySlugs": "decile4_thr_month p40p50_thr_posttax_nat_month thr_p40_dhi_pc_month", "subtitle": "The level of income per month below which 40% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 4th decile (after tax)", "ySlugs": "decile4_thr_year p40p50_thr_posttax_nat_year thr_p40_dhi_pc_year", "subtitle": "The level of income per year below which 40% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 4th decile (before tax)", "ySlugs": "p40p50_thr_pretax_day thr_p40_mi_pc_day", "subtitle": "The level of income per day below which 40% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 4th decile (before tax)", "ySlugs": "p40p50_thr_pretax_month thr_p40_mi_pc_month", "subtitle": "The level of income per month below which 40% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 4th decile (before tax)", "ySlugs": "p40p50_thr_pretax_year thr_p40_mi_pc_year", "subtitle": "The level of income per year below which 40% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the 4th decile (after tax)", "ySlugs": "decile4_share p30p40_share_posttax_nat share_p40_dhi_pc", "subtitle": "The share of income received by the 4th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the 4th decile (before tax)", "ySlugs": "p30p40_share_pretax share_p40_mi_pc", "subtitle": "The share of income received by the 4th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "4", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 5th decile (after tax)", "ySlugs": "decile5_avg_day p40p50_avg_posttax_nat_day avg_p50_dhi_pc_day", "subtitle": "The mean income per day within the 5th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 5th decile (after tax)", "ySlugs": "decile5_avg_month p40p50_avg_posttax_nat_month avg_p50_dhi_pc_month", "subtitle": "The mean income per month within the 5th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 5th decile (after tax)", "ySlugs": "decile5_avg_year p40p50_avg_posttax_nat_year avg_p50_dhi_pc_year", "subtitle": "The mean income per year within the 5th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 5th decile (before tax)", "ySlugs": "p40p50_avg_pretax_day avg_p50_mi_pc_day", "subtitle": "The mean income per day within the 5th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 5th decile (before tax)", "ySlugs": "p40p50_avg_pretax_month avg_p50_mi_pc_month", "subtitle": "The mean income per month within the 5th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 5th decile (before tax)", "ySlugs": "p40p50_avg_pretax_year avg_p50_mi_pc_year", "subtitle": "The mean income per year within the 5th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the 5th decile (after tax)", "ySlugs": "decile5_share p40p50_share_posttax_nat share_p50_dhi_pc", "subtitle": "The share of income received by the 5th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "5", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the 5th decile (before tax)", "ySlugs": "p40p50_share_pretax share_p50_mi_pc", "subtitle": "The share of income received by the 5th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "5", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 5th decile (median) (after tax)", "ySlugs": "decile5_thr_day p50p60_thr_posttax_nat_day thr_p50_dhi_pc_day", "subtitle": "The level of income per day below which 50% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5 (median)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 5th decile (median) (after tax)", "ySlugs": "decile5_thr_month p50p60_thr_posttax_nat_month thr_p50_dhi_pc_month", "subtitle": "The level of income per month below which 50% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5 (median)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 5th decile (median) (after tax)", "ySlugs": "decile5_thr_year p50p60_thr_posttax_nat_year thr_p50_dhi_pc_year", "subtitle": "The level of income per year below which 50% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5 (median)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 5th decile (median) (before tax)", "ySlugs": "p50p60_thr_pretax_day thr_p50_mi_pc_day", "subtitle": "The level of income per day below which 50% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5 (median)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 5th decile (median) (before tax)", "ySlugs": "p50p60_thr_pretax_month thr_p50_mi_pc_month", "subtitle": "The level of income per month below which 50% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5 (median)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 5th decile (median) (before tax)", "ySlugs": "p50p60_thr_pretax_year thr_p50_mi_pc_year", "subtitle": "The level of income per year below which 50% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "5 (median)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 6th decile (after tax)", "ySlugs": "decile6_avg_day p50p60_avg_posttax_nat_day avg_p60_dhi_pc_day", "subtitle": "The mean income per day within the 6th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 6th decile (after tax)", "ySlugs": "decile6_avg_month p50p60_avg_posttax_nat_month avg_p60_dhi_pc_month", "subtitle": "The mean income per month within the 6th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 6th decile (after tax)", "ySlugs": "decile6_avg_year p50p60_avg_posttax_nat_year avg_p60_dhi_pc_year", "subtitle": "The mean income per year within the 6th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 6th decile (before tax)", "ySlugs": "p50p60_avg_pretax_day avg_p60_mi_pc_day", "subtitle": "The mean income per day within the 6th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 6th decile (before tax)", "ySlugs": "p50p60_avg_pretax_month avg_p60_mi_pc_month", "subtitle": "The mean income per month within the 6th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 6th decile (before tax)", "ySlugs": "p50p60_avg_pretax_year avg_p60_mi_pc_year", "subtitle": "The mean income per year within the 6th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 6th decile (after tax)", "ySlugs": "decile6_thr_day p60p70_thr_posttax_nat_day thr_p60_dhi_pc_day", "subtitle": "The level of income per day below which 60% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 6th decile (after tax)", "ySlugs": "decile6_thr_month p60p70_thr_posttax_nat_month thr_p60_dhi_pc_month", "subtitle": "The level of income per month below which 60% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 6th decile (after tax)", "ySlugs": "decile6_thr_year p60p70_thr_posttax_nat_year thr_p60_dhi_pc_year", "subtitle": "The level of income per year below which 60% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 6th decile (before tax)", "ySlugs": "p60p70_thr_pretax_day thr_p60_mi_pc_day", "subtitle": "The level of income per day below which 60% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 6th decile (before tax)", "ySlugs": "p60p70_thr_pretax_month thr_p60_mi_pc_month", "subtitle": "The level of income per month below which 60% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 6th decile (before tax)", "ySlugs": "p60p70_thr_pretax_year thr_p60_mi_pc_year", "subtitle": "The level of income per year below which 60% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the 6th decile (after tax)", "ySlugs": "decile6_share p50p60_share_posttax_nat share_p60_dhi_pc", "subtitle": "The share of income received by the 6th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the 6th decile (before tax)", "ySlugs": "p50p60_share_pretax share_p60_mi_pc", "subtitle": "The share of income received by the 6th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "6", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 7th decile (after tax)", "ySlugs": "decile7_avg_day p60p70_avg_posttax_nat_day avg_p70_dhi_pc_day", "subtitle": "The mean income per day within the 7th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 7th decile (after tax)", "ySlugs": "decile7_avg_month p60p70_avg_posttax_nat_month avg_p70_dhi_pc_month", "subtitle": "The mean income per month within the 7th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 7th decile (after tax)", "ySlugs": "decile7_avg_year p60p70_avg_posttax_nat_year avg_p70_dhi_pc_year", "subtitle": "The mean income per year within the 7th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 7th decile (before tax)", "ySlugs": "p60p70_avg_pretax_day avg_p70_mi_pc_day", "subtitle": "The mean income per day within the 7th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 7th decile (before tax)", "ySlugs": "p60p70_avg_pretax_month avg_p70_mi_pc_month", "subtitle": "The mean income per month within the 7th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 7th decile (before tax)", "ySlugs": "p60p70_avg_pretax_year avg_p70_mi_pc_year", "subtitle": "The mean income per year within the 7th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 7th decile (after tax)", "ySlugs": "decile7_thr_day p70p80_thr_posttax_nat_day thr_p70_dhi_pc_day", "subtitle": "The level of income per day below which 70% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 7th decile (after tax)", "ySlugs": "decile7_thr_month p70p80_thr_posttax_nat_month thr_p70_dhi_pc_month", "subtitle": "The level of income per month below which 70% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 7th decile (after tax)", "ySlugs": "decile7_thr_year p70p80_thr_posttax_nat_year thr_p70_dhi_pc_year", "subtitle": "The level of income per year below which 70% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 7th decile (before tax)", "ySlugs": "p70p80_thr_pretax_day thr_p70_mi_pc_day", "subtitle": "The level of income per day below which 70% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 7th decile (before tax)", "ySlugs": "p70p80_thr_pretax_month thr_p70_mi_pc_month", "subtitle": "The level of income per month below which 70% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 7th decile (before tax)", "ySlugs": "p70p80_thr_pretax_year thr_p70_mi_pc_year", "subtitle": "The level of income per year below which 70% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the 7th decile (after tax)", "ySlugs": "decile7_share p60p70_share_posttax_nat share_p70_dhi_pc", "subtitle": "The share of income received by the 7th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the 7th decile (before tax)", "ySlugs": "p60p70_share_pretax share_p70_mi_pc", "subtitle": "The share of income received by the 7th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "7", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 8th decile (after tax)", "ySlugs": "decile8_avg_day p70p80_avg_posttax_nat_day avg_p80_dhi_pc_day", "subtitle": "The mean income per day within the 8th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 8th decile (after tax)", "ySlugs": "decile8_avg_month p70p80_avg_posttax_nat_month avg_p80_dhi_pc_month", "subtitle": "The mean income per month within the 8th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 8th decile (after tax)", "ySlugs": "decile8_avg_year p70p80_avg_posttax_nat_year avg_p80_dhi_pc_year", "subtitle": "The mean income per year within the 8th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 8th decile (before tax)", "ySlugs": "p70p80_avg_pretax_day avg_p80_mi_pc_day", "subtitle": "The mean income per day within the 8th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 8th decile (before tax)", "ySlugs": "p70p80_avg_pretax_month avg_p80_mi_pc_month", "subtitle": "The mean income per month within the 8th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 8th decile (before tax)", "ySlugs": "p70p80_avg_pretax_year avg_p80_mi_pc_year", "subtitle": "The mean income per year within the 8th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 8th decile (after tax)", "ySlugs": "decile8_thr_day p80p90_thr_posttax_nat_day thr_p80_dhi_pc_day", "subtitle": "The level of income per day below which 80% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 8th decile (after tax)", "ySlugs": "decile8_thr_month p80p90_thr_posttax_nat_month thr_p80_dhi_pc_month", "subtitle": "The level of income per month below which 80% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 8th decile (after tax)", "ySlugs": "decile8_thr_year p80p90_thr_posttax_nat_year thr_p80_dhi_pc_year", "subtitle": "The level of income per year below which 80% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 8th decile (before tax)", "ySlugs": "p80p90_thr_pretax_day thr_p80_mi_pc_day", "subtitle": "The level of income per day below which 80% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 8th decile (before tax)", "ySlugs": "p80p90_thr_pretax_month thr_p80_mi_pc_month", "subtitle": "The level of income per month below which 80% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the 8th decile (before tax)", "ySlugs": "p80p90_thr_pretax_year thr_p80_mi_pc_year", "subtitle": "The level of income per year below which 80% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the 8th decile (after tax)", "ySlugs": "decile8_share p70p80_share_posttax_nat share_p80_dhi_pc", "subtitle": "The share of income received by the 8th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the 8th decile (before tax)", "ySlugs": "p70p80_share_pretax share_p80_mi_pc", "subtitle": "The share of income received by the 8th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "8", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 9th decile (after tax)", "ySlugs": "decile9_avg_day p80p90_avg_posttax_nat_day avg_p90_dhi_pc_day", "subtitle": "The mean income per day within the 9th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 9th decile (after tax)", "ySlugs": "decile9_avg_month p80p90_avg_posttax_nat_month avg_p90_dhi_pc_month", "subtitle": "The mean income per month within the 9th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 9th decile (after tax)", "ySlugs": "decile9_avg_year p80p90_avg_posttax_nat_year avg_p90_dhi_pc_year", "subtitle": "The mean income per year within the 9th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 9th decile (before tax)", "ySlugs": "p80p90_avg_pretax_day avg_p90_mi_pc_day", "subtitle": "The mean income per day within the 9th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 9th decile (before tax)", "ySlugs": "p80p90_avg_pretax_month avg_p90_mi_pc_month", "subtitle": "The mean income per month within the 9th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the 9th decile (before tax)", "ySlugs": "p80p90_avg_pretax_year avg_p90_mi_pc_year", "subtitle": "The mean income per year within the 9th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the 9th decile (after tax)", "ySlugs": "decile9_share p80p90_share_posttax_nat share_p90_dhi_pc", "subtitle": "The share of income received by the 9th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "9", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the 9th decile (before tax)", "ySlugs": "p80p90_share_pretax share_p90_mi_pc", "subtitle": "The share of income received by the 9th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "9", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the richest decile (after tax)", "ySlugs": "decile9_thr_day p90p100_thr_posttax_nat_day thr_p90_dhi_pc_day", "subtitle": "The level of income per day below which 90% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9 (richest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the richest decile (after tax)", "ySlugs": "decile9_thr_month p90p100_thr_posttax_nat_month thr_p90_dhi_pc_month", "subtitle": "The level of income per month below which 90% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9 (richest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the richest decile (after tax)", "ySlugs": "decile9_thr_year p90p100_thr_posttax_nat_year thr_p90_dhi_pc_year", "subtitle": "The level of income per year below which 90% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9 (richest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the richest decile (before tax)", "ySlugs": "p90p100_thr_pretax_day thr_p90_mi_pc_day", "subtitle": "The level of income per day below which 90% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9 (richest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the richest decile (before tax)", "ySlugs": "p90p100_thr_pretax_month thr_p90_mi_pc_month", "subtitle": "The level of income per month below which 90% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9 (richest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Threshold income marking the richest decile (before tax)", "ySlugs": "p90p100_thr_pretax_year thr_p90_mi_pc_year", "subtitle": "The level of income per year below which 90% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "9 (richest)", "Indicator Dropdown": "Decile thresholds", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the richest decile (after tax)", "ySlugs": "decile10_avg_day p90p100_avg_posttax_nat_day avg_p100_dhi_pc_day", "subtitle": "The mean income per day within the richest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "10 (richest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the richest decile (after tax)", "ySlugs": "decile10_avg_month p90p100_avg_posttax_nat_month avg_p100_dhi_pc_month", "subtitle": "The mean income per month within the richest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "10 (richest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the richest decile (after tax)", "ySlugs": "decile10_avg_year p90p100_avg_posttax_nat_year avg_p100_dhi_pc_year", "subtitle": "The mean income per year within the richest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "10 (richest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the richest decile (before tax)", "ySlugs": "p90p100_avg_pretax_day avg_p100_mi_pc_day", "subtitle": "The mean income per day within the richest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Day", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "10 (richest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the richest decile (before tax)", "ySlugs": "p90p100_avg_pretax_month avg_p100_mi_pc_month", "subtitle": "The mean income per month within the richest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Month", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "10 (richest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.", "title": "Mean income within the richest decile (before tax)", "ySlugs": "p90p100_avg_pretax_year avg_p100_mi_pc_year", "subtitle": "The mean income per year within the richest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "Period Radio": "Year", "yScaleToggle": "true", "mapTargetTime": "0", "Decile Dropdown": "10 (richest)", "Indicator Dropdown": "Mean income or consumption, by decile", "hideRelativeToggle": "false", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" }, { "tab": "chart", "title": "Income share of the richest decile (after tax)", "ySlugs": "decile10_share p90p100_share_posttax_nat share_p100_dhi_pc", "subtitle": "The share of income received by the richest decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "10 (richest)", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "After tax" }, { "tab": "chart", "title": "Income share of the richest decile (before tax)", "ySlugs": "p90p100_share_pretax share_p100_mi_pc", "subtitle": "The share of income received by the richest decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.", "yAxisMin": "0", "hasMapTab": "false", "tableSlug": "poverty_inequality", "mapTargetTime": "0", "Decile Dropdown": "10 (richest)", "Indicator Dropdown": "Decile shares", "selectedFacetStrategy": "entity", "Income measure Dropdown": "Before tax" } ] }, { "args": [ "https://catalog.ourworldindata.org/explorers/poverty_inequality/latest/poverty_inequality/poverty_inequality.csv", "poverty_inequality" ], "type": "table", "block": null }, { "args": [ "poverty_inequality" ], "type": "columns", "block": [ { "name": "Country", "slug": "country", "type": "EntityName", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Year", "slug": "year", "type": "Year", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income or consumption (PIP data)", "slug": "mean", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "Mean income or consumption.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "BuGn", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income or consumption (PIP data)", "slug": "median", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which half of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Blues", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 10% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 20% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 30% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 40% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (PIP data)", "slug": "decile5_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 50% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 60% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 70% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 80% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile9_thr", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 90% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (PIP data)", "slug": "decile5_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (PIP data)", "slug": "decile9_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile10_avg", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "1;2;3;4;5", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "1;2;3;4;5;6", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "2;3;4;5;6;7", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "2;3;4;5;6;7;8", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (PIP data)", "slug": "decile5_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "2;3;4;5;6;7;8;9;10", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "4;5;6;7;8;9;10", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "6;7;8;9;10;11;12", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "8;9;10;11;12;13;14", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (PIP data)", "slug": "decile9_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "8;10;12;14;16;18", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile10_share", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The share of income or consumption received by the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "OrRd", "colorScaleNumericBins": "20;25;30;35;40;45;50;55", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income or consumption (PIP data)", "slug": "mean_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean level of income or consumption per day.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "BuGn", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income or consumption (PIP data)", "slug": "median_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which half of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Blues", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile1_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 10% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile2_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 20% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile3_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 30% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile4_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 40% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (PIP data)", "slug": "decile5_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile5_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 50% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile6_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 60% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile7_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 70% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile8_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 80% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile9_thr_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile9_thr 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per day below which 90% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile1_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile2_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile3_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile4_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (PIP data)", "slug": "decile5_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile5_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile6_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile7_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile8_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (PIP data)", "slug": "decile9_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile9_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile10_avg_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile10_avg 1", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per day within the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1;2;5;10;20;50;100", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income or consumption (PIP data)", "slug": "mean_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean level of income or consumption per month.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "BuGn", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income or consumption (PIP data)", "slug": "median_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which half of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Blues", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile1_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 10% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile2_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 20% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile3_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 30% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile4_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 40% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (PIP data)", "slug": "decile5_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile5_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 50% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile6_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 60% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile7_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 70% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile8_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 80% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile9_thr_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile9_thr 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per month below which 90% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile1_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile2_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile3_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile4_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (PIP data)", "slug": "decile5_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile5_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile6_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile7_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile8_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (PIP data)", "slug": "decile9_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile9_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile10_avg_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile10_avg 30", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per month within the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income or consumption (PIP data)", "slug": "mean_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean level of income or consumption per year.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "BuGn", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income or consumption (PIP data)", "slug": "median_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which half of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Blues", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile1_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 10% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile2_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 20% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile3_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 30% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile4_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 40% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (PIP data)", "slug": "decile5_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile5_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 50% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile6_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 60% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile7_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 70% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile8_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 80% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile9_thr_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile9_thr 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The level of income or consumption per year below which 90% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Purples", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (PIP data)", "slug": "decile1_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile1_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (PIP data)", "slug": "decile2_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile2_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (PIP data)", "slug": "decile3_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile3_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (PIP data)", "slug": "decile4_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile4_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (PIP data)", "slug": "decile5_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile5_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (PIP data)", "slug": "decile6_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile6_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (PIP data)", "slug": "decile7_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile7_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (PIP data)", "slug": "decile8_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile8_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (PIP data)", "slug": "decile9_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile9_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (PIP data)", "slug": "decile10_avg_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy decile10_avg 365", "sourceLink": "https://pip.worldbank.org", "sourceName": "World Bank Poverty and Inequality Platform (2024)", "description": "The mean income or consumption per year within the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.", "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.", "colorScaleScheme": "Greens", "colorScaleNumericBins": "1000;2000;5000;10000;20000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (WID data)", "slug": "p0p100_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "Mean income\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (WID data)", "slug": "median_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "This is the level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p10p20_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p20p30_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p30p40_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p40p50_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (WID data)", "slug": "p50p60_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p60p70_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p70p80_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p80p90_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_thr_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_avg_posttax_nat", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_share_posttax_nat", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (WID data)", "slug": "p0p100_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p100_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (WID data)", "slug": "median_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p10p20_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p20p30_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p30p40_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p40p50_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (WID data)", "slug": "p50p60_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p60p70_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p70p80_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p80p90_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_thr_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_thr_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p10_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_avg_posttax_nat_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_avg_posttax_nat 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (WID data)", "slug": "p0p100_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p100_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (WID data)", "slug": "median_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p10p20_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p20p30_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p30p40_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p40p50_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (WID data)", "slug": "p50p60_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p60p70_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p70p80_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p80p90_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_thr_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_thr_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p10_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_avg_posttax_nat_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_avg_posttax_nat 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (WID data)", "slug": "p0p100_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p100_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (WID data)", "slug": "median_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p10p20_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p20p30_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p30p40_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p40p50_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (WID data)", "slug": "p50p60_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p60p70_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p70p80_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p80p90_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_thr_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_thr_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p10_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_avg_posttax_nat_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_avg_posttax_nat 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (WID data)", "slug": "p0p100_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "Mean income\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (WID data)", "slug": "median_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "This is the level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p10p20_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p20p30_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p30p40_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p40p50_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (WID data)", "slug": "p50p60_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p60p70_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p70p80_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p80p90_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_thr_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_avg_pretax", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_share_pretax", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The share of income received by the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (WID data)", "slug": "p0p100_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p100_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (WID data)", "slug": "median_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p10p20_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p20p30_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p30p40_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p40p50_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (WID data)", "slug": "p50p60_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p60p70_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p70p80_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p80p90_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_thr_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_thr_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p10_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_avg_pretax_day", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_avg_pretax 0.00274", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (WID data)", "slug": "p0p100_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p100_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (WID data)", "slug": "median_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p10p20_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p20p30_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p30p40_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p40p50_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (WID data)", "slug": "p50p60_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p60p70_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p70p80_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p80p90_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_thr_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_thr_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p10_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_avg_pretax_month", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_avg_pretax 0.08333", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (WID data)", "slug": "p0p100_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p100_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (WID data)", "slug": "median_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p10p20_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p20p30_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p30p40_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p40p50_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (WID data)", "slug": "p50p60_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p60p70_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p70p80_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p80p90_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_thr_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_thr_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (WID data)", "slug": "p0p10_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p0p10_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (WID data)", "slug": "p10p20_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p10p20_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (WID data)", "slug": "p20p30_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p20p30_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (WID data)", "slug": "p30p40_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p30p40_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (WID data)", "slug": "p40p50_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p40p50_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (WID data)", "slug": "p50p60_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p50p60_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (WID data)", "slug": "p60p70_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p60p70_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (WID data)", "slug": "p70p80_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p70p80_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (WID data)", "slug": "p80p90_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p80p90_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (WID data)", "slug": "p90p100_avg_pretax_year", "type": "Numeric", "unit": "international-$ in 2023 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy p90p100_avg_pretax 1", "sourceLink": "https://wid.world", "sourceName": "World Inequality Database (WID.world) (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).", "dataPublishedBy": "World Inequality Database (WID), https://wid.world", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (LIS data)", "slug": "mean_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "BuGn", "colorScaleNumericBins": "1000;2000;5000;10000;20000;50000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (LIS data)", "slug": "median_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Blues", "colorScaleNumericBins": "1000;2000;5000;10000;20000;50000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "thr_p10_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "thr_p20_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "thr_p30_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "thr_p40_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (LIS data)", "slug": "thr_p50_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "thr_p60_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "thr_p70_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "thr_p80_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "thr_p90_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "avg_p10_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "avg_p20_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "avg_p30_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "avg_p40_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "avg_p50_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "avg_p60_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "avg_p70_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "avg_p80_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "avg_p90_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "avg_p100_dhi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "share_p10_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "share_p20_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "share_p30_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "share_p40_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "share_p50_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "share_p60_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "share_p70_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "share_p80_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "share_p90_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "share_p100_dhi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (LIS data)", "slug": "mean_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (LIS data)", "slug": "median_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "thr_p10_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p10_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "thr_p20_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p20_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "thr_p30_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p30_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "thr_p40_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p40_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (LIS data)", "slug": "thr_p50_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p50_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "thr_p60_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p60_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "thr_p70_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p70_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "thr_p80_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p80_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "thr_p90_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p90_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "avg_p10_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p10_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "avg_p20_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p20_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "avg_p30_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p30_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "avg_p40_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p40_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "avg_p50_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p50_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "avg_p60_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p60_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "avg_p70_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p70_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "avg_p80_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p80_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "avg_p90_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p90_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "avg_p100_dhi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p100_dhi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (LIS data)", "slug": "mean_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (LIS data)", "slug": "median_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "thr_p10_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p10_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "thr_p20_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p20_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "thr_p30_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p30_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "thr_p40_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p40_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (LIS data)", "slug": "thr_p50_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p50_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "thr_p60_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p60_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "thr_p70_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p70_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "thr_p80_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p80_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "thr_p90_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p90_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "avg_p10_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p10_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "avg_p20_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p20_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "avg_p30_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p30_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "avg_p40_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p40_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "avg_p50_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p50_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "avg_p60_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p60_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "avg_p70_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p70_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "avg_p80_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p80_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "avg_p90_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p90_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "avg_p100_dhi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p100_dhi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (LIS data)", "slug": "mean_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (LIS data)", "slug": "median_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "thr_p10_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p10_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "thr_p20_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p20_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "thr_p30_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p30_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "thr_p40_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p40_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (LIS data)", "slug": "thr_p50_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p50_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "thr_p60_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p60_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "thr_p70_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p70_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "thr_p80_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p80_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "thr_p90_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p90_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "avg_p10_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p10_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "avg_p20_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p20_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "avg_p30_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p30_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "avg_p40_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p40_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "avg_p50_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p50_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "avg_p60_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p60_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "avg_p70_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p70_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "avg_p80_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p80_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "avg_p90_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p90_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "avg_p100_dhi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p100_dhi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (LIS data)", "slug": "mean_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "BuGn", "colorScaleNumericBins": "1000;2000;5000;10000;20000;50000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (LIS data)", "slug": "median_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Blues", "colorScaleNumericBins": "1000;2000;5000;10000;20000;50000", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "thr_p10_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "thr_p20_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "thr_p30_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "thr_p40_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (LIS data)", "slug": "thr_p50_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "thr_p60_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "thr_p70_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "thr_p80_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "thr_p90_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "avg_p10_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "avg_p20_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "avg_p30_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "avg_p40_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "avg_p50_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "avg_p60_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "avg_p70_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "avg_p80_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "avg_p90_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "avg_p100_mi_pc", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "share_p10_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "share_p20_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "share_p30_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "share_p40_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "share_p50_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "share_p60_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "share_p70_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "share_p80_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "share_p90_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "share_p100_mi_pc", "type": "Numeric", "unit": "%", "shortUnit": "%", "tolerance": "5", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The share of income received by the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "OrRd", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (LIS data)", "slug": "mean_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (LIS data)", "slug": "median_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "thr_p10_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p10_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "thr_p20_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p20_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "thr_p30_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p30_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "thr_p40_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p40_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (LIS data)", "slug": "thr_p50_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p50_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "thr_p60_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p60_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "thr_p70_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p70_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "thr_p80_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p80_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "thr_p90_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p90_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "avg_p10_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p10_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "avg_p20_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p20_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "avg_p30_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p30_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "avg_p40_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p40_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "avg_p50_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p50_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "avg_p60_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p60_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "avg_p70_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p70_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "avg_p80_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p80_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "avg_p90_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p90_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "avg_p100_mi_pc_day", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p100_mi_pc 0.00274", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (LIS data)", "slug": "mean_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (LIS data)", "slug": "median_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "thr_p10_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p10_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "thr_p20_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p20_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "thr_p30_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p30_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "thr_p40_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p40_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (LIS data)", "slug": "thr_p50_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p50_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "thr_p60_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p60_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "thr_p70_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p70_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "thr_p80_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p80_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "thr_p90_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p90_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "avg_p10_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p10_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "avg_p20_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p20_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "avg_p30_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p30_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "avg_p40_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p40_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "avg_p50_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p50_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "avg_p60_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p60_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "avg_p70_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p70_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "avg_p80_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p80_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "avg_p90_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p90_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "avg_p100_mi_pc_month", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p100_mi_pc 0.08333", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Mean income (LIS data)", "slug": "mean_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy mean_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "BuGn", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Median income (LIS data)", "slug": "median_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy median_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Blues", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "thr_p10_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p10_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "thr_p20_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p20_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "thr_p30_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p30_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "thr_p40_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p40_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (median) (LIS data)", "slug": "thr_p50_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p50_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "thr_p60_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p60_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "thr_p70_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p70_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "thr_p80_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p80_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "thr_p90_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy thr_p90_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Purples", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Poorest decile (LIS data)", "slug": "avg_p10_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p10_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "2nd decile (LIS data)", "slug": "avg_p20_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p20_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "3rd decile (LIS data)", "slug": "avg_p30_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p30_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "4th decile (LIS data)", "slug": "avg_p40_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p40_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "5th decile (LIS data)", "slug": "avg_p50_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p50_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "6th decile (LIS data)", "slug": "avg_p60_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p60_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "7th decile (LIS data)", "slug": "avg_p70_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p70_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "8th decile (LIS data)", "slug": "avg_p80_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p80_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "9th decile (LIS data)", "slug": "avg_p90_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p90_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" }, { "name": "Richest decile (LIS data)", "slug": "avg_p100_mi_pc_year", "type": "Numeric", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": "5", "transform": "multiplyBy avg_p100_mi_pc 1", "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/", "sourceName": "Luxembourg Income Study (2024)", "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.", "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.", "colorScaleScheme": "Greens", "colorScaleEqualSizeBins": "true", "colorScaleNumericMinValue": "0" } ] } ], "_version": 1, "selection": [ "Chile", "Brazil", "South Africa", "United States", "France", "China" ], "wpBlockId": "57742", "entityType": "country or region", "googleSheet": null, "explorerTitle": "Incomes Across the Distribution - World Bank, WID, and LIS", "explorerSubtitle": "Compare World Bank, WID, and LIS data on the distribution of incomes.", "pickerColumnSlugs": [ "mean_year median_year p0p100_avg_posttax_nat_year median_posttax_nat_year mean_dhi_pc_year median_dhi_pc_year" ] }	2023-06-23 15:51:09	2024-06-25 11:17:25

slug

isPublished

config

createdAt

updatedAt

incomes-across-distribution-comparison

{
    "blocks": [
        {
            "args": [],
            "type": "graphers",
            "block": [
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income per day (after tax)",
                    "ySlugs": "mean_day p0p100_avg_posttax_nat_day mean_dhi_pc_day",
                    "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Mean income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income per month (after tax)",
                    "ySlugs": "mean_month p0p100_avg_posttax_nat_month mean_dhi_pc_month",
                    "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Mean income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income per year (after tax)",
                    "ySlugs": "mean_year p0p100_avg_posttax_nat_year mean_dhi_pc_year",
                    "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "defaultView": "true",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Mean income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income per day (before tax)",
                    "ySlugs": "p0p100_avg_pretax_day mean_mi_pc_day",
                    "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Mean income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income per month (before tax)",
                    "ySlugs": "p0p100_avg_pretax_month mean_mi_pc_month",
                    "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Mean income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income per year (before tax)",
                    "ySlugs": "p0p100_avg_pretax_year mean_mi_pc_year",
                    "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Mean income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Median income per day (after tax)",
                    "ySlugs": "median_day median_posttax_nat_day median_dhi_pc_day",
                    "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Median income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Median income per month (after tax)",
                    "ySlugs": "median_month median_posttax_nat_month median_dhi_pc_month",
                    "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Median income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Median income per year (after tax)",
                    "ySlugs": "median_year median_posttax_nat_year median_dhi_pc_year",
                    "subtitle": "LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Median income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Median income per day (before tax)",
                    "ySlugs": "median_pretax_day median_mi_pc_day",
                    "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Median income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Median income per month (before tax)",
                    "ySlugs": "median_pretax_month median_mi_pc_month",
                    "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Median income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Median income per year (before tax)",
                    "ySlugs": "median_pretax_year median_mi_pc_year",
                    "subtitle": "LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Indicator Dropdown": "Median income or consumption",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the poorest decile (after tax)",
                    "ySlugs": "decile1_avg_day p0p10_avg_posttax_nat_day avg_p10_dhi_pc_day",
                    "subtitle": "The mean income per day within the poorest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the poorest decile (after tax)",
                    "ySlugs": "decile1_avg_month p0p10_avg_posttax_nat_month avg_p10_dhi_pc_month",
                    "subtitle": "The mean income per month within the poorest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the poorest decile (after tax)",
                    "ySlugs": "decile1_avg_year p0p10_avg_posttax_nat_year avg_p10_dhi_pc_year",
                    "subtitle": "The mean income per year within the poorest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the poorest decile (before tax)",
                    "ySlugs": "p0p10_avg_pretax_day avg_p10_mi_pc_day",
                    "subtitle": "The mean income per day within the poorest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the poorest decile (before tax)",
                    "ySlugs": "p0p10_avg_pretax_month avg_p10_mi_pc_month",
                    "subtitle": "The mean income per month within the poorest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the poorest decile (before tax)",
                    "ySlugs": "p0p10_avg_pretax_year avg_p10_mi_pc_year",
                    "subtitle": "The mean income per year within the poorest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the poorest decile (after tax)",
                    "ySlugs": "decile1_thr_day p10p20_thr_posttax_nat_day thr_p10_dhi_pc_day",
                    "subtitle": "The level of income per day below which 10% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the poorest decile (after tax)",
                    "ySlugs": "decile1_thr_month p10p20_thr_posttax_nat_month thr_p10_dhi_pc_month",
                    "subtitle": "The level of income per month below which 10% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the poorest decile (after tax)",
                    "ySlugs": "decile1_thr_year p10p20_thr_posttax_nat_year thr_p10_dhi_pc_year",
                    "subtitle": "The level of income per year below which 10% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the poorest decile (before tax)",
                    "ySlugs": "p10p20_thr_pretax_day thr_p10_mi_pc_day",
                    "subtitle": "The level of income per day below which 10% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the poorest decile (before tax)",
                    "ySlugs": "p10p20_thr_pretax_month thr_p10_mi_pc_month",
                    "subtitle": "The level of income per month below which 10% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the poorest decile (before tax)",
                    "ySlugs": "p10p20_thr_pretax_year thr_p10_mi_pc_year",
                    "subtitle": "The level of income per year below which 10% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the poorest decile (after tax)",
                    "ySlugs": "decile1_share p0p10_share_posttax_nat share_p10_dhi_pc",
                    "subtitle": "The share of income received by the poorest decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the poorest decile (before tax)",
                    "ySlugs": "p0p10_share_pretax share_p10_mi_pc",
                    "subtitle": "The share of income received by the poorest decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "1 (poorest)",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 2nd decile (after tax)",
                    "ySlugs": "decile2_avg_day p10p20_avg_posttax_nat_day avg_p20_dhi_pc_day",
                    "subtitle": "The mean income per day within the 2nd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 2nd decile (after tax)",
                    "ySlugs": "decile2_avg_month p10p20_avg_posttax_nat_month avg_p20_dhi_pc_month",
                    "subtitle": "The mean income per month within the 2nd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 2nd decile (after tax)",
                    "ySlugs": "decile2_avg_year p10p20_avg_posttax_nat_year avg_p20_dhi_pc_year",
                    "subtitle": "The mean income per year within the 2nd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 2nd decile (before tax)",
                    "ySlugs": "p10p20_avg_pretax_day avg_p20_mi_pc_day",
                    "subtitle": "The mean income per day within the 2nd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 2nd decile (before tax)",
                    "ySlugs": "p10p20_avg_pretax_month avg_p20_mi_pc_month",
                    "subtitle": "The mean income per month within the 2nd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 2nd decile (before tax)",
                    "ySlugs": "p10p20_avg_pretax_year avg_p20_mi_pc_year",
                    "subtitle": "The mean income per year within the 2nd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 2nd decile (after tax)",
                    "ySlugs": "decile2_thr_day p20p30_thr_posttax_nat_day thr_p20_dhi_pc_day",
                    "subtitle": "The level of income per day below which 20% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 2nd decile (after tax)",
                    "ySlugs": "decile2_thr_month p20p30_thr_posttax_nat_month thr_p20_dhi_pc_month",
                    "subtitle": "The level of income per month below which 20% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 2nd decile (after tax)",
                    "ySlugs": "decile2_thr_year p20p30_thr_posttax_nat_year thr_p20_dhi_pc_year",
                    "subtitle": "The level of income per year below which 20% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 2nd decile (before tax)",
                    "ySlugs": "p20p30_thr_pretax_day thr_p20_mi_pc_day",
                    "subtitle": "The level of income per day below which 20% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 2nd decile (before tax)",
                    "ySlugs": "p20p30_thr_pretax_month thr_p20_mi_pc_month",
                    "subtitle": "The level of income per month below which 20% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 2nd decile (before tax)",
                    "ySlugs": "p20p30_thr_pretax_year thr_p20_mi_pc_year",
                    "subtitle": "The level of income per year below which 20% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 2nd decile (after tax)",
                    "ySlugs": "decile2_share p10p20_share_posttax_nat share_p20_dhi_pc",
                    "subtitle": "The share of income received by the 2nd decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 2nd decile (before tax)",
                    "ySlugs": "p10p20_share_pretax share_p20_mi_pc",
                    "subtitle": "The share of income received by the 2nd decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "2",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 3rd decile (after tax)",
                    "ySlugs": "decile3_avg_day p20p30_avg_posttax_nat_day avg_p30_dhi_pc_day",
                    "subtitle": "The mean income per day within the 3rd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 3rd decile (after tax)",
                    "ySlugs": "decile3_avg_month p20p30_avg_posttax_nat_month avg_p30_dhi_pc_month",
                    "subtitle": "The mean income per month within the 3rd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 3rd decile (after tax)",
                    "ySlugs": "decile3_avg_year p20p30_avg_posttax_nat_year avg_p30_dhi_pc_year",
                    "subtitle": "The mean income per year within the 3rd decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 3rd decile (before tax)",
                    "ySlugs": "p20p30_avg_pretax_day avg_p30_mi_pc_day",
                    "subtitle": "The mean income per day within the 3rd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 3rd decile (before tax)",
                    "ySlugs": "p20p30_avg_pretax_month avg_p30_mi_pc_month",
                    "subtitle": "The mean income per month within the 3rd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 3rd decile (before tax)",
                    "ySlugs": "p20p30_avg_pretax_year avg_p30_mi_pc_year",
                    "subtitle": "The mean income per year within the 3rd decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 3rd decile (after tax)",
                    "ySlugs": "decile3_thr_day p30p40_thr_posttax_nat_day thr_p30_dhi_pc_day",
                    "subtitle": "The level of income per day below which 30% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 3rd decile (after tax)",
                    "ySlugs": "decile3_thr_month p30p40_thr_posttax_nat_month thr_p30_dhi_pc_month",
                    "subtitle": "The level of income per month below which 30% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 3rd decile (after tax)",
                    "ySlugs": "decile3_thr_year p30p40_thr_posttax_nat_year thr_p30_dhi_pc_year",
                    "subtitle": "The level of income per year below which 30% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 3rd decile (before tax)",
                    "ySlugs": "p30p40_thr_pretax_day thr_p30_mi_pc_day",
                    "subtitle": "The level of income per day below which 30% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 3rd decile (before tax)",
                    "ySlugs": "p30p40_thr_pretax_month thr_p30_mi_pc_month",
                    "subtitle": "The level of income per month below which 30% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 3rd decile (before tax)",
                    "ySlugs": "p30p40_thr_pretax_year thr_p30_mi_pc_year",
                    "subtitle": "The level of income per year below which 30% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 3rd decile (after tax)",
                    "ySlugs": "decile3_share p20p30_share_posttax_nat share_p30_dhi_pc",
                    "subtitle": "The share of income received by the 3rd decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 3rd decile (before tax)",
                    "ySlugs": "p20p30_share_pretax share_p30_mi_pc",
                    "subtitle": "The share of income received by the 3rd decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "3",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 4th decile (after tax)",
                    "ySlugs": "decile4_avg_day p30p40_avg_posttax_nat_day avg_p40_dhi_pc_day",
                    "subtitle": "The mean income per day within the 4th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 4th decile (after tax)",
                    "ySlugs": "decile4_avg_month p30p40_avg_posttax_nat_month avg_p40_dhi_pc_month",
                    "subtitle": "The mean income per month within the 4th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 4th decile (after tax)",
                    "ySlugs": "decile4_avg_year p30p40_avg_posttax_nat_year avg_p40_dhi_pc_year",
                    "subtitle": "The mean income per year within the 4th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 4th decile (before tax)",
                    "ySlugs": "p30p40_avg_pretax_day avg_p40_mi_pc_day",
                    "subtitle": "The mean income per day within the 4th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 4th decile (before tax)",
                    "ySlugs": "p30p40_avg_pretax_month avg_p40_mi_pc_month",
                    "subtitle": "The mean income per month within the 4th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 4th decile (before tax)",
                    "ySlugs": "p30p40_avg_pretax_year avg_p40_mi_pc_year",
                    "subtitle": "The mean income per year within the 4th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 4th decile (after tax)",
                    "ySlugs": "decile4_thr_day p40p50_thr_posttax_nat_day thr_p40_dhi_pc_day",
                    "subtitle": "The level of income per day below which 40% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 4th decile (after tax)",
                    "ySlugs": "decile4_thr_month p40p50_thr_posttax_nat_month thr_p40_dhi_pc_month",
                    "subtitle": "The level of income per month below which 40% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 4th decile (after tax)",
                    "ySlugs": "decile4_thr_year p40p50_thr_posttax_nat_year thr_p40_dhi_pc_year",
                    "subtitle": "The level of income per year below which 40% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 4th decile (before tax)",
                    "ySlugs": "p40p50_thr_pretax_day thr_p40_mi_pc_day",
                    "subtitle": "The level of income per day below which 40% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 4th decile (before tax)",
                    "ySlugs": "p40p50_thr_pretax_month thr_p40_mi_pc_month",
                    "subtitle": "The level of income per month below which 40% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 4th decile (before tax)",
                    "ySlugs": "p40p50_thr_pretax_year thr_p40_mi_pc_year",
                    "subtitle": "The level of income per year below which 40% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 4th decile (after tax)",
                    "ySlugs": "decile4_share p30p40_share_posttax_nat share_p40_dhi_pc",
                    "subtitle": "The share of income received by the 4th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 4th decile (before tax)",
                    "ySlugs": "p30p40_share_pretax share_p40_mi_pc",
                    "subtitle": "The share of income received by the 4th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "4",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 5th decile (after tax)",
                    "ySlugs": "decile5_avg_day p40p50_avg_posttax_nat_day avg_p50_dhi_pc_day",
                    "subtitle": "The mean income per day within the 5th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 5th decile (after tax)",
                    "ySlugs": "decile5_avg_month p40p50_avg_posttax_nat_month avg_p50_dhi_pc_month",
                    "subtitle": "The mean income per month within the 5th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 5th decile (after tax)",
                    "ySlugs": "decile5_avg_year p40p50_avg_posttax_nat_year avg_p50_dhi_pc_year",
                    "subtitle": "The mean income per year within the 5th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 5th decile (before tax)",
                    "ySlugs": "p40p50_avg_pretax_day avg_p50_mi_pc_day",
                    "subtitle": "The mean income per day within the 5th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 5th decile (before tax)",
                    "ySlugs": "p40p50_avg_pretax_month avg_p50_mi_pc_month",
                    "subtitle": "The mean income per month within the 5th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 5th decile (before tax)",
                    "ySlugs": "p40p50_avg_pretax_year avg_p50_mi_pc_year",
                    "subtitle": "The mean income per year within the 5th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 5th decile (after tax)",
                    "ySlugs": "decile5_share p40p50_share_posttax_nat share_p50_dhi_pc",
                    "subtitle": "The share of income received by the 5th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 5th decile (before tax)",
                    "ySlugs": "p40p50_share_pretax share_p50_mi_pc",
                    "subtitle": "The share of income received by the 5th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 5th decile (median) (after tax)",
                    "ySlugs": "decile5_thr_day p50p60_thr_posttax_nat_day thr_p50_dhi_pc_day",
                    "subtitle": "The level of income per day below which 50% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5 (median)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 5th decile (median) (after tax)",
                    "ySlugs": "decile5_thr_month p50p60_thr_posttax_nat_month thr_p50_dhi_pc_month",
                    "subtitle": "The level of income per month below which 50% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5 (median)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 5th decile (median) (after tax)",
                    "ySlugs": "decile5_thr_year p50p60_thr_posttax_nat_year thr_p50_dhi_pc_year",
                    "subtitle": "The level of income per year below which 50% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5 (median)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 5th decile (median) (before tax)",
                    "ySlugs": "p50p60_thr_pretax_day thr_p50_mi_pc_day",
                    "subtitle": "The level of income per day below which 50% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5 (median)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 5th decile (median) (before tax)",
                    "ySlugs": "p50p60_thr_pretax_month thr_p50_mi_pc_month",
                    "subtitle": "The level of income per month below which 50% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5 (median)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 5th decile (median) (before tax)",
                    "ySlugs": "p50p60_thr_pretax_year thr_p50_mi_pc_year",
                    "subtitle": "The level of income per year below which 50% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "5 (median)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 6th decile (after tax)",
                    "ySlugs": "decile6_avg_day p50p60_avg_posttax_nat_day avg_p60_dhi_pc_day",
                    "subtitle": "The mean income per day within the 6th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 6th decile (after tax)",
                    "ySlugs": "decile6_avg_month p50p60_avg_posttax_nat_month avg_p60_dhi_pc_month",
                    "subtitle": "The mean income per month within the 6th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 6th decile (after tax)",
                    "ySlugs": "decile6_avg_year p50p60_avg_posttax_nat_year avg_p60_dhi_pc_year",
                    "subtitle": "The mean income per year within the 6th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 6th decile (before tax)",
                    "ySlugs": "p50p60_avg_pretax_day avg_p60_mi_pc_day",
                    "subtitle": "The mean income per day within the 6th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 6th decile (before tax)",
                    "ySlugs": "p50p60_avg_pretax_month avg_p60_mi_pc_month",
                    "subtitle": "The mean income per month within the 6th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 6th decile (before tax)",
                    "ySlugs": "p50p60_avg_pretax_year avg_p60_mi_pc_year",
                    "subtitle": "The mean income per year within the 6th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 6th decile (after tax)",
                    "ySlugs": "decile6_thr_day p60p70_thr_posttax_nat_day thr_p60_dhi_pc_day",
                    "subtitle": "The level of income per day below which 60% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 6th decile (after tax)",
                    "ySlugs": "decile6_thr_month p60p70_thr_posttax_nat_month thr_p60_dhi_pc_month",
                    "subtitle": "The level of income per month below which 60% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 6th decile (after tax)",
                    "ySlugs": "decile6_thr_year p60p70_thr_posttax_nat_year thr_p60_dhi_pc_year",
                    "subtitle": "The level of income per year below which 60% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 6th decile (before tax)",
                    "ySlugs": "p60p70_thr_pretax_day thr_p60_mi_pc_day",
                    "subtitle": "The level of income per day below which 60% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 6th decile (before tax)",
                    "ySlugs": "p60p70_thr_pretax_month thr_p60_mi_pc_month",
                    "subtitle": "The level of income per month below which 60% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 6th decile (before tax)",
                    "ySlugs": "p60p70_thr_pretax_year thr_p60_mi_pc_year",
                    "subtitle": "The level of income per year below which 60% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 6th decile (after tax)",
                    "ySlugs": "decile6_share p50p60_share_posttax_nat share_p60_dhi_pc",
                    "subtitle": "The share of income received by the 6th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 6th decile (before tax)",
                    "ySlugs": "p50p60_share_pretax share_p60_mi_pc",
                    "subtitle": "The share of income received by the 6th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "6",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 7th decile (after tax)",
                    "ySlugs": "decile7_avg_day p60p70_avg_posttax_nat_day avg_p70_dhi_pc_day",
                    "subtitle": "The mean income per day within the 7th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 7th decile (after tax)",
                    "ySlugs": "decile7_avg_month p60p70_avg_posttax_nat_month avg_p70_dhi_pc_month",
                    "subtitle": "The mean income per month within the 7th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 7th decile (after tax)",
                    "ySlugs": "decile7_avg_year p60p70_avg_posttax_nat_year avg_p70_dhi_pc_year",
                    "subtitle": "The mean income per year within the 7th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 7th decile (before tax)",
                    "ySlugs": "p60p70_avg_pretax_day avg_p70_mi_pc_day",
                    "subtitle": "The mean income per day within the 7th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 7th decile (before tax)",
                    "ySlugs": "p60p70_avg_pretax_month avg_p70_mi_pc_month",
                    "subtitle": "The mean income per month within the 7th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 7th decile (before tax)",
                    "ySlugs": "p60p70_avg_pretax_year avg_p70_mi_pc_year",
                    "subtitle": "The mean income per year within the 7th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 7th decile (after tax)",
                    "ySlugs": "decile7_thr_day p70p80_thr_posttax_nat_day thr_p70_dhi_pc_day",
                    "subtitle": "The level of income per day below which 70% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 7th decile (after tax)",
                    "ySlugs": "decile7_thr_month p70p80_thr_posttax_nat_month thr_p70_dhi_pc_month",
                    "subtitle": "The level of income per month below which 70% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 7th decile (after tax)",
                    "ySlugs": "decile7_thr_year p70p80_thr_posttax_nat_year thr_p70_dhi_pc_year",
                    "subtitle": "The level of income per year below which 70% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 7th decile (before tax)",
                    "ySlugs": "p70p80_thr_pretax_day thr_p70_mi_pc_day",
                    "subtitle": "The level of income per day below which 70% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 7th decile (before tax)",
                    "ySlugs": "p70p80_thr_pretax_month thr_p70_mi_pc_month",
                    "subtitle": "The level of income per month below which 70% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 7th decile (before tax)",
                    "ySlugs": "p70p80_thr_pretax_year thr_p70_mi_pc_year",
                    "subtitle": "The level of income per year below which 70% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 7th decile (after tax)",
                    "ySlugs": "decile7_share p60p70_share_posttax_nat share_p70_dhi_pc",
                    "subtitle": "The share of income received by the 7th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 7th decile (before tax)",
                    "ySlugs": "p60p70_share_pretax share_p70_mi_pc",
                    "subtitle": "The share of income received by the 7th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "7",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 8th decile (after tax)",
                    "ySlugs": "decile8_avg_day p70p80_avg_posttax_nat_day avg_p80_dhi_pc_day",
                    "subtitle": "The mean income per day within the 8th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 8th decile (after tax)",
                    "ySlugs": "decile8_avg_month p70p80_avg_posttax_nat_month avg_p80_dhi_pc_month",
                    "subtitle": "The mean income per month within the 8th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 8th decile (after tax)",
                    "ySlugs": "decile8_avg_year p70p80_avg_posttax_nat_year avg_p80_dhi_pc_year",
                    "subtitle": "The mean income per year within the 8th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 8th decile (before tax)",
                    "ySlugs": "p70p80_avg_pretax_day avg_p80_mi_pc_day",
                    "subtitle": "The mean income per day within the 8th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 8th decile (before tax)",
                    "ySlugs": "p70p80_avg_pretax_month avg_p80_mi_pc_month",
                    "subtitle": "The mean income per month within the 8th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 8th decile (before tax)",
                    "ySlugs": "p70p80_avg_pretax_year avg_p80_mi_pc_year",
                    "subtitle": "The mean income per year within the 8th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 8th decile (after tax)",
                    "ySlugs": "decile8_thr_day p80p90_thr_posttax_nat_day thr_p80_dhi_pc_day",
                    "subtitle": "The level of income per day below which 80% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 8th decile (after tax)",
                    "ySlugs": "decile8_thr_month p80p90_thr_posttax_nat_month thr_p80_dhi_pc_month",
                    "subtitle": "The level of income per month below which 80% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 8th decile (after tax)",
                    "ySlugs": "decile8_thr_year p80p90_thr_posttax_nat_year thr_p80_dhi_pc_year",
                    "subtitle": "The level of income per year below which 80% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 8th decile (before tax)",
                    "ySlugs": "p80p90_thr_pretax_day thr_p80_mi_pc_day",
                    "subtitle": "The level of income per day below which 80% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 8th decile (before tax)",
                    "ySlugs": "p80p90_thr_pretax_month thr_p80_mi_pc_month",
                    "subtitle": "The level of income per month below which 80% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the 8th decile (before tax)",
                    "ySlugs": "p80p90_thr_pretax_year thr_p80_mi_pc_year",
                    "subtitle": "The level of income per year below which 80% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 8th decile (after tax)",
                    "ySlugs": "decile8_share p70p80_share_posttax_nat share_p80_dhi_pc",
                    "subtitle": "The share of income received by the 8th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 8th decile (before tax)",
                    "ySlugs": "p70p80_share_pretax share_p80_mi_pc",
                    "subtitle": "The share of income received by the 8th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "8",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 9th decile (after tax)",
                    "ySlugs": "decile9_avg_day p80p90_avg_posttax_nat_day avg_p90_dhi_pc_day",
                    "subtitle": "The mean income per day within the 9th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 9th decile (after tax)",
                    "ySlugs": "decile9_avg_month p80p90_avg_posttax_nat_month avg_p90_dhi_pc_month",
                    "subtitle": "The mean income per month within the 9th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 9th decile (after tax)",
                    "ySlugs": "decile9_avg_year p80p90_avg_posttax_nat_year avg_p90_dhi_pc_year",
                    "subtitle": "The mean income per year within the 9th decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 9th decile (before tax)",
                    "ySlugs": "p80p90_avg_pretax_day avg_p90_mi_pc_day",
                    "subtitle": "The mean income per day within the 9th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 9th decile (before tax)",
                    "ySlugs": "p80p90_avg_pretax_month avg_p90_mi_pc_month",
                    "subtitle": "The mean income per month within the 9th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the 9th decile (before tax)",
                    "ySlugs": "p80p90_avg_pretax_year avg_p90_mi_pc_year",
                    "subtitle": "The mean income per year within the 9th decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 9th decile (after tax)",
                    "ySlugs": "decile9_share p80p90_share_posttax_nat share_p90_dhi_pc",
                    "subtitle": "The share of income received by the 9th decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the 9th decile (before tax)",
                    "ySlugs": "p80p90_share_pretax share_p90_mi_pc",
                    "subtitle": "The share of income received by the 9th decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the richest decile (after tax)",
                    "ySlugs": "decile9_thr_day p90p100_thr_posttax_nat_day thr_p90_dhi_pc_day",
                    "subtitle": "The level of income per day below which 90% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9 (richest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the richest decile (after tax)",
                    "ySlugs": "decile9_thr_month p90p100_thr_posttax_nat_month thr_p90_dhi_pc_month",
                    "subtitle": "The level of income per month below which 90% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9 (richest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the richest decile (after tax)",
                    "ySlugs": "decile9_thr_year p90p100_thr_posttax_nat_year thr_p90_dhi_pc_year",
                    "subtitle": "The level of income per year below which 90% of the population falls. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9 (richest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the richest decile (before tax)",
                    "ySlugs": "p90p100_thr_pretax_day thr_p90_mi_pc_day",
                    "subtitle": "The level of income per day below which 90% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9 (richest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the richest decile (before tax)",
                    "ySlugs": "p90p100_thr_pretax_month thr_p90_mi_pc_month",
                    "subtitle": "The level of income per month below which 90% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9 (richest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Threshold income marking the richest decile (before tax)",
                    "ySlugs": "p90p100_thr_pretax_year thr_p90_mi_pc_year",
                    "subtitle": "The level of income per year below which 90% of the population falls. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "9 (richest)",
                    "Indicator Dropdown": "Decile thresholds",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the richest decile (after tax)",
                    "ySlugs": "decile10_avg_day p90p100_avg_posttax_nat_day avg_p100_dhi_pc_day",
                    "subtitle": "The mean income per day within the richest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "10 (richest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the richest decile (after tax)",
                    "ySlugs": "decile10_avg_month p90p100_avg_posttax_nat_month avg_p100_dhi_pc_month",
                    "subtitle": "The mean income per month within the richest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "10 (richest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. Both LIS and PIP data are measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the richest decile (after tax)",
                    "ySlugs": "decile10_avg_year p90p100_avg_posttax_nat_year avg_p100_dhi_pc_year",
                    "subtitle": "The mean income per year within the richest decile (tenth of the population). LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "10 (richest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the richest decile (before tax)",
                    "ySlugs": "p90p100_avg_pretax_day avg_p100_mi_pc_day",
                    "subtitle": "The mean income per day within the richest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Day",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "10 (richest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the richest decile (before tax)",
                    "ySlugs": "p90p100_avg_pretax_month avg_p100_mi_pc_month",
                    "subtitle": "The mean income per month within the richest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Month",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "10 (richest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "note": "This data is adjusted for inflation and differences in the cost of living between countries. LIS data is measured in 2017 int-$, while WID is measured in 2023 int-$.",
                    "title": "Mean income within the richest decile (before tax)",
                    "ySlugs": "p90p100_avg_pretax_year avg_p100_mi_pc_year",
                    "subtitle": "The mean income per year within the richest decile (tenth of the population). LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "Period Radio": "Year",
                    "yScaleToggle": "true",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "10 (richest)",
                    "Indicator Dropdown": "Mean income or consumption, by decile",
                    "hideRelativeToggle": "false",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the richest decile (after tax)",
                    "ySlugs": "decile10_share p90p100_share_posttax_nat share_p100_dhi_pc",
                    "subtitle": "The share of income received by the richest decile. LIS data refers to disposable household income per capita, WID data to net national income after tax per adult, and, depending on the country and year, PIP data refers to income measured after taxes and benefits, or to consumption, per capita.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "10 (richest)",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "After tax"
                },
                {
                    "tab": "chart",
                    "title": "Income share of the richest decile (before tax)",
                    "ySlugs": "p90p100_share_pretax share_p100_mi_pc",
                    "subtitle": "The share of income received by the richest decile. LIS data refers to market household income per capita, and WID data to net national income before tax per adult, but after the payment of public and private pensions.",
                    "yAxisMin": "0",
                    "hasMapTab": "false",
                    "tableSlug": "poverty_inequality",
                    "mapTargetTime": "0",
                    "Decile Dropdown": "10 (richest)",
                    "Indicator Dropdown": "Decile shares",
                    "selectedFacetStrategy": "entity",
                    "Income measure Dropdown": "Before tax"
                }
            ]
        },
        {
            "args": [
                "https://catalog.ourworldindata.org/explorers/poverty_inequality/latest/poverty_inequality/poverty_inequality.csv",
                "poverty_inequality"
            ],
            "type": "table",
            "block": null
        },
        {
            "args": [
                "poverty_inequality"
            ],
            "type": "columns",
            "block": [
                {
                    "name": "Country",
                    "slug": "country",
                    "type": "EntityName",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Year",
                    "slug": "year",
                    "type": "Year",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income or consumption (PIP data)",
                    "slug": "mean",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "Mean income or consumption.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income or consumption (PIP data)",
                    "slug": "median",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which half of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Blues",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 10% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 20% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 30% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 40% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (PIP data)",
                    "slug": "decile5_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 50% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 60% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 70% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 80% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile9_thr",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 90% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (PIP data)",
                    "slug": "decile5_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (PIP data)",
                    "slug": "decile9_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile10_avg",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100;100.0001",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "1;2;3;4;5",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "1;2;3;4;5;6",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "2;3;4;5;6;7",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "2;3;4;5;6;7;8",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (PIP data)",
                    "slug": "decile5_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "2;3;4;5;6;7;8;9;10",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "4;5;6;7;8;9;10",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "6;7;8;9;10;11;12",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "8;9;10;11;12;13;14",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (PIP data)",
                    "slug": "decile9_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "8;10;12;14;16;18",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile10_share",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The share of income or consumption received by the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleNumericBins": "20;25;30;35;40;45;50;55",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income or consumption (PIP data)",
                    "slug": "mean_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean level of income or consumption per day.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income or consumption (PIP data)",
                    "slug": "median_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which half of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Blues",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile1_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 10% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile2_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 20% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile3_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 30% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile4_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 40% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (PIP data)",
                    "slug": "decile5_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile5_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 50% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile6_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 60% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile7_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 70% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile8_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 80% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile9_thr_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile9_thr 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per day below which 90% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile1_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile2_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile3_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile4_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (PIP data)",
                    "slug": "decile5_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile5_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile6_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile7_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile8_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (PIP data)",
                    "slug": "decile9_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile9_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile10_avg_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile10_avg 1",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per day within the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1;2;5;10;20;50;100",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income or consumption (PIP data)",
                    "slug": "mean_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean level of income or consumption per month.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income or consumption (PIP data)",
                    "slug": "median_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which half of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Blues",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile1_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 10% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile2_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 20% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile3_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 30% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile4_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 40% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (PIP data)",
                    "slug": "decile5_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile5_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 50% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile6_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 60% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile7_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 70% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile8_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 80% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile9_thr_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile9_thr 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per month below which 90% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile1_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile2_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile3_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile4_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (PIP data)",
                    "slug": "decile5_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile5_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile6_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile7_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile8_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (PIP data)",
                    "slug": "decile9_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile9_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile10_avg_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile10_avg 30",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per month within the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "10;20;50;100;200;500;1000;2000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income or consumption (PIP data)",
                    "slug": "mean_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean level of income or consumption per year.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income or consumption (PIP data)",
                    "slug": "median_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which half of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Blues",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile1_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 10% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile2_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 20% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile3_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 30% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile4_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 40% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (PIP data)",
                    "slug": "decile5_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile5_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 50% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile6_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 60% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile7_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 70% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile8_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 80% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile9_thr_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile9_thr 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The level of income or consumption per year below which 90% of the population falls.\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Purples",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (PIP data)",
                    "slug": "decile1_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile1_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the poorest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (PIP data)",
                    "slug": "decile2_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile2_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the 2nd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (PIP data)",
                    "slug": "decile3_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile3_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the 3rd decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (PIP data)",
                    "slug": "decile4_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile4_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the 4th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (PIP data)",
                    "slug": "decile5_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile5_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the 5th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (PIP data)",
                    "slug": "decile6_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile6_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the 6th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (PIP data)",
                    "slug": "decile7_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile7_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the 7th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (PIP data)",
                    "slug": "decile8_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile8_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the 8th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (PIP data)",
                    "slug": "decile9_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile9_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the 9th decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (PIP data)",
                    "slug": "decile10_avg_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy decile10_avg 365",
                    "sourceLink": "https://pip.worldbank.org",
                    "sourceName": "World Bank Poverty and Inequality Platform (2024)",
                    "description": "The mean income or consumption per year within the richest decile (tenth of the population).\\n\\nDepending on the country and year, the data relates to income measured after taxes and benefits, or to consumption, per capita. 'Per capita' means that the incomes of each household are attributed equally to each member of the household (including children).\\n\\nNon-market sources of income, including food grown by subsistence farmers for their own consumption, are taken into account.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nFor most countries in the PIP dataset, estimates relate to _either_ disposable income or consumption, for all available years. A number of countries, however, have a mix of income and consumption data points, with both data types sometimes available for particular years.\\n\\nIn most of our charts, we present the data with some data points dropped in order to present single series for each country. This allows us to make readable visualizations that combine multiple countries and metrics. In choosing which data points to drop, we try to strike a balance between maintaining comparability over time and showing as long a time series as possible. As such, the exact approach varies somewhat across countries.\\n\\nIf you would like to see the original data with _all_ available income and consumption data points shown separately, you can do so in our [Incomes Across the Distribution - World Bank Data Explorer](https://ourworldindata.org/explorers/incomes-across-distribution-wb?Indicator=Decile+thresholds&Decile=9+%28richest%29&Household+survey+data+type=Show+data+from+both+income+and+consumption+surveys&Period=Day&Show+breaks+between+less+comparable+surveys=true&country=ROU~CHN~BLR~PER). You can also download this data in our [complete dataset](https://github.com/owid/poverty-data#a-global-dataset-of-poverty-and-inequality-measures-prepared-by-our-world-in-data-from-the-world-banks-poverty-and-inequality-platform-pip-database) of the World Bank PIP data.",
                    "dataPublishedBy": "World Bank (2024). Poverty and Inequality Platform (version 20240326_2017 and 20240326_2011) [Data set]. World Bank Group. https://pip.worldbank.org/. Accessed March 27, 2024.",
                    "colorScaleScheme": "Greens",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (WID data)",
                    "slug": "p0p100_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "Mean income\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (WID data)",
                    "slug": "median_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "This is the level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p10p20_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p20p30_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p30p40_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p40p50_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (WID data)",
                    "slug": "p50p60_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p60p70_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p70p80_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p80p90_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_thr_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_avg_posttax_nat",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_share_posttax_nat",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (WID data)",
                    "slug": "p0p100_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p100_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (WID data)",
                    "slug": "median_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p10p20_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p20p30_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p30p40_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p40p50_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (WID data)",
                    "slug": "p50p60_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p60p70_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p70p80_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p80p90_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_thr_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_thr_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p10_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_avg_posttax_nat_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_avg_posttax_nat 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (WID data)",
                    "slug": "p0p100_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p100_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (WID data)",
                    "slug": "median_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p10p20_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p20p30_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p30p40_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p40p50_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (WID data)",
                    "slug": "p50p60_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p60p70_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p70p80_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p80p90_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_thr_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_thr_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p10_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_avg_posttax_nat_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_avg_posttax_nat 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (WID data)",
                    "slug": "p0p100_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p100_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (WID data)",
                    "slug": "median_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p10p20_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p20p30_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p30p40_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p40p50_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (WID data)",
                    "slug": "p50p60_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p60p70_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p70p80_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p80p90_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_thr_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_thr_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p10_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_avg_posttax_nat_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_avg_posttax_nat 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).\\n\\nIn the case of national post-tax income, when the data sources are not available, distributions are constructed by using the more widely available pre-tax distributions, combined with tax revenue and government expenditure aggregates. This method is described in more detail in this [technical note](https://wid.world/document/preliminary-estimates-of-global-posttax-income-distributions-world-inequality-lab-technical-note-2023-02/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (WID data)",
                    "slug": "p0p100_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "Mean income\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (WID data)",
                    "slug": "median_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "This is the level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p10p20_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p20p30_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p30p40_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p40p50_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (WID data)",
                    "slug": "p50p60_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p60p70_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p70p80_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p80p90_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_thr_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_avg_pretax",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_share_pretax",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The share of income received by the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (WID data)",
                    "slug": "p0p100_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p100_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (WID data)",
                    "slug": "median_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p10p20_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p20p30_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p30p40_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p40p50_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (WID data)",
                    "slug": "p50p60_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p60p70_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p70p80_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p80p90_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_thr_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_thr_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p10_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_avg_pretax_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_avg_pretax 0.00274",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (WID data)",
                    "slug": "p0p100_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p100_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (WID data)",
                    "slug": "median_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p10p20_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p20p30_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p30p40_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p40p50_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (WID data)",
                    "slug": "p50p60_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p60p70_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p70p80_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p80p90_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_thr_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_thr_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p10_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_avg_pretax_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_avg_pretax 0.08333",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (WID data)",
                    "slug": "p0p100_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p100_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (WID data)",
                    "slug": "median_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "This is the level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p10p20_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p20p30_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p30p40_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p40p50_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (WID data)",
                    "slug": "p50p60_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p60p70_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p70p80_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p80p90_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_thr_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_thr_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (WID data)",
                    "slug": "p0p10_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p0p10_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (WID data)",
                    "slug": "p10p20_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p10p20_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (WID data)",
                    "slug": "p20p30_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p20p30_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (WID data)",
                    "slug": "p30p40_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p30p40_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (WID data)",
                    "slug": "p40p50_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p40p50_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (WID data)",
                    "slug": "p50p60_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p50p60_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (WID data)",
                    "slug": "p60p70_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p60p70_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (WID data)",
                    "slug": "p70p80_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p70p80_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (WID data)",
                    "slug": "p80p90_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p80p90_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (WID data)",
                    "slug": "p90p100_avg_pretax_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2023 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy p90p100_avg_pretax 1",
                    "sourceLink": "https://wid.world",
                    "sourceName": "World Inequality Database (WID.world) (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received. It is, however, measured after the operation of pension schemes, both private and public.\\n\\nThe data is measured in international-$ at 2023 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nThe data is estimated from a combination of household surveys, tax records and national accounts data. This combination can provide a more accurate picture of the incomes of the richest, which tend to be captured poorly in household survey data alone.\\n\\nThese underlying data sources are not always available. For some countries, observations are extrapolated from data relating to other years, or are sometimes modeled based on data observed in other countries. For more information on this methodology, see this related [technical note](https://wid.world/document/countries-with-regional-income-imputations-on-wid-world-world-inequality-lab-technical-note-2021-15/).",
                    "dataPublishedBy": "World Inequality Database (WID), https://wid.world",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (LIS data)",
                    "slug": "mean_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000;50000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (LIS data)",
                    "slug": "median_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Blues",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000;50000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "thr_p10_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "thr_p20_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "thr_p30_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "thr_p40_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (LIS data)",
                    "slug": "thr_p50_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "thr_p60_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "thr_p70_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "thr_p80_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "thr_p90_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "avg_p10_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "avg_p20_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "avg_p30_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "avg_p40_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "avg_p50_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "avg_p60_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "avg_p70_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "avg_p80_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "avg_p90_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "avg_p100_dhi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "share_p10_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "share_p20_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "share_p30_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "share_p40_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "share_p50_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "share_p60_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "share_p70_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "share_p80_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "share_p90_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "share_p100_dhi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (LIS data)",
                    "slug": "mean_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (LIS data)",
                    "slug": "median_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "thr_p10_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p10_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "thr_p20_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p20_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "thr_p30_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p30_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "thr_p40_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p40_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (LIS data)",
                    "slug": "thr_p50_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p50_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "thr_p60_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p60_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "thr_p70_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p70_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "thr_p80_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p80_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "thr_p90_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p90_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "avg_p10_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p10_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "avg_p20_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p20_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "avg_p30_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p30_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "avg_p40_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p40_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "avg_p50_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p50_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "avg_p60_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p60_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "avg_p70_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p70_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "avg_p80_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p80_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "avg_p90_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p90_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "avg_p100_dhi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p100_dhi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (LIS data)",
                    "slug": "mean_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (LIS data)",
                    "slug": "median_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "thr_p10_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p10_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "thr_p20_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p20_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "thr_p30_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p30_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "thr_p40_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p40_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (LIS data)",
                    "slug": "thr_p50_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p50_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "thr_p60_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p60_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "thr_p70_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p70_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "thr_p80_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p80_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "thr_p90_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p90_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "avg_p10_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p10_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "avg_p20_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p20_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "avg_p30_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p30_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "avg_p40_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p40_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "avg_p50_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p50_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "avg_p60_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p60_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "avg_p70_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p70_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "avg_p80_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p80_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "avg_p90_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p90_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "avg_p100_dhi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p100_dhi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (LIS data)",
                    "slug": "mean_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (LIS data)",
                    "slug": "median_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "thr_p10_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p10_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "thr_p20_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p20_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "thr_p30_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p30_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "thr_p40_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p40_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (LIS data)",
                    "slug": "thr_p50_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p50_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "thr_p60_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p60_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "thr_p70_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p70_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "thr_p80_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p80_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "thr_p90_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p90_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "avg_p10_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p10_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "avg_p20_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p20_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "avg_p30_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p30_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "avg_p40_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p40_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "avg_p50_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p50_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "avg_p60_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p60_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "avg_p70_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p70_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "avg_p80_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p80_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "avg_p90_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p90_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "avg_p100_dhi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p100_dhi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (LIS data)",
                    "slug": "mean_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000;50000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (LIS data)",
                    "slug": "median_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Blues",
                    "colorScaleNumericBins": "1000;2000;5000;10000;20000;50000",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "thr_p10_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "thr_p20_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "thr_p30_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "thr_p40_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (LIS data)",
                    "slug": "thr_p50_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "thr_p60_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "thr_p70_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "thr_p80_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "thr_p90_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "avg_p10_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "avg_p20_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "avg_p30_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "avg_p40_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "avg_p50_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "avg_p60_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "avg_p70_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "avg_p80_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "avg_p90_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "avg_p100_mi_pc",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "share_p10_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "share_p20_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "share_p30_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "share_p40_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "share_p50_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "share_p60_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "share_p70_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "share_p80_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "share_p90_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "share_p100_mi_pc",
                    "type": "Numeric",
                    "unit": "%",
                    "shortUnit": "%",
                    "tolerance": "5",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The share of income received by the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "OrRd",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (LIS data)",
                    "slug": "mean_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (LIS data)",
                    "slug": "median_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "thr_p10_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p10_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "thr_p20_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p20_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "thr_p30_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p30_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "thr_p40_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p40_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (LIS data)",
                    "slug": "thr_p50_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p50_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "thr_p60_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p60_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "thr_p70_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p70_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "thr_p80_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p80_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "thr_p90_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p90_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "avg_p10_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p10_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "avg_p20_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p20_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "avg_p30_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p30_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "avg_p40_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p40_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "avg_p50_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p50_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "avg_p60_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p60_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "avg_p70_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p70_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "avg_p80_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p80_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "avg_p90_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p90_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "avg_p100_mi_pc_day",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p100_mi_pc 0.00274",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (LIS data)",
                    "slug": "mean_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (LIS data)",
                    "slug": "median_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "thr_p10_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p10_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "thr_p20_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p20_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "thr_p30_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p30_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "thr_p40_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p40_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (LIS data)",
                    "slug": "thr_p50_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p50_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "thr_p60_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p60_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "thr_p70_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p70_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "thr_p80_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p80_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "thr_p90_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p90_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "avg_p10_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p10_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "avg_p20_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p20_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "avg_p30_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p30_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "avg_p40_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p40_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "avg_p50_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p50_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "avg_p60_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p60_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "avg_p70_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p70_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "avg_p80_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p80_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "avg_p90_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p90_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "avg_p100_mi_pc_month",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p100_mi_pc 0.08333",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Mean income (LIS data)",
                    "slug": "mean_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy mean_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "Mean income.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "BuGn",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Median income (LIS data)",
                    "slug": "median_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy median_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which half of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nWe obtain Gini coefficients by using [Stata\u2019s ineqdec0 function](https://ideas.repec.org/c/boc/bocode/s366007.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). We also calculate mean and median values from this function..",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Blues",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "thr_p10_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p10_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 10% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "thr_p20_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p20_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 20% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "thr_p30_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p30_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 30% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "thr_p40_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p40_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 40% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (median) (LIS data)",
                    "slug": "thr_p50_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p50_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 50% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "thr_p60_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p60_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 60% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "thr_p70_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p70_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 70% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "thr_p80_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p80_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 80% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "thr_p90_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy thr_p90_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The level of income below which 90% of the population falls.\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Purples",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Poorest decile (LIS data)",
                    "slug": "avg_p10_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p10_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the poorest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "2nd decile (LIS data)",
                    "slug": "avg_p20_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p20_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 2nd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "3rd decile (LIS data)",
                    "slug": "avg_p30_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p30_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 3rd decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "4th decile (LIS data)",
                    "slug": "avg_p40_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p40_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 4th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "5th decile (LIS data)",
                    "slug": "avg_p50_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p50_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 5th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "6th decile (LIS data)",
                    "slug": "avg_p60_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p60_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 6th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "7th decile (LIS data)",
                    "slug": "avg_p70_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p70_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 7th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "8th decile (LIS data)",
                    "slug": "avg_p80_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p80_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 8th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "9th decile (LIS data)",
                    "slug": "avg_p90_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p90_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the 9th decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                },
                {
                    "name": "Richest decile (LIS data)",
                    "slug": "avg_p100_mi_pc_year",
                    "type": "Numeric",
                    "unit": "international-$ in 2017 prices",
                    "shortUnit": "$",
                    "tolerance": "5",
                    "transform": "multiplyBy avg_p100_mi_pc 1",
                    "sourceLink": "https://www.lisdatacenter.org/our-data/lis-database/",
                    "sourceName": "Luxembourg Income Study (2024)",
                    "description": "The mean income within the richest decile (tenth of the population).\\n\\nIncome is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.\\n\\nIncome is per capita, which means that household income is divided by the total number of household members.\\n\\nThe data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.\\n\\nNOTES ON HOW WE PROCESSED THIS INDICATOR\\n\\nWe create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform.\\n\\nWe obtain after tax income by using the disposable household income variable (`dhi`).\\n\\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\\n\\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\\n\\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\\n\\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\\n\\nIncome shares and thresholds by decile are obtained by using [Stata\u2019s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform.",
                    "dataPublishedBy": "Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; June 2024). Luxembourg: LIS.",
                    "colorScaleScheme": "Greens",
                    "colorScaleEqualSizeBins": "true",
                    "colorScaleNumericMinValue": "0"
                }
            ]
        }
    ],
    "_version": 1,
    "selection": [
        "Chile",
        "Brazil",
        "South Africa",
        "United States",
        "France",
        "China"
    ],
    "wpBlockId": "57742",
    "entityType": "country or region",
    "googleSheet": null,
    "explorerTitle": "Incomes Across the Distribution - World Bank, WID, and LIS",
    "explorerSubtitle": "Compare World Bank, WID, and LIS data on the distribution of incomes.",
    "pickerColumnSlugs": [
        "mean_year median_year p0p100_avg_posttax_nat_year median_posttax_nat_year mean_dhi_pc_year median_dhi_pc_year"
    ]
}

2023-06-23 15:51:09

2024-06-25 11:17:25

Links from other tables

0 rows from explorerSlug in explorer_charts
0 rows from explorerSlug in explorer_variables