variables
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id ▲ | name | unit | description | createdAt | updatedAt | code | coverage | timespan | datasetId | sourceId | shortUnit | display | columnOrder | originalMetadata | grapherConfigAdmin | shortName | catalogPath | dimensions | schemaVersion | processingLevel | processingLog | titlePublic | titleVariant | attributionShort | attribution | descriptionShort | descriptionFromProducer | descriptionKey | descriptionProcessing | licenses | license | grapherConfigETL | type | sort | dataChecksum | metadataChecksum |
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943788 | Richest decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:07 | 2024-07-25 22:56:13 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Richest decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p100_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p100_mi_eq | 2 | major | The mean income per year within the richest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
c62a419ac3f3cdf003722935b05ef96d | 905c092198ee3a73107cf92a5e8969fe | ||||||||||||||||
943787 | Richest decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:07 | 2024-07-25 22:56:13 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Richest decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p100_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p100_dhi_eq | 2 | major | The mean income per year within the richest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
c38272ae2934698dc16da148b2b149a3 | 53ce99ba07f63d886650f0d24ebd44dd | ||||||||||||||||
943786 | Richest decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:13 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Richest decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p100_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p100_mi_pc | 2 | major | The mean income per year within the richest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
5ee5bdce6ea018ab0d1af67899db9779 | 2bd731c9e65e695a400fa93d9e6e7de3 | ||||||||||||||||
943785 | Richest decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:13 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Richest decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p100_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p100_dhi_pc | 2 | major | The mean income per year within the richest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
3165dac3ea3e791b3a77f9e1574252b4 | ebb51b9024e94a74aca237f66da9976f | ||||||||||||||||
943784 | Richest decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:13 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Richest decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p100_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p100_dhci_pc | 2 | major | The mean income per year within the richest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
ddf203e3e97c3ceb931e3abb71d16d06 | 894d55b14d858e46302e64ee57f3e116 | ||||||||||||||||
943783 | Richest decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:13 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Richest decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p100_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p100_dhci_eq | 2 | major | The mean income per year within the richest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
02239ca3868fd9266925fadbe61e4002 | 6fed3b8bb40eccad9692228d79948940 | ||||||||||||||||
943782 | 9th decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "9th decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p90_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p90_dhi_eq | 2 | major | The mean income per year within the 9th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
493f5abb860bda35f5a78b759390f6c5 | 5cc902053a35aca3a152825586737cf0 | ||||||||||||||||
943781 | 9th decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "9th decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p90_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p90_mi_eq | 2 | major | The mean income per year within the 9th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
e3247e1942aec0f44f81e606b1f215de | fb711f3f7062c037a20d3fc9dc57d8a5 | ||||||||||||||||
943780 | 9th decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "9th decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p90_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p90_dhi_pc | 2 | major | The mean income per year within the 9th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
feea48c274fd3f4276f8c9404d383154 | eabe78822c20453d8963cea28499487d | ||||||||||||||||
943779 | 9th decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "9th decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p90_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p90_mi_pc | 2 | major | The mean income per year within the 9th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
cf07aafbf4caf79122d05bff9d799539 | a03b62aa4ddffc4d99c0bd1c65a81bed | ||||||||||||||||
943778 | 9th decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "9th decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p90_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p90_dhci_eq | 2 | major | The mean income per year within the 9th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
cd932b4de330566167f12cf97bdfefbf | cad013e6777a02508061a07a207fde5e | ||||||||||||||||
943777 | 9th decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "9th decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p90_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p90_dhci_pc | 2 | major | The mean income per year within the 9th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
7cfcb52395866f568053094be70ff9fe | 45a4f4a2affde064bf5d83371531e9f9 | ||||||||||||||||
943776 | 8th decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "8th decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p80_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p80_mi_eq | 2 | major | The mean income per year within the 8th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
e133ce67a20fbdcdbb4d41dfbbb37809 | 546687df10ba8a383443be4b7387676c | ||||||||||||||||
943775 | 8th decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "8th decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p80_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p80_dhi_eq | 2 | major | The mean income per year within the 8th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
da60d1a77b48be19544a024360745aa3 | ecd8a1c22face8e37235c09efdb304a2 | ||||||||||||||||
943774 | 8th decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "8th decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p80_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p80_dhi_pc | 2 | major | The mean income per year within the 8th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
fb972b6bd0ed66d3762811eb6c42a541 | 28c1e42bf6229c5ade7af1b27aff801a | ||||||||||||||||
943773 | 8th decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "8th decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p80_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p80_mi_pc | 2 | major | The mean income per year within the 8th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
5bec3c0fad58b70f68110a5f705a259b | c929d418071e51fc706d3b3ca071a2e9 | ||||||||||||||||
943772 | 8th decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "8th decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p80_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p80_dhci_eq | 2 | major | The mean income per year within the 8th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
8d572baa4167ad81d09ecd64263515c8 | 49544b0003ede97741d6776add745fcf | ||||||||||||||||
943771 | 8th decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:06 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "8th decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p80_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p80_dhci_pc | 2 | major | The mean income per year within the 8th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
a918804d1d808341e420645195375732 | 98ec59a02f7a3109f4db9e1788616ec7 | ||||||||||||||||
943770 | 7th decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "7th decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p70_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p70_dhi_eq | 2 | major | The mean income per year within the 7th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
1b5d76a15ccc6b65fb70a1ae35302dff | 9e9cad94a07cab4abba5777bb3aadef0 | ||||||||||||||||
943769 | 7th decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "7th decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p70_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p70_mi_eq | 2 | major | The mean income per year within the 7th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
750ff7a6d2a89f64b8962c595c17a8e3 | f68e331d162c716584b28ea07cee001e | ||||||||||||||||
943768 | 7th decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "7th decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p70_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p70_dhci_eq | 2 | major | The mean income per year within the 7th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
bdc0542a5bc70923be844708e6e922d6 | 2f3542a0c024ac3501c6514fae0d7b9c | ||||||||||||||||
943767 | 7th decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "7th decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p70_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p70_mi_pc | 2 | major | The mean income per year within the 7th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
49e1f517b44113887caadf878dfb7705 | 622cc8feeccf2336b068808c1a5e740b | ||||||||||||||||
943766 | 7th decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "7th decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p70_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p70_dhi_pc | 2 | major | The mean income per year within the 7th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
71ef2becfe5045f29035b9990ff9fc6d | dbfbdd723aa3461f17b8cf557bef5818 | ||||||||||||||||
943765 | 7th decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "7th decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p70_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p70_dhci_pc | 2 | major | The mean income per year within the 7th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
b28dd3b4723bae3726cb0347d7fb23f4 | 1e8ac4e835171b8d28180f6572eddf29 | ||||||||||||||||
943764 | 6th decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "6th decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p60_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p60_dhi_pc | 2 | major | The mean income per year within the 6th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
e1519ffb1f9b755c384b2c3cf3984156 | 0a3a4b37ae51d6009d79093ebefe97fb | ||||||||||||||||
943763 | 6th decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "6th decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p60_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p60_dhi_eq | 2 | major | The mean income per year within the 6th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
f0199d79de4aedac9462675de5b091f9 | 0dfa8e9fbe5492d2540281213254d109 | ||||||||||||||||
943762 | 6th decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "6th decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p60_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p60_mi_eq | 2 | major | The mean income per year within the 6th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
16570b62b73cd2e85ca091aa0db9baf3 | 9b5cc67a7fac992e34f2bfe85c5b1936 | ||||||||||||||||
943761 | 6th decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "6th decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p60_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p60_dhci_eq | 2 | major | The mean income per year within the 6th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
6db2da531c3f54f0db91864caa1a4f79 | 1240b822608094133824518c1078b358 | ||||||||||||||||
943760 | 6th decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "6th decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p60_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p60_mi_pc | 2 | major | The mean income per year within the 6th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
f8b0d2d66902d002f364c8560aa7bc5c | fa1e9fbdbf6d512d8eea12b3827c935d | ||||||||||||||||
943759 | 6th decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:12 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "6th decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p60_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p60_dhci_pc | 2 | major | The mean income per year within the 6th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
6b29bbd33262d32bf222dcb4226c4928 | b2d3c1bebf9753b7758a586538c8a1be | ||||||||||||||||
943758 | 5th decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:11 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "5th decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p50_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p50_mi_eq | 2 | major | The mean income per year within the 5th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
d35664e97fceb622af3617969e7a40d7 | 97fab1c0a79e278bf5eb918eb24e6b46 | ||||||||||||||||
943757 | 5th decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:11 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "5th decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p50_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p50_mi_pc | 2 | major | The mean income per year within the 5th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
06802f71e51742d8ce4e9af7fd4266ce | 041727e8226dadaa1237717898da0856 | ||||||||||||||||
943756 | 5th decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "5th decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p50_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p50_dhi_eq | 2 | major | The mean income per year within the 5th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
b2054d33347769117758c267df2be212 | 956c67099d4cd2adff6c827864d6ccb4 | ||||||||||||||||
943755 | 5th decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:05 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "5th decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p50_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p50_dhi_pc | 2 | major | The mean income per year within the 5th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
caf75886d2e0fb834eca9d164d616e75 | ad20112239d9b6657158c434a85a98ed | ||||||||||||||||
943754 | 5th decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "5th decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p50_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p50_dhci_eq | 2 | major | The mean income per year within the 5th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
9e0f0e9754a1173cf17f41a22351ae3d | 3aa39dcb99c61ba244552c31f5376aeb | ||||||||||||||||
943753 | 5th decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "5th decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p50_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p50_dhci_pc | 2 | major | The mean income per year within the 5th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
d38cd9a0ce424d6502b307ebec4601f1 | b26852622bc252e8d5e431ed8895e4c1 | ||||||||||||||||
943752 | 4th decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "4th decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p40_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p40_dhi_eq | 2 | major | The mean income per year within the 4th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
78ffd4adce99c245990aef1481913c01 | 48841e2aee070733c504d318a285ef1b | ||||||||||||||||
943751 | 4th decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "4th decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p40_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p40_mi_pc | 2 | major | The mean income per year within the 4th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
925d8062e73e0a1f3975f58c31aa14ae | e7a793e999be6022bc834bc6f21939db | ||||||||||||||||
943750 | 4th decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "4th decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p40_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p40_mi_eq | 2 | major | The mean income per year within the 4th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
ce26e3f341ef1c4a79f6e1680b0c2553 | 455d7bfe0e095b23a978f0ff0b8aa8b6 | ||||||||||||||||
943749 | 4th decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "4th decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p40_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p40_dhi_pc | 2 | major | The mean income per year within the 4th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
14bdeaeda8e75a9febd87cc9396dc0d7 | 41509931ff8cf810145782eed75a720b | ||||||||||||||||
943748 | 4th decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "4th decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p40_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p40_dhci_eq | 2 | major | The mean income per year within the 4th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
c37097e4937bd1cf9ab7fed5250ae8ec | 7d398c4be76d0133014eb8dbc1706d53 | ||||||||||||||||
943747 | 4th decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "4th decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p40_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p40_dhci_pc | 2 | major | The mean income per year within the 4th decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
5db11cd83f141e91e20b9898ae8e3d95 | 31f93a59080f96d5642a2120ff5c6881 | ||||||||||||||||
943746 | 3rd decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "3rd decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p30_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p30_dhi_pc | 2 | major | The mean income per year within the 3rd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
d4d12c7db972bc7093bcbc91ae70f3d5 | 3c87bd8b32d78c7db5f55e0d03938963 | ||||||||||||||||
943745 | 3rd decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "3rd decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p30_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p30_dhi_eq | 2 | major | The mean income per year within the 3rd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
0399e55a9eb19ee840c8802fbd2d4891 | 0e67f08e8bf8ed326cbe73a92e225f1a | ||||||||||||||||
943744 | 3rd decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "3rd decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p30_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p30_mi_eq | 2 | major | The mean income per year within the 3rd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
c4c874cb4b537909dcf635902bfb673e | 4bb9b42b03e021d16aae8d3ae58635aa | ||||||||||||||||
943743 | 3rd decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "3rd decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p30_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p30_mi_pc | 2 | major | The mean income per year within the 3rd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
63dfa7bbe1251b0ad30df7cb54e24f50 | f6c0c939663d6fce8eb53d351b300483 | ||||||||||||||||
943742 | 3rd decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "3rd decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p30_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p30_dhci_pc | 2 | major | The mean income per year within the 3rd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
59d49f73f5caef8cdd77033c9b3ae0c5 | 62f750cf3af4423bc566f6f038f24758 | ||||||||||||||||
943741 | 3rd decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "3rd decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p30_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p30_dhci_eq | 2 | major | The mean income per year within the 3rd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
6aa479b0da123347325489c22e758da5 | 5604a2f7c346af70656ccf3d73655e60 | ||||||||||||||||
943740 | 2nd decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:04 | 2024-07-25 22:56:11 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "2nd decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p20_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p20_mi_eq | 2 | major | The mean income per year within the 2nd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
ae3bc7d45225224b6085a4b995fabefd | 345c0dc48f4612e57240f2ca15ea9e6d | ||||||||||||||||
943739 | 2nd decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "2nd decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p20_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p20_dhi_pc | 2 | major | The mean income per year within the 2nd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
8fc0de225a7f4b73221bd8ef91fad858 | 2007970f773e00dfa4dbb8aa0039c121 | ||||||||||||||||
943738 | 2nd decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:11 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "2nd decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p20_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p20_dhi_eq | 2 | major | The mean income per year within the 2nd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
f904248f6e0104730c0a07b88f2cb0c6 | 722b29e567fc293cbbb082e88fe81ec0 | ||||||||||||||||
943737 | 2nd decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "2nd decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p20_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p20_dhci_eq | 2 | major | The mean income per year within the 2nd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
80ae2e0dd698ff65bd434a6cbad6eb01 | 8adfd05f117b61fc706c575b8efa3bb3 | ||||||||||||||||
943736 | 2nd decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "2nd decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p20_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p20_mi_pc | 2 | major | The mean income per year within the 2nd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
c34f1a0a7fcc6e2a68a4e7b6e8bfd650 | f05fce3c75b13773faffc0f46655ce9c | ||||||||||||||||
943735 | 2nd decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "2nd decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p20_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p20_dhci_pc | 2 | major | The mean income per year within the 2nd decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
4d770f4331d2e61b9a3e45c35931acfe | 6d47e09db05b859af35f62c78ceb42d3 | ||||||||||||||||
943734 | Poorest decile - Average (Disposable household income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Poorest decile - Average (Disposable household income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p10_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p10_dhi_eq | 2 | major | The mean income per year within the poorest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
2de9191e88b861b7948ba316a2f4bdff | b092b2c9fa47822017d833853a1a66eb | ||||||||||||||||
943733 | Poorest decile - Average (Market income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Poorest decile - Average (Market income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p10_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p10_mi_eq | 2 | major | The mean income per year within the poorest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
027aaf4c8548b86bd560b77befb0ee1d | 03825d6502f123d8e250d451b8370681 | ||||||||||||||||
943732 | Poorest decile - Average (Market income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Poorest decile - Average (Market income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p10_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p10_mi_pc | 2 | major | The mean income per year within the poorest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
a8353bcc38363e01a21899840571b4ca | 9cff0be794e594b02662475c8c1228ce | ||||||||||||||||
943731 | Poorest decile - Average (Disposable household cash income, equivalized) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Poorest decile - Average (Disposable household cash income, equivalized)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p10_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p10_dhci_eq | 2 | major | The mean income per year within the poorest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
c8c8f40d7d6780b73d0a229743062ee0 | 1ed69a06535bb43488633c8c45d8d238 | ||||||||||||||||
943730 | Poorest decile - Average (Disposable household income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Poorest decile - Average (Disposable household income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p10_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p10_dhi_pc | 2 | major | The mean income per year within the poorest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
0857027851c0c50534edbf969d1e8edd | dfaf56068e199299a79d13ba8ce0696c | ||||||||||||||||
943729 | Share of the middle 40% (Disposable household cash income, equivalized) | % | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the middle 40% (Disposable household cash income, equivalized)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_middle40_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_middle40_dhci_eq | 2 | major | The share of income received by the middle 40%. The middle 40% is the share of the population whose income lies between the poorest 50% and the richest 10%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
56b13f865d31a089b24e720be43e8876 | ab5a64fec3508dc0078e6172fd02df8d | ||||||||||||||||
943728 | Poorest decile - Average (Disposable household cash income, per capita) | international-$ in 2017 prices | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | $ | { "name": "Poorest decile - Average (Disposable household cash income, per capita)", "unit": "international-$ in 2017 prices", "shortUnit": "$", "tolerance": 5, "numDecimalPlaces": 0 } |
0 | avg_p10_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#avg_p10_dhci_pc | 2 | major | The mean income per year within the poorest decile (tenth of the population). | [ "The data is measured in international-$ at 2017 prices \u2013 this adjusts for inflation and for differences in the cost of living between countries.", "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. Income shares and thresholds by decile are obtained by using [Stata’s sumdist function](https://ideas.repec.org/c/boc/bocode/s366005.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt) and the number of quantile groups as 10. We estimate threshold ratios, share ratios and averages by decile in Python after processing in the LISSY platform. | float | [] |
a241fdc2c833ab57e42c7313dd0373e7 | 4b1bec77cf08cac0561902232c6814ab | ||||||||||||||||
943727 | Share of the middle 40% (Disposable household income, per capita) | % | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the middle 40% (Disposable household income, per capita)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_middle40_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_middle40_dhi_pc | 2 | major | The share of income received by the middle 40%. The middle 40% is the share of the population whose income lies between the poorest 50% and the richest 10%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
b6786204d1334007722411f7837ad285 | 0d4410d399818018f9affd0d963cb64e | ||||||||||||||||
943726 | Share of the middle 40% (Disposable household income, equivalized) | % | 2024-06-25 14:17:03 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the middle 40% (Disposable household income, equivalized)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_middle40_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_middle40_dhi_eq | 2 | major | The share of income received by the middle 40%. The middle 40% is the share of the population whose income lies between the poorest 50% and the richest 10%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
e330176136c0a92a15b3e542f387e44f | 989ed6399e876c20a3cb986fb2e8183d | ||||||||||||||||
943725 | Share of the middle 40% (Market income, equivalized) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:10 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the middle 40% (Market income, equivalized)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_middle40_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_middle40_mi_eq | 2 | major | The share of income received by the middle 40%. The middle 40% is the share of the population whose income lies between the poorest 50% and the richest 10%. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
e8a87a5aa279577d3f2ef557693a59f0 | dcf5f40469f9f71bd97c1397b8a57eda | ||||||||||||||||
943724 | Share of the middle 40% (Market income, per capita) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:10 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the middle 40% (Market income, per capita)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_middle40_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_middle40_mi_pc | 2 | major | The share of income received by the middle 40%. The middle 40% is the share of the population whose income lies between the poorest 50% and the richest 10%. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
47b3030e8b66be99d237346da255ac8f | 4ccc79bf7ccc21eaef9dca0eb7e57ebe | ||||||||||||||||
943723 | Share of the middle 40% (Disposable household cash income, per capita) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the middle 40% (Disposable household cash income, per capita)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_middle40_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_middle40_dhci_pc | 2 | major | The share of income received by the middle 40%. The middle 40% is the share of the population whose income lies between the poorest 50% and the richest 10%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
8416172fee9e15cdcc10b9603ba2a7b6 | 9ccdbd46748ae8a192d2bee568c68cd3 | ||||||||||||||||
943722 | Share of the bottom 50% (Market income, equivalized) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:10 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the bottom 50% (Market income, equivalized)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_bottom50_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_bottom50_mi_eq | 2 | major | The share of income received by the poorest 50%. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
c9e7b911543e201e9bcca4e66fee5ffd | 1b663d814ee7216c69f0151a7b2ed972 | ||||||||||||||||
943721 | Share of the bottom 50% (Market income, per capita) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:10 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the bottom 50% (Market income, per capita)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_bottom50_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_bottom50_mi_pc | 2 | major | The share of income received by the poorest 50%. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
68487b93bc3cb236466b6459da0e0b03 | a1779601351a12972b552fae5604704f | ||||||||||||||||
943720 | Share of the bottom 50% (Disposable household income, equivalized) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the bottom 50% (Disposable household income, equivalized)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_bottom50_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_bottom50_dhi_eq | 2 | major | The share of income received by the poorest 50%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
6551d2b2f583b1b1d24e0ee3cadc8ea8 | 3df47b051c40e1b8cbd77160fb6a2cbf | ||||||||||||||||
943719 | Share of the bottom 50% (Disposable household cash income, per capita) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the bottom 50% (Disposable household cash income, per capita)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_bottom50_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_bottom50_dhci_pc | 2 | major | The share of income received by the poorest 50%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
8416ea0c0f03bb58496a76159b3a0e96 | 3311b1e8bfcfe0fc31bd79b33ce221df | ||||||||||||||||
943718 | Share of the bottom 50% (Disposable household income, per capita) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:10 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the bottom 50% (Disposable household income, per capita)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_bottom50_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_bottom50_dhi_pc | 2 | major | The share of income received by the poorest 50%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
6660aa4a9b16e95bc8708f953ef40a2b | 6e296215ae3918986925083ddf067142 | ||||||||||||||||
943717 | Share of the bottom 50% (Disposable household cash income, equivalized) | % | 2024-06-25 14:17:02 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | % | { "name": "Share of the bottom 50% (Disposable household cash income, equivalized)", "unit": "%", "shortUnit": "%", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | share_bottom50_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#share_bottom50_dhci_eq | 2 | major | The share of income received by the poorest 50%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
0f8bd75721bdc29c98c3f35635ed3688 | c55e429b2d810fda63bd5dc4263f5232 | ||||||||||||||||
943716 | P50/P10 ratio (Disposable household income, equivalized) | 2024-06-25 14:17:02 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P50/P10 ratio (Disposable household income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p50_p10_ratio_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p50_p10_ratio_dhi_eq | 2 | major | The P50/P10 ratio measures the degree of inequality within the poorest half of the population. A ratio of 2 means that the median income is two times higher than that of someone just falling in the poorest tenth of the population. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
dc63ac5ea0c9a6d5ebce573065f883ac | ab25bbd6a594aa5dbcf42028bf0dd1a0 | ||||||||||||||||||
943715 | P50/P10 ratio (Market income, per capita) | 2024-06-25 14:17:02 | 2024-07-25 22:56:09 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P50/P10 ratio (Market income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p50_p10_ratio_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p50_p10_ratio_mi_pc | 2 | major | The P50/P10 ratio measures the degree of inequality within the poorest half of the population. A ratio of 2 means that the median income is two times higher than that of someone just falling in the poorest tenth of the population. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
821ba62dbb6ffee26be407488fc2d6d6 | ccf417070433bd6e685a57d513a8548c | ||||||||||||||||||
943714 | P50/P10 ratio (Market income, equivalized) | 2024-06-25 14:17:02 | 2024-07-25 22:56:09 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P50/P10 ratio (Market income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p50_p10_ratio_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p50_p10_ratio_mi_eq | 2 | major | The P50/P10 ratio measures the degree of inequality within the poorest half of the population. A ratio of 2 means that the median income is two times higher than that of someone just falling in the poorest tenth of the population. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
e9293c7e45e4d95225955020b29eecbc | 7c65e7e57af6cc42d3fbc0df8b0a85c7 | ||||||||||||||||||
943713 | P50/P10 ratio (Disposable household income, per capita) | 2024-06-25 14:17:02 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P50/P10 ratio (Disposable household income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p50_p10_ratio_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p50_p10_ratio_dhi_pc | 2 | major | The P50/P10 ratio measures the degree of inequality within the poorest half of the population. A ratio of 2 means that the median income is two times higher than that of someone just falling in the poorest tenth of the population. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
e5429f5c3e92e913a3a0856539c30a25 | fbd4ee100c6e3bbfdf607ddc9b5aa13c | ||||||||||||||||||
943712 | P50/P10 ratio (Disposable household cash income, equivalized) | 2024-06-25 14:17:02 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P50/P10 ratio (Disposable household cash income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p50_p10_ratio_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p50_p10_ratio_dhci_eq | 2 | major | The P50/P10 ratio measures the degree of inequality within the poorest half of the population. A ratio of 2 means that the median income is two times higher than that of someone just falling in the poorest tenth of the population. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
d0ee27176b05905dbacc70f06bdf3bf7 | 74c5eedb980a5986073679c27538f4c4 | ||||||||||||||||||
943711 | P50/P10 ratio (Disposable household cash income, per capita) | 2024-06-25 14:17:02 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P50/P10 ratio (Disposable household cash income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p50_p10_ratio_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p50_p10_ratio_dhci_pc | 2 | major | The P50/P10 ratio measures the degree of inequality within the poorest half of the population. A ratio of 2 means that the median income is two times higher than that of someone just falling in the poorest tenth of the population. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
799a9410d9fd02133890bb4678b4d757 | 6882468594d57db3aee0daf08b45c177 | ||||||||||||||||||
943710 | P90/P50 ratio (Disposable household income, equivalized) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P50 ratio (Disposable household income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p50_ratio_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p50_ratio_dhi_eq | 2 | major | The P90/P50 ratio measures the degree of inequality within the richest half of the population. A ratio of 2 means that someone just falling in the richest tenth of the population has twice the median income. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
8a353b47e43a6569456297b20b37c68f | 41122d7de07108d415ed341643e659e5 | ||||||||||||||||||
943709 | P90/P50 ratio (Market income, equivalized) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P50 ratio (Market income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p50_ratio_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p50_ratio_mi_eq | 2 | major | The P90/P50 ratio measures the degree of inequality within the richest half of the population. A ratio of 2 means that someone just falling in the richest tenth of the population has twice the median income. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
53aa874e76a0d314d74967d08b8d2c79 | 90bc0fd6e9f40bb50056edd3289a2232 | ||||||||||||||||||
943708 | P90/P50 ratio (Market income, per capita) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P50 ratio (Market income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p50_ratio_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p50_ratio_mi_pc | 2 | major | The P90/P50 ratio measures the degree of inequality within the richest half of the population. A ratio of 2 means that someone just falling in the richest tenth of the population has twice the median income. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
dc7ce1870483989ddf1be6617f29dd9c | 4006df38dda3b4fa6a2771bec3508843 | ||||||||||||||||||
943707 | P90/P50 ratio (Disposable household cash income, equivalized) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P50 ratio (Disposable household cash income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p50_ratio_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p50_ratio_dhci_eq | 2 | major | The P90/P50 ratio measures the degree of inequality within the richest half of the population. A ratio of 2 means that someone just falling in the richest tenth of the population has twice the median income. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
00c32c1ca2270c81c1ba14bdd11103b9 | dced4b4acdfa4b2a7d3e278c4addfd5c | ||||||||||||||||||
943706 | P90/P50 ratio (Disposable household income, per capita) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P50 ratio (Disposable household income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p50_ratio_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p50_ratio_dhi_pc | 2 | major | The P90/P50 ratio measures the degree of inequality within the richest half of the population. A ratio of 2 means that someone just falling in the richest tenth of the population has twice the median income. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
0f412a81e5345e4b4d80a2a380db8bf3 | a5ef1614fb15df97296b00f971a4f110 | ||||||||||||||||||
943705 | P90/P50 ratio (Disposable household cash income, per capita) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P50 ratio (Disposable household cash income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p50_ratio_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p50_ratio_dhci_pc | 2 | major | The P90/P50 ratio measures the degree of inequality within the richest half of the population. A ratio of 2 means that someone just falling in the richest tenth of the population has twice the median income. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
8b184993969a4249d979cd6948af96f5 | a4a158b5beb7638cc95f9d860b7ba667 | ||||||||||||||||||
943704 | P90/P10 ratio (Disposable household income, equivalized) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P10 ratio (Disposable household income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p10_ratio_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p10_ratio_dhi_eq | 2 | major | P90 and P10 are the levels of income below which 90% and 10% of the population live, respectively. This variable gives the ratio of the two. It is a measure of inequality that indicates the gap between the richest and poorest tenth of the population. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
98bf3a4c49d4349efa4540b47088c74f | e3a5f9f609bfeccd7a4501271cd51985 | ||||||||||||||||||
943703 | P90/P10 ratio (Market income, equivalized) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P10 ratio (Market income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p10_ratio_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p10_ratio_mi_eq | 2 | major | P90 and P10 are the levels of income below which 90% and 10% of the population live, respectively. This variable gives the ratio of the two. It is a measure of inequality that indicates the gap between the richest and poorest tenth of the population. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
b928398683284cde892004fe252f7a6c | 93207dfc027b8e0cff64039f7989f563 | ||||||||||||||||||
943702 | P90/P10 ratio (Market income, per capita) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P10 ratio (Market income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p10_ratio_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p10_ratio_mi_pc | 2 | major | P90 and P10 are the levels of income below which 90% and 10% of the population live, respectively. This variable gives the ratio of the two. It is a measure of inequality that indicates the gap between the richest and poorest tenth of the population. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
e449b85227d6e3cdcbc5d93ba38e4337 | 4cdd145a7ab57f08c176d98f2d2843fb | ||||||||||||||||||
943701 | P90/P10 ratio (Disposable household cash income, equivalized) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P10 ratio (Disposable household cash income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p10_ratio_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p10_ratio_dhci_eq | 2 | major | P90 and P10 are the levels of income below which 90% and 10% of the population live, respectively. This variable gives the ratio of the two. It is a measure of inequality that indicates the gap between the richest and poorest tenth of the population. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
7552bf0701af2c15189cc0a58d16174b | 2f2ec99f1ecca31a38834996472ece1c | ||||||||||||||||||
943700 | P90/P10 ratio (Disposable household income, per capita) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P10 ratio (Disposable household income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p10_ratio_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p10_ratio_dhi_pc | 2 | major | P90 and P10 are the levels of income below which 90% and 10% of the population live, respectively. This variable gives the ratio of the two. It is a measure of inequality that indicates the gap between the richest and poorest tenth of the population. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
a7185b7f148cf33e7a1a7f58d06b188e | 59eb49a67473e65a78a4bc6d71104fe7 | ||||||||||||||||||
943699 | P90/P10 ratio (Disposable household cash income, per capita) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "P90/P10 ratio (Disposable household cash income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | p90_p10_ratio_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#p90_p10_ratio_dhci_pc | 2 | major | P90 and P10 are the levels of income below which 90% and 10% of the population live, respectively. This variable gives the ratio of the two. It is a measure of inequality that indicates the gap between the richest and poorest tenth of the population. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
15134b1078430aaa222f54ec748be1a2 | 5575d53545c85a7951156231816e2a7d | ||||||||||||||||||
943698 | S80/S20 ratio (Market income, equivalized) | 2024-06-25 14:17:01 | 2024-07-25 22:56:09 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "S80/S20 ratio (Market income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | s80_s20_ratio_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#s80_s20_ratio_mi_eq | 2 | major | The S80/S20 ratio is the share of total income of the top 20% divided by the share of the bottom 20%. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
eb52daab6d25a78a486b91bb378375e6 | f7e01049eeb8b19c9d28901976165cb7 | ||||||||||||||||||
943697 | S80/S20 ratio (Disposable household income, equivalized) | 2024-06-25 14:17:00 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "S80/S20 ratio (Disposable household income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | s80_s20_ratio_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#s80_s20_ratio_dhi_eq | 2 | major | The S80/S20 ratio is the share of total income of the top 20% divided by the share of the bottom 20%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
b448795ac85076a66234d55e47ed84a7 | b2b233e5ab08827b6da0277077038cd1 | ||||||||||||||||||
943696 | S80/S20 ratio (Disposable household cash income, equivalized) | 2024-06-25 14:17:00 | 2024-07-25 22:56:08 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "S80/S20 ratio (Disposable household cash income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | s80_s20_ratio_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#s80_s20_ratio_dhci_eq | 2 | major | The S80/S20 ratio is the share of total income of the top 20% divided by the share of the bottom 20%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
82d2d3b24e3ac768e6b84c708a942616 | b899b574a918b2fdf864976060f2f344 | ||||||||||||||||||
943695 | S80/S20 ratio (Disposable household income, per capita) | 2024-06-25 14:17:00 | 2024-07-25 22:56:08 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "S80/S20 ratio (Disposable household income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | s80_s20_ratio_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#s80_s20_ratio_dhi_pc | 2 | major | The S80/S20 ratio is the share of total income of the top 20% divided by the share of the bottom 20%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
10b3ca7ee78383cdcc812321c6ae624b | 4c93b854181d2b366b86c283080c5b50 | ||||||||||||||||||
943694 | S80/S20 ratio (Market income, per capita) | 2024-06-25 14:17:00 | 2024-07-25 22:56:09 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "S80/S20 ratio (Market income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | s80_s20_ratio_mi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#s80_s20_ratio_mi_pc | 2 | major | The S80/S20 ratio is the share of total income of the top 20% divided by the share of the bottom 20%. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
dde424dfff02a3e2e91a39822103330d | 94b4a89b1346fc8c0a2e093f59b6326c | ||||||||||||||||||
943693 | S80/S20 ratio (Disposable household cash income, per capita) | 2024-06-25 14:17:00 | 2024-07-25 22:56:09 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "S80/S20 ratio (Disposable household cash income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | s80_s20_ratio_dhci_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#s80_s20_ratio_dhci_pc | 2 | major | The S80/S20 ratio is the share of total income of the top 20% divided by the share of the bottom 20%. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
98bf4109b39baebd84787c9796031ee6 | 38fc97d46febd5bd415fc6ae17993359 | ||||||||||||||||||
943692 | Palma ratio (Disposable household income, per capita) | 2024-06-25 14:17:00 | 2024-07-25 22:56:08 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "Palma ratio (Disposable household income, per capita)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | palma_ratio_dhi_pc | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#palma_ratio_dhi_pc | 2 | major | The Palma ratio is a measure of inequality that divides the share received by the richest 10% by the share of the poorest 40%. Higher values indicate higher inequality. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income is per capita, which means that each person (including children) is attributed an equal share of the total income received by all members of their household." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
3ee3da90fbdcdb855379e949eb4d5dc4 | 596f244d8f69df8a4ef778b3091b7d29 | ||||||||||||||||||
943691 | Palma ratio (Disposable household income, equivalized) | 2024-06-25 14:17:00 | 2024-07-25 22:56:08 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "Palma ratio (Disposable household income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | palma_ratio_dhi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#palma_ratio_dhi_eq | 2 | major | The Palma ratio is a measure of inequality that divides the share received by the richest 10% by the share of the poorest 40%. Higher values indicate higher inequality. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
8547abcf9a554d9c1d13f00e33160eca | d414b12875dca95ba51bab00ce0e56d8 | ||||||||||||||||||
943690 | Palma ratio (Market income, equivalized) | 2024-06-25 14:17:00 | 2024-07-25 22:56:08 | 1968-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "Palma ratio (Market income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | palma_ratio_mi_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#palma_ratio_mi_eq | 2 | major | The Palma ratio is a measure of inequality that divides the share received by the richest 10% by the share of the poorest 40%. Higher values indicate higher inequality. | [ "Income is \u2018pre-tax\u2019 \u2014 measured before taxes have been paid and most government benefits have been received.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
2f3c193575fb4873ad25fcbf27af70f9 | 07466139f9909926d35f3a920e9de1ea | ||||||||||||||||||
943689 | Palma ratio (Disposable household cash income, equivalized) | 2024-06-25 14:17:00 | 2024-07-25 22:56:08 | 1963-2022 | Luxembourg Income Study (LIS) 6582 | { "name": "Palma ratio (Disposable household cash income, equivalized)", "tolerance": 5, "numDecimalPlaces": 1 } |
0 | palma_ratio_dhci_eq | grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#palma_ratio_dhci_eq | 2 | major | The Palma ratio is a measure of inequality that divides the share received by the richest 10% by the share of the poorest 40%. Higher values indicate higher inequality. | [ "Income is \u2018post-tax\u2019 \u2014 measured after taxes have been paid and most government benefits have been received and excluding fringe benefits, home production, in-kind benefits and transfers.", "Income has been equivalized \u2013 adjusted to account for the fact that people in the same household can share costs like rent and heating." ] |
We create the Luxembourg Income Study data from standardized household survey microdata available in their [LISSY platform](https://www.lisdatacenter.org/data-access/lissy/). The estimations follow the methodology available in LIS, Key Figures and DART platform. We obtain after tax income by using the disposable household income variable (`dhi`). We estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed. We obtain after tax income (cash) by using the disposable household cash income variable (`dhci`). We convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform. We top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range. We equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members. We obtain Gini coefficients by using [Stata’s 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. | float | [] |
33c95aade78c68b44d447e12e15b149d | 15a2a9322021fa784844cd95ff3573d4 |
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CREATE TABLE "variables" ( "id" INTEGER PRIMARY KEY AUTOINCREMENT, "name" VARCHAR(750) NULL , "unit" VARCHAR(255) NOT NULL , "description" TEXT NULL , "createdAt" DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP , "updatedAt" DATETIME NULL , "code" VARCHAR(255) NULL , "coverage" VARCHAR(255) NOT NULL , "timespan" VARCHAR(255) NOT NULL , "datasetId" INTEGER NOT NULL , "sourceId" INTEGER NULL , "shortUnit" VARCHAR(255) NULL , "display" TEXT NOT NULL , "columnOrder" INTEGER NOT NULL DEFAULT '0' , "originalMetadata" TEXT NULL , "grapherConfigAdmin" TEXT NULL , "shortName" VARCHAR(255) NULL , "catalogPath" VARCHAR(767) NULL , "dimensions" TEXT NULL , "schemaVersion" INTEGER NOT NULL DEFAULT '1' , "processingLevel" VARCHAR(30) NULL , "processingLog" TEXT NULL , "titlePublic" VARCHAR(512) NULL , "titleVariant" VARCHAR(255) NULL , "attributionShort" VARCHAR(512) NULL , "attribution" TEXT NULL , "descriptionShort" TEXT NULL , "descriptionFromProducer" TEXT NULL , "descriptionKey" TEXT NULL , "descriptionProcessing" TEXT NULL , "licenses" TEXT NULL , "license" TEXT NULL , "grapherConfigETL" TEXT NULL , "type" TEXT NULL , "sort" TEXT NULL , "dataChecksum" VARCHAR(64) NULL , "metadataChecksum" VARCHAR(64) NULL, FOREIGN KEY("datasetId") REFERENCES "datasets" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT, FOREIGN KEY("sourceId") REFERENCES "sources" ("id") ON UPDATE RESTRICT ON DELETE RESTRICT ); CREATE UNIQUE INDEX "idx_catalogPath" ON "variables" ("catalogPath"); CREATE UNIQUE INDEX "unique_short_name_per_dataset" ON "variables" ("shortName", "datasetId"); CREATE UNIQUE INDEX "variables_code_fk_dst_id_7bde8c2a_uniq" ON "variables" ("code", "datasetId"); CREATE INDEX "variables_datasetId_50a98bfd_fk_datasets_id" ON "variables" ("datasetId"); CREATE UNIQUE INDEX "variables_name_fk_dst_id_f7453c33_uniq" ON "variables" ("name", "datasetId"); CREATE INDEX "variables_sourceId_31fce80a_fk_sources_id" ON "variables" ("sourceId");