variables: 943129

This table contains all the variables of all the datasets we have at Our World In Data. Note that this includes only the information about the variables like name and default display settings, not the data itself.

Data license: CC-BY

This data as json

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
943129 50% of the median - Poverty Gap Index (Disposable household cash income, per capita) %   2024-06-25 14:16:24 2024-07-25 22:55:43     1963-2022 6582   % 
{
    "name": "50% of the median - Poverty Gap Index (Disposable household cash income, per capita)",
    "unit": "%",
    "shortUnit": "%",
    "tolerance": 5,
    "numDecimalPlaces": 1
}
 0     poverty_gap_index_50_median_dhci_pc grapher/lis/2024-06-13/luxembourg_income_study/luxembourg_income_study#poverty_gap_index_50_median_dhci_pc   2 major           The poverty gap index is a poverty measure that reflects both the prevalence and the depth of poverty. It is calculated as the share of population in poverty multiplied by the average shortfall from the poverty line (expressed as a % of the poverty line).   
[
    "This is a measure of _relative_ poverty \u2013 it captures the share of people whose income is low by the standards typical in their own country.",
    "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 poverty indicators by using [Stata’s povdeco function](https://ideas.repec.org/c/boc/bocode/s366004.html). We set weights as the product between the number of household members (nhhmem) and the normalized household weight (hwgt). The function generates FGT(0) and FGT(1), headcount ratio and poverty gap index. After extraction, we do further data processing steps to estimate other poverty indicators using these values, population and poverty lines for absolute and relative poverty.       float 
[]
 327edb972937e36df2b607fc307676b0 a8bc0ac2825a463a80548b549d68d822

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