variables: 943785

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.

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
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 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

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