{"chart":{"title":"Median income (after tax)","subtitle":"This data is adjusted for inflation and for differences in living costs between countries. Income here is measured after taxes and benefits.","note":"This data is measured in [international-$](#dod:int_dollar_abbreviation) at 2017 prices. Income has been [equivalized](#dod:equivalization).","citation":"Luxembourg Income Study (2024)","originalChartUrl":"https://ourworldindata.org/grapher/median-income-after-tax-lis","selection":["Canada","Australia","United States","France","Germany","Sweden"]},"columns":{"Median (Disposable household income, equivalized)":{"titleShort":"Median","titleLong":"Median","descriptionShort":"Median income.","descriptionKey":["The data is measured in international-$ at 2017 prices – this adjusts for inflation and for differences in living costs between countries.","Income is \"post-tax\" — measured after taxes have been paid and most government benefits have been received.","Income has been equivalized – adjusted to account for the fact that people in the same household can share costs like rent and heating."],"descriptionProcessing":"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.\n\nWe obtain after tax income by using the disposable household income variable (`dhi`).\n\nWe estimate before tax income by calculating the sum of income from labor and capital (variable `hifactor`), cash transfers and in-kind goods and services from privates (`hiprivate`) and private pensions (`hi33`). We do this only for surveys where tax and contributions are fully captured, collected or imputed.\n\nWe obtain after tax income (cash) by using the disposable household cash income variable (`dhci`).\n\nWe convert income data from local currency into international-$ by dividing by the [LIS PPP factor](https://www.lisdatacenter.org/resources/ppp-deflators/), available as an additional database in the LISSY platform.\n\nWe top and bottom-code incomes by replacing negative values with zeros and setting boundaries for extreme values of log income: at the top Q3 plus 3 times the interquartile range (Q3-Q1), and at the bottom Q1 minus 3 times the interquartile range.\n\nWe equivalize incomes by dividing each household observation by the square root of the number of household members (nhhmem). Per capita estimates are calculated by dividing incomes by the number of household members.\n\n\nWe 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.","shortUnit":"$","unit":"international-$ in 2017 prices","timespan":"1963-2022","type":"Numeric","owidVariableId":1009256,"shortName":"median_dhi_eq","lastUpdated":"2025-01-24","nextUpdate":"2025-08-09","citationShort":"Luxembourg Income Study (2024) – with major processing by Our World in Data","citationLong":"Luxembourg Income Study (2024) – with major processing by Our World in Data. “Median – Luxembourg Income Study” [dataset]. Luxembourg Income Study, “Luxembourg Income Study (LIS)” [original data].","fullMetadata":"https://api.ourworldindata.org/v1/indicators/1009256.metadata.json"}},"dateDownloaded":"2025-07-09"}