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Data

Median income per year (after tax)

See all data and research on:
PovertyEconomic Inequality

What you should know about this indicator

  • This data is expressed in constant international dollars to adjust for inflation and differences in living costs between countries. Read more in our article, What are international dollars?
  • 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.
Median income per year (after tax)
Value of income per year below which 50% of the population live.
Source
Luxembourg Income Study (2026) – with minor processing by Our World in Data
Last updated
March 16, 2026
Next expected update
June 2026
Date range
1963–2024
Unit
international-$ in 2021 prices

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Sources and processing

This data is based on the following sources

Luxembourg Income Study – Luxembourg Income Study (LIS)

The Luxembourg Income Study Database (LIS) is the largest available income database of harmonized microdata collected from over 50 countries in Europe, North America, Latin America, Africa, Asia, and Australasia spanning five decades.

Harmonized into a common framework, LIS datasets contain household- and person-level data on labor income, capital income, pensions, public social benefits (excl. pensions) and private transfers, as well as taxes and contributions, demography, employment, and expenditures.

Retrieved on
March 16, 2026
Retrieved from
https://www.lisdatacenter.org/our-data/lis-database/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; March 2026). Luxembourg: LIS.

The Luxembourg Income Study Database (LIS) is the largest available income database of harmonized microdata collected from over 50 countries in Europe, North America, Latin America, Africa, Asia, and Australasia spanning five decades.

Harmonized into a common framework, LIS datasets contain household- and person-level data on labor income, capital income, pensions, public social benefits (excl. pensions) and private transfers, as well as taxes and contributions, demography, employment, and expenditures.

Retrieved on
March 16, 2026
Retrieved from
https://www.lisdatacenter.org/our-data/lis-database/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Luxembourg Income Study (LIS) Database, http://www.lisdatacenter.org (multiple countries; March 2026). Luxembourg: LIS.

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Median income per year (after tax)”, part of the following publication: Joe Hasell, Bertha Rohenkohl, Pablo Arriagada, Esteban Ortiz-Ospina, and Max Roser (2022) - “Poverty”. Data adapted from Luxembourg Income Study. Retrieved from https://archive.ourworldindata.org/20260316-112104/grapher/median-income-after-tax-lis.html [online resource] (archived on March 16, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Luxembourg Income Study (2026) – with minor processing by Our World in Data

Full citation

Luxembourg Income Study (2026) – with minor processing by Our World in Data. “Median income per year (after tax)” [dataset]. Luxembourg Income Study, “Luxembourg Income Study (LIS)” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260316-112104/grapher/median-income-after-tax-lis.html (archived on March 16, 2026).

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Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

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Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/median-income-after-tax-lis.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/median-income-after-tax-lis.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/median-income-after-tax-lis.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/median-income-after-tax-lis.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/median-income-after-tax-lis.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/median-income-after-tax-lis.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/median-income-after-tax-lis.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/median-income-after-tax-lis.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear