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GDP per capitaLong-run data in constant international-$

Average economic output per person in a country or region per year. This data is adjusted for inflation and differences in living costs between countries.

Data source

Maddison Project Database

Unit
international-$ in 2011 prices
Last updated
2024-04-26
Next expected update
2027-04-22
Managed by
Pablo Arriagada and Lucas Rodés-Guirao

  • GDP per capita is a comprehensive measure of people's average income. It helps compare income levels across countries and track how they change over time. It is especially useful for understanding trends in economic growth and living standards.

  • GDP per capita is calculated as the value of all final goods and services produced each year in a country (the ), divided by the population. It represents the average economic output per person.

  • This indicator shows the large inequality between people in different countries. In the poorest countries, average incomes are below $1,000 per year; in rich countries, they are more than 50 times higher.

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  • This data comes from the Maddison Project Database, which provides GDP per capita estimates for the very long run. Some country series extend as far back as 1 CE, and regional estimates start in 1820.

  • This work builds on the efforts of many researchers who have carefully reconstructed historical data on economic growth and population for individual countries. You can find the full list of sources in the original dataset.

  • This data is expressed in constant international dollars at 2011 prices to adjust for inflation and differences in living costs between countries. Read more in our article, What are international dollars?

  • This dataset combines multiple (PPP) benchmarks to ensure historical consistency and comparability over time. 1990 PPPs are used up to 1990, and 2011 PPPs are used from 2011 onward. For the years in between, they adjust the series to smoothly connect the two benchmarks. This approach preserves consistency with the original long-run estimates calculated by Angus Maddison.

  • Time series for former countries and territories are calculated forward by estimating values based on their last official borders.

  • For more frequently updated estimates since 1990, explore our chart of GDP per capita from the World Bank.

Data sources

Bolt and van Zanden – Maddison Project Database

The Maddison Project Database provides information on comparative economic growth and income levels over the very long run. The 2023 version of this database covers 169 countries and the period up to 2022. The new estimates are presented and discussed in Bolt and Van Zanden (2024), "Maddison style estimates of the evolution of the world economy: A new 2023 update", Journal of Economic Surveys, 1–41.

Retrieved on
April 26, 2024
Retrieved from
https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-project-database-2023
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. 
    

  • Bolt, Jutta and Jan Luiten van Zanden (2024), "Maddison style estimates of the evolution of the world economy: A new 2023 update", Journal of Economic Surveys, 1–41. DOI: 10.1111/joes.12618.
    • 

  • The Maddison Project Database builds on the efforts of many researchers who have carefully reconstructed historical data on economic growth and population for individual countries. You can find the full list of sources in the original dataset.
    •

Citations

How should I cite this data in a news article?

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

Bolt and van Zanden – Maddison Project Database 2023 – with minor processing by Our World in Data

How should I cite this in an academic article or report?

Bolt and van Zanden – Maddison Project Database 2023 – with minor processing by Our World in Data. “GDP per capita – Maddison Project Database – Long-run data in constant international-$” [dataset]. Bolt and van Zanden, “Maddison Project Database 2023” [original data]. Retrieved June 12, 2026 from https://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database

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. 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.

Frequently Asked Questions

What are international-$ and why are they used to measure incomes?

Much of the economic data we use to understand the world, such as the incomes people receive or the goods and services firms produce and people buy, is recorded in the local currencies of each country. That means the numbers start out in rupees, US dollars, yuan, and many others, and without adjusting for inflation over time. This is known as being in “current prices” or “nominal” terms.

Before these figures can be meaningfully compared, they need to be converted into common units. International dollars (int.-$) are a hypothetical currency that is used for this.

The idea is simple: one international dollar should buy the same quantity and quality of goods and services, no matter where or when it is spent. To achieve this, international dollars adjust for two things. First, they account for inflation within each country, so that values from different years can be compared (showing “constant” prices). Second, they account for differences in living costs across countries. This second adjustment uses purchasing power parity (PPP) rates, which reflect how much local currency is needed to buy what one US dollar would buy in the United States.

The United States is the benchmark, so that one 2021 int.-$ is defined as the value of goods and services that one US dollar would buy in the US in 2021. One 2011 int.-$ is defined in the same way, but for prices in 2011.

You can read more in our article, What are international dollars?

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Data URL (CSV format)
https://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database.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://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database.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://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://datapage-v2.owid.pages.dev/grapher/gdp-per-capita-maddison-project-database.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear