Data

Global average GDP per capita over the long run

Historical data – World Bank, Maddison Project Database, Maddison Database
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What you should know about this indicator

  • This GDP per capita indicator provides information on global economic growth and income levels in the very long run. Estimates are available as far back as 1 CE.
  • This data is adjusted for inflation and for differences in the cost of living between countries.
  • This data is expressed in at 2017 prices, merging data from the World Bank, backwards extended with growth rates from Maddison Project Database and Maddison Database.
Learn more in the FAQs

GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser's prices is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2017 international dollars.

For the concept and methodology of 2017 PPP, please refer to the International Comparison Program (ICP)’s website.

Global average GDP per capita over the long run
Historical data – World Bank, Maddison Project Database, Maddison Database
This data is adjusted for inflation and differences in the cost of living between countries.
Source
World Bank (2023); Bolt and van Zanden - Maddison Project Database 2023; Maddison Database 2010 – with major processing by Our World in Data
Last updated
May 16, 2024
Next expected update
May 2025
Date range
1–2022
Unit
international-$ in 2017 prices

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 – for instance on the goods and services bought or produced by households, firms and governments, or the incomes they receive – is initially recorded in terms of the units in which these transactions took place. That means this data starts out being expressed in a variety of local currencies – as so many rupees, US dollars, or yuan, etc. – and without adjusting for inflation over time. This is known as being in ‘current prices’, or in ‘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. It is the result of adjusting both for inflation within countries over time and for differences in the cost of living between countries.

The goal of international-$ is to provide a unit whose purchasing power is held fixed over time and across countries, such that one int.-$ can buy the same quantity and quality of goods and services no matter where or when it is spent.

The price level in the US is used as the benchmark – or ‘numeraire’ – so that one 2017 int.-$ is defined as the value of goods and services that one US dollar would buy in the US in 2017. Similarly, one 2011 int.-$ is defined as the value of goods and services that one US dollar would buy in the US in 2011.

The year 2017 (2011) here indicates two things, related to the two adjustments mentioned. Firstly, it tells us the base year used for the inflation adjustment within countries. This is the year whose prices are chosen to be the benchmark. If prices are higher than this benchmark year, nominal data will be adjusted downwards. If prices are lower, nominal data will be adjusted upwards. In the base year itself, the nominal and inflation-adjusted figures are the same by definition.

Secondly, 2017 (2011) indicates the year in which the differences in the cost of living between countries was assessed.

Purchasing Power Parity rates

Converting data in local currencies to international-$ means dividing the figures by a set of ‘exchange’ rates, known as Purchasing Power Parity (PPP) rates. Unlike the exchange rates between currencies you would see at the foreign exchange counter, these account for differences in the cost of living between countries.

If you have ever shopped or eaten in a restaurant abroad, you may have noticed a country as being a particularly expensive or particularly cheap place to live. A given amount of your own currency, when exchanged for another country’s currency, may buy you considerably more or less there than it would have done at home.

The goal of PPP rates is to account for these price differences. They express, for each country, the amount of local currency that is needed to buy the same goods and services there as 1 US dollar buys in the US.

You can read more about this in our article What are PPP adjustments and why do we need them?

The ‘rounds’ of the International Comparison Program

The calculation of PPP rates is the task of the International Comparison Program (ICP), which gathers data on the prices of thousands of goods and services in each country in a particular year.

The ICP does not calculate PPP rates every year, but rather conducts its work in ‘rounds’ that are several years apart. The most recent round was conducted in 2017 and the previous round was conducted in 2011.

In converting economic data to international-$, which round of PPPs are used to adjust for cost-of-living differences between countries is, in principle, a separate issue to the base year used to adjust for inflation over time. By convention, however, the same year tends to be chosen for both. When converted to 2017 international-$, nominal local currencies are first adjusted for inflation to local 2017 prices, and are then adjusted to US prices using the PPPs calculated in the ICP’s 2017 round. Likewise, 2011 international-$ adjust for inflation using 2011 local prices, and then use the 2011 PPPs to adjust for cost-of-living differences.

Sources and processing

This data is based on the following sources

The World Development Indicators (WDI) is the World Bank's primary collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available and includes national, regional, and global estimates.

[Text from World Bank data catalog]

Retrieved on
May 29, 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. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
World Development Indicators, The World Bank (2023).

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
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.
  • 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 is based on the work of many researchers who have produced estimates of economic growth and population for individual countries. The full list of sources for this historical data is given in the original dataset.

The final database version provided by Angus Maddison, covering world population, GDP and per capita GDP from 1-2008 AD.

Retrieved on
December 23, 2022
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.
Maddison, A. (2010). Maddison Database 2010. Retrieved from https://www.rug.nl/ggdc/historicaldevelopment/maddison/releases/maddison-database-2010

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
Notes on our processing step for this indicator

The data presented here from 1990 onwards is from the World Bank. Data before 1990 is constructed using the 1990 World Bank observation and applying the growth rates implied by the Maddison Project Database. Similarly, data before 1820 is built using the adjusted 1820 estimate calculated by the previous method and applying the growth rates implied by the Maddison Database. These steps are necessary because World Bank data adjusted for inflation and the cost of living between countries is only available from 1990 onwards and also because the three datasets estimate GDP with different prices.

The adjusted results before 1990 have been rounded to address uncertainty in the underlying data. GDP data is rounded to the nearest million, and GDP is rounded to the nearest hundred.

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: Global average GDP per capita over the long run”, part of the following publication: Max Roser, Pablo Arriagada, Joe Hasell, Hannah Ritchie and Esteban Ortiz-Ospina (2023) - “Economic Growth”. Data adapted from World Bank, Bolt and van Zanden, Angus Maddison. Retrieved from https://ourworldindata.org/grapher/global-average-gdp-per-capita-over-the-long-run [online resource]
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:

World Bank (2023); Bolt and van Zanden - Maddison Project Database 2023; Maddison Database 2010 – with major processing by Our World in Data

Full citation

World Bank (2023); Bolt and van Zanden - Maddison Project Database 2023; Maddison Database 2010 – with major processing by Our World in Data. “Global average GDP per capita over the long run – World Bank, Maddison Project Database, Maddison Database – Historical data” [dataset]. World Bank, “World Bank World Development Indicators”; Bolt and van Zanden, “Maddison Project Database 2023”; Angus Maddison, “Maddison Database 2010” [original data]. Retrieved November 24, 2024 from https://ourworldindata.org/grapher/global-average-gdp-per-capita-over-the-long-run