Our World
in Data
Data

GDP per capita

Penn World Table
See all data and research on:
Economic Growth

What you should know about this indicator

  • This GDP per capita indicator provides information on economic growth and income levels in the medium run. Some country estimates are available as far back as 1950.
  • This data is adjusted for inflation and for differences in the cost of living between countries.
  • This data is expressed in international-$ at 2017 prices, using multiple benchmark years to adjust for differences in the cost of living between countries over time.
  • For GDP per capita estimates in the very long run, see the Maddison Project Database's indicator.
  • For more up-to-date estimates of GDP per capita, see the World Bank's indicator.
Learn more in the FAQs

Output-side real GDP at chained PPPs (in mil. 2017US$) [From GDP description]

GDP per capita
Penn World Table
This data is adjusted for inflation and for differences in the cost of living between countries.
Source
Feenstra et al. (2015), Penn World Table (2021) – with major processing by Our World in Data
Last updated
November 28, 2022
Next expected update
December 2024
Date range
1950–2019
Unit
international-$ in 2017 prices

Related research and writing

A dark blue background with a lighter blue world map superimposed over it. Yellow text that says Vaccination by Our World in Data

Vaccination

Samantha Vanderslott, Saloni Dattani, Fiona Spooner and Max Roser
legacy-wordpress-upload

Do workers in richer countries work longer hours?

Charlie Giattino and Esteban Ortiz-Ospina

Explore charts that include this data

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

Penn World Table is a database with information on GDP and its composition, employment, productivity and trade, covering 183 countries between 1950 and 2019. Data comes from national accounts, ICP PPP estimations, multiple other sources

Retrieved on
November 28, 2022
Retrieved from
https://www.rug.nl/ggdc/productivity/pwt/
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.
Feenstra, R. C., Inklaar, R. and Timmer, M.P. (2015), "The Next Generation of the Penn World Table". American Economic Review, 105(10), 3150-3182

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

Estimated as the GDP (output, multiple price benchmarks) divided by the population of each country.

This variable uses ICP PPP benchmarks from multiple years to correct for changing prices over time.

Values for Bermuda have been replaced by estimates on GDP per capita (output, single price benchmark) due to the unusual changes on prices in this country.

Values considered outliers from the original dataset (i_outlier = "Outlier") have been excluded from the dataset, due to implausible relative prices (PPPs divided by exchange rates).

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: GDP per capita”, part of the following publication: Max Roser, Pablo Arriagada, Joe Hasell, Hannah Ritchie and Esteban Ortiz-Ospina (2023) - “Economic Growth”. Data adapted from Feenstra et al. (2015), Penn World Table (2021). Retrieved from https://ourworldindata.org/grapher/gdp-per-capita-penn-world-table [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:

Feenstra et al. (2015), Penn World Table (2021) – with major processing by Our World in Data

Full citation

Feenstra et al. (2015), Penn World Table (2021) – with major processing by Our World in Data. “GDP per capita – Penn World Table” [dataset]. Feenstra et al. (2015), Penn World Table (2021), “Penn World Table” [original data]. Retrieved November 23, 2024 from https://ourworldindata.org/grapher/gdp-per-capita-penn-world-table