Data

Gross national income (GNI) per capita

In constant international-$ – World Bank
See all data and research on:

What you should know about this indicator

  • Gross national income (GNI) is a measure of the total income earned by residents of a country or region each year. It is calculated as GDP plus net income received from abroad, plus taxes (minus subsidies) on production. GNI per capita is GNI divided by population.
  • This GNI per capita indicator provides information on economic growth and income levels from 1990.
  • This data is adjusted for inflation and differences in living costs between countries.
  • This data is expressed in at 2021 prices.
Learn more in the FAQs

How is this data described by its producer - World Bank?

This indicator provides values for gross national income (GNI) per person expressed in constant international dollars, converted by purchasing power parities (PPPs). PPPs account for the different price levels across countries and thus PPP-based comparisons of economic output are more appropriate for comparing the output of economies and the average material well-being of their inhabitants than exchange-rate based comparisons.

Gross national income is the total income earned by all residents within an economic territory during an accounting period. It is equal to gross domestic product plus earned income receivable from abroad minus earned income payable abroad. The core indicator has been divided by the general population to achieve a per capita estimate. This indicator is expressed in constant prices, meaning the series has been adjusted to account for price changes over time. The reference year for this adjustment is 2021. The PPP conversion factor is a currency conversion factor and a spatial price deflator. PPPs convert different currencies to a common currency and, in the process of conversion, equalize their purchasing power by eliminating the differences in price levels between countries, thereby allowing volume or output comparisons of GDP and its expenditure components.

Aggregation method:

Weighted average

Statistical concept and methodology:

Methodology: The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The recent 2021 ICP comparison covered 176 countries, including 49 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model. ICP estimated PPPs cover years from 2011 to 2021. WDI extrapolates 2011 PPPs for years earlier years, and 2021 PPPs for later years. For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases.

National accounts are compiled in accordance with international standards: System of National Accounts, 2008 or 1993 versions. Specific information on how countries compile their national accounts can be found on the IMF website: https://dsbb.imf.org/ Linked series have been smoothed to remove breaks resulting from changes in base years, data sources or compilation methods. The linking is performed using historical nominal growth rates from archived WDI databases.

Statistical concept(s): PPPs are primarily used to convert the national accounts data of economies, such as GDP and its expenditure components, into a common currency. In the process of conversion, they control for differences in the price levels of economies, and thus equalize purchasing power. PPP-based comparisons of economic output differ from market exchange rate-based comparisons as the latter do not distinguish between the relative price levels of different items in economies. Overall price levels are normally higher in higher-income economies than they are in lower-income economies (Balassa-Samuelson effect), mostly because of the large differences in price levels for non-traded products. If no account is taken of the larger price level differences for non-traded products when converting GDP to a common currency, the size of higher-income economies with high price levels will be overstated and the size of lower-income economies with low price levels will be understated. No distinction is made between traded products and non-traded products when market exchange rates are used to convert GDP to a common currency: the rate is the same for all products. PPP-converted GDP does not have this bias because PPPs account for the different price levels of traded products and non-traded products. Thus, PPPs are more appropriate for comparing the output of economies and the average material well-being of their inhabitants and are also less impacted by the potential volatility of market exchange rates. PPPs are calculated by the International Comparison Program (ICP) based on the prices of goods and services within an economy and national accounts expenditures.

The conceptual elements of the SNA (System of National Accounts) measure what takes place in the economy, between which agents, and for what purpose. At the heart of the SNA is the production of goods and services. These may be used for consumption in the period to which the accounts relate or may be accumulated for use in a later period. In simple terms, the amount of value added generated by production represents GDP. The income corresponding to GDP is distributed to the various agents or groups of agents as income and it is the process of distributing and redistributing income that allows one agent to consume the goods and services produced by another agent or to acquire goods and services for later consumption. The way in which the SNA captures this pattern of economic flows is to identify the activities concerned by recognizing the institutional units in the economy and by specifying the structure of accounts capturing the transactions relevant to one stage or another of the process by which goods and services are produced and ultimately consumed.

Development relevance:

PPPs are used to convert national accounts data from different countries, such as GDP and its expenditure components, into a common currency, while also eliminating the effect of price level differences between countries. PPPs are also used to derive price level indexes (PLIs), the ratio of a country’s PPP to its market exchange rate, to directly compare price levels across countries. The PPP-based expenditures to which they give rise are primarily used to make spatial comparisons of volume and per capita consumption or levels of GDP and its expenditure components across countries. PPP-based indicators are used for national, regional, and global policy making and analysis across the socioeconomic spectrum from poverty and inequality, to health and education, to energy and climate, through to economic growth, labor, productivity, trade, competitiveness, and infrastructure. A number of Sustainable Development Goals use PPP-based indicators to measure development progress.

This indicator is related to the national accounts, which are critical for understanding and managing a country's economy. They provide a framework for the analysis of economic performance. National accounts are the basis for estimating the Gross Domestic Product (GDP) and Gross National Income (GNI), which are the most widely used indicator of economic performance. They are essential for government policymakers, providing the data needed to design and assess fiscal and monetary policies; and are also used by businesses and investors to assess the economic climate and make investment decisions. NAS enable comparison between economies, which is crucial for international trade, investment decisions, and economic competitiveness. More specifically, this indicator is related to national accounts aggregates. Gross Domestic Product (GDP), Gross National Income (GNI), and other aggregates provide a snapshot of the size and health of an economy by measuring the total economic activity within a country. They can thus be used by policymakers to design and implement economic policies, as they reflect the overall economic performance and can indicate the need for intervention in certain areas. Aggregates also allow for comparisons between different economies, which can be useful for trade negotiations, investment decisions, and economic benchmarking. By examining aggregates over time, economists and analysts can identify trends, cycles, and potential areas of concern within an economy, and investors can use national accounts aggregates to assess the potential risks and returns of investing in a particular country. Overall, national accounts aggregates are fundamental tools for economic analysis, policy formulation, and decision-making at both the national and international levels.

Gross national income (GNI) per capita
In constant international-$ – World Bank
Average income per person earned by residents of a country or region, including income earned abroad. This data is adjusted for inflation and differences in living costs between countries.
Source
Eurostat, OECD, IMF, and World Bank (2026)with minor processing by Our World in Data
Last updated
February 27, 2026
Next expected update
February 2027
Date range
1990–2024
Unit
international-$ in 2021 prices

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?

Sources and processing

Eurostat, OECD, IMF, and World Bank – World Development Indicators

The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades.WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability.The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization.WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally.Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.

Retrieved on
February 27, 2026
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.
International Comparison Program (ICP), World Bank (WB), uri: https://www.worldbank.org/en/programs/icp/data, note: This information is for ICP’s PPPs utilized in WDI, publisher: International Comparison Program (ICP), date accessed: May 30, 2024, date published: May 30, 2024;
The Eurostat PPP Programme, Eurostat (ESTAT), uri: https://ec.europa.eu/eurostat/databrowser/explore/all/all_themes, publisher: Eurostat;
The OECD PPP Programme, Organisation for Economic Co-operation and Development (OECD), uri: https://data-explorer.oecd.org/, publisher: OECD;
Staff estimates, World Bank (WB);
National Accounts data files, Organisation for Economic Co-operation and Development (OECD);
World Economic Outlook database, International Monetary Fund (IMF). Indicator NY.GNP.PCAP.PP.KD (https://data.worldbank.org/indicator/NY.GNP.PCAP.PP.KD). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.

The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades.WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability.The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization.WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally.Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.

Retrieved on
February 27, 2026
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.
International Comparison Program (ICP), World Bank (WB), uri: https://www.worldbank.org/en/programs/icp/data, note: This information is for ICP’s PPPs utilized in WDI, publisher: International Comparison Program (ICP), date accessed: May 30, 2024, date published: May 30, 2024;
The Eurostat PPP Programme, Eurostat (ESTAT), uri: https://ec.europa.eu/eurostat/databrowser/explore/all/all_themes, publisher: Eurostat;
The OECD PPP Programme, Organisation for Economic Co-operation and Development (OECD), uri: https://data-explorer.oecd.org/, publisher: OECD;
Staff estimates, World Bank (WB);
National Accounts data files, Organisation for Economic Co-operation and Development (OECD);
World Economic Outlook database, International Monetary Fund (IMF). Indicator NY.GNP.PCAP.PP.KD (https://data.worldbank.org/indicator/NY.GNP.PCAP.PP.KD). World Development Indicators - World Bank (2026). Accessed on 2026-02-27.

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

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: Gross national income (GNI) per capita”, part of the following publication: Max Roser, Bertha Rohenkohl, Pablo Arriagada, Joe Hasell, Hannah Ritchie, and Esteban Ortiz-Ospina (2023) - “Economic Growth”. Data adapted from Eurostat, OECD, IMF, and World Bank. Retrieved from https://archive.ourworldindata.org/20260512-185716/grapher/gross-national-income-per-capita-worldbank.html [online resource] (archived on May 12, 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:

Eurostat, OECD, IMF, and World Bank (2026) – with minor processing by Our World in Data

Full citation

Eurostat, OECD, IMF, and World Bank (2026) – with minor processing by Our World in Data. “Gross national income (GNI) per capita – World Bank – In constant international-$” [dataset]. Eurostat, OECD, IMF, and World Bank, “World Development Indicators 125” [original data]. Retrieved May 13, 2026 from https://archive.ourworldindata.org/20260512-185716/grapher/gross-national-income-per-capita-worldbank.html (archived on May 12, 2026).

Quick download

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.

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/gross-national-income-per-capita-worldbank.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/gross-national-income-per-capita-worldbank.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/gross-national-income-per-capita-worldbank.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/gross-national-income-per-capita-worldbank.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/gross-national-income-per-capita-worldbank.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/gross-national-income-per-capita-worldbank.csv?v=1&csvType=full&useColumnShortNames=false")

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