The "Global Country Rankings Dataset" is a comprehensive collection of metrics and indicators that ranks countries worldwide based on their socioeconomic performance. This datasets are providing valuable insights into the relative standings of nations in terms of key factors such as GDP per capita, economic growth, and various other relevant criteria.
Researchers, analysts, and policymakers can leverage this dataset to gain a deeper understanding of the global economic landscape and track the progress of countries over time. The dataset covers a wide range of metrics, including but not limited to:
Economic growth: the rate of change of real GDP- Country rankings: The average for 2021 based on 184 countries was 5.26 percent.The highest value was in the Maldives: 41.75 percent and the lowest value was in Afghanistan: -20.74 percent. The indicator is available from 1961 to 2021.
GDP per capita, Purchasing Power Parity - Country rankings: The average for 2021 based on 182 countries was 21283.21 U.S. dollars.The highest value was in Luxembourg: 115683.49 U.S. dollars and the lowest value was in Burundi: 705.03 U.S. dollars. The indicator is available from 1990 to 2021.
GDP per capita, current U.S. dollars - Country rankings: The average for 2021 based on 186 countries was 17937.03 U.S. dollars.The highest value was in Monaco: 234315.45 U.S. dollars and the lowest value was in Burundi: 221.48 U.S. dollars. The indicator is available from 1960 to 2021.
GDP per capita, constant 2010 dollars - Country rankings: The average for 2021 based on 184 countries was 15605.8 U.S. dollars.The highest value was in Monaco: 204190.16 U.S. dollars and the lowest value was in Burundi: 261.02 U.S. dollars. The indicator is available from 1960 to 2021.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The GDP per capita for countries is shown in this dataset for the different years. This economic metric shows the economic output per person and determines the country’s situation based on its economic growth. This dataset can be used to analyze the prosperity of a country based on its economic growth. Countries with higher GDP per countries are determined to be developed whereas countries with low GDP per capita are determined to be developing countries. This dataset can be used to analyze a country’s wealth and prosperity.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Gross Domestic Product per capita in the United States was last recorded at 65875.18 US dollars in 2023. The GDP per Capita in the United States is equivalent to 522 percent of the world's average. This dataset provides - United States GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.
In 2025, Luxembourg was the country with the highest gross domestic product per capita in the world. Of the 20 listed countries, 13 are in Europe and five are in Asia, alongside the U.S. and Australia. There are no African or Latin American countries among the top 20. Correlation with high living standards While GDP is a useful indicator for measuring the size or strength of an economy, GDP per capita is much more reflective of living standards. For example, when compared to life expectancy or indices such as the Human Development Index or the World Happiness Report, there is a strong overlap - 14 of the 20 countries on this list are also ranked among the 20 happiest countries in 2024, and all 20 have "very high" HDIs. Misleading metrics? GDP per capita figures, however, can be misleading, and to paint a fuller picture of a country's living standards then one must look at multiple metrics. GDP per capita figures can be skewed by inequalities in wealth distribution, and in countries such as those in the Middle East, a relatively large share of the population lives in poverty while a smaller number live affluent lifestyles.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset provides values for GDP PER CAPITA PPP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.
Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically
This dataset contains 25 columns which are: 1. Country: Corresponding country. 2. Poverty headcount ratio at $2.15 a day (2017 PPP) (% of population): Poverty in country. 3. Life expectancy at birth, total (years): Expected life from birth. 4. Population, total: Population of Country. 5. Population growth (annual %): Population growth each year. 6. Net migration: is the difference between the number of immigrants and the number of emigrants divided by the population. 7. Human Capital Index (HCI) (scale 0-1): is an annual measurement prepared by the World Bank. HCI measures which countries are best in mobilizing their human capital, the economic and professional potential of their citizens. The index measures how much capital each country loses through lack of education and health. 8. GDP (current US$)current US$constant US$current LCUconstant LCU: Gross domestic product is a monetary measure of the market value of all the final goods and services produced in a specific time period by a country or countries. 9. GDP per capita (current US$)current US$constant US$current LCUconstant LCU: the sum of gross value added by all resident producers in the economy plus any product taxes (less subsidies) not included in the valuation of output, divided by mid-year population. 10. GDP growth (annual %): The annual average rate of change of the gross domestic product (GDP) at market prices based on constant local currency, for a given national economy, during a specified period of time. 11. Unemployment, total (% of total labor force) (modeled ILO estimate) 12. Inflation, consumer prices (annual %) 13. Personal remittances, received (% of GDP) 14. CO2 emissions (metric tons per capita) 15. Forest area (% of land area) 16. Access to electricity (% of population) 17. Annual freshwater withdrawals, total (% of internal resources) 18. Electricity production from renewable sources, excluding hydroelectric (% of total) 19. People using safely managed sanitation services (% of population) 20. Intentional homicides (per 100,000 people) 21. Central government debt, total (% of GDP) 22. Statistical performance indicators (SPI): Overall score (scale 0-100) 23. Individuals using the Internet (% of population) 24. Proportion of seats held by women in national parliaments (%) 25. Foreign direct investment, net inflows (% of GDP): is when an investor becomes a significant or lasting investor in a business or corporation in a foreign country, which can be a boost to the global economy.
Economic
217
$5.50
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Gross Domestic Product per capita in China was last recorded at 12175.20 US dollars in 2023. The GDP per Capita in China is equivalent to 96 percent of the world's average. This dataset provides - China GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.
This dataset provides statistics on gross domestic product and gross domestic product per capita, for large regions (TL2) and small regions (TL3).
Data source and definition
Regional gross domestic product data is collected at current prices, in millions of national currency from Eurostat (reg_eco10) for EU countries and via delegates of the OECD Working Party on Territorial Indicators (WPTI), as well as from national statistical offices' websites. In order to allow comparability over time and across countries, data in current prices are transformed into constant prices and PPP measures (link). Regional GDP per capita is calculated by dividing the regional GDP by the average annual population of the region.
Definition of regions
Regions are subnational units below national boundaries. OECD countries have two regional levels: large regions (territorial level 2 or TL2) and small regions (territorial level 3 or TL3). The OECD regions are presented in the OECD Territorial grid (pdf) and in the OECD Territorial correspondence table (xlsx).
Use of economic data on small regions
When economic analyses are carried out at the TL3 level, it is advisable to aggregate data at the metropolitan region level when several TL3 regions are associated to the same metropolitan region. Metropolitan regions combine TL3 regions when 50% or more of the regional population live in a functionnal urban areas above 250 000 inhabitants. This approach corrects the distortions created by commuting, see the list of OECD metropolitan regions (xlsx) and the EU methodology (link).
Small regions (TL3) are categorized based on shared characteristics into regional typologies. See the economic indicators aggregated by territorial typology at country level on the access to City typology (link) and by urban-rural typology (link).
Cite this dataset
OECD Regions and Cities databases http://oe.cd/geostats
Further information
Contact: RegionStat@oecd.org
http://opendatacommons.org/licenses/dbcl/1.0/http://opendatacommons.org/licenses/dbcl/1.0/
This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the countries in this dataset have a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.
See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.
VARIABLE DESCRIPTIONS:
unid: ISO numeric country code (used by the United Nations)
wbid: ISO alpha country code (used by the World Bank)
SES: Country socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174)
country: Short country name
year: Survey year
gdppc: GDP per capita: Single time-series (imputed)
yrseduc: Completed years of education in the adult (15+) population
region5: Five category regional coding schema
regionUN: United Nations regional coding schema
DATA SOURCES:
The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita:
Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls.
World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm
Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/
Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.
United Nations Population Division. 2009.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Gross Domestic Product per capita in Japan was last recorded at 36990.33 US dollars in 2023. The GDP per Capita in Japan is equivalent to 293 percent of the world's average. This dataset provides - Japan GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Germany DE: GDP: Real: per Capita data was reported at 39,960.579 EUR in 2023. This records an increase from the previous number of 39,819.663 EUR for 2022. Germany DE: GDP: Real: per Capita data is updated yearly, averaging 27,920.436 EUR from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 39,960.579 EUR in 2023 and a record low of 11,356.630 EUR in 1960. Germany DE: GDP: Real: per Capita data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Gross Domestic Product: Real. GDP per capita is gross domestic product divided by midyear population. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy 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 local currency.;World Bank national accounts data, and OECD National Accounts data files.;;
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
GDP: per Capita: Shandong: Liaocheng data was reported at 46,995.000 RMB in 2022. This records an increase from the previous number of 44,485.000 RMB for 2021. GDP: per Capita: Shandong: Liaocheng data is updated yearly, averaging 32,968.200 RMB from Dec 2001 (Median) to 2022, with 21 observations. The data reached an all-time high of 51,935.000 RMB in 2018 and a record low of 5,733.780 RMB in 2001. GDP: per Capita: Shandong: Liaocheng data remains active status in CEIC and is reported by Liaocheng Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: per Capita.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The Gross Domestic Product per capita in Argentina was last recorded at 12933.25 US dollars in 2023. The GDP per Capita in Argentina is equivalent to 102 percent of the world's average. This dataset provides - Argentina GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Description
This comprehensive dataset provides a wealth of information about all countries worldwide, covering a wide range of indicators and attributes. It encompasses demographic statistics, economic indicators, environmental factors, healthcare metrics, education statistics, and much more. With every country represented, this dataset offers a complete global perspective on various aspects of nations, enabling in-depth analyses and cross-country comparisons.
Key Features
- Country: Name of the country.
- Density (P/Km2): Population density measured in persons per square kilometer.
- Abbreviation: Abbreviation or code representing the country.
- Agricultural Land (%): Percentage of land area used for agricultural purposes.
- Land Area (Km2): Total land area of the country in square kilometers.
- Armed Forces Size: Size of the armed forces in the country.
- Birth Rate: Number of births per 1,000 population per year.
- Calling Code: International calling code for the country.
- Capital/Major City: Name of the capital or major city.
- CO2 Emissions: Carbon dioxide emissions in tons.
- CPI: Consumer Price Index, a measure of inflation and purchasing power.
- CPI Change (%): Percentage change in the Consumer Price Index compared to the previous year.
- Currency_Code: Currency code used in the country.
- Fertility Rate: Average number of children born to a woman during her lifetime.
- Forested Area (%): Percentage of land area covered by forests.
- Gasoline_Price: Price of gasoline per liter in local currency.
- GDP: Gross Domestic Product, the total value of goods and services produced in the country.
- Gross Primary Education Enrollment (%): Gross enrollment ratio for primary education.
- Gross Tertiary Education Enrollment (%): Gross enrollment ratio for tertiary education.
- Infant Mortality: Number of deaths per 1,000 live births before reaching one year of age.
- Largest City: Name of the country's largest city.
- Life Expectancy: Average number of years a newborn is expected to live.
- Maternal Mortality Ratio: Number of maternal deaths per 100,000 live births.
- Minimum Wage: Minimum wage level in local currency.
- Official Language: Official language(s) spoken in the country.
- Out of Pocket Health Expenditure (%): Percentage of total health expenditure paid out-of-pocket by individuals.
- Physicians per Thousand: Number of physicians per thousand people.
- Population: Total population of the country.
- Population: Labor Force Participation (%): Percentage of the population that is part of the labor force.
- Tax Revenue (%): Tax revenue as a percentage of GDP.
- Total Tax Rate: Overall tax burden as a percentage of commercial profits.
- Unemployment Rate: Percentage of the labor force that is unemployed.
- Urban Population: Percentage of the population living in urban areas.
- Latitude: Latitude coordinate of the country's location.
- Longitude: Longitude coordinate of the country's location.
Potential Use Cases
- Analyze population density and land area to study spatial distribution patterns.
- Investigate the relationship between agricultural land and food security.
- Examine carbon dioxide emissions and their impact on climate change.
- Explore correlations between economic indicators such as GDP and various socio-economic factors.
- Investigate educational enrollment rates and their implications for human capital development.
- Analyze healthcare metrics such as infant mortality and life expectancy to assess overall well-being.
- Study labor market dynamics through indicators such as labor force participation and unemployment rates.
- Investigate the role of taxation and its impact on economic development.
- Explore urbanization trends and their social and environmental consequences.
Data from 1st of June 2022. For most recent GDP data, consult dataset nama_10_gdp. Gross domestic product (GDP) is a measure for the economic activity. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The volume index of GDP per capita in Purchasing Power Standards (PPS) is expressed in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country's level of GDP per head is higher than the EU average and vice versa. Basic figures are expressed in PPS, i.e. a common currency that eliminates the differences in price levels between countries allowing meaningful volume comparisons of GDP between countries. Please note that the index, calculated from PPS figures and expressed with respect to EU27_2020 = 100, is intended for cross-country comparisons rather than for temporal comparisons."
The statistic shows the gross domestic product (GDP) per capita in India from 1987 to 2030. In 2020, the estimated gross domestic product per capita in India amounted to about 1,915.55 U.S. dollars. See figures on India's economic growth here. For comparison, per capita GDP in China had reached about 6,995.25 U.S. dollars in 2013. India's economic progress India’s progress as a country over the past decade can be attributed to a global dependency on cheaper production of goods and services from developed countries around the world. India’s economy is built upon its agriculture, manufacturing and services sector, which, along with its drastic rise in population and demand for employment, led to a significant increase of the nation’s GDP per capita. Despite experiencing rather momentous economic gains since the mid 2000s, the Indian economy stagnated around 2012, with a decrease in general growth as well as the value of its currency. Residents and consumers in India have recently shown pessimism regarding the future of the Indian economy as well as their own financial situation, and with the recent economic standstill, consumer confidence in the country could potentially lower in the near future. Typical Indian exports consist of agricultural products, jewelry, chemicals and ores. Imports consist primarily of crude oil, gold and precious stones, used primarily in the manufacturing of jewelry. As a result, India has seen a rather highly increased demand of several gems in order to boost their jewelry industry and in general their exports. Although India does not export an extensive amount of goods, especially when considering the stature of the country, India has remained as one of the world’s largest exporters.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
GDP: per Capita: Shandong: Heze data was reported at 48,294.000 RMB in 2022. This records an increase from the previous number of 45,366.000 RMB for 2021. GDP: per Capita: Shandong: Heze data is updated yearly, averaging 20,095.535 RMB from Dec 2001 (Median) to 2022, with 22 observations. The data reached an all-time high of 48,294.000 RMB in 2022 and a record low of 2,647.090 RMB in 2001. GDP: per Capita: Shandong: Heze data remains active status in CEIC and is reported by Heze Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: per Capita.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
GDP: per Capita: Fujian: Fuzhou data was reported at 152,845.937 RMB in 2023. This records an increase from the previous number of 145,935.886 RMB for 2022. GDP: per Capita: Fujian: Fuzhou data is updated yearly, averaging 15,835.000 RMB from Dec 1950 (Median) to 2023, with 45 observations. The data reached an all-time high of 152,845.937 RMB in 2023 and a record low of 66.000 RMB in 1950. GDP: per Capita: Fujian: Fuzhou data remains active status in CEIC and is reported by Fuzhou Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AE: Gross Domestic Product: Prefecture Level City: per Capita.
Data from 1st of December 2021. For most recent GDP data, consult dataset nama_10_gdp. Gross domestic product (GDP) is a measure for the economic activity. It is defined as the value of all goods and services produced less the value of any goods or services used in their creation. The volume index of GDP per capita in Purchasing Power Standards (PPS) is expressed in relation to the European Union average set to equal 100. If the index of a country is higher than 100, this country's level of GDP per head is higher than the EU average and vice versa. Basic figures are expressed in PPS, i.e. a common currency that eliminates the differences in price levels between countries allowing meaningful volume comparisons of GDP between countries. Please note that the index, calculated from PPS figures and expressed with respect to EU27_2020 = 100, is intended for cross-country comparisons rather than for temporal comparisons."
Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically
Context
Happiness and well-being are essential indicators of societal progress, often influenced by economic conditions such as GDP and inflation. This dataset combines data from the World Happiness Index (WHI) and inflation metrics to explore the relationship between economic stability and happiness levels across 148 countries from 2015 to 2023. By analyzing key economic indicators alongside social well-being factors, this dataset provides insights into global prosperity trends.
Content
This dataset is provided in CSV format and includes 16 columns, covering both happiness-related features and economic indicators such as GDP per capita, inflation rates, and corruption perception. The main columns include:
Happiness Score & Rank (World Happiness Index ranking per country) Economic Indicators (GDP per capita, inflation metrics) Social Factors (Freedom, Social Support, Generosity) Geographical Information (Country & Continent)
Acknowledgements
The dataset is created using publicly available data from World Happiness Report, Gallup World Poll, and the World Bank. It has been structured for research, machine learning, and policy analysis purposes.
Inspiration
How do economic factors like inflation, GDP, and corruption affect happiness? Can we predict a country's happiness score based on economic conditions? This dataset allows you to analyze these relationships and build models to predict well-being trends worldwide.
The "Global Country Rankings Dataset" is a comprehensive collection of metrics and indicators that ranks countries worldwide based on their socioeconomic performance. This datasets are providing valuable insights into the relative standings of nations in terms of key factors such as GDP per capita, economic growth, and various other relevant criteria.
Researchers, analysts, and policymakers can leverage this dataset to gain a deeper understanding of the global economic landscape and track the progress of countries over time. The dataset covers a wide range of metrics, including but not limited to:
Economic growth: the rate of change of real GDP- Country rankings: The average for 2021 based on 184 countries was 5.26 percent.The highest value was in the Maldives: 41.75 percent and the lowest value was in Afghanistan: -20.74 percent. The indicator is available from 1961 to 2021.
GDP per capita, Purchasing Power Parity - Country rankings: The average for 2021 based on 182 countries was 21283.21 U.S. dollars.The highest value was in Luxembourg: 115683.49 U.S. dollars and the lowest value was in Burundi: 705.03 U.S. dollars. The indicator is available from 1990 to 2021.
GDP per capita, current U.S. dollars - Country rankings: The average for 2021 based on 186 countries was 17937.03 U.S. dollars.The highest value was in Monaco: 234315.45 U.S. dollars and the lowest value was in Burundi: 221.48 U.S. dollars. The indicator is available from 1960 to 2021.
GDP per capita, constant 2010 dollars - Country rankings: The average for 2021 based on 184 countries was 15605.8 U.S. dollars.The highest value was in Monaco: 204190.16 U.S. dollars and the lowest value was in Burundi: 261.02 U.S. dollars. The indicator is available from 1960 to 2021.