TThe ERS International Macroeconomic Data Set provides historical and projected data for 181 countries that account for more than 99 percent of the world economy. These data and projections are assembled explicitly to serve as underlying assumptions for the annual USDA agricultural supply and demand projections, which provide a 10-year outlook on U.S. and global agriculture. The macroeconomic projections describe the long-term, 10-year scenario that is used as a benchmark for analyzing the impacts of alternative scenarios and macroeconomic shocks.

Explore the International Macroeconomic Data Set 2015 for annual growth rates, consumer price indices, real GDP per capita, exchange rates, and more. Get detailed projections and forecasts for countries worldwide.

Annual growth rates, Consumer price indices (CPI), Real GDP per capita, Real exchange rates, Population, GDP deflator, Real gross domestic product (GDP), Real GDP shares, GDP, projections, Forecast, Real Estate, Per capita, Deflator, share, Exchange Rates, CPI

Afghanistan, Albania, Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Côte d'Ivoire, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Mauritania, Mauritius, Mexico, Moldova, Mongolia, Morocco, Mozambique, Myanmar, Namibia, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, Norway, Oman, Pakistan, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, South Africa, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, Zimbabwe, WORLD Follow data.kapsarc.org for timely data to advance energy economics research. Notes:

Developed countries/1 Australia, New Zealand, Japan, Other Western Europe, European Union 27, North America

Developed countries less USA/2 Australia, New Zealand, Japan, Other Western Europe, European Union 27, Canada

Developing countries/3 Africa, Middle East, Other Oceania, Asia less Japan, Latin America;

Low-income developing countries/4 Haiti, Afghanistan, Nepal, Benin, Burkina Faso, Burundi, Central African Republic, Chad, Democratic Republic of Congo, Eritrea, Ethiopia, Gambia, Guinea, Guinea-Bissau, Liberia, Madagascar, Malawi, Mali, Mozambique, Niger, Rwanda, Senegal, Sierra Leone, Somalia, Tanzania, Togo, Uganda, Zimbabwe;

Emerging markets/5 Mexico, Brazil, Chile, Czech Republic, Hungary, Poland, Slovakia, Russia, China, India, Korea, Taiwan, Indonesia, Malaysia, Philippines, Thailand, Vietnam, Singapore

BRIICs/5 Brazil, Russia, India, Indonesia, China; Former Centrally Planned Economies

Former centrally planned economies/7 Cyprus, Malta, Recently acceded countries, Other Central Europe, Former Soviet Union

USMCA/8 Canada, Mexico, United States

Europe and Central Asia/9 Europe, Former Soviet Union

Middle East and North Africa/10 Middle East and North Africa

Other Southeast Asia outlook/11 Malaysia, Philippines, Thailand, Vietnam

Other South America outlook/12 Chile, Colombia, Peru, Bolivia, Paraguay, Uruguay

Indicator Source

Real gross domestic product (GDP) World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service all converted to a 2015 base year.

Real GDP per capita U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table and Population table.

GDP deflator World Bank World Development Indicators, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Real GDP shares U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, GDP table.

Real exchange rates U.S. Department of Agriculture, Economic Research Service, Macroeconomic Data Set, CPI table, and Nominal XR and Trade Weights tables developed by the Economic Research Service.

Consumer price indices (CPI) International Financial Statistics International Monetary Fund, IHS Global Insight, Oxford Economics Forecasting, as well as estimated and projected values developed by the Economic Research Service, all converted to a 2015 base year.

Population Department of Commerce, Bureau of the Census, U.S. Department of Agriculture, Economic Research Service, International Data Base.

In 2024, the growth of the real gross domestic product (GDP) in Argentina stood at -1.34 percent. Between 1980 and 2024, the figure dropped by 2.04 percentage points, though the decline followed an uneven course rather than a steady trajectory. From 2024 to 2030, the growth will rise by 4.55 percentage points, showing an overall upward trend with periodic ups and downs.This indicator describes the annual change in the gross domestic product at constant prices, expressed in national currency units. Here the gross domestic product represents the total value of the final goods and services produced during a year.

In 2024, the finance, real estate, insurance, rental, and leasing industry added the most value to the GDP of the United States. In that year, this industry added 6.2 trillion U.S. dollars to the national GDP. Gross Domestic Product Gross domestic product is a measure of how much a country produces in a certain amount of time. Countries with a high GDP tend to have large economies, for example, the United States. However, GDP does not take into consideration the cost of living and inflation rates, so it is not a good measure of the standard of living. GDP per capita at purchasing power parity is thought to be more reflective of living conditions within a particular country. U.S. GDP California added the largest amount of value to the real GDP of the U.S. in 2022. California was followed by Texas and New York. In California, the professional and business services industry was the most valuable to GDP in 2022. In New York, the finance, insurance, real estate, rental, and leasing industry added the most value to the state GDP. While the business sector added the highest value to the U.S. real GDP in 2021, it was the information industry that had the biggest percentage change in value added to the GDP between 2010 and 2021.

Graph and download economic data for Infra-Annual Labor Statistics: Unemployment Rate Total: From 15 to 64 Years for Poland (LRUN64TTPLQ156N) from Q1 1999 to Q2 2025 about Poland, 15 to 64 years, unemployment, and rate.

India PFS: Real GDP: Growth Rate: Current Fiscal Year: Mean data was reported at 7.000 % in Mar 2019. This records a decrease from the previous number of 7.200 % for Dec 2018. India PFS: Real GDP: Growth Rate: Current Fiscal Year: Mean data is updated quarterly, averaging 7.100 % from Jun 2017 (Median) to Mar 2019, with 8 observations. The data reached an all-time high of 7.400 % in Sep 2018 and a record low of 6.500 % in Dec 2017. India PFS: Real GDP: Growth Rate: Current Fiscal Year: Mean data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under Global Database’s India – Table IN.SE002: Professional Forecasters Survey (PFS): Reserve Bank of India: Annual Forecasts: Real GDP Growth Rate.

Georgia GDP Index: GVA: Agriculture, Forestry and Fishing data was reported at 97.452 Same Qtr PY=100 in Jun 2018. This records an increase from the previous number of 96.243 Same Qtr PY=100 for Mar 2018. Georgia GDP Index: GVA: Agriculture, Forestry and Fishing data is updated quarterly, averaging 99.443 Same Qtr PY=100 from Mar 1998 (Median) to Jun 2018, with 82 observations. The data reached an all-time high of 120.741 Same Qtr PY=100 in Sep 2007 and a record low of 78.806 Same Qtr PY=100 in Sep 2006. Georgia GDP Index: GVA: Agriculture, Forestry and Fishing data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.A017: GDP: by Industry: Index: Same Quarter Previous Year=100.

GDP Index: Guangxi data was reported at 104.200 Prev Year=100 in 2024. This records an increase from the previous number of 104.100 Prev Year=100 for 2023. GDP Index: Guangxi data is updated yearly, averaging 108.345 Prev Year=100 from Dec 1952 (Median) to 2024, with 73 observations. The data reached an all-time high of 126.600 Prev Year=100 in 1969 and a record low of 85.700 Prev Year=100 in 1961. GDP Index: Guangxi data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under Global Database’s China – Table CN.AB: Gross Domestic Product: Index: by Province.

【リソース】Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Nominal Gross Domestic Product (original series) (csv:28KB) / GDP (expenditure approach) and its components / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Annual Nominal GDP (fiscal year) (csv:8KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Nominal Gross Domestic Product (seasonally adjusted series) (csv:29KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Annual Nominal GDP (calendar year) (csv:8KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Real Gross Domestic Product (original series) (csv:31KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Annual Real GDP (fiscal year) (csv:9KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Real Gross Domestic Product (seasonally adjusted series) (csv:32KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Annual Real GDP (calendar year) (csv:9KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Changes from the previous year (at current prices: original series) (csv:14KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Changes from the previous year (at current prices: fiscal year) (csv:5KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Changes from the previous quarter (at current prices: seasonally adjusted series) (csv:14KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Changes from the previous year (at current prices: calendar year) (csv:4KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Changes from the previous year (at chained (2011) prices: original series) (csv:15KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Changes from the previous year (at chained (2011) prices: fiscal year) (csv:5KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Changes from the previous quarter (at chained (2011) prices: seasonally adjusted series) (csv:15KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Changes from the previous year (at chained (2011) prices: calendar year) (csv:4KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Annualized rate of changes from the previous quarter (at current prices: seasonally adjusted series) (csv:13KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Annualized rate of changes from the previous quarter (at chained (2011) prices: seasonally adjusted series) (csv:13KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Contributions to Changes in Nominal GDP (original series) (csv:15KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Contributions to Changes in Annual Nominal GDP (fiscal year) (csv:5KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Contributions to Changes in Nominal GDP (seasonally adjusted series) (csv:15KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Contributions to Changes in Annual Nominal GDP (calendar year) (csv:5KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Contributions to Changes in Real GDP (original series) (csv:15KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Contributions to Changes in Annual Real GDP (fiscal year) (csv:6KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Contributions to Changes in Real GDP (seasonally adjusted series) (csv:16KB) / Quarterly Estimates of GDP Apr.-Jun. 2018 (The 2nd Preliminary) : GDP (expenditure approach) and its components : Contributions to Changes in Annual Real GDP (calendar Year) (csv:5KB) / Quarterly Estimates of GDP

Vietnam GDP: HCMC: Year to Date: IC: Industry data was reported at 170,590.000 VND bn in Sep 2018. This records an increase from the previous number of 107,991.000 VND bn for Jun 2018. Vietnam GDP: HCMC: Year to Date: IC: Industry data is updated quarterly, averaging 92,268.500 VND bn from Jun 2004 (Median) to Sep 2018, with 54 observations. The data reached an all-time high of 1,193,626.000 VND bn in Jun 2016 and a record low of 18,056.000 VND bn in Mar 2007. Vietnam GDP: HCMC: Year to Date: IC: Industry data remains active status in CEIC and is reported by Ho Chi Minh City Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.A029: Gross Domestic Product: Ho Chi Minh City: Quarterly.

Indonesia ID: Average Productive Capital Stocks: Over the Year: Growth data was reported at 4.374 % in 2025. This records an increase from the previous number of 4.090 % for 2024. Indonesia ID: Average Productive Capital Stocks: Over the Year: Growth data is updated yearly, averaging 4.306 % from Dec 1991 (Median) to 2025, with 35 observations. The data reached an all-time high of 6.688 % in 1997 and a record low of 1.911 % in 2000. Indonesia ID: Average Productive Capital Stocks: Over the Year: Growth data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Indonesia – Table ID.OECD.EO: GDP: Potential Output and Output Gap: Forecast: Non OECD Member: Annual. KTPV_AV_ANNPCT - Productive capital stock, volume, annual average, growth

Georgia GDP Index: GVA: Transport and Storage data was reported at 100.224 Same Qtr PY=100 in Mar 2018. This records a decrease from the previous number of 110.625 Same Qtr PY=100 for Dec 2017. Georgia GDP Index: GVA: Transport and Storage data is updated quarterly, averaging 106.570 Same Qtr PY=100 from Mar 1998 (Median) to Mar 2018, with 81 observations. The data reached an all-time high of 237.533 Same Qtr PY=100 in Sep 1998 and a record low of 78.630 Same Qtr PY=100 in Sep 2008. Georgia GDP Index: GVA: Transport and Storage data remains active status in CEIC and is reported by National Statistics Office of Georgia. The data is categorized under Global Database’s Georgia – Table GE.A017: GDP: by Industry: Index: Same Quarter Previous Year=100.

Employment, Commuting, Occupation, Income, Health Insurance, Poverty, and more. This service is updated annually with American Community Survey (ACS) 5-year data. Contact: District of Columbia, Office of Planning. Email: planning@dc.gov. Geography: 2022 Wards (State Legislative Districts [Upper Chamber]). Current Vintage: 2019-2023. ACS Table(s): DP03. Data downloaded from: Census Bureau's API for American Community Survey. Date of API call: January 2, 2025. National Figures: data.census.gov. Please cite the Census and ACS when using this data. Data Note from the Census: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables. Data Processing Notes: This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2020 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page. Data processed using R statistical package and ArcGIS Desktop. Margin of Error was not included in this layer but is available from the Census Bureau. Contact the Office of Planning for more information about obtaining Margin of Error values.

Real Household Income Index: PY=100: CF: Tula Region data was reported at 111.400 Prev Year=100 in 2024. This records an increase from the previous number of 107.000 Prev Year=100 for 2023. Real Household Income Index: PY=100: CF: Tula Region data is updated yearly, averaging 103.200 Prev Year=100 from Dec 1994 (Median) to 2024, with 31 observations. The data reached an all-time high of 119.800 Prev Year=100 in 2006 and a record low of 78.000 Prev Year=100 in 1998. Real Household Income Index: PY=100: CF: Tula Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Russia Premium Database’s Household Survey – Table RU.HA008: Real Household Income Index: by Region: Previous Year=100.

The Gross Domestic Product (GDP) in Slovenia expanded 0.80 percent in the third quarter of 2025 over the previous quarter. This dataset provides - Slovenia GDP Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The Gross Domestic Product per capita in Georgia was last recorded at 6840.01 US dollars in 2024. The GDP per Capita in Georgia is equivalent to 54 percent of the world's average. This dataset provides - Georgia GDP per capita - actual values, historical data, forecast, chart, statistics, economic calendar and news.

CN:(GDP) Gross Domestic ProductIndex: PY=100: Beijing: Xicheng data was reported at 105.800 Prev Year=100 in 2023. This records an increase from the previous number of 104.100 Prev Year=100 for 2022. CN:(GDP) Gross Domestic ProductIndex: PY=100: Beijing: Xicheng data is updated yearly, averaging 106.507 Prev Year=100 from Dec 2011 (Median) to 2023, with 13 observations. The data reached an all-time high of 114.700 Prev Year=100 in 2011 and a record low of 98.900 Prev Year=100 in 2020. CN:(GDP) Gross Domestic ProductIndex: PY=100: Beijing: Xicheng data remains active status in CEIC and is reported by Beijing Municipal Bureau of Statistics. The data is categorized under China Premium Database’s National Accounts – Table CN.AI: Gross Domestic Product: Index: PY=100: Municipality District.

Graph and download economic data for Infra-Annual Labor Statistics: Labor Force Total: From 15 to 74 Years for Denmark (LFAC74TTDKQ647S) from Q1 1999 to Q2 2025 about 15 to 74 years, Denmark, labor force, labor, and personal.

Kazakhstan GDP Deflator: Goods: Industry: Electricity, Gas, Steam & Air Conditioning Supply data was reported at 107.900 Prev Year=100 in 2017. This records a decrease from the previous number of 111.300 Prev Year=100 for 2016. Kazakhstan GDP Deflator: Goods: Industry: Electricity, Gas, Steam & Air Conditioning Supply data is updated yearly, averaging 110.700 Prev Year=100 from Dec 2010 (Median) to 2017, with 8 observations. The data reached an all-time high of 127.100 Prev Year=100 in 2010 and a record low of 104.400 Prev Year=100 in 2012. Kazakhstan GDP Deflator: Goods: Industry: Electricity, Gas, Steam & Air Conditioning Supply data remains active status in CEIC and is reported by The Agency of Statistics of the Republic of Kazakhstan. The data is categorized under Global Database’s Kazakhstan – Table KZ.A019: GDP Deflator: Previous Year=100: Annual.

Poland PL: Primary Completion Rate: Total: % of Relevant Age Group data was reported at 100.163 % in 2016. This records an increase from the previous number of 98.755 % for 2015. Poland PL: Primary Completion Rate: Total: % of Relevant Age Group data is updated yearly, averaging 96.132 % from Dec 1971 (Median) to 2016, with 45 observations. The data reached an all-time high of 100.919 % in 1989 and a record low of 92.210 % in 1973. Poland PL: Primary Completion Rate: Total: % of Relevant Age Group data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Poland – Table PL.World Bank: Education Statistics. Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.; ; UNESCO Institute for Statistics; Weighted average; Each economy is classified based on the classification of World Bank Group's fiscal year 2018 (July 1, 2017-June 30, 2018).

Denton economic data from the American Community Survey (ACS)