100+ datasets found
  1. T

    MAPS by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 13, 2009
    + more versions
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    TRADING ECONOMICS (2009). MAPS by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/maps
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    xml, json, excel, csvAvailable download formats
    Dataset updated
    Mar 13, 2009
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

    This dataset provides values for MAPS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  2. U

    USA Percent of world GDP - data, chart | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Mar 16, 2016
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    Globalen LLC (2016). USA Percent of world GDP - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/usa/gdp_share/
    Explore at:
    csv, excel, xmlAvailable download formats
    Dataset updated
    Mar 16, 2016
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1980 - Dec 31, 2023
    Area covered
    United States
    Description

    The USA: Percent of world GDP: The latest value from 2023 is 26.3 percent, an increase from 25.73 percent in 2022. In comparison, the world average is 0.53 percent, based on data from 188 countries. Historically, the average for the USA from 1980 to 2023 is 26.89 percent. The minimum value, 21.2 percent, was reached in 2011 while the maximum of 35.32 percent was recorded in 1985.

  3. Countries with the largest gross domestic product (GDP) 2025

    • statista.com
    Updated May 28, 2025
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    Statista (2025). Countries with the largest gross domestic product (GDP) 2025 [Dataset]. https://www.statista.com/statistics/268173/countries-with-the-largest-gross-domestic-product-gdp/
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    Dataset updated
    May 28, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    Worldwide
    Description

    In 2025, the United States had the largest economy in the world, with a gross domestic product of over 30 trillion U.S. dollars. China had the second largest economy, at around 19.23 trillion U.S. dollars. Recent adjustments in the list have seen Germany's economy overtake Japan's to become the third-largest in the world in 2023, while Brazil's economy moved ahead of Russia's in 2024. Global gross domestic product Global gross domestic product amounts to almost 110 trillion U.S. dollars, with the United States making up more than one-quarter of this figure alone. The 12 largest economies in the world include all Group of Seven (G7) economies, as well as the four largest BRICS economies. The U.S. has consistently had the world's largest economy since the interwar period, and while previous reports estimated it would be overtaken by China in the 2020s, more recent projections estimate the U.S. economy will remain the largest by a considerable margin going into the 2030s.The gross domestic product of a country is calculated by taking spending and trade into account, to show how much the country can produce in a certain amount of time, usually per year. It represents the value of all goods and services produced during that year. Those countries considered to have emerging or developing economies account for almost 60 percent of global gross domestic product, while advanced economies make up over 40 percent.

  4. G

    Percent of world GDP by country, around the world | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Nov 18, 2016
    + more versions
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    Globalen LLC (2016). Percent of world GDP by country, around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/gdp_share/
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    xml, excel, csvAvailable download formats
    Dataset updated
    Nov 18, 2016
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1980 - Dec 31, 2023
    Area covered
    World, World
    Description

    The average for 2023 based on 188 countries was 0.53 percent. The highest value was in the USA: 26.3 percent and the lowest value was in Andorra: 0 percent. The indicator is available from 1980 to 2023. Below is a chart for all countries where data are available.

  5. T

    Japan GDP

    • tradingeconomics.com
    • tr.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Nov 10, 2021
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    TRADING ECONOMICS (2021). Japan GDP [Dataset]. https://tradingeconomics.com/japan/gdp
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    xml, json, csv, excelAvailable download formats
    Dataset updated
    Nov 10, 2021
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2024
    Area covered
    Japan
    Description

    The Gross Domestic Product (GDP) in Japan was worth 4026.21 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Japan represents 3.79 percent of the world economy. This dataset provides - Japan GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  6. U

    Ukraine Percent of world GDP - data, chart | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Mar 20, 2016
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    Globalen LLC (2016). Ukraine Percent of world GDP - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Ukraine/gdp_share/
    Explore at:
    excel, csv, xmlAvailable download formats
    Dataset updated
    Mar 20, 2016
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1987 - Dec 31, 2023
    Area covered
    Ukraine
    Description

    Ukraine: Percent of world GDP: The latest value from 2023 is 0.17 percent, an increase from 0.16 percent in 2022. In comparison, the world average is 0.53 percent, based on data from 188 countries. Historically, the average for Ukraine from 1987 to 2023 is 0.21 percent. The minimum value, 0.1 percent, was reached in 1999 while the maximum of 0.42 percent was recorded in 1989.

  7. WWII: pre-war GDP of selected countries and regions 1938

    • statista.com
    Updated Jan 1, 1998
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    Statista (1998). WWII: pre-war GDP of selected countries and regions 1938 [Dataset]. https://www.statista.com/statistics/1334182/wwii-pre-war-gdp/
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    Dataset updated
    Jan 1, 1998
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1938
    Area covered
    World
    Description

    In 1938, the year before the Second World War, the United States had, by far, the largest economy in the world in terms of gross domestic product (GDP). The five Allied Great Powers that emerged victorious from the war, along with the three Axis Tripartite Pact countries that were ultimately defeated made up the eight largest independent economies in 1938.

    When values are converted into 1990 international dollars, the U.S. GDP was over 800 billion dollars in 1938, which was more than double that of the second largest economy, the Soviet Union. Even the combined economies of the UK, its dominions, and colonies had a value of just over 680 billion 1990 dollars, showing that the United States had established itself as the world's leading economy during the interwar period (despite the Great Depression).

    Interestingly, the British and Dutch colonies had larger combined GDPs than their respective metropoles, which was a key motivator for the Japanese invasion of these territories in East Asia during the war. Trade with neutral and non-belligerent countries also contributed greatly to the economic development of Allied and Axis powers throughout the war; for example, natural resources from Latin America were essential to the American war effort, while German manufacturing was often dependent on Swedish iron supplies.

  8. z

    Global Socio-Economic Vulnerability Maps

    • zenodo.org
    zip
    Updated Jun 15, 2025
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    Miguel Toquica; Christopher Burton; Miguel Toquica; Christopher Burton (2025). Global Socio-Economic Vulnerability Maps [Dataset]. http://doi.org/10.13117/gem-social-vulnerability-map
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    zipAvailable download formats
    Dataset updated
    Jun 15, 2025
    Dataset provided by
    GEM Foundation
    Authors
    Miguel Toquica; Christopher Burton; Miguel Toquica; Christopher Burton
    License

    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

    Description

    GEM's Global Socio-Economic Vulnerability Maps

    The Global Social Vulnerability Map (viewable here: https://maps.openquake.org/map/sv-global-human-vulnerability) is a composite index that was developed to measure characteristics or qualities of social systems that create the potential for loss or harm. Here, social vulnerability helps to explain why some countries will experience adverse impacts from earthquakes differentially where the linking of social capacities with demographic attributes suggests that communities with higher percentages of age-dependent populations, homeless, disabled, under-educated, and foreign migrants are likely to exhibit higher social vulnerability than communities lacking these characteristics. Other relevant factors that affect the social vulnerability of populations include in-migration from foreign countries, population density, an accounting of slum populations, and international tourist arrivals.

    The Global Economic Vulnerability Map (viewable here: https://maps.openquake.org/map/sv-global-economic-vulnerability) is a composite index that was designed primarily to measure the potential for economic losses from earthquakes due to a country’s macroeconomic exposure. This index is also an appraisal of the ability of countries to respond to shocks to their economic systems. Relevant indicators include the density of exposed economic assets such as commercial and industrial infrastructure. Metrics used to measure the ability of a country to withstand shocks to its economic system include reliance on imports/exports, government debt, and purchasing power. The economic vulnerability category also considers the economic vitality of countries since the economic vitality of a country can be directly related to the vulnerability and resilience of its populations. The latter includes measurements of single-sector economic dependence, income inequality, and employment status.

    The Recovery/Reconstruction Potential Map (viewable here: https://maps.openquake.org/map/sv-global-recovery-and-reconstruction) is closely aligned with the concept of disaster resilience. Enhancing a country’s resilience to earthquakes is to improve its capacity to anticipate threats, to reduce its overall vulnerability, and to allow its communities to recover from adverse impacts from earthquakes when they occur. The measurement of recovery and reconstruction potential includes capturing inherent conditions that allow communities within a country to absorb impacts and cope with a damaging earthquake event, such as the density of the built environment, education levels, and political participation. It also encompasses post-event processes that facilitate a population’s ability to reorganize, change, and learn in response to a damaging earthquake.


    Criteria for indicator selection
    To choose indicators contextually exclusive for use in each map, the starting point was an exhaustive review of the literature on earthquake social vulnerability and resilience. For a variable to be considered appropriate and selected, three equally important criteria were met:

    - variables were justified based on the literature regarding its relevance to one or more of the indices.
    - variables needed to be of consistent quality and freely available from sources such as the United Nations and the World Bank; and
    - variables must be scalable or available at various levels of geography to promote sub-country level analyses.

    This procedure resulted in a ‘wish list’ of approximately 300 variables of which 78 were available and fit for use based on the three criteria.

    Process for indicator selection
    For variables to be allocated to an index, a two-tiered validation procedure was utilized. For the first tier, variables were assigned to each of the respective indices based on how each variable was cited within the literature, i.e., as being part of an index of social vulnerability, economic vulnerability, or recovery/resilience. For the second tier, machine learning and a multivariate ordinal logistic regression modelling procedure was used for external validation. Here, focus was placed on the statistical association between the socio-economic vulnerability indicators and the adverse impacts from historical earthquakes on a country-by country-basis.

    The Global Significant Earthquake Database provided the external validation metrics that were used as dependent variables in the statistical analysis. To include both severe and moderate earthquakes within the dependent variables, adverse impact data was collected from damaging earthquake events that conformed to at least one of five criteria: 1) caused deaths, 2) caused moderate damage (approximately 1 million USD or more), 3) had a magnitude 7.5 or greater 4) had a Modified Mercalli Intensity (MMI) X or greater, or 5) generated a tsunami. This database was chosen because it considers low magnitude earthquakes that were damaging (e.g., MW >=2.5 & MW<=5.5) and contains socio-economic data such as the total number of fatalities, injuries, houses damaged or destroyed, and dollar loss estimates in USD.

    Countries not demonstrating at least a minimal earthquake risk, i.e., seismicity <0.05 PGA (Pagani et al. 2018) and <$10,000 USD in predicted average annual losses (Silva et al. 2018) were eliminated from the analyses so as not to include countries with minimal to no earthquake risk. A total study area consists of 136 countries.

  9. T

    United States GDP

    • tradingeconomics.com
    • fa.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 15, 2025
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    TRADING ECONOMICS (2025). United States GDP [Dataset]. https://tradingeconomics.com/united-states/gdp
    Explore at:
    xml, excel, json, csvAvailable download formats
    Dataset updated
    Jun 15, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2024
    Area covered
    United States
    Description

    The Gross Domestic Product (GDP) in the United States was worth 29184.89 billion US dollars in 2024, according to official data from the World Bank. The GDP value of the United States represents 27.49 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  10. d

    Global 15 x 15 Minute Grids of the Downscaled GDP Based on the SRES B2...

    • catalog.data.gov
    • s.cnmilf.com
    • +4more
    Updated Apr 24, 2025
    + more versions
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    SEDAC (2025). Global 15 x 15 Minute Grids of the Downscaled GDP Based on the SRES B2 Scenario, 1990 and 2025 [Dataset]. https://catalog.data.gov/dataset/global-15-x-15-minute-grids-of-the-downscaled-gdp-based-on-the-sres-b2-scenario-1990-and-2
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    Dataset updated
    Apr 24, 2025
    Dataset provided by
    SEDAC
    Description

    The Global 15x15 Minute Grids of the Downscaled GDP Based on the Special Report on Emissions Scenarios (SRES) B2 Scenario, 1990 and 2025, are geospatial distributions of Gross Domestic Product (GDP) per Unit area (GDP densities). These global grids were generated using the Country-level GDP and Downscaled Projections Based on the SRES B2 Scenario, 1990-2100 data set, and CIESIN's Gridded Population of World, Version 2 (GPWv2) data set as the base map. First, the GDP per capita was developed at a country-level for 1990 and 2025. Then the gridded GDP was developed within each country by applying the GDP per capita to each grid cell of the GPW, under the assumption that the GDP per capita was uniform within a country. This data set is produced and distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).

  11. T

    GDP by Country Dataset

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 29, 2011
    + more versions
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    TRADING ECONOMICS (2011). GDP by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/gdp
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jun 29, 2011
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    World
    Description

    This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

  12. Global Sectoral GDP map at 30'' resolution (SectGDP30) v2.0

    • zenodo.org
    application/gzip
    Updated Jul 1, 2025
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    Takeshi Shoji; Takeshi Shoji; Kiyoharu Kajiyama; Kiyoharu Kajiyama; Dai Yamazaki; Dai Yamazaki; Yuki Kita; Yuki Kita; Megumi Watanabe; Megumi Watanabe (2025). Global Sectoral GDP map at 30'' resolution (SectGDP30) v2.0 [Dataset]. http://doi.org/10.5281/zenodo.15774017
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    application/gzipAvailable download formats
    Dataset updated
    Jul 1, 2025
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Takeshi Shoji; Takeshi Shoji; Kiyoharu Kajiyama; Kiyoharu Kajiyama; Dai Yamazaki; Dai Yamazaki; Yuki Kita; Yuki Kita; Megumi Watanabe; Megumi Watanabe
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    - This dataset provides global sector-specific GDP distribution maps (in GeoTIFF format) with a 30-second spatial resolution. It allocates GDP at the 30-arcsecond grid level for three sectors (services, industry, and agriculture) by the distribution of country-level GDP data using high-resolution land cover map.
    - The source GDP data for allocation is based on nominal GDP for the years 2010, 2015, and 2020, obtained from the World Bank. As the high-resolution land cover map, it uses the built-up area and non-residential area data by the Global Human Settlement Layer (Pesaresi and Politis, 2022) for the service and industrial sectors and the Global cropland map by Potapov et al. (2022) for the agriculture sector. Detailed descriptions of the data creation methodology can be found in Shoji et al. (In Review).
    - Each pixel represents the monetary value of added value generated by economic activity hypothetically occurring within that pixel. The unit of each pixel value is in millions of USD (current prices for 2010, 2015, and 2020).

    (Updated to v2.0 on July 1, 2025)

    This update includes a major change to the spatial allocation method for service and agricultural GDP. For details on the new GDP mapping methodology, please refer to Shoji et al. (In Review). There are no changes to the industrial GDP map.

    Reference:
    - Pesaresi M, Politis P.: GHS-BUILT-S R2022A: GHS built-up surface grid, derived from Sentinel2 composite and Landsat, multitemporal (1975–2030). European Commission, Joint Research Centre (JRC), 2022.
    - Potapov P, Svetlana T, Matthew CH, Alexandra T, Viviana Z, Ahmad K, Xiao-Peng S, Amy P, Quan S, Jocelyn C.: Global maps of cropland extent and change show accelerated cropland expansion in the twenty-first century. Nature Food 3: 19–28, 2022.
    - Shoji T, Kajiyama K, Yamazaki D, Kita Y, Watanabe M.: Global spatially-distributed sectoral GDP map for disaster risk analysis. In Review.

  13. G

    Asia-Pacific Economic Cooperation (APEC)

    • open.canada.ca
    • ouvert.canada.ca
    • +1more
    pdf
    Updated Mar 14, 2022
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    Natural Resources Canada (2022). Asia-Pacific Economic Cooperation (APEC) [Dataset]. https://open.canada.ca/data/en/dataset/2ca13772-9756-5ddf-91dc-10714c733e64
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    pdfAvailable download formats
    Dataset updated
    Mar 14, 2022
    Dataset provided by
    Natural Resources Canada
    License

    Open Government Licence - Canada 2.0https://open.canada.ca/en/open-government-licence-canada
    License information was derived automatically

    Area covered
    Asia-Pacific
    Description

    This world map shows the member economies of Asia-Pacific Economic Cooperation (APEC).

  14. Global merchandise exports index 2019-2024, by region

    • statista.com
    Updated Sep 19, 2023
    + more versions
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    Jose Sanchez (2023). Global merchandise exports index 2019-2024, by region [Dataset]. https://www.statista.com/topics/6139/covid-19-impact-on-the-global-economy/
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    Dataset updated
    Sep 19, 2023
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Jose Sanchez
    Description

    In July 2024, the merchandise exports index worldwide, excluding the U.S., stood at 204.8. This is compared to an index value of 143 for the United States in the same month. The index was highest in emerging economies, reaching an index score of 353. Moreover, the merchandise imports index was also highest in emerging economies. The merchandise exports index is the U.S. dollar value of goods sold to the rest of the world, deflated by the U.S. Consumer Price Index (CPI).

  15. S

    Sweden Percent of world GDP - data, chart | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Mar 20, 2016
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    Globalen LLC (2016). Sweden Percent of world GDP - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Sweden/gdp_share/
    Explore at:
    xml, excel, csvAvailable download formats
    Dataset updated
    Mar 20, 2016
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1980 - Dec 31, 2023
    Area covered
    Sweden
    Description

    Sweden: Percent of world GDP: The latest value from 2023 is 0.56 percent, a decline from 0.57 percent in 2022. In comparison, the world average is 0.53 percent, based on data from 188 countries. Historically, the average for Sweden from 1980 to 2023 is 0.85 percent. The minimum value, 0.56 percent, was reached in 2023 while the maximum of 1.31 percent was recorded in 1980.

  16. T

    Iran GDP

    • tradingeconomics.com
    • it.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Iran GDP [Dataset]. https://tradingeconomics.com/iran/gdp
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    excel, xml, csv, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2024
    Area covered
    Iran
    Description

    The Gross Domestic Product (GDP) in Iran was worth 436.91 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Iran represents 0.41 percent of the world economy. This dataset provides - Iran GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

  17. U.S. gross domestic product 2024, by state

    • statista.com
    Updated Jul 31, 2025
    + more versions
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    Statista (2025). U.S. gross domestic product 2024, by state [Dataset]. https://www.statista.com/statistics/248023/us-gross-domestic-product-gdp-by-state/
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    Dataset updated
    Jul 31, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2024
    Area covered
    United States
    Description

    The gross domestic product (GDP) of California was about 4.1 trillion U.S. dollars in 2024, meaning that it contributed the most out of any state to the country’s GDP in that year. In contrast, Vermont had the lowest GDP in the United States, with 45.71 billion U.S. dollars. What is GDP? Gross domestic product, or GDP, is the total monetary value of all goods and services produced by an economy within a certain time period. GDP is used by economists to determine the economic health of an area, as well as to determine the size of the economy. GDP can be determined for countries, states and provinces, and metropolitan areas. While GDP is a good measure of the absolute size of a country's economy and economic activity, it does account for many other factors, making it a poor indicator for measuring the cost or standard of living in a country, or for making cross-country comparisons. GDP of the United States The United States has the largest gross domestic product in the world as of 2023, with China, Japan, Germany, and India rounding out the top five. The GDP of the United States has almost quadrupled since 1990, when it was about 5.9 trillion U.S. dollars, to about 25.46 trillion U.S. dollars in 2022.

  18. T

    Euro Area GDP

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Euro Area GDP [Dataset]. https://tradingeconomics.com/euro-area/gdp
    Explore at:
    xml, csv, json, excelAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1960 - Dec 31, 2024
    Area covered
    Euro Area
    Description

    The Gross Domestic Product (GDP) In the Euro Area was worth 16406.13 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Euro Area represents 14.74 percent of the world economy. This dataset provides the latest reported value for - Euro Area GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  19. T

    Russia GDP

    • tradingeconomics.com
    • jp.tradingeconomics.com
    • +13more
    csv, excel, json, xml
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    TRADING ECONOMICS, Russia GDP [Dataset]. https://tradingeconomics.com/russia/gdp
    Explore at:
    json, xml, excel, csvAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1988 - Dec 31, 2024
    Area covered
    Russia
    Description

    The Gross Domestic Product (GDP) in Russia was worth 2173.84 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Russia represents 2.05 percent of the world economy. This dataset provides the latest reported value for - Russia GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  20. S

    South Korea Percent of world GDP - data, chart | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Mar 30, 2016
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    Globalen LLC (2016). South Korea Percent of world GDP - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/South-Korea/gdp_share/
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    xml, excel, csvAvailable download formats
    Dataset updated
    Mar 30, 2016
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1980 - Dec 31, 2023
    Area covered
    South Korea
    Description

    South Korea: Percent of world GDP: The latest value from 2023 is 1.62 percent, a decline from 1.66 percent in 2022. In comparison, the world average is 0.53 percent, based on data from 188 countries. Historically, the average for South Korea from 1980 to 2023 is 1.54 percent. The minimum value, 0.61 percent, was reached in 1980 while the maximum of 2.05 percent was recorded in 2006.

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TRADING ECONOMICS (2009). MAPS by Country Dataset [Dataset]. https://tradingeconomics.com/country-list/maps

MAPS by Country Dataset

MAPS by Country Dataset (2025)

Explore at:
89 scholarly articles cite this dataset (View in Google Scholar)
xml, json, excel, csvAvailable download formats
Dataset updated
Mar 13, 2009
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
2025
Area covered
World
Description

This dataset provides values for MAPS reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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