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.

Based on IMF forecasts from October 2023, the real GDP growth in industrial countries will slow in 2023, only growing by *** percent. This is because of the impact of the high global inflation rates. On the other hand, the GDP of emerging and developing countries is expected to grow by around **** percent both in 2022, 2023, and 2024.

This study examines the determinants influencing the likelihood of Sub-Saharan African (SSA) countries seeking assistance from the International Monetary Fund (IMF). The IMF, as a global institution, aims to promote sustainable growth and prosperity among its member countries by supporting economic strategies that foster financial stability and collaboration in monetary affairs. Utilising panel-probit regression, this study analyses data from thirty-nine SSA countries spanning from 2000 to 2022, focusing on twelve factors: Current Account Balance (CAB), inflation, corruption, General Government Net Lending and Borrowing (GGNLB), General Government Gross Debt (GGGD), Gross Domestic Product Growth (GDPG), United Nations Security Council (UNSC) involvement, regime types (Closed Autocracy, Electoral Democracy, Electoral Autocracy, Liberal Democracy) and China Loan. The results indicate that corruption and GDP growth rate have the most significant influence on the likelihood of SSA countries seeking IMF assistance. Conversely, factors such as CAB, UNSC involvement, LD and inflation show inconsequential effects. Notable, countries like Sudan, Burundi, and Guinea consistently rank high in seeking IMF assistance over various time frames within the observed period. Sudan emerges with a probability of more than 44% in seeking IMF assistance, holding the highest ranking. Study emphasises the importance of understanding SSA region rankings and the variability of variables for policymakers, investors, and international organisations to effectively address economic challenges and provide financial assistance.

Vietnam VN: IMF Forecast: General Government: Gross Debt: % of GDP data was reported at 58.120 % in 2023. This records an increase from the previous number of 57.648 % for 2022. Vietnam VN: IMF Forecast: General Government: Gross Debt: % of GDP data is updated yearly, averaging 48.237 % from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 59.942 % in 2016 and a record low of 31.432 % in 2000. Vietnam VN: IMF Forecast: General Government: Gross Debt: % of GDP data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Vietnam – Table VN.IMF.FM: Government Finance Statistics.

This dataset has all the countries listed with their continents, GDP, population and GDP_per_capita. We can use GDP per capita as a label and play with the dataset. Using linear regression , is there a possibility to explore in terms of reciprocal relation between the features.

Graph and download economic data for Gross Domestic Product in Current Prices for Georgia (GEONGDPDUSD) from 2000 to 2025 about Georgia, REO, and GDP.

APD Regional Economic Outlook (REO) provides information on recent economic developments and prospects for countries in Asia and Pacific. Data for the REO for Asia and Pacific is prepared in conjunction with the semi-annual World Economic Outlook (WEO) exercises, spring and fall. Data are consistent with the projections underlying the WEO. REO aggregate data may differ from WEO aggregates due to differences in group membership. Composite data for country groups are weighted averages of data for individual countries. Arithmetic weighted averages are used for all concepts except for inflation and broad money, for which geometric averages are used. PPP GDP weights from the WEO database are used for the aggregation of real GDP growth, real non-oil GDP growth, real per capita GDP growth, investment, national savings, broad money, claims on the nonfinancial private sector, and real and nominal effective exchange rates. Aggregates for other concepts are weighted by GDP in U.S. dollars at market exchange rates.

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.

IMF World Economic Outlook (WEO) database. The "http://www.imf.org/external/ns/cs.aspx?id=29">IMF World Economic Outlook is a twice-yearly survey by IMF staff that presents IMF staff economists' analyses of global economic developments during the near and medium term. Associated with the report is the "http://www.imf.org/external/ns/cs.aspx?id=28">World Economic Outlook Database, a country-level dataset of major macro-economic variables (GDP, Unemployment, Debt etc). It is the data from that database which is provided here.

Data

The source database is made of annual values for each country on 45 indicators since 1980. In addition the database includes the IMF projects approximately 6 years into the future.

We extract this data and normalize into 2 files:

• Indicators - data/indicators.csv - the list of indicators
• Values - data/values.csv - set of values for each indicator, country, year tuple.

Sources

Note the XLS files actual turn out to be tsv files!

• Listing page for WEO Database
• 2014 - http://www.imf.org/external/pubs/ft/weo/2014/01/weodata/index.aspx
  • http://www.imf.org/external/pubs/ft/weo/2014/01/weodata/WEOApr2014all.xls
• 2011 - http://www.imf.org/external/pubs/ft/weo/2011/02/weodata/index.aspx
  • http://www.imf.org/external/pubs/ft/weo/2011/02/weodata/WEOSep2011all.xls

Preparation

Code to extract the data from the source WEO Database is in the scripts directory.

The BRICS countries overtook the G7 countries share of the world's total gross domestic product (GDP) in terms of purchasing power parity (PPP) in 2018. By 2024, the difference had increased even further, the BRICS now holding a total 35 percent of the world's GDP compared to 30 percent held by the G7 countries.

AFR Regional Economic Outlook (REO) provides information on recent economic developments and prospects for countries in Sub-Saharan Africa. Data for the REO for Sub-Saharan Africa is prepared in conjunction with the semi-annual World Economic Outlook (WEO) exercises, spring and fall. Data are consistent with the projections underlying the WEO. REO aggregate data may differ from WEO aggregates due to differences in group membership. Composite data for country groups are weighted averages of data for individual countries. Arithmetic weighted averages are used for all concepts except for inflation and broad money, for which geometric averages are used. PPP GDP weights from the WEO database are used for the aggregation of real GDP growth, real non-oil GDP growth, real per capita GDP growth, investment, national savings, broad money, claims on the nonfinancial private sector, and real and nominal effective exchange rates. Aggregates for other concepts are weighted by GDP in U.S. dollars at market exchange rates.

GDP per capita (current US$) is an economic indicator that measures the average economic output per person in a country. It is calculated by dividing the total Gross Domestic Product (GDP) of a country by its population, both measured in current US dollars. GDP per capita provides a useful metric for comparing the economic well-being and living standards between different countries.

There are various sources where you can find GDP per capita data, including international organizations, government agencies, and financial institutions. Some prominent sources for GDP per capita data include:

1. World Bank: The World Bank provides comprehensive data on GDP per capita for countries around the world. They maintain the World Development Indicators (WDI) database, which includes GDP per capita figures for different years.

2. International Monetary Fund (IMF): The IMF also offers GDP per capita data through their World Economic Outlook (WEO) database. It provides economic indicators and forecasts, including GDP per capita figures for various countries.

3. National Statistical Agencies: Many countries have their own national statistical agencies that publish GDP per capita data. These agencies collect and analyze economic data, including GDP and population figures, to calculate GDP per capita.

4. Central Banks: In some cases, central banks may also provide GDP per capita data for their respective countries. They often publish economic indicators and reports that include GDP per capita figures.

When using GDP per capita data, it's important to note that it represents an average measure and does not necessarily reflect the distribution of wealth within a country. Additionally, GDP per capita figures are often adjusted for inflation to provide real GDP per capita, which accounts for changes in the purchasing power of money over time.

To access the most up-to-date and accurate GDP per capita data, it is recommended to refer to reputable sources mentioned above or consult the official websites of international organizations, government agencies, or central banks that specialize in economic data and analysis.

The Fiscal Monitor surveys and analyzes the latest public finance developments, it updates fiscal implications of the crisis and medium-term fiscal projections, and assesses policies to put public finances on a sustainable footing.

Country-specific data and projections for key fiscal variables are based on the April 2020 World Economic Outlook database, unless indicated otherwise, and compiled by the IMF staff. Historical data and projections are based on information gathered by IMF country desk officers in the context of their missions and through their ongoing analysis of the evolving situation in each country; they are updated on a continual basis as more information becomes available. Structural breaks in data may be adjusted to produce smooth series through splicing and other techniques. IMF staff estimates serve as proxies when complete information is unavailable. As a result, Fiscal Monitor data can differ from official data in other sources, including the IMF's International Financial Statistics.

The country classification in the Fiscal Monitor divides the world into three major groups: 35 advanced economies, 40 emerging market and middle-income economies, and 40 low-income developing countries. The seven largest advanced economies as measured by GDP (Canada, France, Germany, Italy, Japan, United Kingdom, United States) constitute the subgroup of major advanced economies, often referred to as the Group of Seven (G7). The members of the euro area are also distinguished as a subgroup. Composite data shown in the tables for the euro area cover the current members for all years, even though the membership has increased over time. Data for most European Union member countries have been revised following the adoption of the new European System of National and Regional Accounts (ESA 2010). The low-income developing countries (LIDCs) are countries that have per capita income levels below a certain threshold (currently set at $2,700 in 2016 as measured by the World Bank's Atlas method), structural features consistent with limited development and structural transformation, and external financial linkages insufficiently close to be widely seen as emerging market economies. Zimbabwe is included in the group. Emerging market and middle-income economies include those not classified as advanced economies or low-income developing countries. See Table A, "Economy Groupings," for more details.

Most fiscal data refer to the general government for advanced economies, while for emerging markets and developing economies, data often refer to the central government or budgetary central government only (for specific details, see Tables B-D). All fiscal data refer to the calendar years, except in the cases of Bangladesh, Egypt, Ethiopia, Haiti, Hong Kong Special Administrative Region, India, the Islamic Republic of Iran, Myanmar, Nepal, Pakistan, Singapore, and Thailand, for which they refer to the fiscal year.

Composite data for country groups are weighted averages of individual-country data, unless otherwise specified. Data are weighted by annual nominal GDP converted to U.S. dollars at average market exchange rates as a share of the group GDP.

In many countries, fiscal data follow the IMF's Government Finance Statistics Manual 2014. The overall fiscal balance refers to net lending (+) and borrowing ("") of the general government. In some cases, however, the overall balance refers to total revenue and grants minus total expenditure and net lending.

The fiscal gross and net debt data reported in the Fiscal Monitor are drawn from official data sources and IMF staff estimates. While attempts are made to align gross and net debt data with the definitions in the IMF's Government Finance Statistics Manual, as a result of data limitations or specific country circumstances, these data can sometimes deviate from the formal definitions.

Contains the GDP growth (% change) from 1980 to 2023 (predicted from 2019 and onwards) for countries around the world. The data was sourced from the International Monetary Fund (IMF), World Economic Outlook (Oct 2018), and from Focus Economics. The spatial data (polygons) were sourced from the World Countries layer by Esri.You can view and download the data here: https://www.imf.org/external/datamapper/NGDP_RPCH@WEO/OEMDC/ADVEC/WEOWORLDhttps://www.focus-economics.com/blog/emerging-markets-2019-economic-outlook

By the year 2030, it is projected that China will eclipse the United States and have the largest gross domestic product (GDP) in the world, at 31.7 trillion U.S. dollars. The United States is projected to have the second largest GDP, at 22.9 trillion U.S. dollars.

What is gross domestic product?

Gross domestic product, or GDP, is an economic measure of a country’s production in time. It includes all goods and services produced by a country and is used by economists to determine the health of a country’s economy. However, since GDP just shows the size of an economy and is not adjusted for the country’s size, this can make direct country comparisons complicated.

The growth of the global economy

Currently, the United States has the largest GDP in the world, at 20.5 trillion U.S. dollars. China has the second largest GDP, at 13.4 trillion U.S. dollars. In the coming years, production will become faster and more global, which will help to grow the global economy.

The database used includes annual frequency data for 43 countries, defined by the IMF as 24 advanced countries and 19 emerging countries, for the years 1992-2018.The database contains the fiscal stress variable and a set of variables that can be classified as follows: macroeconomic and global economy (interest rates in the US, OECD; real GDP in the US, y-o-y, OECD; real GDP in China, y-o-y, World Bank; oil price, y-o-y, BP p.l.c.; VIX, CBOE; real GDP, y-o-y, World Bank, OECD, IMF WEO; GDP per capita in PPS, World Bank); financial (nominal USD exchange rate, y-o-y, IMF IFS; private credit to GDP, change in p.p., IMF IFS, World Bank and OECD); fiscal (general government balance, % GDP, IMF WEO; general government debt, % GDP, IMF WEO, effective interest rate on the g.g. debt, IMF WEO); competitiveness and domestic demand (currency overvaluation, IMF WEO; current account balance, % GDP, IMF WEO; share in global exports, y-o-y, World Bank, OECD; gross fixed capital formation, y-o-y, World Bank, OECD; CPI, IMF IFS, IMF WEO; real consumption, y-o-y, World Bank, OECD); labor market (unemployment rate, change in p.p., IMF WEO; labor productivity, y-o-y, ILO).In line with the convention adopted in the literature, the fiscal stress variable is a binary variable equal to 1 in the case of a fiscal stress event and 0 otherwise. In more recent literature in this field, the dependent variable tends to be defined broadly, reflecting not only outright default or debt restructuring, but also less extreme events. Therefore, following Baldacci et al. (2011), the definition used in the present database is broad, and the focus is on signalling fiscal stress events, in contrast to the narrower event of a fiscal crisis related to outright default or debt restructuring. Fiscal problems can take many forms; in particular, some of the outright defaults can be avoided through timely, targeted responses, like support programs of international institutions. The fiscal stress variable is shifted with regard to the other variables: crisis_next_year – binary variable shifted by 1 year, all years of a fiscal stress coded as 1; crisis_next_period – binary variable shifted by 2 years, all years of a fiscal stress coded as 1; crisis_first_year1 – binary variable shifted by 1 year, only the first year of a fiscal stress coded as 1; crisis_first_year2 - binary variable shifted by 2 years, only the first year of a fiscal stress coded as 1.

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.

Observations for the current and future years are projections.

The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis.

For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications.

Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).

Imports of environmental goods comprise all environmental goods entering the national territory. A relatively high share of environmental goods imports indicates that an economy purchases a significant share of environmental goods from other economies. Exports of environmental goods comprise all environmental goods leaving the national territory. A relatively high share of environmental goods exports indicates that an economy produces and sells a significant share of environmental goods to other economies. An economy’s environmental goods trade balance is the difference between its exports and imports of environmental goods.Comparative advantage is a measure of the relative advantage or disadvantage a particular economy has in a certain class of goods (in this case, environmental goods), and can be used to evaluate export potential in that class of goods. A value greater than one indicates a relative advantage in environmental goods, while a value of less than one indicates a relative disadvantage.Sources: Department of Economic and Social Affairs/United Nations. 2022. United Nations Comtrade database. https://comtrade.un.org. Accessed on 2023-06-28; International Monetary Fund (IMF) Direction of Trade Statistics (DOTS). https://data.imf.org/dot. Accessed on 2023-06-28. World Economic Outlook (WEO) Database. https://www.imf.org/en/Publications/WEO/weo-database/2022/April. Accessed on 2023-06-28; IMF staff calculations.Category: Cross-Border IndicatorsData series: Comparative advantage in environmental goodsEnvironmental goods exportsEnvironmental goods exports as percent of GDPEnvironmental goods exports as share of total exportsEnvironmental goods importsEnvironmental goods imports as percent of GDPEnvironmental goods imports as share of total importsEnvironmental goods trade balanceEnvironmental goods trade balance as percent of GDPTotal trade in environmental goodsTotal trade in environmental goods as percent of GDPMetadata:Sources: Trade data from UN Comtrade Database (https://comtrade.un.org/). Harmonized Commodity Description and Coding System (HS) 2017. Trade aggregates from IMF Direction of Trade Statistics (DOTS) (data.imf.org/dot). GDP data from World Economic Outlook.Methodology:Environmental goods imports and exports are estimated by aggregating HS 6-digit commodities identified as environmental goods based on OECD and Eurostat, The Environmental Goods & Services Industry: Manual for Data Collection and Analysis, 1999, and IMF research. Total goods imports and exports are estimated by aggregating all commodities. Environmental goods trade balance is calculated as environmental goods exports less environmental goods imports. A positive trade balance means an economy has a surplus in environmental goods, while a negative trade balance means an economy has a deficit in environmental goods.Total goods are estimated by aggregating all commodities. Comparative advantage is calculated as the proportion of an economy’s exports that are environmental goods to the proportion of global exports that are environmental goods. Total trade in environmental goods is calculated as the sum of environmental goods exports and environmental goods imports. This measure provides an indication of an economy’s involvement (openness) to trade in environmental goods.National-accounts basis GDP at current prices from the World Economic Outlook is used to calculate the percent of GDP. This measure provides an indication of an economy’s involvement (openness) to trade in environmental goods.Methodology Attachment Environmental Goods Harmonized System Codes

Observations for the current and future years are projections.

The IMF provides these series as part of their Regional Economic Outlook (REO) reports. These reports discuss recent economic developments and prospects for countries in various regions. They also address economic policy developments that have affected economic performance in their regions and provide country-specific data and analysis.

For more information, please see the Regional Economic Outlook (https://www.imf.org/en/publications/reo) publications.

Copyright © 2016, International Monetary Fund. Reprinted with permission. Complete terms of use and contact details are available here (http://www.imf.org/external/terms.htm).