The entire World Economic Outlook database from the International Monetary Fund (IMF).

Reference: https://www.imf.org/external/pubs/ft/weo/2017/01/weodata/download.aspx

License: https://www.imf.org/external/terms.htm

The entire World Economic Outlook database.

The World Economic Outlook (WEO) database contains selected macroeconomic data series from the statistical appendix of the World Economic Outlook report, which presents the IMF staff's analysis and projections of economic developments at the global level, in major country groups and in many individual 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.

The WHD Regional Economic Outlook (REO) provides information on recent economic developments and prospects for countries in the Western Hemisphere. Data for the Western Hemisphere REO are prepared in conjunction and are consistent with the semi-annual World Economic Outlook (WEO) exercises. 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.

Imports of low carbon technology products comprise all low carbon technology products entering the national territory. A relatively high share of low carbon technology products imports indicates that an economy purchases a significant share of low carbon technology products from other economies. Exports of low carbon technology products comprise all low carbon technology products leaving the national territory. A relatively high share of low carbon technology products exports indicates that an economy produces and sells a significant share of low carbon technology products to other economies. An economy’s trade balance in low carbon technology products is the difference between its exports and imports of low carbon technology products.Comparative advantage is a measure of the relative advantage or disadvantage a particular economy has in a certain class of goods (in this case, low carbon technology products), and can be used to evaluate export potential in that class of goods. A value greater than one indicates a relative advantage in low carbon technology products, 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. International Monetary Fund (IMF) Direction of Trade Statistics (DOTS). https://data.imf.org/dot. World Economic Outlook (WEO) Database. https://www.imf.org/en/Publications/WEO/weo-database/2022/April. IMF staff calculations.Category: Mitigation,Transition to a Low-Carbon EconomyData series: Comparative advantage in low carbon technology productsExports of low carbon technology productsExports of low carbon technology products as percent of GDPExports of low carbon technology products as share of total exportsImports of low carbon technology productsImports of low carbon technology products as percent of GDPImports of low carbon technology products as share of total importsTotal trade in low carbon technology productsTotal trade in low carbon technology products as percent of GDPTrade balance in low carbon technology productsTrade balance in low carbon technology products 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:Low carbon technology products are estimated by aggregating HS 6-digit commodities identified as low carbon technology products based on Pigato, Miria A., Simon J. Black, Damien Dussaux, Zhimin Mao, Miles McKenna, Ryan Rafaty, and Simon Touboul. 2020. Technology Transfer and Innovation for Low-Carbon Development. International Development in Focus. Washington, DC: World Bank, and IMF research. Trade balance in low carbon technology products is calculated as low carbon technology products exports less low carbon technology products imports. A positive trade balance means an economy has a surplus in low carbon technology products, while a negative trade balance means an economy has a deficit in low carbon technology products.Total goods are estimated by aggregating all commodities. Comparative advantage is calculated as the proportion of an economy’s exports that are low carbon technology products to the proportion of global exports that are low carbon technology products. Total trade in low carbon technology products is calculated as the sum of low carbon technology products exports and low carbon technology products imports. 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 low carbon technology products, which is important for understanding how these technologies can be transferred between economies.Methodology Attachment Low Carbon Technology Harmonized System Codes

This is the data used to estimate the monetary value of Disability-Adjusted Life Years (DALYs) lost from all causes in Mauritius in 2019. The file has (a) Disability-Adjusted Life Years (DALYs) by cause data for Mauritius from 'Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Results. Seattle, United States: Institute for Health Metrics and Evaluation (IHME), 2020. Available online from: http://ghdx.healthdata.org/gbd-results-tool. Accessed 27 October 2020'; (b) Mauritius gross domestic product (GDP) per capita in International Dollars (Int$) from 'International Monetary Fund (IMF). World Economic Outlook Database. [Updated: October 2020]. Available online from: https://www.imf.org/en/Publications/WEO/weo-database/2020/October/select-country-group . Accessed 28 October 2020.'; (c). Mauritius current health expenditure per capita (CHEPC) projected from 'World Health Organization (WHO). Global Health Expenditure Database. Available online from: Available online from: http://apps.who.int/nha/database/Select/Indicators/en . Accessed 28 October 2020.'; and (d) authors estimate of the net GDP per capita in 2019 (Int$) for Mauritius, which is the difference between GDP per capita and current health expenditure per capita.

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 contains Sub-Saharan Africa Regional Economic Outlook from 2004 - 2021.Data from International Monetary Fund. Follow datasource.kapsarc.org for timely data to advance energy economics research.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.

Switzerland IMF Forecast: General Government: Expenditure: % of GDP data was reported at 33.006 % in 2023. This records a decrease from the previous number of 33.024 % for 2022. Switzerland IMF Forecast: General Government: Expenditure: % of GDP data is updated yearly, averaging 32.917 % from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 34.695 % in 2002 and a record low of 28.236 % in 1990. Switzerland IMF Forecast: General Government: Expenditure: % of GDP data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Switzerland – Table CH.IMF.FM: Government Finance Statistics.

Switzerland IMF Forecast: General Government: Revenue: % of GDP data was reported at 33.329 % in 2023. This stayed constant from the previous number of 33.329 % for 2022. Switzerland IMF Forecast: General Government: Revenue: % of GDP data is updated yearly, averaging 32.416 % from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 33.497 % in 2015 and a record low of 28.201 % in 1991. Switzerland IMF Forecast: General Government: Revenue: % of GDP data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Switzerland – Table CH.IMF.FM: Government Finance Statistics.

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

This metadata considers the data on total and insured economic losses and the number of fatalities from weather- and climate-related events in EU Member States and EEA member countries since 1980. Weather- and climate-related hazards considered are those types classified as meteorological hazards (e.g. storms), hydrological hazards (e.g. floods) and climatological hazards (e.g. heatwaves) based on the classification by the International Council for Science (ICSU). The geophysical hazards (e.g. earthquakes and volcanoes) are included for comparison purposes. An event can occur in several countries, but the information is split per country.

The data is based on the RiskLayer CATDAT and the MunichRe NatCatSERVICE datasets (both received under institutional agreement), and on the Eurostat collection of economic indicators, whereas data from earlier years not covered by Eurostat have been completed using data from the Annual Macro-Economic Database of the European Commission (AMECO), the International Monetary Fund’s (IMF) World Economic Outlook (WEO), the Total Economy Database (TED) and the World Bank database. The average population of a country over the period of the time series is used.

The data contains details related to EEA’s indicator “Economic losses from climate-related events in Europe” (https://www.eea.europa.eu/ims/economic-losses-from-climate-related), updated annually. Additional detail on the data and the indicator can be found in the EEA briefing "Economic losses and fatalities from weather- and climate-related events in Europe", 2022 (https://www.eea.europa.eu/publications/economic-losses-and-fatalities-from/economic-losses-and-fatalities-from).

Thailand TH: IMF Forecast: General Government: Primary Balance: % of GDP data was reported at -0.658 % in 2023. This records a decrease from the previous number of -0.649 % for 2022. Thailand TH: IMF Forecast: General Government: Primary Balance: % of GDP data is updated yearly, averaging -0.107 % from Dec 2000 (Median) to 2023, with 24 observations. The data reached an all-time high of 3.254 % in 2006 and a record low of -5.505 % in 2002. Thailand TH: IMF Forecast: General Government: Primary Balance: % of GDP data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Thailand – Table TH.IMF.FM: Government Finance Statistics.

Thailand TH: IMF Forecast: General Government: Expenditure: % of GDP data was reported at 22.810 % in 2023. This records an increase from the previous number of 22.735 % for 2022. Thailand TH: IMF Forecast: General Government: Expenditure: % of GDP data is updated yearly, averaging 21.713 % from Dec 1995 (Median) to 2023, with 29 observations. The data reached an all-time high of 26.472 % in 1999 and a record low of 17.176 % in 1995. Thailand TH: IMF Forecast: General Government: Expenditure: % of GDP data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Thailand – Table TH.IMF.FM: Government Finance Statistics.

Uganda UG: IMF Forecast: General Government: Overall Balance: % of GDP data was reported at 0.631 % in 2023. This records an increase from the previous number of -1.925 % for 2022. Uganda UG: IMF Forecast: General Government: Overall Balance: % of GDP data is updated yearly, averaging -2.097 % from Dec 1997 (Median) to 2023, with 27 observations. The data reached an all-time high of 0.631 % in 2023 and a record low of -5.931 % in 2019. Uganda UG: IMF Forecast: General Government: Overall Balance: % of GDP data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Uganda – Table UG.IMF.FM: Government Finance Statistics.

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.

Uzbekistan UZ: IMF Forecast: General Government: Primary Balance: % of GDP data was reported at -2.440 % in 2023. This records a decrease from the previous number of -2.378 % for 2022. Uzbekistan UZ: IMF Forecast: General Government: Primary Balance: % of GDP data is updated yearly, averaging -2.209 % from Dec 1997 (Median) to 2023, with 27 observations. The data reached an all-time high of 8.125 % in 2012 and a record low of -7.544 % in 2002. Uzbekistan UZ: IMF Forecast: General Government: Primary Balance: % of GDP data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Uzbekistan – Table UZ.IMF.FM: Government Finance Statistics.

The Statistics on Public Expenditures for Economic Development (SPEED) database is a resource of the International Food Policy Research Institute (IFPRI) that contains information on agricultural and other sectoral public expenditures in 147 countries from 1980 to 2016. Policymakers, researchers, and other stakeholders can use this robust database to examine both historical trends and the allocation of government resources across sectors. It also allows for comparisons with other countries within a region or at a similar level of development. Because the SPEED database covers many countries for a long time period, it allows analysts of government spending to examine national policy priorities, as reflected in the allocation of public expenditures, and track development goals and the cost-effectiveness of public spending both within and across countries. Indicators reported in this data study include total agricultural expenditure, agricultural spending per capita, and the ratio of agricultural spending to the agricultural gross domestic product (GDP) for years 1995, 2000, and 2016. IFPRI researchers have compiled data from multiple sources, including the International Monetary Fund, World Bank, United Nations, and national governments, and conducted extensive data checks and adjustments to ensure consistent spending measurements over time that are free of exchange-rate fluctuations and currency denomination changes.

Venezuela VE: IMF Forecast: General Government: Primary Balance: % of GDP data was reported at -30.808 % in 2023. This records a decrease from the previous number of -30.321 % for 2022. Venezuela VE: IMF Forecast: General Government: Primary Balance: % of GDP data is updated yearly, averaging -2.197 % from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 12.831 % in 1996 and a record low of -31.522 % in 2017. Venezuela VE: IMF Forecast: General Government: Primary Balance: % of GDP data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Venezuela – Table VE.IMF.FM: Government Finance Statistics.