IMF World Economic Outlook (WEO) database. The IMF World Economic Outlook is a twice-yearly survey by IMF staff that presents IMF staff economists' analyses of global economic developments during th...

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.

The entire World Economic Outlook database.

Abstract copyright UK Data Service and data collection copyright owner. The International Monetary Fund (IMF) 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. Main Topics: Topics covered include:national accountsinflationunemployment ratesbalance of paymentsdebtfiscal indicatorstrade for countries and country groups (aggregates)government financecommodity prices

Abstract

Key components of the WFSO database cover the prevalence of severe food insecurity, including estimates for countries lacking official data, population sizes of the severely food insecure, and required safety net financing. Data is presented in a user-friendly format.

WFSO data primarily relies on hunger and malnutrition data from the State of Food Security and Nutrition in the World (SOFI) report, led by the Food and agriculture Organization (FAO) in collaboration with multiple UN agencies. WFSO complements SOFI data by providing estimates for unreported countries. Historical estimates are produced with a machine learning model leveraging World Development Indicators (WDI) for global coverage.

Financing needs for safety nets are calculated similarly to past approaches by the International Development Association (IDA) to assess food insecurity response needs (IDA (2020) and IDA (2021)). Preliminary estimates and projections rely on the same model and incorporate International Monetary Fund (IMF)'s World Economic Outlook (WEO) growth and inflation forecasts. WEO data reflects the IMF's expert analysis from various sources, including government agencies, central banks, and international organizations.

Minor gaps in WDI data inflation data are replaced with unofficial WEO estimates. Minor inflation data gaps not covered by both, are replaced with unofficial inflation estimates from the World Bank's Real Time Food Prices (RTFP) data.

The WFSO is updated three times a year, coinciding with IMF's WEO and SOFI releases. It provides food security projections that align with economic forecasts, aiding policymakers in integrating food security into economic planning.

The WFSO database serves various purposes, aiding World Bank economists and researchers in economic analysis, policy recommendations, and the assessment of global financing needs to address food insecurity.

Additionally, the WFSO enhances transparency in global food security data by tracking regional and global figures and breaking them down by individual countries. Historical estimates support research and long-term trend assessments, especially in the context of relating outlooks to past food security crises.

Geographic coverage

World

Geographic coverage notes

191 countries and territories mutually included by the World Bank's WDI and IMF's WEO databases. The country coverage is based on mutual inclusion in both the World Bank World Development Indicators database and the International Monetary Fund’s World Economic Outlook database. Some countries and territories may not be covered. Every attempt is made to provide comprehensive coverage. To produce complete historical predictions, missing data in the WDI are completed with unofficial data from the WEO and the World Bank's RTFP data when inflation data is not available in either database. Final gaps in the WDI and WEO are interpolated using a Kernel-based pattern-matching algorithm. See background documentation for equations.

Analysis unit

Country

Kind of data

Process-produced data [pro]

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 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.

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

Japan JP: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario data was reported at 3.442 % in Dec 2021. This records a decrease from the previous number of 3.501 % for Sep 2021. Japan JP: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario data is updated quarterly, averaging 2.460 % from Mar 1968 (Median) to Dec 2021, with 216 observations. The data reached an all-time high of 4.790 % in Dec 2007 and a record low of -2.087 % in Mar 1974. Japan JP: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario 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 Japan – Table JP.OECD.EO: Balance of Payments: Current Account: Forecast: OECD Member: Quarterly. CBGDPR-Current account balance, as a percentage of GDP Sixth Edition of the IMF's Balance of Payments and International Investment Position Manual (BPM6):https://www.imf.org/external/pubs/ft/bop/2007/bopman6.htm OECD Economic Outlook, Database Inventory:https://www.oecd.org/eco/outlook/Database_Inventory.pdf

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 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.

China Balance of Payment: Current Account Balance: as % of GDP: Single Hit Scenario data was reported at 0.870 % in 2021. This records an increase from the previous number of 0.601 % for 2020. China Balance of Payment: Current Account Balance: as % of GDP: Single Hit Scenario data is updated yearly, averaging 1.791 % from Dec 1982 (Median) to 2021, with 40 observations. The data reached an all-time high of 9.948 % in 2007 and a record low of -2.876 % in 1985. China Balance of Payment: Current Account Balance: as % of GDP: Single Hit Scenario 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 China – Table CN.OECD.EO: Balance of Payments: Current Account: Forecast: Non OECD Member: Annual. CBGDPR-Current account balance, as a percentage of GDP Sixth Edition of the IMF's Balance of Payments and International Investment Position Manual (BPM6):https://www.imf.org/external/pubs/ft/bop/2007/bopman6.htm OECD Economic Outlook, Database Inventory:https://www.oecd.org/eco/outlook/Database_Inventory.pdf

Costa Rica CR: Balance of Payment: Current Account Balance: as % of GDP: Single Hit Scenario data was reported at -3.758 % in 2021. This records an increase from the previous number of -4.363 % for 2020. Costa Rica CR: Balance of Payment: Current Account Balance: as % of GDP: Single Hit Scenario data is updated yearly, averaging -3.758 % from Dec 2009 (Median) to 2021, with 13 observations. The data reached an all-time high of -1.725 % in 2009 and a record low of -5.404 % in 2011. Costa Rica CR: Balance of Payment: Current Account Balance: as % of GDP: Single Hit Scenario 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 Costa Rica – Table CR.OECD.EO: Balance of Payments: Current Account: Forecast: OECD Member: Annual. CBGDPR-Current account balance, as a percentage of GDP Sixth Edition of the IMF's Balance of Payments and International Investment Position Manual (BPM6):https://www.imf.org/external/pubs/ft/bop/2007/bopman6.htm OECD Economic Outlook, Database Inventory:https://www.oecd.org/eco/outlook/Database_Inventory.pdf

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.

Norway NO: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario data was reported at 1.018 % in Dec 2021. This records an increase from the previous number of 0.940 % for Sep 2021. Norway NO: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario data is updated quarterly, averaging 4.655 % from Mar 1975 (Median) to Dec 2021, with 188 observations. The data reached an all-time high of 18.975 % in Dec 2005 and a record low of -15.076 % in Sep 1977. Norway NO: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario 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 Norway – Table NO.OECD.EO: Balance of Payments: Current Account: Forecast: OECD Member: Quarterly. CBGDPR-Current account balance, as a percentage of GDP Sixth Edition of the IMF's Balance of Payments and International Investment Position Manual (BPM6):https://www.imf.org/external/pubs/ft/bop/2007/bopman6.htm OECD Economic Outlook, Database Inventory:https://www.oecd.org/eco/outlook/Database_Inventory.pdf

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.

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).

The IMF's World Revenue Longitudinal Data set (WoRLD) is a compilation of government tax and non-tax revenues from the IMF's Government Finance Statistics and World Economic Outlook, and drawing on the OECD Revenue Statistics and Revenue Statistics in Latin American and the Caribbean.

The dataset comprises of spliced revenue data taken from the following sources: WEO, GFS, OECD and various IMF Staff Reports.

Ireland IE: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario data was reported at -27.375 % in Dec 2021. This records an increase from the previous number of -28.077 % for Sep 2021. Ireland IE: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario data is updated quarterly, averaging -0.631 % from Mar 1990 (Median) to Dec 2021, with 128 observations. The data reached an all-time high of 20.456 % in Dec 2017 and a record low of -38.125 % in Jun 2017. Ireland IE: Balance of Payment: Current Account Balance: as % of GDP: Double Hit Scenario 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 Ireland – Table IE.OECD.EO: Balance of Payments: Current Account: Forecast: OECD Member: Quarterly. CBGDPR-Current account balance, as a percentage of GDP Sixth Edition of the IMF's Balance of Payments and International Investment Position Manual (BPM6):https://www.imf.org/external/pubs/ft/bop/2007/bopman6.htm OECD Economic Outlook, Database Inventory:https://www.oecd.org/eco/outlook/Database_Inventory.pdf