Employment by sector and gender (% of total) - Mining - Female

Employment of Females within Mining is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Mining - Male

Country Climate and Development Report (CCDR)

Employment of Males within Mining is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.

Global Jobs Indicators Database, The World Bank. Available at: https://databank.worldbank.org/source/global-jobs-indicators-database-(join)


Employment by sector and gender (% of total) - Other services - Female

Employment of Females within Other services is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Other services - Male

Employment of Males within Other services is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Public Administration - Female

Employment of Females within Public Administration is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Public Administration - Male

Employment of Males within Public Administration is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Public sector employment - Female

Employment of Females within Public sector employment is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Public sector employment - Male

Employment of Males within Public sector employment is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Services - Female

Employment of Females within Services is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Services - Male

Employment of Males within Services is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Transport & Communication - Female

Employment of Females within Transport & Communication is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Employment by sector and gender (% of total) - Transport & Communication - Male

Employment of Males within Transport & Communication is disaggregated from the Global Jobs Indicators Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Control of Corruption: Estimate

Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests. Estimate gives the country's score on the aggregate indicator, in units of a standard normal distribution, i.e. ranging from approximately -2.5 to 2.5.

Detailed documentation of the WGI, interactive tools for exploring the data, and full access to the underlying source data available at www.govindicators.org. The WGI are produced by Daniel Kaufmann (Natural Resource Governance Institute and Brookings Institution) and Aart Kraay (World Bank Development Research Group).  Please cite Kaufmann, Daniel, Aart Kraay and Massimo Mastruzzi (2010).  "The Worldwide Governance Indicators:  Methodology and Analytical Issues".  World Bank Policy Research Working Paper No. 5430 (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1682130).  The WGI do not reflect the official views of the Natural Resource Governance Institute, the Brookings Institution, the World Bank, its Executive Directors, or the countries they represent.


Food GHG emissions by system stage (Share of total) - Consumption

Food GHG emissions disaggregated by system stage are generated from EDGAR-FOOD, a global emission inventory of GHGs from the food systems. EDGAR-FOOD has been developed to aid the understanding of the activities underlying the energy demand and use, agriculture and land use change emissions associated with the production, distribution, consumption and disposal of food through the various stages and sectors of the composite global food system. These data were complemented with data from the FAOSTAT database on GHG emissions from land use related to agriculture (FAO, 2020). EDGAR-FOOD represents the first database consistently covering each stage of the food chain for all countries with yearly frequency for the period 1990-2015. Details regarding the methodology applied are available in Crippa et al. (2021).

Crippa, M., Solazzo, E., Guizzardi, D., Monforti-Ferrario, F., Tubiello, F.N. and Leip, A. EDGAR-FOOD data. Figshare, doi:10.6084/m9.figshare.13476666 (2021).


Food GHG emissions by system stage (Share of total) - End_of_Life


Food GHG emissions by system stage (Share of total) - LULUC (Production)


Food GHG emissions by system stage (Share of total) - Packaging


Food GHG emissions by system stage (Share of total) - Production


Food GHG emissions by system stage (Share of total) - Processing


Food GHG emissions by system stage (Share of total) - Retail


Food GHG emissions by system stage (Share of total) - Transport


Population exposed to floods (share of population below $5.50)

Share of population that falls into the defined poverty threshold of $5.50 (consumption per day) that is exposed to floods within a country

Rentschler, Jun; Salhab, Melda. 2020. People in Harm's Way : Flood Exposure and Poverty in 189 Countries. Policy Research Working Paper;No. 9447. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/34655 License: CC BY 3.0 IGO.


Population exposed to floods (share of total population)

Share of total population that is exposed to floods within a country


Share of animal products in food supply (% of total)

Animal products supply is taken from New Food Balances (domain), Food Supply (element) of the Food Balance Sheet (FAOSTAT). FAOSTAT Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.

FAOSTAT. Available at: http://www.fao.org/faostat/en/#data


Share of vegetal products in food supply (% of total)

Vegetal supply is taken from New Food Balances (domain), Food Supply (element) of the Food Balance Sheet (FAOSTAT). FAOSTAT Food Balance Sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per caput food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.


Freight volume by mode (billion tons-km) - Air transport

This indicator presents the volume of freight attributable to air transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Freight volume by mode of transport (tonne kilometres)

UN Open Data Hub. Available at: https://unstats-undesa.opendata.arcgis.com/


Freight volume by mode (billion tons-km) - Inland waterway transport

This indicator presents the volume of freight attributable to inland waterway transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Freight volume by mode of transport (tonne kilometres)


Freight volume by mode (billion tons-km) - Rail transport

This indicator presents the volume of freight attributable to rail transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Freight volume by mode of transport (tonne kilometres)


Freight volume by mode (billion tons-km) - Road transport

This indicator presents the volume of freight attributable to road transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Freight volume by mode of transport (tonne kilometres)


Gas pipeline capacity by project status (barrels of oil equivalent per day) - Cancelled

Gas pipeline capacity (barrels of oil equivalent per day), by capacity, is generated from the Global Fossil Infrastructure Tracker (GFIT). The GFIT is an information resource on fossil fuel infrastructure projects and their development. Currently, the GFIT includes all global LNG import terminals and export terminals, and all global oil and gas transmission pipelines over a pre-determined size threshold. The Tracker organizes information in both map and table format. The interactive map format allows users to geographically visualize pipeline routes and terminal locations, while the table format allows users to access additional data points on each project. Both the map and table provide menu-based data filtering options as well as links to further information in project-specific wiki pages housed on GEM.wiki. GFIT was accessed in July 2021 to generate this data.

Global Fossil Infrastructure Tracker, Global Energy Monitor. Available at: https://globalenergymonitor.org/projects/global-fossil-infrastructure-tracker/


Gas pipeline capacity by project status (barrels of oil equivalent per day) - Construction


Gas pipeline capacity by project status (barrels of oil equivalent per day) - In Development (Proposed + Construction)


Gas pipeline capacity by project status (barrels of oil equivalent per day) - Mothballed


Gas pipeline capacity by project status (barrels of oil equivalent per day) - Operating


Gas pipeline capacity by project status (barrels of oil equivalent per day) - Proposed


Gas pipeline capacity by project status (barrels of oil equivalent per day) - Retired


Gas pipeline capacity by project status (barrels of oil equivalent per day) - Shelved


Total GHG emissions by sector (Mt CO2 eq) - Agriculture

Agriculture sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.

Climate Watch. 2020. Washington, DC: World Resources Institute. Available online at: https://www.climatewatchdata.org.


Total GHG emissions by sector (Mt CO2 eq) - Bunker Fuels

Bunker fuels sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Building

Building sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Electricity/Heat

Electricity and heat sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Total excluding LUCF

Total greenhouse gas emissions (excluding LUCF) are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Energy

Energy sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Fugitive Emissions

Fugitive sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Total including LUCF

Total greenhouse gas emissions (including LUCF) are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Industrial Processes

Industrial Processes sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Land-Use Change and Forestry

Land-Use Change and Forestry sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Manufacturing/Construction

Manufacturing and construction sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Other Fuel Combustion

Other fuel combustion sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Transportation

Transportation sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total GHG emissions by sector (Mt CO2 eq) - Waste

Waste sector greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


GHG emissions from food systems, by gas (Mt CO2 eq) - Methane

GHG emissions from food systems disaggregated by gas are generated from EDGAR-FOOD, a global emission inventory of GHGs from the food systems. EDGAR-FOOD has been developed to aid the understanding of the activities underlying the energy demand and use, agriculture and land use change emissions associated with the production, distribution, consumption and disposal of food through the various stages and sectors of the composite global food system. These data were complemented with data from the FAOSTAT database on GHG emissions from land use related to agriculture (FAO, 2020). EDGAR-FOOD represents the first database consistently covering each stage of the food chain for all countries with yearly frequency for the period 1990-2015. Details regarding the methodology applied are available in Crippa et al. (2021).


GHG emissions from food systems, by gas (Mt CO2 eq) - CO2


GHG emissions from food systems, by gas (Mt CO2 eq) - F-gases


GHG emissions from food systems, by gas (Mt CO2 eq) - N2O


GHG growth (annual %)

Greenhouse gas emissions growth is generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Macro drivers of GHG emissions growth in the period 2012-2018 - Emission Intensity of GDP

Data reflects the impact of the emissions intensity of GDP (as a macro-driver) to total emission growth (excluding LUCF) across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Macro drivers of GHG emissions growth in the period 2012-2018 - GDP per capita

Data reflects the impact of GDP-per capita (as a macro-driver) to total emission growth (excluding LUCF) across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Macro drivers of GHG emissions growth in the period 2012-2018 - Population

Data reflects the impact of population (as a macro-driver) to total emission growth (excluding LUCF) across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Per capita GHG emissions (tons/capita)

Per capita greenhouse gas emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Agriculture (contribution to total growth, %)

Data reflects the aggregate contribution of the Agriculture sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Building (contribution to total growth, %)

Data reflects the aggregate contribution of the Building sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Electricity/Heat (contribution to total growth, %)

Data reflects the aggregate contribution of the Electricity and Heat sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Fugitive Emissions (contribution to total growth, %)

Data reflects the aggregate contribution of the Fugitive Emissions sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Industrial Processes (contribution to total growth, %)


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Land-Use Change and Forestry (contribution to total growth, %)

Data reflects the aggregate contribution of the Land-Use Change and Forestry sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Manufacturing/Construction (contribution to total growth, %)

Data reflects the aggregate contribution of the Manufacturing and Construction sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Other Fuel Combustion (contribution to total growth, %)

Data reflects the aggregate contribution of the Other Fuel Combustion sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Transportation (contribution to total growth, %)

Data reflects the aggregate contribution of the Transportation sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Sectoral drivers of GHG emissions growth in the period 2012-2018 - Waste (contribution to total growth, %)

Data reflects the aggregate contribution of the Waste sector to total emission growth across the period 2012-2018. This data has been calculated by World Bank staff using greenhouse gas emissions data from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Total sovereign green bonds issuance (billion US$)

Sovereign green bond issuance is disaggregated from Green Bond Issuances by Type of Issuer data. Green Bonds are created to fund projects that have positive environmental and/or climate benefits. Note: While green finance indicators may cover more than climate finance (i.e. to include environmental issues at large) they do provide a good proxy for the greening of the finance system in the country. Countries that rank well on these indicators are more likely to mobilize green finance to facilitate their climate transition.

IMF Climate Change Dashboard. Sources:  Refinitiv; Country authorities; IMF staff calculations.


Emission Totals - Indirect emissions (N2O) - AFOLU

The FAOSTAT domain Emissions Totals summarizes the greenhouse gas (GHG) emissions generated from agriculture and forest land. They consist of methane (CH4), nitrous oxide (N2O) and carbon dioxide (CO2) emissions from crop and livestock activities, forest management and include land use and land use change processes. Data are computed at Tier 1 of the IPCC Guidelines for National greenhouse gas (GHG) Inventories (IPCC, 1996; 1997; 2000; 2002; 2006; 2014). Estimates are available by country, with global coverage for the period 1961–2019 with projections for 2030 and 2050 for some categories of emissions or 1990–2019 for others. The database is updated annually.  The FAOSTAT domain Emissions Totals disseminates information estimates of CH4, N2O and CO2 emissions/removals and their aggregates in CO2eq in units of kilotonnes (kt, or 106 kg). The latter are computed by using the IPCC Fifth Assessment report global warming potentials, AR5 (IPCC, 2014).

FAO, FAOSTAT Climate Change, Emissions Totals, http://www.fao.org/faostat/en/#data/GT.


Emission Totals - Indirect emissions (N2O) - Agricultural Soils


Emission Totals - Indirect emissions (N2O) - Crop Residues


Emission Totals - Indirect emissions (N2O) - Emissions on agricultural land


Emission Totals - Indirect emissions (N2O) - Farm-gate emissions


Emission Totals - Indirect emissions (N2O) - IPCC Agriculture


Emission Totals - Indirect emissions (N2O) - Manure left on Pasture


Emission Totals - Indirect emissions (N2O) - Manure applied to Soils


Emission Totals - Indirect emissions (N2O) - Synthetic Fertilizers


Annual investment needs for coastal protection, by risk strategy (% of GDP) - low risk tolerance

Data reflects the cost of a risk taking strategy that adopts an ambititious low-risk strategy. This is discussed in Policy Note 5 of the Beyond the Gap report.

Rozenberg, Julie; Fay, Marianne. 2019. Beyond the Gap : How Countries Can Afford the Infrastructure They Need while Protecting the Planet. Sustainable Infrastructure;. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/31291 License: CC BY 3.0 IGO


Annual investment needs for coastal protection, by risk strategy (% of GDP) - constant relative flood risk

Data reflects the cost of a risk taking strategy that keeps the risk relative to GDP constant. This is discussed in Policy Note 5 of the Beyond the Gap report.


Annual investment needs for coastal protection, by risk strategy (% of GDP) - optimal protection

Data reflects the level of spending in protection that minimizes the cost of floods, including the prevention of expenditure and damages. This is discussed in Policy Note 5 of the Beyond the Gap report.


Informal employment by sector and gender (% of total) - Agriculture, forestry and fishing - Female

This indicator presents the share of agriculture (female) employment which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


Informal employment by sector and gender (% of total) - Agriculture, forestry and fishing - Male

This indicator presents the share of agriculture (male) employment which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


Informal employment by sector and gender (% of total) - Non-agriculture - Female

This indicator presents the share of non-agriculture (female) employment which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


Informal employment by sector and gender (% of total) - Non-agriculture - Male

This indicator presents the share of non-agriculture (male) employment which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


Informal employment by sector and gender (% of total) - No breakdown - Female

This indicator presents the share of employment that had no-breakdown as either non-agricultural or agricultural (female), which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


Informal employment by sector and gender (% of total) - No breakdown - Male

This indicator presents the share of employment that had no-breakdown as either non-agricultural or agricultural (male), which is classified as informal employment in the total economy. Data is taken from the United Nations Sustainable Goals, representing Indicator 8.3.1: Proportion of informal employment in total employment, by sector and sex.


Proportion of freshwater key biodiversity areas (KBAs) covered by protected areas (%)

This indicator presents the proportion of freshwater key biodiversity areas (KBAs) covered by protected areas. Data is taken from the United Nations Sustainable Goals, representing Indicator 15.1.2: Average proportion of Freshwater Key Biodiversity Areas (KBAs) covered by protected areas (percent).


Proportion of terrestrial key biodiversity areas (KBAs) covered by protected areas (%)

This indicator presents the proportion of terrestrial key biodiversity areas (KBAs) covered by protected areas. Data is taken from the United Nations Sustainable Goals, representing Indicator 15.1.2: Average proportion of Terrestrial Key Biodiversity Areas (KBAs) covered by protected areas (percent).


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Agriculture

Agriculture sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Total excluding LUCF

Total non-CO2 emissions (excluding LUCF) are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Energy

Energy sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Fugitive Emissions

Fugitive sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Total including LUCF

Total non-CO2 emissions (including LUCF) are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Industrial Processes

Industrial Processes sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Land-Use Change and Forestry


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Other Fuel Combustion

Other fuel combustion sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Non-CO2 GHG emissions by sector (Mt CO2 eq) - Waste

Waste sector non-CO2 emissions are generated from the World Resource Institute's Climate Watch. Climate Watch Historical Emission data contains sector-level greenhouse gas (GHG) emissions data for 194 countries and the European Union (EU) for the period 1990-2018, including emissions of the six major GHGs from most major sources and sinks. Non-CO2 emissions are expressed in CO2 equivalents using 100-year global warming potential values from IPCC Fourth Assessment Report. Climate Watch Historical GHG Emissions data (previously published through CAIT Climate Data Explorer) are derived from several sources. Any use of the Land-Use Change and Forestry or Agriculture indicator should be cited as FAO 2020, FAOSTAT Emissions Database. Any use of CO2 emissions from fuel combustion data should be cited as CO2 Emissions from Fuel Combustion, OECD/IEA, 2020.


Net food imports by crop - Barley

Net food imports are generated from FAOSTAT, taking Export level (tonnes) from the Import level (tonnes) [both under Trade: Crops and Livestock Products]. Net food imports are a proxy for the country's vulnerability to global food prices.


Net food imports by crop - Rice, paddy (rice milled equivalent)


Net food imports by crop - Rice, milled/husked


Control of Corruption: Number of Sources

Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests. Number of sources indicates the number of underlying data sources on which the aggregate estimate is based.


Oil pipeline capacity by project status (barrels of oil equivalent per day) - Cancelled

Oil pipeline capacity (barrels of oil equivalent per day), by capacity, is generated from the Global Fossil Infrastructure Tracker (GFIT). The GFIT is an information resource on fossil fuel infrastructure projects and their development. Currently, the GFIT includes all global LNG import terminals and export terminals, and all global oil and gas transmission pipelines over a pre-determined size threshold. The Tracker organizes information in both map and table format. The interactive map format allows users to geographically visualize pipeline routes and terminal locations, while the table format allows users to access additional data points on each project. Both the map and table provide menu-based data filtering options as well as links to further information in project-specific wiki pages housed on GEM.wiki. GFIT was accessed in July 2021 to generate this data.


Oil pipeline capacity by project status (barrels of oil equivalent per day) - Construction


Oil pipeline capacity by project status (barrels of oil equivalent per day) - In Development (Proposed + Construction)


Oil pipeline capacity by project status (barrels of oil equivalent per day) - Operating


Oil pipeline capacity by project status (barrels of oil equivalent per day) - Proposed


Oil pipeline capacity by project status (barrels of oil equivalent per day) - Retired


Oil pipeline capacity by project status (barrels of oil equivalent per day) - Shelved


Operating coal power capacity by plant age (MW) - Coal plant age (0-9 years)

Operating coal power capacity, by plant age, is generated from the Global Coal Plant Tracker (GCPT). The GCPT provides information on coal-fired power units from around the world generating 30 megawatts and above. The GCPT catalogues every operating coal-fired generating unit, every new unit proposed since 2010, and every unit retired since 2000. Units often consist of a boiler and turbine, and several units may make up one coal-fired power station. The map and underlying data is updated bi-annually, in January and July. Each plant included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GCPT was accessed in July 2021 to generate this data.

Global Coal Plant Tracker, Global Energy Monitor. Available at: https://globalenergymonitor.org/projects/global-coal-plant-tracker/


Operating coal power capacity by plant age (MW) - Coal plant age (10-19 years)


Operating coal power capacity by plant age (MW) - Coal plant age (20-29 years)


Operating coal power capacity by plant age (MW) - Coal plant age (30-39 years)


Operating coal power capacity by plant age (MW) - Coal plant age (40-49 years)


Operating coal power capacity by plant age (MW) - Coal plant age (50-plus years)


Operating coal power capacity by plant type (MW) - Plant Type (Subcritical/CCS)


Operating coal power capacity by plant type (MW) - Plant Type (CFB)


Operating coal power capacity by plant type (MW) - Plant Type (IGCC)


Operating coal power capacity by plant type (MW) - Plant Type (Supercritical)


Operating coal power capacity by plant type (MW) - Plant Type (Subcritical)


Operating coal power capacity by plant type (MW) - Plant Type (Unknown)


Operating coal power capacity by plant type (MW) - Plant Type (Ultra-super)


Control of Corruption: Percentile Rank

Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests.  Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.


Control of Corruption: Percentile Rank, Lower Bound of 90% Confidence Interval

Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests.  Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.  Percentile Rank Lower refers to lower bound of 90 percent confidence interval for governance, expressed in percentile rank terms.


Control of Corruption: Percentile Rank, Upper Bound of 90% Confidence Interval

Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests.  Percentile rank indicates the country's rank among all countries covered by the aggregate indicator, with 0 corresponding to lowest rank, and 100 to highest rank.  Percentile ranks have been adjusted to correct for changes over time in the composition of the countries covered by the WGI.  Percentile Rank Upper refers to upper bound of 90 percent confidence interval for governance, expressed in percentile rank terms.


Percentage of people who believe it is somewhat very likely that they could use the right to use their property of part of it against their will in the next 5 years

Indicator reflects percentage of people who believe it is somewhat very likely that they could lose the right to use their property of part of it against their will in the next 5 years

Prindex. Available at: https://www.prindex.net/data/


Percentage of people who believe it is very unlikely or unlikely that they could use the right to use their property of part of it against their will in the next 5 years

Indicator reflects percentage of people who believe it is very unlikely or unlikely that they could lose the right to use their property of part of it against their will in the next 5 years


Percentage of people who say they have formal documents, legally-binding documents that demonstrate their right to live in or use any of their properties

Indicator reflects percentage of people who say they have formal documents, legally-binding documents that demonstrate their right to live in or use any of their properties


Percentage of people who say they have informal documents that demonstrate their right to live in or use any of their properties

Indicator reflects percentage of people who say they have informal documents that demonstrate their right to live in or use any of their properties


Percentage of people who say they have no documents or informal documents that demonstrate their right to live in or use any of their properties

Indicator reflects percentage of people who say they have no documents or informal documents that demonstrate their right to live in or use any of their properties


Average supply of protein of animal origin (g/cap/day)

Average supply of protein of animal origin reflects a 3-year average from the Suite of Food Security Indicators on FAOSTAT. Suite of Food Security Indicators presents the core set of food security indicators. Following the recommendation of experts gathered in the Committee on World Food Security (CFS) Round Table on hunger measurement, hosted at FAO headquarters in September 2011, an initial set of indicators aiming to capture various aspects of food insecurity is presented on FAOSTAT. The choice of the indicators has been informed by expert judgment and the availability of data with sufficient coverage to enable comparisons across regions and over time. Many of these indicators are produced and published elsewhere by FAO and other international organizations. They are reported on FAOSTAT in a single database with the aim of building a wide food security information system. More indicators will be added to this set as more data will become available. Indicators are classified along the four dimensions of food security -- availability, access, utilization and stability. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.


Passenger volume by mode (billion tons-km) - Air transport


Passenger volume by mode (billion tons-km) - Rail transport

This indicator presents the passenger volume attributable to rail transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Passenger volume (passenger kilometres) by mode of transport.


Passenger volume by mode (billion tons-km) - Road transport

This indicator presents the passenger volume attributable to road transport. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.1.2: Passenger volume (passenger kilometres) by mode of transport.


Prevalence of undernourishment (3-year average) (% of total)

Prevalence of undernourishment relfects a 3-year average from the Suite of Food Security Indicators on FAOSTAT. Suite of Food Security Indicators presents the core set of food security indicators. Following the recommendation of experts gathered in the Committee on World Food Security (CFS) Round Table on hunger measurement, hosted at FAO headquarters in September 2011, an initial set of indicators aiming to capture various aspects of food insecurity is presented on FAOSTAT. The choice of the indicators has been informed by expert judgment and the availability of data with sufficient coverage to enable comparisons across regions and over time. Many of these indicators are produced and published elsewhere by FAO and other international organizations. They are reported on FAOSTAT in a single database with the aim of building a wide food security information system. More indicators will be added to this set as more data will become available. Indicators are classified along the four dimensions of food security -- availability, access, utilization and stability. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.


Rice supply quantity (g/capita/day)

Rice supply is taken from crops processed (domain), food supply quantity (element), rice milled (item) of the Crop statistics (FAOSTAT). FAOSTAT Crop statistics are recorded for 173 products, covering the following categories: Crops Primary, Fibre Crops Primary, Cereals, Coarse Grain, Citrus Fruit, Fruit, Jute Jute-like Fibres, Oilcakes Equivalent, Oil crops Primary, Pulses, Roots and Tubers, Treenuts and Vegetables and Melons. Data are expressed in terms of area harvested, production quantity and yield. The objective is to comprehensively cover production of all primary crops for all countries and regions in the world.Cereals: Area and production data on cereals relate to crops harvested for dry grain only. Cereal crops harvested for hay or harvested green for food, feed or silage or used for grazing are therefore excluded. Area data relate to harvested area. Some countries report sown or cultivated area only. This work is made available under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 IGO license (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/licenses/by-nc-sa/3.0/igo). In addition to this license, some database specific terms of use are listed: Terms of Use of Datasets.


Risk to asset (average annual losses as % of GDP)

Risk to asset indicator is intended to be viewed with risk to wellbeing indicator (both reported as average annual losses as % of GDP). The Unbreakable report which the indicators are taken from moves beyond asset and production losses and shifts its attention to how natural disasters affect people’s well-being. Disasters are far greater threats to well-being than traditional estimates suggest. This approach provides a more nuanced view of natural disasters than usual reporting, and a perspective that takes fuller account of poor people’s vulnerabilities.

Hallegatte, Stephane; Vogt-Schilb, Adrien; Bangalore, Mook; Rozenberg, Julie. 2017. Unbreakable : Building the Resilience of the Poor in the Face of Natural Disasters. Climate Change and Development;. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/25335 License: CC BY 3.0 IGO.


Risk to wellbeing (average annual losses as % of GDP)

Risk to wellbeing indicator is intended to be viewed with risk to asset indicator (both reported as average annual losses as % of GDP). The Unbreakable report which the indicators are taken from moves beyond asset and production losses and shifts its attention to how natural disasters affect people’s well-being. Disasters are far greater threats to well-being than traditional estimates suggest. This approach provides a more nuanced view of natural disasters than usual reporting, and a perspective that takes fuller account of poor people’s vulnerabilities.


Percentage of population with No Education


Percentage of population with Primary Education

Education status as a percentage of the total population is disaggregated from the Global Jobs Indicatos Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Percentage of population with Secondary Education


Percentage of population with Post Secondary Education


Mean number of years of education completed, aged 17 and older

Mean number of years of education completed (aged 17+) is disaggregated from the Global Jobs Indicatos Database. The Database covers socio-demographics, labor force status and employment type, employment composition by sector and occupation, education level completed, hours worked, and earnings. The database was compiled from national surveys and subnational microdata which was first harmonized for the Bank-wide I2D2 database, then quality checked by the Jobs Group.


Mortality rate attributable to household air pollution (deaths per 100 000 population)

This indicator presents the mortality rate attributable to household air pollution as a factor of deaths per 100 000 population. Data is taken from the United Nations Sustainable Goals, representing Indicator 3.9.1: Crude death rate attributed to ambient air pollution (deaths per 100 000 population).


Mortality rate attributable to ambient air pollution (deaths per 100 000 population)

This indicator presents the mortality rate attributable to ambient air pollution as a factor of deaths per 100 000 population. Data is taken from the United Nations Sustainable Goals, representing Indicator 3.9.1: Crude death rate attributed to household air pollution (deaths per 100 000 population).


Share of population covered by at least one social protection benefit (%)

This indicator conveys the share of the population effectively covered by a social protection system, including social protection floors. It also provides the coverage rates of the main components of social protection: child and maternity benefits, support for persons without a job, persons with disabilities, victims of work injuries and older persons. For more information, refer to the concepts and definitions page. Alternate source for this information is UN open data hub, SDG Indicator 1.3.1: Proportion of population covered by social protection floors/systems (%) | Annual

International Labour Organization - ILOSTAT database, https://ilostat.ilo.org/data


Public social protection expenditure (%of GDP)


Control of Corruption: Standard Error

Control of Corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests.   Standard error indicates the precision of the estimate of governance.  Larger values of the standard error indicate less precise estimates.  A 90 percent confidence interval for the governance estimate is given by the estimate +/- 1.64 times the standard error.


Number of companies that are TCFD compliant by sector - Central Bank

TCFD compliant company data is sourced from the Task Force on Climate-Related Financial Disclosures and aggregated into sector brackets. The Task Force on Climate-related Financial Disclosures (TCFD) provides a framework for companies and other organizations to develop more effective climate related financial disclosures through their existing reporting processes.

Task Force on Climate-Related Financial Disclosures. Available at: https://www.fsb-tcfd.org/supporters/


Number of companies that are TCFD compliant by sector - Consumer Discretionary


Number of companies that are TCFD compliant by sector - Communication Services


Number of companies that are TCFD compliant by sector - Consumer Staples


Number of companies that are TCFD compliant by sector - Energy


Number of companies that are TCFD compliant by sector - Financials


Number of companies that are TCFD compliant by sector - Government


Number of companies that are TCFD compliant by sector - Health Care


Number of companies that are TCFD compliant by sector - Industrials


Number of companies that are TCFD compliant by sector - Information Technology


Number of companies that are TCFD compliant by sector - Materials


Number of companies that are TCFD compliant by sector - Other


Number of companies that are TCFD compliant by sector - Real Estate


Number of companies that are TCFD compliant by sector - Transportation


Number of companies that are TCFD compliant by sector - Utilities


Natural hazard levels - Coastal flood

Natural Hazard levels from Coastal Flood are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.

ThinkHazard! data [https://thinkhazard.org/en/] taken from the Climate Change Knowledge Portal [available at: https://climateknowledgeportal.worldbank.org/]


Natural hazard levels - Cyclone

Natural Hazard levels from Cyclones are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


Natural hazard levels - Extreme heat

Natural Hazard levels from Extreme Heat are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


Natural hazard levels - Earthquake

Natural Hazard levels from Earthquakes are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


Natural hazard levels - Landslide

Natural Hazard levels from Landslides are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


Natural hazard levels - River flood

Natural Hazard levels from River Flood are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


Natural hazard levels - Tsunami

Natural Hazard levels from Tsunamis are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


Natural hazard levels - Urban flood

Natural Hazard levels from Urban Flood are generated from ThinkHazard! data available from the Climate Change Knowledge Portal. ThinkHazard! provides a general view of the hazards, for a given location, that should be considered in project design and implementation to promote disaster and climate resilience.  Teams interested in historical and future climate, vulnerabilities and impacts should utilize the CCKP resource [available at: https://climateknowledgeportal.worldbank.org/]. This resource allows users to explore data across 40+ indicators, at different aggregations (national and sub-national), with annual and seasonal calculations.


Share of transport network exposed to cyclones (%)

Share of transport network that is exposed to cyclones, represented as a percentage of the total transport network within a given country. This metric measures the fraction of the transport network that has a significant risk of experiencing an intense cyclone (the threshold is country dependent, based on the expected resistance of the infrastructure in the country).

Hallegatte, Stephane; Rentschler, Jun; Rozenberg, Julie. 2019. Lifelines : The Resilient Infrastructure Opportunity. Sustainable Infrastructure;. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/31805 License: CC BY 3.0 IGO.


Share of transport network exposed to earthquakes (%)

Share of transport network that is exposed to earthquakes, represented as a percentage of the total transport network within a given country. This metric measures the fraction of the transport network that has a significant risk of experiencing an intense earthquake (the threshold is country dependent, based on the expected resistance of the infrastructure in the country).


Share of transport network exposed to floods (%)

Share of transport network that is exposed to floods, represented as a percentage of the total transport network within a given country. This metric measures the fraction of the transport network that has a significant risk of experiencing an intense flood (the threshold is country dependent, based on the expected resistance of the infrastructure in the country).


Annual investments needed to make transport infrastructure more resilient by 2030 (% of baseline investment costs)


Share of transport network exposed to natural disasters (%)

Share of transport network that is exposed to natural disasters, represented as a percentage of the total transport network within a given country. This metric measures the fraction of the transport network that has a significant risk of experiencing an intense natural disaster (the threshold is country dependent, based on the expected resistance of the infrastructure in the country). In this instance natural disaster total reflects the results of earthquakes, floods, and cyclones.


Resilient infrastructure would reduce annual repair cost by a factor


Total GHG emissions growth in the period 2012-2018 (%)


Total coal capacity by plant status (MW) - Announced


Total coal capacity by plant status (MW) - Cancelled

Total coal capacity by plant status is generated from the Global Coal Plant Tracker (GCPT). The GCPT provides information on coal-fired power units from around the world generating 30 megawatts and above. The GCPT catalogues every operating coal-fired generating unit, every new unit proposed since 2010, and every unit retired since 2000. Units often consist of a boiler and turbine, and several units may make up one coal-fired power station. The map and underlying data is updated bi-annually, in January and July. Each plant included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GCPT was accessed in July 2021 to generate this data.


Total coal capacity by plant status (MW) - Construction


Total coal capacity by plant status (MW) - Mothballed


Total coal capacity by plant status (MW) - Operating


Total coal capacity by plant status (MW) - Permitted


Total coal capacity by plant status (MW) - Pre-permit


Total coal capacity by plant status (MW) - Retired


Total coal capacity by plant status (MW) - Shelved


Financing via international capital markets (gross inflows, % of GDP)


S&P Global Equity Indices (annual % change)

S&P Global Equity Indices measure the U.S. dollar price change in the stock markets covered by the S&P/IFCI and S&P/Frontier BMI country indices.

Standard & Poor's, Global Stock Markets Factbook and supplemental S&P data.


Market capitalization of listed domestic companies (current US$)

Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.


Market capitalization of listed domestic companies (% of GDP)

Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. Data are end of year values.


Listed domestic companies, total

Listed domestic companies, including foreign companies which are exclusively listed, are those which have shares listed on an exchange at the end of the year. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies, such as holding companies and investment companies, regardless of their legal status, are excluded. A company with several classes of shares is counted once. Only companies admitted to listing on the exchange are included.


Stocks traded, total value (current US$)

The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.


Stocks traded, total value (% of GDP)

The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values.


Stocks traded, turnover ratio of domestic shares (%)

Turnover ratio is the value of domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12.


Affordability of an energy sufficient diet: ratio of cost to food expenditures


Percent of the population who cannot afford sufficient calories


Affordability of an energy sufficient diet: ratio of cost to the food poverty line


Millions of people who cannot afford sufficient calories


Cost share for animal-sourced foods in a least-cost healthy diet


Cost of animal-sourced foods relative to the starchy staples in a least-cost healthy diet


Cost of a healthy diet relative to the cost of sufficient energy from starchy staples


Cost share for fruits in a least-cost healthy diet


Cost of fruits relative to the starchy staples in a least-cost healthy diet


Affordability of a healthy diet: ratio of cost to food expenditures


Percent of the population who cannot afford a healthy diet


Cost share for legumes, nuts and seeds in a least-cost healthy diet


Cost of legumes, nuts and seeds relative to the starchy staples in a least-cost healthy diet


Cost share for oils and fats in a least-cost healthy diet


Cost of oils and fats relative to the starchy staples in a least-cost healthy diet


Affordability of a healthy diet: ratio of cost to the food poverty line


Cost share for starchy staples in a least-cost healthy diet


Millions of people who cannot afford a healthy diet


Cost share for vegetables in a least-cost healthy diet


Cost of vegetables relative to the starchy staples in a least-cost healthy diet


Affordability of a nutrient adequate diet: ratio of cost to food expenditures


Percent of the population who cannot afford nutrient adequacy


Affordability of a nutrient adequate diet: ratio of cost to the food poverty line


Millions of people who cannot afford nutrient adequacy


CPI Price, nominal

The consumer price index reflects the change in prices for the average consumer of a constant basket of consumer goods. Data is not seasonally adjusted.

World Bank staff calculations based on Datastream data.


CPI Price, % y-o-y, median weighted, seas. adj.

Median inflation rate calculated for geographical aggregates (regions, world, etc) of the annual percent change of the CPI. Data is seasonally adjusted.


CPI Price, nominal, seas. adj.

The consumer price index reflects the change in prices for the average consumer of a constant basket of consumer goods. Data is in nominal terms and seasonally adjusted.


CPI Price, % y-o-y, nominal, seas. adj.

The consumer price index reflects the change in prices for the average consumer of a constant basket of consumer goods. Data is in nominal percentage terms, measured on a year-on-year basis, and seasonally adjusted.


Budget alignment with climate change strategies


Compliance of climate-related expenditure


Effectiveness of the systems of controls


Climate-responsive fiscal decentralization arrangements


Climate-responsive PFM arrangements applied by subnational governments


Climate related information in performance plans


Climate  related  information  in  performance reports


Climate-related evaluation of expenditure


Expenditure  outturn for climate activities


Aggregate climate related-expenditure outturn


Climate-related expenditure composition outturn


Legislative scrutiny of audit and evaluation reports


Climate-responsive public investment management


Climate-responsive  provisions in regulatory framework for public investment management


Climate-responsive provisions for project appraisal


Climate-responsive provisions for project selection


Reporting from entities in charge of implementation


Climate-responsive non-financial asset management


Fiscal risks arising from climate-related contingent liabilities


Climate-responsive public procurement framework


Climate-responsive public procurement operations


Climate-responsive public procurement monitoring


Climate-responsive public procurement reporting


Climate-related tax management, audit, and investigation


(i) Annual deviation of actual budget support from the forecast provided by the donor agencies at least six weeks prior to the government submitting its budget proposals to the legislature (or equivalent approving body)


(ii) In-year timeliness of donor disbursements (compliance with aggregate quarterly estimates)


Financial information provided by donors for budgeting and reporting on project and program aid


(i) Completeness and timeliness of budget estimates by donors for project support


(ii) Frequency and coverage of reporting by donors on actual donor flows for project support


Proportion of aid that is managed by use of national procedures


063.Product Entry Rate of Incumbents: Mean

Exporter Dynamics Database – Indicators at Country-Year Level

Exporter-level information on export transactions - Customs


064.Product Entry Rate of Incumbents: Median


065.Product Entry Rate of Incumbents: StDev.


066.Product Entry Rate of Surviving Entrants: Mean


067.Product Entry Rate of Surviving Entrants: Median


068.Product Entry Rate of Surviving Entrants: StDev.


069.Share of New Products in TEV of Incumbents: Mean


070.Share of New Products in TEV of Incumbents: Median


071.Share of New Products in TEV of Incumbents: StDev.


072.Share of New Products in TEV of Surviving Entrants: Mean


073.Share of New Products in TEV of Surviving Entrants: Median


074.Share of New Products in TEV of Surviving Entrants: StDev.


075.Product Exit Rate of Incumbents: Mean


076.Product Exit Rate of Incumbents: Median


077.Product Exit Rate of Incumbents: StDev.


078.Product Survival Rate of 2-year Incumbents: Mean


079.Product Survival Rate of 2-year Incumbents: Median


080.Product Survival Rate of 2-year Incumbents: StDev.


Total Specific Allocation Grant for Agriculture (in IDR Billion)

Indonesia Database for Policy and Economic Research

The Specific Allocation Grant (DAK) is a fund sourced from revenue in the Central Budget (APBN) allocated to a certain region with the aim of funding special activities of the region in accordance with national priorities. The DAK allocation has a formula component that takes into account the fiscal gap and has a 10 percent matching requirement. The DAK is earmarked for capital spending and cannot be used for research, training, administration, or official travel.

Ministry of Finance, Ministry of Finance Regulation


Total Specific Allocation Grant for Education (in IDR Billion)


Total Specific Allocation Grant for Environment (in IDR Billion)


Total Specific Allocation Grant for Forestry (in IDR Billion)


Total Specific Allocation Grant for Fishery (in IDR Billion)


Total Specific Allocation Grant for Government Sector (in IDR Billion)


Total Specific Allocation Grant for Health Sector (Subsect: Basic Services) (in IDR Billion)


Total Specific Allocation Grant for Health (in IDR Billion)


Total Specific Allocation Grant for Health Sector (Subsect: Recommended Services) (in IDR Billion)


Total Specific Allocation Grant for Infrastructure (in IDR Billion)


Total Specific Allocation Grant for Infrastructure Sector (Subsect: Water) (in IDR Billion)


Total Specific Allocation Grant for Infrastructure Sector (Subsect: Irrigation) (in IDR Billion)


Total Specific Allocation Grant for Infrastructure Sector (Subsect: Road) (in IDR Billion)


Total Specific Allocation Grant for Demographic (in IDR Billion)


Total Specific Allocation Grant for Trade (in IDR Billion)


Total Specific Allocation Grant for Village (in IDR Billion)


Official aid provided to part II countries (current US$)