IndicatorName: Median earnings per hour, aged 15-64, deflated to 2010 local currency values, urban


IndicatorName: Real median earnings per hour, aged 15-24, deflated to 2010 and PPP adjusted

License_Type: CC BY-4.0

Periodicity: Annual

Shortdefinition: Median earnings for wage workers per hour aged 15-64, inflation corrected to 2010 values and adjusted for purchasing power parity using WDI provided exchange values. The sub-groups are: Urban shows the results for only the urban population, rural shows the results for the rural population, youth shows the results for the young population between 15 to 24 years, adult shows the results for the adults aged between 25 to 64 years, male shows the results for the male population and female shows the results for the female population. Low educated shows the results for those with primary education or less, and high educated shows the results for everyone who obtained a higher education.

Source: Global Jobs Indicators Database, The World Bank (https://datacatalog.worldbank.org/dataset/global-jobs-indicators-database)

Topic: Social Protection & Labor


IndicatorName: Median earnings per hour, aged 15-24, local currency values

Shortdefinition: Median earnings for wage workers per hour aged 15-64 reported in local currency values. Currency values are typically reported for the year when the survey was conducted. The sub-groups are: Urban shows the results for only the urban population, rural shows the results for the rural population, youth shows the results for the young population between 15 to 24 years, adult shows the results for the adults aged between 25 to 64 years, male shows the results for the male population and female shows the results for the female population. Low educated shows the results for those with primary education or less, and high educated shows the results for everyone who obtained a higher education.


IndicatorName: Median earnings per hour, aged 15-24, deflated to 2010 local currency values

Shortdefinition: Median earnings for wage workers per hour aged 15-64, inflation corrected to 2010 values. The sub-groups are: Urban shows the results for only the urban population, rural shows the results for the rural population, youth shows the results for the young population between 15 to 24 years, adult shows the results for the adults aged between 25 to 64 years, male shows the results for the male population and female shows the results for the female population. Low educated shows the results for those with primary education or less, and high educated shows the results for everyone who obtained a higher education.


IndicatorName: Real median earnings per month, aged 15-64, deflated to 2010 and PPP adjusted, total

Shortdefinition: Median earnings for wage workers per month aged 15-64, inflation corrected to 2010 values and adjusted for purchasing power parity using WDI provided exchange values. The sub-groups are: Urban shows the results for only the urban population, rural shows the results for the rural population, youth shows the results for the young population between 15 to 24 years, adult shows the results for the adults aged between 25 to 64 years, male shows the results for the male population and female shows the results for the female population. Low educated shows the results for those with primary education or less, and high educated shows the results for everyone who obtained a higher education.


IndicatorName: Median earnings per month, aged 15-64, local currency values, total

Shortdefinition: Median earnings for wage workers per month aged 15-64 reported in local currency values. Currency values are typically reported for the year when the survey was conducted. The sub-groups are: Urban shows the results for only the urban population, rural shows the results for the rural population, youth shows the results for the young population between 15 to 24 years, adult shows the results for the adults aged between 25 to 64 years, male shows the results for the male population and female shows the results for the female population. Low educated shows the results for those with primary education or less, and high educated shows the results for everyone who obtained a higher education.


IndicatorName: Median earnings per month, aged 15-64, deflated to 2010 local currency values, total

Shortdefinition: Median earnings for wage workers per month aged 15-64, inflation corrected to 2010 values. The sub-groups are: Urban shows the results for only the urban population, rural shows the results for the rural population, youth shows the results for the young population between 15 to 24 years, adult shows the results for the adults aged between 25 to 64 years, male shows the results for the male population and female shows the results for the female population. Low educated shows the results for those with primary education or less, and high educated shows the results for everyone who obtained a higher education.


IndicatorName: Real median earnings per month, aged 15-64, deflated to 2010 and PPP adjusted, female


IndicatorName: Median earnings per month, aged 15-64, local currency values, female


IndicatorName: Median earnings per month, aged 15-64, deflated to 2010 local currency values, female


IndicatorName: Real median earnings per month, aged 15-64, deflated to 2010 and PPP adjusted, above primary education


IndicatorName: Median earnings per month, aged 15-64, local currency values, above primary education


IndicatorName: Median earnings per month, aged 15-64, deflated to 2010 local currency values, above primary education


IndicatorName: Real median earnings per month, aged 15-64, deflated to 2010 and PPP adjusted, primary education and below


IndicatorName: Median earnings per month, aged 15-64, local currency values, primary education and below


IndicatorName: Median earnings per month, aged 15-64, deflated to 2010 local currency values, primary education and below


IndicatorName: Real median earnings per month, aged 15-64, deflated to 2010 and PPP adjusted, male


IndicatorName: Median earnings per month, aged 15-64, local currency values, male


IndicatorName: Median earnings per month, aged 15-64, deflated to 2010 local currency values, male


IndicatorName: Real median earnings per month, aged 25-64, deflated to 2010 and PPP adjusted


IndicatorName: Median earnings per month, aged 25-64, local currency values


IndicatorName: Median earnings per month, aged 25-64, deflated to 2010 local currency values


IndicatorName: Real median earnings per month, aged 15-64, deflated to 2010 and PPP adjusted, rural


IndicatorName: Median earnings per month, aged 15-64, local currency values, rural


IndicatorName: Median earnings per month, aged 15-64, deflated to 2010 local currency values, rural


IndicatorName: Real median earnings per month, aged 15-64, deflated to 2010 and PPP adjusted, urban


IndicatorName: Median earnings per month, aged 15-64, local currency values, urban


IndicatorName: Median earnings per month, aged 15-64, deflated to 2010 local currency values, urban


IndicatorName: Real median earnings per month, aged 15-24, deflated to 2010 and PPP adjusted


IndicatorName: Median earnings per month, aged 15-24, local currency values


IndicatorName: Median earnings per month, aged 15-24, deflated to 2010 local currency values


IndicatorName: Public to private wage gap, aged 15-64, total

Shortdefinition: Public to private wage gap for wage workers aged 15-64. Reports the ratio of public wage workers earnings to private wage workers earnings. The sub-groups are: Urban shows the results for only the urban population, rural shows the results for the rural population, youth shows the results for the young population between 15 to 24 years, adult shows the results for the adults aged between 25 to 64 years, male shows the results for the male population and female shows the results for the female population. Low educated shows the results for those with primary education or less, and high educated shows the results for everyone who obtained a higher education.


IndicatorName: Public to private wage gap, aged 15-64, female


IndicatorName: Public to private wage gap, aged 15-64, above primary education


IndicatorName: Public to private wage gap, aged 15-64, primary education and below


IndicatorName: Public to private wage gap, aged 15-64, male


IndicatorName: Public to private wage gap, aged 25-64


IndicatorName: Public to private wage gap, aged 15-64, rural


IndicatorName: Public to private wage gap, aged 15-64, urban


IndicatorName: Public to private wage gap, aged 15-24


Aggregationmethod: Weighted average

Dataset: Global Findex

IndicatorName: Account (% age 15+)

Longdefinition: The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution (see definition for financial institution account) or report personally using a mobile money service in the .past 12 months (see definition for mobile money account).

Periodicity: Triennial

Source: Global Findex database

Topic: Adaptation

Unitofmeasure: Percent


IndicatorName: Account, income, poorest 40% (% ages 15+)

Longdefinition: The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution (see definition for financial institution account) or report personally using a mobile money service in the past 12 months (see definition for mobile money account), income, poorest 40%  (% age 15+).


Developmentrelevance:
Agricultural land covers more than one-third of the world's land area, with arable land representing less than one-third of agricultural land (about 10 percent of the world's land area). Agricultural land constitutes only a part of any country's total area, which can include areas not suitable for agriculture, such as forests, mountains, and inland water bodies.

In many industrialized countries, agricultural land is subject to zoning regulations. In the context of zoning, agricultural land (or more properly agriculturally zoned land) refers to plots that may be used for agricultural activities, regardless of the physical type or quality of land.

FAO's agricultural land data contains a wide range of information on variables that are significant for: understanding the structure of a country's agricultural sector; making economic plans and policies for food security; deriving environmental indicators, including those related to investment in agriculture and data on gross crop area and net crop area which are useful for policy formulation and monitoring.

There is no single correct mix of inputs to the agricultural land, as it is dependent on local climate, land quality, and economic development; appropriate levels and application rates vary by country and over time and depend on the type of crops, the climate and soils, and the production process used.

IndicatorName: Agricultural land (% of land area)

Limitationsandexceptions: The data are collected by the Food and Agriculture Organization of the United Nations (FAO) from official national sources through annual questionnaires and are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.. The FAO tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries. Data on agricultural employment, in particular, should be used with caution. In many countries much agricultural employment is informal and unrecorded, including substantial work performed by women and children. To address some of these concerns, this indicator is heavily footnoted in the database in sources, definition, and coverage.

Longdefinition: Agricultural land refers to the share of land area that is arable, under permanent crops, and under permanent pastures. Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded. Land under permanent crops is land cultivated with crops that occupy the land for long periods and need not be replanted after each harvest, such as cocoa, coffee, and rubber. This category includes land under flowering shrubs, fruit trees, nut trees, and vines, but excludes land under trees grown for wood or timber. Permanent pasture is land used for five or more years for forage, including natural and cultivated crops.

Othernotes: Areas of former states are included in the successor states.

Source: Food and Agriculture Organization, electronic files and web site.

Statisticalconceptandmethodology:
Agriculture is still a major sector in many economies, and agricultural activities provide developing countries with food and revenue. But agricultural activities also can degrade natural resources. Poor farming practices can cause soil erosion and loss of soil fertility. Efforts to increase productivity by using chemical fertilizers, pesticides, and intensive irrigation have environmental costs and health impacts. Excessive use of chemical fertilizers can alter the chemistry of soil. Pesticide poisoning is common in developing countries. And salinization of irrigated land diminishes soil fertility. Thus, inappropriate use of inputs for agricultural production has far-reaching effects.

Agricultural land is also sometimes classified as irrigated and non-irrigated land. In arid and semi-arid countries agriculture is often confined to irrigated land, with very little farming possible in non-irrigated areas. Land abandoned as a result of shifting cultivation is excluded from Arable land.

Data on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.

Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area.

Topic: Mitigation

Unitofmeasure: % of land area


Developmentrelevance:
Agricultural land covers more than one-third of the world's land area. Agricultural land constitutes only a part of any country's total area, which can include areas not suitable for agriculture, such as forests, mountains, and inland water bodies.

Agriculture is still a major sector in many economies, and agricultural activities provide developing countries with food and revenue. But agricultural activities also can degrade natural resources. Poor farming practices can cause soil erosion and loss of soil fertility. Efforts to increase productivity by using chemical fertilizers, pesticides, and intensive irrigation have environmental costs and health impacts. Excessive use of chemical fertilizers can alter the chemistry of soil. Pesticide poisoning is common in developing countries. And salinization of irrigated land diminishes soil fertility. Thus, inappropriate use of inputs for agricultural production has far-reaching effects.

There is significant geographic variation in the availability of land considered suitable for agriculture. Increasing population and demand from other sectors place growing pressure on available resources. According to FAO, the world's cultivated area has grown by 12 percent over the last 50 years. The global irrigated area has doubled over the same period, accounting for most of the net increase in cultivated land. Agriculture already uses 11 percent of the world's land surface for crop production. It also makes use of 70 percent of all water withdrawn from aquifers, streams and lakes. Agricultural policies have primarily benefitted farmers with productive land and access to water, bypassing the majority of small-scale producers who are still locked in a poverty trap of high vulnerability, land degradation and climatic uncertainty.

Land resources are central to agriculture and rural development, and are intrinsically linked to global challenges of food insecurity and poverty, climate change adaptation and mitigation, as well as degradation and depletion of natural resources that affect the livelihoods of millions of rural people across the world.

In many industrialized countries, agricultural land is subject to zoning regulations. In the context of zoning, agricultural land (or more properly agriculturally zoned land) refers to plots that may be used for agricultural activities, regardless of the physical type or quality of land.

FAO's agricultural land data contains a wide range of information on variables that are significant for: understanding the structure of a country's agricultural sector; making economic plans and policies for food security; deriving environmental indicators, including those related to investment in agriculture and data on gross crop area and net crop area which are useful for policy formulation and monitoring.

IndicatorName: Arable land (% of land area)

Limitationsandexceptions:
The Food and Agriculture Organization (FAO) tries to impose standard definitions and reporting methods, but complete consistency across countries and over time is not possible. Thus, data on agricultural land in different climates may not be comparable. For example, permanent pastures are quite different in nature and intensity in African countries and dry Middle Eastern countries.

The data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations. Data on agricultural land are valuable for conducting studies on a various perspectives concerning agricultural production, food security and for deriving cropping intensity among others uses. Agricultural land indicator, along with land-use indicators, can also elucidate the environmental sustainability of countries' agricultural practices.

True comparability of the data is limited, by variations in definitions, statistical methods, and quality of data. Countries use different definitions land use. The Food and Agriculture Organization of the United Nations (FAO), the primary compiler of the data, occasionally adjusts its definitions of land use categories and revises earlier data. Because the data reflect changes in reporting procedures as well as actual changes in land use, apparent trends should be interpreted cautiously.

Satellite images show land use that differs from that of ground-based measures in area under cultivation and type of land use. Moreover, land use data in some countries (India is an example) are based on reporting systems designed for collecting tax revenue. With land taxes no longer a major source of government revenue, the quality and coverage of land use data have declined.

Longdefinition: Arable land includes land defined by the FAO as land under temporary crops (double-cropped areas are counted once), temporary meadows for mowing or for pasture, land under market or kitchen gardens, and land temporarily fallow. Land abandoned as a result of shifting cultivation is excluded.

Statisticalconceptandmethodology: Temporary fallow land refers to land left fallow for less than five years. The abandoned land resulting from shifting cultivation is not included in this category. Data for "Arable land" are not meant to indicate the amount of land that is potentially cultivable. Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. The data collected by the Food and Agriculture Organization (FAO) of the United Nations from official national sources through the questionnaire are supplemented with information from official secondary data sources. The secondary sources cover official country data from websites of national ministries, national publications and related country data reported by various international organizations.


Developmentrelevance:
As threats to biodiversity mount, the international community is increasingly focusing on conserving diversity. Deforestation is a major cause of loss of biodiversity, and habitat conservation is vital for stemming this loss. Conservation efforts have focused on protecting areas of high biodiversity.

On a global average, more than one-third of all forest is primary forest, i.e. forest of native species where there are no clearly visible indications of human activities and the ecological processes have not been significantly disturbed. Primary forests, in particular tropical moist forests, include the most species-rich, diverse terrestrial ecosystems. The decrease of forest area, .11 percent over a ten-year period, is largely due to reclassification of primary forest to "other naturally regenerated forest" because of selective logging and other human interventions.

Destruction of rainforests remains a significant environmental problem Much of what remains of the world's rainforests is in the Amazon basin, where the Amazon Rainforest covers approximately 4 million square kilometers. The regions with the highest tropical deforestation rate are in Central America and tropical Asia. FAO estimates that the decrease of primary forest area, 0.4 percent over a ten-year period, is largely due to reclassification of primary forest to "other naturally regenerated forest" because of selective logging and other human interventions. Large-scale planting of trees is significantly reducing the net loss of forest area globally, and afforestation and natural expansion of forests in some countries and regions have reduced the net loss of forest area significantly at the global level.

Forests cover about 31 percent of total land area of the world; the world's total forest area is just over 4 billion hectares. On a global average, more than one-third of all forest is primary forest, i.e. forest of native species where there are no clearly visible indications of human activities and the ecological processes have not been significantly disturbed. Primary forests, in particular tropical moist forests, include the most species-rich, diverse terrestrial ecosystems.

National parks, game reserves, wilderness areas and other legally established protected areas cover more than 10 percent of the total forest area in most countries and regions. FAO estimates that around 10 million people are employed in forest management and conservation - but many more are directly dependent on forests for their livelihoods. Close to 1.2 billion hectares of forest are managed primarily for the production of wood and non-wood forest products. An additional 25 percent of forest area is designated for multiple uses - in most cases including the production of wood and non-wood forest products. The area designated primarily for productive purposes has decreased by more than 50 million hectares since 1990 as forests have been designated for other purposes.

IndicatorName: Forest area (% of land area)

Limitationsandexceptions:
FAO has been collecting and analyzing data on forest area since 1946. This is done at intervals of 5-10 years as part of the Global Forest Resources Assessment (FRA). FAO reports data for 229 countries and territories; for the remaining 56 small island states and territories where no information is provided, a report is prepared by FAO using existing information and a literature search. The data are aggregated at sub-regional, regional and global levels by the FRA team at FAO, and estimates are produced by straight summation.

The lag between the reference year and the actual production of data series as well as the frequency of data production varies between countries. Deforested areas do not include areas logged but intended for regeneration or areas degraded by fuelwood gathering, acid precipitation, or forest fires. Negative numbers indicate an increase in forest area.

Data includes areas with bamboo and palms; forest roads, firebreaks and other small open areas; forest in national parks, nature reserves and other protected areas such as those of specific scientific, historical, cultural or spiritual interest; windbreaks, shelterbelts and corridors of trees with an area of more than 0.5 hectares and width of more than 20 meters; plantations primarily used for forestry or protective purposes, such as rubber-wood plantations and cork oak stands. Data excludes tree stands in agricultural production systems, such as fruit plantations and agroforestry systems. Forest area also excludes trees in urban parks and gardens. The proportion of forest area to total land area is calculated and changes in the proportion are computed to identify trends.

Longdefinition: Forest area is land under natural or planted stands of trees of at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural production systems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.

Statisticalconceptandmethodology:
Forest is determined both by the presence of trees and the absence of other predominant land uses. The trees should reach a minimum height of 5 meters in situ. Areas under reforestation that have not yet reached but are expected to reach a canopy cover of 10 percent and a tree height of 5 meters are included, as are temporarily unstocked areas, resulting from human intervention or natural causes, which are expected to regenerate.

The Food and Agriculture Organization (FAO) provides detail information on forest cover, and adjusted estimates of forest cover. The survey uses a uniform definition of forest. Although FAO provides a breakdown of forest cover between natural forest and plantation for developing countries, forest data used to derive this indictor data does not reflect that breakdown. Total land area does not include inland water bodies such as major rivers and lakes. Variations from year to year may be due to updated or revised data rather than to change in area. The indictor is derived by dividing total area under forest of a country by country's total land area, and multiplying by 100.

Unitofmeasure: % of total


IndicatorName: Total protests and riots by event type since 2018

Longdefinition: Total protests and riots reflects the aggregate of  taken from ACLED. ACLED collects real-time data on the locations, dates, actors, fatalities, and types of all reported political violence and protest events across Africa, the Middle East, Latin America & the Caribbean, East Asia, South Asia, Southeast Asia, Central Asia & the Caucasus, Europe, and the United States of America.

Source: Armed Conflict Location & Event Data Project (ACLED). Available at: https://acleddata.com/#/dashboard

Topic: Managing the transition

Unitofmeasure: Number


IndicatorName: Additional population exposed to annual coastal floods due to sea level rise, as a share of actual population (%) - Min. exposure, 2100

Longdefinition: Additional population exposed to annual coastal floods due to sea level rise, as a share of actual population, is reported as a percentage and is reflective of the population in the year 2100, determined by the minimum exposure scenario (RCP26)

Source: Kulp, S.A., Strauss, B.H. New elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding. Nat Commun 10, 4844 (2019). https://doi.org/10.1038/s41467-019-12808-z


IndicatorName: Additional population exposed to annual coastal floods due to sea level rise, as a share of actual population (%) - Max exposure, 2100

Longdefinition: Additional population exposed to annual coastal floods due to sea level rise, as a share of actual population, is reported as a percentage and is reflective of the population in the year 2100, determined by the maximum exposure scenario (RCP85)


IndicatorName: Additional population exposed to annual coastal floods due to sea level rise, as a share of actual population (%) - Min. exposure, 2050

Longdefinition: Additional population exposed to annual coastal floods due to sea level rise, as a share of actual population, is reported as a percentage and is reflective of the population in the year 2050, determined by the minimum exposure scenario (RCP26)


IndicatorName: Additional population exposed to annual coastal floods due to sea level rise, as a share of actual population (%) - Max exposure, 2050

Longdefinition: Additional population exposed to annual coastal floods due to sea level rise, as a share of actual population, is reported as a percentage and is reflective of the population in the year 2050, determined by the maximum exposure scenario (RCP85)


IndicatorName: Nitrogen application (tons per ha)

Longdefinition: Data generated by taking Nutrient Nitrogen N (tonnes) [Fertilizers by Nutrient sheet] and dividing it by Area Harvested (ha) [Crops and Livestock Products sheet] from FAOSTAT. FAOSTAT data 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.

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

Unitofmeasure: tons per ha


IndicatorName: Additional people below $1.90 as % of total population by impact - All impacts

Longdefinition: Additional people below $1.90 as % of total population for all impacts, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.

Source: Hallegatte, Stephane; Bangalore, Mook; Bonzanigo, Laura; Fay, Marianne; Kane, Tamaro; Narloch, Ulf; Rozenberg, Julie; Treguer, David; Vogt-Schilb, Adrien. 2016. Shock Waves : Managing the Impacts of Climate Change on Poverty. Climate Change and Development;. Washington, DC: World Bank. © World Bank. https://openknowledge.worldbank.org/handle/10986/22787 License: CC BY 3.0 IGO.

Topic: Country profile

Unitofmeasure: % of total population


IndicatorName: Additional people below $1.90 as % of total population by impact - Agriculture Revenues

Longdefinition: Additional people below $1.90 as % of total population by impact, from climate change impacts relating to Agriculture Revenues, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $1.90 as % of total population by impact - Disasters

Longdefinition: Additional people below $1.90 as % of total population by impact, from climate change impacts relating to Disasters, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $1.90 as % of total population by impact - Food prices

Longdefinition: Additional people below $1.90 as % of total population by impact, from climate change impacts relating to Food Prices, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $1.90 as % of total population by impact - Health

Longdefinition: Additional people below $1.90 as % of total population by impact, from climate change impacts relating to Health, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $1.90 as % of total population by impact - Labor productivity

Longdefinition: Additional people below $1.90 as % of total population by impact, from climate change impacts relating to Labor Productivity, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $4 as % of total population by impact, by 2030 - Agriculture

Longdefinition: Additional people below $4 as % of total population by impact, by 2030, from climate change impacts relating to Agriculture, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $4 as % of total population by impact, by 2030 - All Impacts

Longdefinition: Additional people below $4 as % of total population by impact, by 2030, from all impacts, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $4 as % of total population by impact, by 2030 - Disasters

Longdefinition: Additional people below $4 as % of total population by impact, by 2030, from climate change impacts relating to Disasters, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $4 as % of total population by impact, by 2030 - Health

Longdefinition: Additional people below $4 as % of total population by impact, by 2030, from climate change impacts relating to Health, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Additional people below $4 as % of total population by impact, by 2030 - Temperature

Longdefinition: Additional people below $4 as % of total population by impact, by 2030, from climate change impacts relating to Temperature, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Change in income (%) for bottom 40% of the population by impact, by 2030 - Agriculture

Longdefinition: Change in income (%) for bottom 40% of the population by impact, by 2030, from climate change impacts relating to Agriculture, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Change in income (%) for bottom 40% of the population by impact, by 2030 - All Impacts

Longdefinition: Change in income (%) for bottom 40% of the population for all impacts impact, by 2030, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Change in income (%) for bottom 40% of the population by impact, by 2030 - Disasters

Longdefinition: Change in income (%) for bottom 40% of the population by impact, by 2030, from climate change impacts relating to Disasters, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Change in income (%) for bottom 40% of the population by impact, by 2030 - Health

Longdefinition: Change in income (%) for bottom 40% of the population by impact, by 2030, from climate change impacts relating to Health, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Change in income (%) for bottom 40% of the population by impact, by 2030 - Temperature

Longdefinition: Change in income (%) for bottom 40% of the population by impact, by 2030, from climate change impacts relating to Temperature, is generated from data within Shock Waves : Managing the Impacts of Climate Change on Poverty. This report examines the potential impact of climate change and climate policies on poverty reduction. It also provides guidance on how to create a “win-win” situation so that climate change policies contribute to poverty reduction and poverty-reduction policies contribute to climate change mitigation and resilience building. The key finding of the report is that climate change represents a significant obstacle to the sustained eradication of poverty, but future impacts on poverty are determined by policy choices: rapid, inclusive, and climate-informed development can prevent most short-term impacts whereas immediate pro-poor, emissions-reduction policies can drastically limit long-term ones.


IndicatorName: Change in income (%) for bottom 40% of the population by impact - Agriculture Revenues


IndicatorName: Change in income (%) for bottom 40% of the population by impact - All impacts


IndicatorName: Change in income (%) for bottom 40% of the population by impact - Disasters


IndicatorName: Change in income (%) for bottom 40% of the population by impact - Food prices


IndicatorName: Change in income (%) for bottom 40% of the population by impact - Health


IndicatorName: Change in income (%) for bottom 40% of the population by impact - Labor productivity


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Bunker Fuels

Longdefinition: Bunker fuels sector 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.

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

Unitofmeasure: Mt CO2 eq


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Building

Longdefinition: Building sector 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.


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Electricity/Heat

Longdefinition: Electricity and heat sector 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.


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

Longdefinition: Total 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.


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Energy

Longdefinition: Energy sector 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.


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Fugitive Emissions

Longdefinition: Fugitive sector 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.


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

Longdefinition: Total 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.


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Industrial Processes

Longdefinition: Industrial Processes sector 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.


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Land-Use Change and Forestry

Longdefinition: Land-Use Change and Forestry sector 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.


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Manufacturing/Construction

Longdefinition: Manufacturing and construction sector 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.


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Other Fuel Combustion

Longdefinition: Other fuel combustion sector 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.


IndicatorName: CO2 emissions by sector (Mt CO2 eq) - Transportation

Longdefinition: Transportation sector 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.


IndicatorName: Operating coal mining GHG emissions (Mt CO2eq) - Methane

Longdefinition: Methane emissions from operating coal mining (Mt CO2eq) is generated from the Global Coal Mine Tracker (GCMT). The GCMT provides information on the world’s major coal mines: every operating mine producing 3 million tonnes per annum (mtpa) or greater, and every proposed mine with a capacity of 1 mtpa or greater. The map and underlying data are updated bi-annually, in January and July. With each update, coverage is expanded to include smaller mines. By January 2022, GCMT will have cataloged every coal mine producing 1 mtpa or greater. Each mine included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GCMT was accessed in July 2021 to generate this data.

Source: Global Coal Mine Tracker, Global Energy Monitor. Available at: https://globalenergymonitor.org/projects/global-coal-mine-tracker/


IndicatorName: Operating coal mining GHG emissions (Mt CO2eq) - CO2

Longdefinition: CO2 emissions from operating coal mining (Mt CO2eq) is generated from the Global Coal Mine Tracker (GCMT). The GCMT provides information on the world’s major coal mines: every operating mine producing 3 million tonnes per annum (mtpa) or greater, and every proposed mine with a capacity of 1 mtpa or greater. The map and underlying data are updated bi-annually, in January and July. With each update, coverage is expanded to include smaller mines. By January 2022, GCMT will have cataloged every coal mine producing 1 mtpa or greater. Each mine included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GCMT was accessed in July 2021 to generate this data.


IndicatorName: Proposed coal mining GHG emissions (Mt CO2eq) - Methane

Longdefinition: Methane emissions from proposed coal mining (Mt CO2eq) is generated from the Global Coal Mine Tracker (GCMT). The GCMT provides information on the world’s major coal mines: every operating mine producing 3 million tonnes per annum (mtpa) or greater, and every proposed mine with a capacity of 1 mtpa or greater. The map and underlying data are updated bi-annually, in January and July. With each update, coverage is expanded to include smaller mines. By January 2022, GCMT will have cataloged every coal mine producing 1 mtpa or greater. Each mine included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GCMT was accessed in July 2021 to generate this data.


IndicatorName: Proposed coal mining GHG emissions (Mt CO2eq) - CO2

Longdefinition: CO2 emissions from proposed coal mining (Mt CO2eq) is generated from the Global Coal Mine Tracker (GCMT). The GCMT provides information on the world’s major coal mines: every operating mine producing 3 million tonnes per annum (mtpa) or greater, and every proposed mine with a capacity of 1 mtpa or greater. The map and underlying data are updated bi-annually, in January and July. With each update, coverage is expanded to include smaller mines. By January 2022, GCMT will have cataloged every coal mine producing 1 mtpa or greater. Each mine included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GCMT was accessed in July 2021 to generate this data.


IndicatorName: Annual coal production (Mt per year) - Operating

Longdefinition: Annual coal production (Mt per year) 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.

Unitofmeasure: Mt per year


IndicatorName: Annual coal production (Mt per year) - Proposed Projects (Total)


IndicatorName: Children under 5 years of age who are stunted (% of total)

Longdefinition: Children under 5 years of age who are stunted reflects modelled estimate 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.


IndicatorName: Emission Totals - Direct emissions (N2O) - AFOLU

License_Type: CC BY-3.0

Longdefinition:
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).

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

Unitofmeasure: kilotonnes


IndicatorName: Emission Totals - Direct emissions (N2O) - Agricultural Soils


IndicatorName: Emission Totals - Direct emissions (N2O) - Crop Residues


IndicatorName: Emission Totals - Direct emissions (N2O) - Emissions on agricultural land


IndicatorName: Emission Totals - Direct emissions (N2O) - Farm-gate emissions


IndicatorName: Emission Totals - Direct emissions (N2O) - IPCC Agriculture


IndicatorName: Emission Totals - Direct emissions (N2O) - Manure left on Pasture


IndicatorName: Emission Totals - Direct emissions (N2O) - Manure applied to Soils


IndicatorName: Emission Totals - Direct emissions (N2O) - Synthetic Fertilizers


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - AFOLU


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Agricultural Soils


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Burning - Crop residues


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Crop Residues


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Drained organic soils (CO2)


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Drained organic soils (N2O)


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Drained organic soils


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Emissions on agricultural land


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Enteric Fermentation


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Forest fires


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Farm-gate emissions


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Forestland


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Fires in organic soils


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Fires in humid tropical forests


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - IPCC Agriculture


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Land Use change


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - LULUCF


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Manure left on Pasture


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Manure Management


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Net Forest conversion


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - On-farm energy use


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Rice Cultivation


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Manure applied to Soils


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Synthetic Fertilizers


IndicatorName: Emission Totals - Emissions (CO2eq) (AR5) - Savanna fires


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - AFOLU


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Burning - Crop residues


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Emissions on agricultural land


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Enteric Fermentation


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Forest fires


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Farm-gate emissions


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Fires in organic soils


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Fires in humid tropical forests


IndicatorName: Capacity of Liquefied Natural Gas export terminals (Mt per year) - Cancelled

Longdefinition: LNG terminal 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.


IndicatorName: Capacity of Liquefied Natural Gas export terminals (Mt per year) - In Development (Proposed + Construction)


IndicatorName: Capacity of Liquefied Natural Gas export terminals (Mt per year) - Operating


IndicatorName: Capacity of Liquefied Natural Gas export terminals (Mt per year) - Shelved


IndicatorName: Capacity of Liquefied Natural Gas import terminals (Mt per year) - Cancelled


IndicatorName: Capacity of Liquefied Natural Gas import terminals (Mt per year) - In Development (Proposed + Construction)


IndicatorName: Capacity of Liquefied Natural Gas import terminals (Mt per year) - Operating


IndicatorName: Capacity of Liquefied Natural Gas import terminals (Mt per year) - Shelved


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - IPCC Agriculture


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Land Use change


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - LULUCF


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Manure Management


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - On-farm energy use


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Rice Cultivation


IndicatorName: Emission Totals - Emissions (CO2eq) from CH4 (AR5) - Savanna fires


IndicatorName: Emission Totals - Emissions (CH4) - AFOLU


IndicatorName: Emission Totals - Emissions (CH4) - Burning - Crop residues


IndicatorName: Emission Totals - Emissions (CH4) - Emissions on agricultural land


IndicatorName: Emission Totals - Emissions (CH4) - Enteric Fermentation


IndicatorName: Emission Totals - Emissions (CH4) - Forest fires


IndicatorName: Emission Totals - Emissions (CH4) - Farm-gate emissions


IndicatorName: Emission Totals - Emissions (CH4) - Fires in organic soils


IndicatorName: Emission Totals - Emissions (CH4) - Fires in humid tropical forests


IndicatorName: Emission Totals - Emissions (CH4) - IPCC Agriculture


IndicatorName: Emission Totals - Emissions (CH4) - Land Use change


IndicatorName: Emission Totals - Emissions (CH4) - LULUCF


IndicatorName: Emission Totals - Emissions (CH4) - Manure Management


IndicatorName: Emission Totals - Emissions (CH4) - On-farm energy use


IndicatorName: Emission Totals - Emissions (CH4) - Rice Cultivation


IndicatorName: Emission Totals - Emissions (CH4) - Savanna fires


IndicatorName: Emission Totals - Emissions (CO2) - AFOLU


IndicatorName: Emission Totals - Emissions (CO2) - Drained organic soils (CO2)


IndicatorName: Emission Totals - Emissions (CO2) - Emissions on agricultural land


IndicatorName: Emission Totals - Emissions (CO2) - Farm-gate emissions


IndicatorName: Emission Totals - Emissions (CO2) - Forestland


IndicatorName: Emission Totals - Emissions (CO2) - Fires in organic soils


IndicatorName: Emission Totals - Emissions (CO2) - Land Use change


IndicatorName: Emission Totals - Emissions (CO2) - LULUCF


IndicatorName: Emission Totals - Emissions (CO2) - Net Forest conversion


IndicatorName: Emission Totals - Emissions (CO2) - On-farm energy use


IndicatorName: Per capita daily coal consumption (barrels per capita per day)

Longdefinition: Per capita data has been generated by World Bank staff by taking Energy consumption data [U.S EIA] and applying country population data from the World Bank Group - World Development Indicators.

Source: U.S Energy Information Administration. Available at: https://www.eia.gov/opendata/

Unitofmeasure: barrels per capita per day


IndicatorName: Per capita daily gas consumption (barrels per capita per day)


IndicatorName: Per capita daily oil consumption (barrels per capita per day)


IndicatorName: CO2 emissions per dollar of manufacturing value added (kgCO2 per constant 2010 US$)

Longdefinition: This indicator presents CO2 emissions that can be attributed to each dollar generated from manufacturing value add. Data is taken from the United Nations Sustainable Goals, representing Indicator 9.4.1: Carbon dioxide emissions per unit of manufacturing value added (kilogrammes of CO2 per constant 2015 United States dollars).

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

Unitofmeasure: kgCO2 per constant 2010 US$


IndicatorName: Energy intensity of the economy (kWh per 2011$PPP)

Longdefinition: Energy intensity is measured as primary energy consumption per unit of gross domestic product. This is measured in kilowatt-hours per 2011$ (PPP).

Source: Our World in Data based on BP; World Bank; and Maddison Project Database

Unitofmeasure: kWh per 2011$PPP


IndicatorName: Average practical solar potential (kWh/kWp/day)

Longdefinition: Solar potential reflects analysis based on high-resolution datasets and GIS mask layers by Solargis's (https://solargis.com/) . These indicators have been generated as part of the Energy Sector Management Assistance Program [ESMAP]. Further information is available at: https://www.esmap.org/. Visualization of the data can be found at: https://globalsolaratlas.info/map.

Source: Global Photovoltaic Power Potential By Country, generated by Solaris, with ESMAP and World Bank Group contributions. Available at: https://datacatalog.worldbank.org/int/search/dataset/0038379

Unitofmeasure: kWh/kWp/day


IndicatorName: Total steelmaking capacity (thousand tonnes per annum)

Longdefinition: Steel making capacity is generated from the Global Steel Plant Tracker (GSPT). The GSPT provides information on global crude steel production plants, and includes information on every plant currently operating at a capacity of one million tonnes per year (mtpa) or more of crude steel. The GSPT is currently being expanded to include all plants meeting the one mtpa threshold that have been proposed since 2017 or retired or mothballed since 2020. Steel plants consist of multiple units, depending on the iron and steel production method used. Crude steel is typically produced through coal-based methods (blast furnace and basic oxygen furnace or open hearth furnace) or electricity-based production (electric arc furnace charged with scrap metal, pig iron, direct reduced iron, or a combination). The GSPT map and underlying data are updated annually in January. Each plant included in the tracker is linked to a wiki page on GEM.wiki, which provides additional details. GSPT was accessed in July 2021 to generate this data.

Source: Global Steel Plant Tracker, Global Energy Monitor. Available at: https://globalenergymonitor.org/projects/global-steel-plant-tracker/

Unitofmeasure: thousand tonnes per annum


IndicatorName: Fossil-fuel pre-tax subsidies (consumption and production) USD per capita

Longdefinition: This indicator presents the pre-tax subsidies (consumption and production) on fossil fuels as an index of USD per capita. Data is taken from the United Nations Sustainable Goals, representing Indicator 12.c.1: Fossil-fuel subsidies (consumption and production) per capita (constant United States dollars).

Unitofmeasure: USD per capita


IndicatorName: Offshore wind potential - Per capita (kW/cap)

Longdefinition: The offshore wind technical potential is an estimate of the amount of generation capacity that could be technically feasible, considering only wind speed and water depth. This is intended as an initial, high-level estimate and does not look at other technical, environmental, social, or economic constraints. These indicators have been generated as part of the Energy Sector Management Assistance Program [ESMAP]. Further information is available at: https://www.esmap.org/. Visualization of the data can be found at: https://globalwindatlas.info/

Source: Global Offshore Wind Technical Potential, the World Bank Group. Available at: https://datacatalog.worldbank.org/int/search/dataset/0037787/Global-Offshore-Wind-Technical-Potential

Unitofmeasure: kW/cap


IndicatorName: Offshore wind potential - Total (GW)

Unitofmeasure: GW


IndicatorName: Electricity net consumption

Longdefinition: Total electric power consumption = total net electricity generation + electricity imports - electricity exports - electricity transmission and distribution losses. Data are reported as net consumption, not gross consumption. Net consumption excludes the energy consumed by the generating units.

Unitofmeasure: Billion kWh


IndicatorName: Electricity net generation

Longdefinition: Generation data consist of both utility and non-utility sources from electricity and combined heat and power plants. Data are reported as net generation, not gross generation. The difference between gross and net generation is generally about 6% for fossil fuels stations, 1% for hydro stations, and 5% for all others. Fossil Fuels electricity generation consists of electricity generated from coal, petroleum, and natural gas. Solar electricity generation includes solar photovoltaic and solar thermal generation, and distributed solar generation where available. The term biomass and waste used here is similar to the term combustible renewables and waste. Electricity net generation excludes the energy consumed by the generating units and generation from hydroelectric pumped storage. Generation from hydroelectric pumped storage plants is included in total generation.


Longdefinition: Lifetime CO2 emissions from coal plants (Mt CO2) 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.

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

Unitofmeasure: Mt CO2


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - AFOLU


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Agricultural Soils


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Burning - Crop residues


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Crop Residues


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Drained organic soils (N2O)


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Emissions on agricultural land


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Forest fires


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Farm-gate emissions


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Fires in humid tropical forests


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - IPCC Agriculture


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Land Use change


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - LULUCF


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Manure left on Pasture


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Manure Management


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - On-farm energy use


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Manure applied to Soils


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Synthetic Fertilizers


IndicatorName: Emission Totals - Emissions (CO2eq) from N2O (AR5) - Savanna fires


IndicatorName: Emission Totals - Emissions (N2O) - AFOLU


IndicatorName: Emission Totals - Emissions (N2O) - Agricultural Soils


IndicatorName: Emission Totals - Emissions (N2O) - Burning - Crop residues


IndicatorName: Emission Totals - Emissions (N2O) - Crop Residues


IndicatorName: Emission Totals - Emissions (N2O) - Drained organic soils (N2O)


IndicatorName: Emission Totals - Emissions (N2O) - Emissions on agricultural land


IndicatorName: Emission Totals - Emissions (N2O) - Forest fires


IndicatorName: Emission Totals - Emissions (N2O) - Farm-gate emissions


IndicatorName: Emission Totals - Emissions (N2O) - Fires in humid tropical forests


IndicatorName: Emission Totals - Emissions (N2O) - IPCC Agriculture


IndicatorName: Emission Totals - Emissions (N2O) - Land Use change


IndicatorName: Emission Totals - Emissions (N2O) - LULUCF


IndicatorName: Emission Totals - Emissions (N2O) - Manure left on Pasture


IndicatorName: Emission Totals - Emissions (N2O) - Manure Management


IndicatorName: Emission Totals - Emissions (N2O) - On-farm energy use


IndicatorName: Emission Totals - Emissions (N2O) - Manure applied to Soils


IndicatorName: Emission Totals - Emissions (N2O) - Synthetic Fertilizers


IndicatorName: Emission Totals - Emissions (N2O) - Savanna fires


IndicatorName: Total energy tax revenue (% of GDP)

Longdefinition: Revenues from taxes raised on energy products (fossil fuels and electricity) including those used in transportation (petrol and diesel). This includes all CO2-related taxes.

Source: Policy Instrument for the Environment Data Base, OECD. Available at: https://www.oecd.org/env/indicators-modelling-outlooks/policy-instrument-database/

Unitofmeasure: % of GDP


IndicatorName: Total environmental tax revenue (% of GDP)

Longdefinition: Total environmentally related tax revenue includes the revenue generated by energy, transport, pollution and resources tax bases.


IndicatorName: Comparative advantage in environmental goods (index)

Longdefinition:
Environmental goods include both goods connected to environmental protection—such as goods related to pollution management and resource management—and adapted goods—which are goods that have been specifically modified to be more “environmentally friendly” or “cleaner.”

Comparative advantage is a measure of the relative advantage or disadvantage a particular country has in a certain class of goods (in this case, environmental goods), and can be used to evaluate export potential in that class of goods. Environmental goods include both goods connected to environmental protection—such as goods related to pollution management and resource management—and adapted goods—which are goods that have been specifically modified to be more “environmentally friendly” or “cleaner.” A value greater than one indicates a relative advantage in environmental goods, while a value of less than one indicates a relative disadvantage.

Source: IMF Climate Change Dashboard. Data sources: UN Comtrade, DESA/UNSD; IMF staff calculations.

Unitofmeasure: Index


IndicatorName: Trade in environmental goods as share of total exports

Longdefinition:
Environmental goods include both goods connected to environmental protection—such as goods related to pollution management and resource management—and adapted goods—which are goods that have been specifically modified to be more “environmentally friendly” or “cleaner.”

A relatively high share of environmental goods imports indicates that a country purchases a significant share of environmental goods from other countries. A relatively high share of environmental goods exports indicates that a country produces and sells a significant share of environmental goods to other countries. A country’s environmental goods trade balance is the difference between its exports and imports of environmental goods.

Unitofmeasure: % of total exports


IndicatorName: Trade in environmental goods as share of total imports

Unitofmeasure: % of total imports


IndicatorName: Employment by sector and gender (% of total) - Agriculture - Female

Longdefinition: Employment of Females within Agriculture 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.

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

Unitofmeasure: % of total


IndicatorName: Employment by sector and gender (% of total) - Agriculture - Male

Longdefinition: Employment of Males within Agriculture 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.


IndicatorName: Employment by sector and gender (% of total) - Commerce - Female

Longdefinition: Employment of Females within Commerce 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.


IndicatorName: Employment by sector and gender (% of total) - Commerce - Male

Longdefinition: Employment of Males within Commerce 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.


IndicatorName: Employment by sector and gender (% of total) - Construction - Female

Longdefinition: Employment of Females within Construction 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.


IndicatorName: Employment by sector and gender (% of total) - Construction - Male

Longdefinition: Employment of Males within Construction 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.


IndicatorName: Employment by sector and gender (% of total) - Electricity and utilities - Female

Longdefinition: Employment of Females within Electricity and Utilities 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.


IndicatorName: Employment by sector and gender (% of total) - Electricity and utilities - Male

Longdefinition: Employment of Males within Electricity and Utilities 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.


IndicatorName: Employment by sector and gender (% of total) - Financial and Business Services - Female

Longdefinition: Employment of Females within Financial and Business 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.


IndicatorName: Employment by sector and gender (% of total) - Financial and Business Services - Male

Longdefinition: Employment of Males within Financial and Business 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.


IndicatorName: Employment by sector and gender (% of total) - Industry - Female

Longdefinition: Employment of Females within Industry 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.


IndicatorName: Employment by sector and gender (% of total) - Industry - Male

Longdefinition: Employment of Males within Industry 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.


IndicatorName: Employment by sector and gender (% of total) - Manufacturing - Female

Longdefinition: Employment of Females within Manufacturing 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.


IndicatorName: Employment by sector and gender (% of total) - Manufacturing - Male

Longdefinition: Employment of Males within Manufacturing 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.


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

Longdefinition: 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.


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

Longdefinition: 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.


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

Longdefinition: 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.


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

Longdefinition: 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.


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

Longdefinition: 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.


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

Longdefinition: 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.


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

Longdefinition: 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.


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

Longdefinition: 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.


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

Longdefinition: 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.