Developmentrelevance: Industrial development generally entails a structural transition from resource-based and low technology activities to medium and high-tech industry (MHT) activities. A modern, highly complex production structure offers better opportunities for skills development and technological innovation. MHT activities are also the high value addition industries of manufacturing with higher technological intensity and labour productivity. Increasing the share of MHT sectors also reflects the impact of innovation

IndicatorName: Medium and high-tech manufacturing value added (% manufacturing value added)

Limitationsandexceptions: Value added by economic activity should be reported at least at 3-digit ISIC for compiling MHT values. Missing values at country level are imputed based on the methodology from Competitive Industrial Performance Report (UNIDO, 2017. Conversion to USD or difference in ISIC combinations may cause discrepancy between national and international figures. For additional information please see UNIDO (2017): http://stat.unido.org/content/publications/volume-i%252c-competitive-industrial-performance-report-2016

Longdefinition: The proportion of medium and high-tech industry value added in total value added of manufacturing

Source: United Nations Industrial Development Organization (UNIDO), Competitive Industrial Performance (CIP) database

Statisticalconceptandmethodology: The indicator is calculated as the share of the sum of the value added from medium and high-tech industry economic activities to manufacturing value added. The medium and high-tech industry is defined using OECD classification as the following by International Standard Industrial Classification of All Economic Activities (ISIC) Revision 3 and Revision 4 Division respectively: ISIC Rev. 3 (24, 29, 30, 31, 32, 33, 34, 35 excluding 351). Manufacturing value added is the value added of manufacturing industry, which is Section C of ISIC Rev.4, and Section D of ISIC Rev.3.  Data can be found in UNIDO INDSTAT4 Database by ISIC Revision 3 and ISIC Revision 4 respectively. Data are collected using General Industrial Statistics Questionnaire which is filled by NSOs and submitted to UNIDO annually. Data for OECD countries are obtained directly from OECD. Country data are also collected from official publications and official web-sites. For additional information please see Table B.2.2 in Appendix B of UNIDO (2017): http://stat.unido.org/content/publications/volume-i%252c-competitive-industrial-performance-report-2016


Aggregationmethod: Weighted average

Developmentrelevance: Labor productivity is used to assess a country's economic ability to create and sustain decent employment opportunities with fair and equitable remuneration. Productivity increases obtained through investment, trade, technological progress, or changes in work organization can increase social protection and reduce poverty, which in turn reduce vulnerable employment and working poverty. Productivity increases do not guarantee these improvements, but without them—and the economic growth they bring—improvements are highly unlikely. Please also see GDP per person employed (constant 2011 PPP $) [SL.GDP.PCAP.EM.KD], which is a key measure for monitoring the Sustainable Development Goal 8 of promoting sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all.

IndicatorName: Services, value added per worker (constant 2015 US$)

License_Type: CC BY-4.0

Limitationsandexceptions: For comparability of individual sectors labor productivity is estimated according to national accounts conventions. However, there are still significant limitations on the availability of reliable data. Information on consistent series of output is not easily available, especially in low- and middle-income countries, because the definition, coverage, and methodology are not always consistent across countries. For more details, see Agriculture, forestry, and fishing, value added (constant 2015 US$) [NV.AGR.TOTL.KD], Industry (including construction), value added (constant 2015 US$) [NV.IND.TOTL.KD], and Services, value added (constant 2015 US$) [NV.SRV.TOTL.KD].

Longdefinition: Value added per worker is a measure of labor productivity—value added per unit of input. Value added denotes the net output of a sector after adding up all outputs and subtracting intermediate inputs. Data are in constant 2015 U.S. dollars. Services corresponds to the International Standard Industrial Classification (ISIC) tabulation categories G-P (revision 3) or tabulation categories G-U (revision 4), and includes wholesale and retail trade and restaurants and hotels; transport, storage, and communications; financing, insurance, real estate, and business services; and community, social and personal services.

Othernotes: Caution should be used for aggregates (population-weighted averages); world totals can be presented without a large economy such as USA.

Periodicity: Annual

Source: Derived using World Bank national accounts data and OECD National Accounts data files, and employment data from International Labour Organization, ILOSTAT database.

Statisticalconceptandmethodology:
Value added per worker is calculated by dividing value added of a sector by the number employed in the sector.
Gross domestic product (GDP) represents the sum of value added by all producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Value added by industry is normally measured at basic prices, while total GDP is measured at purchaser prices.
Data on employment are modeled estimates by the International Labour Organization (ILO) ILOSTAT database. The concept of employment generally refers to people above a certain age who worked, or who held a job, during a reference period. Employment data include both full-time and part-time workers.

Topic: Economic Policy & Debt: National accounts: US$ at constant 2015 prices: Value added


IndicatorName: Adjusted net savings, excluding particulate emission damage (% of GNI)

Longdefinition: Adjusted net savings are equal to net national savings plus education expenditure and minus energy depletion, mineral depletion, net forest depletion, and carbon dioxide. This series excludes particulate emissions damage.

Source: World Bank staff estimates based on sources and methods in World Bank's "The Changing Wealth of Nations: Measuring Sustainable Development in the New Millennium" (2011).

Topic: Economic Policy & Debt: National accounts: Adjusted savings & income


Developmentrelevance:
Accounting for the contribution of natural resources to economic output is important in building an analytical framework for sustainable development. In some countries earnings from natural resources, especially from fossil fuels and minerals, account for a sizable share of GDP, and much of these earnings come in the form of economic rents - revenues above the cost of extracting the resources.

Natural resources give rise to economic rents because they are not produced. For produced goods and services competitive forces expand supply until economic profits are driven to zero, but natural resources in fixed supply often command returns well in excess of their cost of production. Rents from nonrenewable resources - fossil fuels and minerals - as well as rents from overharvesting of forests indicate the liquidation of a country's capital stock. When countries use such rents to support current consumption rather than to invest in new capital to replace what is being used up, they are, in effect, borrowing against their future.

IndicatorName: Coal rents (% of GDP)

Longdefinition: Coal rents are the difference between the value of both hard and soft coal production at world prices and their total costs of production.

Source: World Bank staff estimates based on sources and methods described in the World Bank's The Changing Wealth of Nations.

Statisticalconceptandmethodology: The estimates of natural resources rents are calculated as the difference between the price of a commodity and the average cost of producing it. This is done by estimating the price of units of specific commodities and subtracting estimates of average unit costs of extraction or harvesting costs. These unit rents are then multiplied by the physical quantities countries extract or harvest to determine the rents for each commodity as a share of gross domestic product (GDP).

Topic: Environment: Natural resources contribution to GDP


IndicatorName: Forest rents (% of GDP)

Longdefinition: Forest rents are roundwood harvest times the product of regional prices and a regional rental rate.


IndicatorName: Mineral rents (% of GDP)

Longdefinition: Mineral rents are the difference between the value of production for a stock of minerals at world prices and their total costs of production. Minerals included in the calculation are tin, gold, lead, zinc, iron, copper, nickel, silver, bauxite, and phosphate.


Aggregationmethod: Gap-filled total

IndicatorName: GDP (current US$)

Limitationsandexceptions:
Gross domestic product (GDP), though widely tracked, may not always be the most relevant summary of aggregated economic performance for all economies, especially when production occurs at the expense of consuming capital stock.

While GDP estimates based on the production approach are generally more reliable than estimates compiled from the income or expenditure side, different countries use different definitions, methods, and reporting standards. World Bank staff review the quality of national accounts data and sometimes make adjustments to improve consistency with international guidelines. Nevertheless, significant discrepancies remain between international standards and actual practice. Many statistical offices, especially those in developing countries, face severe limitations in the resources, time, training, and budgets required to produce reliable and comprehensive series of national accounts statistics.

Among the difficulties faced by compilers of national accounts is the extent of unreported economic activity in the informal or secondary economy. In developing countries a large share of agricultural output is either not exchanged (because it is consumed within the household) or not exchanged for money.

Longdefinition: GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars. Dollar figures for GDP are converted from domestic currencies using single year official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used.

Source: World Bank national accounts data, and OECD National Accounts data files.

Statisticalconceptandmethodology: Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices.

Topic: Economic Policy & Debt: National accounts: US$ at current prices: Aggregate indicators


IndicatorName: GDP (current LCU)

Longdefinition: GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current local currency.

Topic: Economic Policy & Debt: National accounts: Local currency at current prices: Aggregate indicators


Developmentrelevance: An economy's growth is measured by the change in the volume of its output or in the real incomes of its residents. The 2008 United Nations System of National Accounts (2008 SNA) offers three plausible indicators for calculating growth: the volume of gross domestic product (GDP), real gross domestic income, and real gross national income. The volume of GDP is the sum of value added, measured at constant prices, by households, government, and industries operating in the economy. GDP accounts for all domestic production, regardless of whether the income accrues to domestic or foreign institutions.

IndicatorName: GDP (constant 2015 US$)

Limitationsandexceptions:
Each industry's contribution to growth in the economy's output is measured by growth in the industry's value added. In principle, value added in constant prices can be estimated by measuring the quantity of goods and services produced in a period, valuing them at an agreed set of base year prices, and subtracting the cost of intermediate inputs, also in constant prices. This double-deflation method requires detailed information on the structure of prices of inputs and outputs.

In many industries, however, value added is extrapolated from the base year using single volume indexes of outputs or, less commonly, inputs. Particularly in the services industries, including most of government, value added in constant prices is often imputed from labor inputs, such as real wages or number of employees. In the absence of well defined measures of output, measuring the growth of services remains difficult.

Moreover, technical progress can lead to improvements in production processes and in the quality of goods and services that, if not properly accounted for, can distort measures of value added and thus of growth. When inputs are used to estimate output, as for nonmarket services, unmeasured technical progress leads to underestimates of the volume of output. Similarly, unmeasured improvements in quality lead to underestimates of the value of output and value added. The result can be underestimates of growth and productivity improvement and overestimates of inflation.

Informal economic activities pose a particular measurement problem, especially in developing countries, where much economic activity is unrecorded. A complete picture of the economy requires estimating household outputs produced for home use, sales in informal markets, barter exchanges, and illicit or deliberately unreported activities. The consistency and completeness of such estimates depend on the skill and methods of the compiling statisticians.

Rebasing of national accounts can alter the measured growth rate of an economy and lead to breaks in series that affect the consistency of data over time. When countries rebase their national accounts, they update the weights assigned to various components to better reflect current patterns of production or uses of output. The new base year should represent normal operation of the economy - it should be a year without major shocks or distortions. Some developing countries have not rebased their national accounts for many years. Using an old base year can be misleading because implicit price and volume weights become progressively less relevant and useful.

To obtain comparable series of constant price data for computing aggregates, the World Bank rescales GDP and value added by industrial origin to a common reference year. Because rescaling changes the implicit weights used in forming regional and income group aggregates, aggregate growth rates are not comparable with those from earlier editions with different base years. Rescaling may result in a discrepancy between the rescaled GDP and the sum of the rescaled components. To avoid distortions in the growth rates, the discrepancy is left unallocated. As a result, the weighted average of the growth rates of the components generally does not equal the GDP growth rate.

Longdefinition: GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2015 prices, expressed in U.S. dollars. Dollar figures for GDP are converted from domestic currencies using 2015 official exchange rates. For a few countries where the official exchange rate does not reflect the rate effectively applied to actual foreign exchange transactions, an alternative conversion factor is used.

Statisticalconceptandmethodology:
Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices. When value added is measured at producer prices.

Growth rates of GDP and its components are calculated using the least squares method and constant price data in the local currency. Constant price U.S. dollar series are used to calculate regional and income group growth rates. Local currency series are converted to constant U.S. dollars using an exchange rate in the common reference year.

Topic: Economic Policy & Debt: National accounts: US$ at constant 2015 prices: Aggregate indicators


IndicatorName: GDP growth (annual %)

Longdefinition: Annual percentage growth rate of GDP at market prices based on constant local currency. Aggregates are based on constant 2015 prices, expressed in U.S. dollars. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.

Statisticalconceptandmethodology:
Gross domestic product (GDP) represents the sum of value added by all its producers. Value added is the value of the gross output of producers less the value of intermediate goods and services consumed in production, before accounting for consumption of fixed capital in production. The United Nations System of National Accounts calls for value added to be valued at either basic prices (excluding net taxes on products) or producer prices (including net taxes on products paid by producers but excluding sales or value added taxes). Both valuations exclude transport charges that are invoiced separately by producers. Total GDP is measured at purchaser prices. Value added by industry is normally measured at basic prices. When value added is measured at producer prices.

Growth rates of GDP and its components are calculated using the least squares method and constant price data in the local currency. Constant price in U.S. dollar series are used to calculate regional and income group growth rates. Local currency series are converted to constant U.S. dollars using an exchange rate in the common reference year.

Topic: Economic Policy & Debt: National accounts: Growth rates


BasePeriod: varies by country

IndicatorName: GDP (constant LCU)

Longdefinition: GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant local currency.

Topic: Economic Policy & Debt: National accounts: Local currency at constant prices: Aggregate indicators


IndicatorName: GDP, PPP (current international $)

Longdefinition:
This indicator provides values for gross domestic product (GDP) expressed in current international dollars, converted by purchasing power parity (PPP) conversion factor.
GDP is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. PPP conversion factor is a spatial price deflator and currency converter that eliminates the effects of the differences in price levels between countries.
From April 2020, “GDP: linked series (current LCU)” [NY.GDP.MKTP.CN.AD] is used as underlying GDP in local currency unit so that it’s in line with time series of PPP conversion factors for GDP, which are extrapolated with linked GDP deflators.

Source: International Comparison Program, World Bank | World Development Indicators database, World Bank | Eurostat-OECD PPP Programme.

Statisticalconceptandmethodology:
Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.

For more information on underlying GDP in local currency, please refer to the metadata for “GDP: linked series (current LCU)” [NY.GDP.MKTP.CN.AD]. For more information on underlying PPP conversion factor, please refer to the metadata for "PPP conversion factor, GDP (LCU per international $)" [PA.NUS.PPP].

For the concept and methodology of PPP, please refer to the International Comparison Program (ICP)’s website (https://www.worldbank.org/en/programs/icp).

Topic: Economic Policy & Debt: Purchasing power parity


IndicatorName: GDP, PPP (constant 2017 international $)

Longdefinition: PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2017 international dollars.

Statisticalconceptandmethodology: For the concept and methodology of 2017 PPP, please refer to the International Comparison Program (ICP)’s website (https://www.worldbank.org/en/programs/icp).


IndicatorName: Natural gas rents (% of GDP)

Longdefinition: Natural gas rents are the difference between the value of natural gas production at regional prices and total costs of production.


IndicatorName: GDP per capita (current US$)

Longdefinition: GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current U.S. dollars.

Statisticalconceptandmethodology: For more information, see the metadata for current U.S. dollar GDP (NY.GDP.MKTP.CD) and total population (SP.POP.TOTL).


IndicatorName: GDP per capita (current LCU)

Longdefinition: GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in current local currency.


IndicatorName: GDP per capita (constant 2015 US$)

Longdefinition: GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2015 U.S. dollars.

Statisticalconceptandmethodology: For more information, see the metadata for constant U.S. dollar GDP (NY.GDP.MKTP.KD) and total population (SP.POP.TOTL).


IndicatorName: GDP per capita growth (annual %)

Longdefinition: Annual percentage growth rate of GDP per capita based on constant local currency. GDP per capita is gross domestic product divided by midyear population. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources.


IndicatorName: GDP per capita (constant LCU)

Longdefinition: GDP per capita is gross domestic product divided by midyear population. GDP at purchaser's prices is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant local currency.


IndicatorName: GDP per capita, PPP (current international $)

Longdefinition:
This indicator provides per capita values for gross domestic product (GDP) expressed in current international dollars converted by purchasing power parity (PPP) conversion factor.

GDP is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. conversion factor is a spatial price deflator and currency converter that controls for price level differences between countries. Total population is a mid-year population based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Statisticalconceptandmethodology:
Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.

For more information on underlying GDP in current international dollar, please refer to the metadata for "GDP, PPP (current international $)" [NY.GDP.MKTP.PP.CD].
For more information on underlying population, please refer to the metadata for "total population” [SP.POP.TOTL].
For the concept and methodology of PPP, please refer to the International Comparison Program (ICP)’s website (https://www.worldbank.org/en/programs/icp).


IndicatorName: GDP per capita, PPP (constant 2017 international $)

Longdefinition: GDP per capita based on purchasing power parity (PPP). PPP GDP is gross domestic product converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GDP as the U.S. dollar has in the United States. GDP at purchaser's prices is the sum of gross value added by all resident producers in the country plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for depreciation of fabricated assets or for depletion and degradation of natural resources. Data are in constant 2017 international dollars.


IndicatorName: Oil rents (% of GDP)

Longdefinition: Oil rents are the difference between the value of crude oil production at regional prices and total costs of production.


IndicatorName: Total natural resources rents (% of GDP)

Longdefinition: Total natural resources rents are the sum of oil rents, natural gas rents, coal rents (hard and soft), mineral rents, and forest rents.


Developmentrelevance: Because development encompasses many factors - economic, environmental, cultural, educational, and institutional - no single measure gives a complete picture. However, the total earnings of the residents of an economy, measured by its gross national income (GNI), is a good measure of its capacity to provide for the well-being of its people.

IndicatorName: GNI (constant 2015 US$)

Longdefinition: GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2015 prices, expressed in U.S. dollars.


IndicatorName: GNI growth (annual %)

Longdefinition: GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad.


IndicatorName: GNI (constant LCU)

Longdefinition: GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant local currency.


IndicatorName: GNI per capita (US$)

Longdefinition: GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current U.S. dollars.


IndicatorName: GNI, PPP (current international $)

Longdefinition:
This indicator provides values for gross national income (GNI. Formerly GNP) expressed in current international dollars converted by purchasing power parity (PPP) conversion factor.
Gross national income is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. PPP conversion factor is a spatial price deflator and currency converter that eliminates the effects of the differences in price levels between countries.

From July 2020, “GNI: linked series (current LCU)” [NY.GNP.MKTP.CN.AD] is used as underlying GNI in local currency unit so that it’s in line with time series of PPP conversion factors, which are extrapolated with linked deflators.

Statisticalconceptandmethodology:
Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.

For more information on underlying GNI in local currency, please refer to the metadata for "GNI (current LCU)" [NY.GNP.MKTP.CN]. For more information on underlying PPP conversion factor, please refer to the metadata for "PPP conversion factor, GDP (LCU per international $)" [PA.NUS.PPP].

For the concept and methodology of PPP, please refer to the International Comparison Program (ICP)’s website (https://www.worldbank.org/en/programs/icp).


IndicatorName: GNI, PPP (constant 2017 international $)

Longdefinition: PPP GNI (formerly PPP GNP) is gross national income (GNI) converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GNI as a U.S. dollar has in the United States. Gross national income is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2017 international dollars.


IndicatorName: GNI per capita, Atlas method (current US$)

Longdefinition: GNI per capita (formerly GNP per capita) is the gross national income, converted to U.S. dollars using the World Bank Atlas method, divided by the midyear population. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI, calculated in national currency, is usually converted to U.S. dollars at official exchange rates for comparisons across economies, although an alternative rate is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate actually applied in international transactions. To smooth fluctuations in prices and exchange rates, a special Atlas method of conversion is used by the World Bank. This applies a conversion factor that averages the exchange rate for a given year and the two preceding years, adjusted for differences in rates of inflation between the country, and through 2000, the G-5 countries (France, Germany, Japan, the United Kingdom, and the United States). From 2001, these countries include the Euro area, Japan, the United Kingdom, and the United States.

Statisticalconceptandmethodology: The World Bank uses Atlas method GNI per capita in U.S. dollars to classify countries for analytical purposes and to determine borrowing eligibility. For more information, see the metadata for Atlas method GNI in current U.S. dollars (NY.GNP.ATLS.CD) and total population (SP.POP.TOTL).

Topic: Economic Policy & Debt: National accounts: Atlas GNI & GNI per capita


IndicatorName: GNI per capita (current LCU)

Longdefinition: GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current local currency.


IndicatorName: GNI per capita (constant 2015 US$)

Longdefinition: GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2015 U.S. dollars.


IndicatorName: GNI per capita growth (annual %)

Longdefinition: Annual percentage growth rate of GNI per capita based on constant local currency. Aggregates are based on constant 2010 U.S. dollars. GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad.


IndicatorName: GNI per capita (constant LCU)

Longdefinition: GNI per capita is gross national income divided by midyear population. GNI (formerly GNP) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant local currency.


IndicatorName: GNI per capita, PPP (current international $)

Longdefinition:
This indicator provides per capita values for gross national income (GNI. Formerly GNP) expressed in current international dollars converted by purchasing power parity (PPP) conversion factor.
GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. PPP conversion factor is a spatial price deflator and currency converter that eliminates the effects of the differences in price levels between countries.

Statisticalconceptandmethodology:
Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.

For more information on underlying GNI in current international dollar, please refer to the metadata for "GNI, PPP (current international $)" [NY.GNP.MKTP.PP.CD]. For more information on underlying population, please refer to the metadata for "total population" [SP.POP.TOTL].
For the concept and methodology of PPP, please refer to the International Comparison Program (ICP)’s website (https://www.worldbank.org/en/programs/icp).


IndicatorName: GNI per capita, PPP (constant 2017 international $)

Longdefinition: GNI per capita based on purchasing power parity (PPP). PPP GNI is gross national income (GNI) converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GNI as a U.S. dollar has in the United States. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in constant 2017 international dollars.


Generalcomments: In the WDI database, the DEC alternative conversion factor is used to convert data in local currency units (LCU) into U.S. dollars.

IndicatorName: DEC alternative conversion factor (LCU per US$)

Longdefinition: The DEC alternative conversion factor is the underlying annual exchange rate used for the World Bank Atlas method. As a rule, it is the official exchange rate reported in the IMF's International Financial Statistics (line rf). Exceptions arise where further refinements are made by World Bank staff. It is expressed in local currency units per U.S. dollar.

Source: International Monetary Fund, International Financial Statistics, supplemented by World Bank staff estimates.

Statisticalconceptandmethodology: The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. In certain countries, multiple or dual exchange rate activity exists and must be accounted for appropriately in underlying statistics. Doing so better reflects economic reality and leads to more accurate cross-country comparisons and country classifications by income level. Consequently, an alternative conversion factor is used when the official exchange rate is judged to diverge by an exceptionally large margin from the rate effectively applied to domestic transactions of foreign currencies and traded products. This applies to only a small number of countries, as shown in the country-level metadata. An alternative conversion factor is also used when the period covered by national accounts differs from the calendar year and the alternative conversion factor will then cover the same period. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors.

Topic: Financial Sector: Exchange rates & prices


Developmentrelevance:
PPP can be used to convert national accounts data, like GDP and its expenditure components, into a common currency, while also eliminating the effect of price level differences between countries. They can also be used to derive price level indexes (PLIs), the ratio of a country’s PPP to its market exchange rate, to directly compare price levels across countries.

PPPs and the PLIs and real (or PPP-adjusted) expenditures to which they give rise allow for many use-cases, but they are particularly valuable for empirical work involving comparisons of per capita consumption or levels of GDP (or other GDP aggregates) across countries and for the measurement of global poverty and global income inequality. The breadth and depth of ICP data allows its use-cases to cover other areas of economics, including empirical analyses of economic growth, productivity and trade, and even beyond, for instance, to help track global targets such as the UN Sustainable Development Goals related to health, education, energy and emissions and labor. Other applications of ICP data include their use in the construction of indexes, for example cost-of-living measures. Uses-cases can even be extended into the policymaking domain at all levels (global, regional and national) given the increased importance of cross-country benchmarking, among other possibilities.

Recommended uses of PPPs include: To make spatial comparisons of GDP and its expenditure components | To make spatial comparisons of price levels | To group countries by their per capita volume indexes and price level indexes

Recommended uses of PPPs with limitations  include: To analyze changes over time in relative GDP per capita and relative prices | To analyze price convergence | To make spatial comparisons of the cost of living | To use PPPs calculated for GDP and its expenditure components as deflators for other values.

IndicatorName: PPP conversion factor, GDP (LCU per international $)

Limitationsandexceptions:
Global PPP estimates provided by ICP are produced by the ICP Global Office and regional implementing agencies, based on data supplied by participating countries, and in accordance with the methodology recommended by the ICP Technical Advisory Group and approved by the ICP Governing Board. As such, these results are not produced by participating countries as part of their national official statistics.

PPPs are not recommended use: As a precise measure to establish strict rankings of countries | As a means of constructing national growth rates | As a measure to generate output and productivity comparisons by industry | As an indicator of the undervaluation or overvaluation of currencies | As an equilibrium exchange rate.

Longdefinition: Purchasing power parity (PPP) conversion factor is a spatial price deflator and currency converter that controls for price level differences between countries, thereby allowing volume comparisons of gross domestic product (GDP) and its expenditure components. This conversion factor is for GDP.

Statisticalconceptandmethodology:
PPPs are both currency conversion factors and spatial price indexes. PPPs convert different currencies to a common currency and, in the process of conversion, equalize their purchasing power by controlling differences in price levels between countries.

Typically, higher income countries have higher price levels, while lower income countries have lower price levels (Balassa-Samuelson effect). Market exchange rate-based cross-country comparisons of GDP at its expenditure components reflect both differences in economic outputs (volumes) and prices. Given the differences in price levels, the size of higher income countries is inflated, while the size of lower income countries is depressed in the comparison. PPP-based cross-country comparisons of GDP at its expenditure components only reflect differences in economic outputs (volume), as PPPs control for price level differences between the countries. Hence, the comparison reflects the real size of the countries.

The International Comparison Program (ICP) estimates PPPs for the world’s countries. The ICP is conducted as a global partnership of countries, multilateral agencies, and academia. The most recent 2017 ICP comparison covered 176 countries, including 47 Eurostat-OECD countries. For countries that have not participated in ICP comparisons, the PPP are imputed based on a regression model.

ICP estimated PPPs cover years from 2011 to 2017. WDI extrapolates 2011 PPPs for years earlier years, and 2017 PPPs for later years. Description of WDI extrapolation approach is available here: https://datahelpdesk.worldbank.org/knowledgebase/articles/665452-how-do-you-extrapolate-the-ppp-conversion-factors

For the member countries of Eurostat-OECD PPP Programme, PPP conversion factors are periodically updated based on the organizations’ databases. For Eurostat-OECD PPP Programme, please refer to the following websites.
(http://www.oecd.org/sdd/prices-ppp/)
(https://ec.europa.eu/eurostat/web/purchasing-power-parities/overview)

For more information on the ICP and PPPs, please refer to the ICP website at https://www.worldbank.org/en/programs/icp.


IndicatorName: PPP conversion factor, private consumption (LCU per international $)

Longdefinition: Purchasing power parity (PPP) conversion factor is a spatial price deflator and currency converter that controls for price level differences between countries, thereby allowing volume comparisons of gross domestic product (GDP) and its expenditure components. This conversion factor is for household final consumption expenditure.


IndicatorName: Coverage of unemployment benefits and ALMP (% of population)

Limitationsandexceptions: When interpreting ASPIRE performance indicators based on household surveys, it is important to note that the extent to which information on specific transfers and programs is captured in the household surveys can vary a lot across countries. Moreover, household surveys do not capture the universe of social protection programs in the country, in best practice cases just the largest programs.  As a consequence, ASPIRE indicators are not fully comparable across program categories and countries; however, they provide approximate measures of social protection systems performance.  In addition, there may be cases where ASPIRE performance indicators differ from official WB country reports as ASPIRE indicators are based on a first level analysis of original survey data  and unified methodology that does not necessarily reflect country-specific knowledge and in depth country analysis relying on administrative program level data and/or imputations.

Longdefinition: Coverage of unemployment benefits and active labor market programs (ALMP) shows the percentage of population participating in unemployment compensation, severance pay, and early retirement due to labor market reasons, labor market services (intermediation), training (vocational, life skills, and cash for training), job rotation and job sharing, employment incentives and wage subsidies, supported employment and rehabilitation, and employment measures for the disabled. Estimates include both direct and indirect beneficiaries.

Source: ASPIRE: The Atlas of Social Protection - Indicators of Resilience and Equity, The World Bank. Data are based on national representative household surveys. (datatopics.worldbank.org/aspire/)

Topic: Social Protection & Labor: Performance


IndicatorName: Coverage of unemployment benefits and ALMP in poorest quintile (% of population)


IndicatorName: Coverage of unemployment benefits and ALMP in 2nd quintile (% of population)


IndicatorName: Coverage of unemployment benefits and ALMP in 3rd quintile (% of population)


IndicatorName: Coverage of unemployment benefits and ALMP in 4th quintile (% of population)


IndicatorName: Coverage of unemployment benefits and ALMP in richest quintile (% of population)


IndicatorName: Coverage of social safety net programs (% of population)

Longdefinition: Coverage of social safety net programs shows the percentage of population participating in cash transfers and last resort programs, noncontributory social pensions, other cash transfers programs (child, family and orphan allowances, birth and death grants, disability benefits, and other allowances), conditional cash transfers, in-kind food transfers (food stamps and vouchers, food rations, supplementary feeding, and emergency food distribution), school feeding, other social assistance programs (housing allowances, scholarships, fee waivers, health subsidies, and other social assistance) and public works programs (cash for work and food for work). Estimates include both direct and indirect beneficiaries.


IndicatorName: Coverage of social safety net programs in poorest quintile (% of population)


IndicatorName: Coverage of social safety net programs in 2nd quintile (% of population)


IndicatorName: Coverage of social safety net programs in 3rd quintile (% of population)


IndicatorName: Coverage of social safety net programs in 4th quintile (% of population)


IndicatorName: Coverage of social safety net programs in richest quintile (% of population)


IndicatorName: Coverage of social insurance programs (% of population)

Longdefinition: Coverage of social insurance programs shows the percentage of population participating in programs that provide old age contributory pensions (including survivors and disability) and social security and health insurance benefits (including occupational injury benefits, paid sick leave, maternity and other social insurance). Estimates include both direct and indirect beneficiaries.


IndicatorName: Coverage of social insurance programs in poorest quintile (% of population)


IndicatorName: Coverage of social insurance programs in 2nd quintile (% of population)


IndicatorName: Coverage of social insurance programs in 3rd quintile (% of population)


IndicatorName: Coverage of social insurance programs in 4th quintile (% of population)


IndicatorName: Coverage of social insurance programs in richest quintile (% of population)


Developmentrelevance:
Literacy rate is an outcome indicator to evaluate educational attainment. This data can predict the quality of future labor force and can be used in ensuring policies for life skills for men and women.

It can be also used as a proxy instrument to see the effectiveness of education system; a high literacy rate suggests the capacity of an education system to provide a large population with opportunities to acquire literacy skills. The accumulated achievement of education is fundamental for further intellectual growth and social and economic development, although it doesn't necessarily ensure the quality of education.

Literate women implies that they can seek and use information for the betterment of the health, nutrition and education of their household members. Literate women are also empowered to play a meaningful role.

Generalcomments: For aggregate data, each economy is classified based on the classification of World Bank Group's fiscal year 2022 (July 1, 2021-June 30, 2022).

IndicatorName: Literacy rate, youth female (% of females ages 15-24)

Limitationsandexceptions: In practice, literacy is difficult to measure. Estimating literacy rates requires census or survey measurements under controlled conditions. Many countries report the number of literate people from self-reported data. Some use educational attainment data as a proxy but apply different lengths of school attendance or levels of completion. Ant there is a trend among recent national and international surveys toward using a direct reading test of literacy skills. Because definitions and methods of data collection differ across countries, data should be used cautiously.

Longdefinition: Youth literacy rate is the percentage of people ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.

Source: UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of June 2022.

Statisticalconceptandmethodology:
Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.

Data on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.

Topic: Education: Outcomes


Developmentrelevance:
Literacy rate is an outcome indicator to evaluate educational attainment. This data can predict the quality of future labor force and can be used in ensuring policies for life skills for men and women.

It can be also used as a proxy instrument to see the effectiveness of education system; a high literacy rate suggests the capacity of an education system to provide a large population with opportunities to acquire literacy skills. The accumulated achievement of education is fundamental for further intellectual growth and social and economic development, although it doesn't necessarily ensure the quality of education.

The Gender Parity Index (GPI) indicates parity between girls and boys. A GPI of less than 1 suggests girls are more disadvantaged than boys in learning opportunities and a GPI of greater than 1 suggests the other way around. Eliminating gender disparities in education would help increase the status and capabilities of women. Literate women implies that they can seek and use information for the betterment of the health, nutrition and education of their household members. Literate women are also empowered to play a meaningful role.

IndicatorName: Literacy rate, youth (ages 15-24), gender parity index (GPI)

Longdefinition: Gender parity index for youth literacy rate is the ratio of females to males ages 15-24 who can both read and write with understanding a short simple statement about their everyday life.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female youth literacy rate by male youth literacy rate.

Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.

Data on literacy are compiled by the UNESCO Institute for Statistics based on national censuses and household surveys and, for countries without recent literacy data, using the Global Age-Specific Literacy Projection Model (GALP). For detailed information, see www.uis.unesco.org.


IndicatorName: Literacy rate, youth male (% of males ages 15-24)


IndicatorName: Literacy rate, youth total (% of people ages 15-24)


IndicatorName: Literacy rate, adult female (% of females ages 15 and above)

Longdefinition: Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life.


IndicatorName: Literacy rate, adult male (% of males ages 15 and above)


IndicatorName: Literacy rate, adult total (% of people ages 15 and above)


Aggregationmethod: Median

Generalcomments: For aggregate data, each economy is classified based on the classification of World Bank Group's fiscal year 2023 (July 1, 2022-June 30, 2023).

IndicatorName: Compulsory education, duration (years)

Longdefinition: Duration of compulsory education is the number of years that children are legally obliged to attend school.

Statisticalconceptandmethodology:
Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


Developmentrelevance: The Gender Parity Index (GPI) indicates parity between girls and boys. A GPI of less than 1 suggests girls are more disadvantaged than boys in learning opportunities and a GPI of greater than 1 suggests the other way around. Eliminating gender disparities in education would help increase the status and capabilities of women.

IndicatorName: School enrollment, primary (gross), gender parity index (GPI)

Longdefinition: Gender parity index for gross enrollment ratio in primary education is the ratio of girls to boys enrolled at primary level in public and private schools.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female gross enrollment ratio in primary education by male gross enrollment ratio in primary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).

Topic: Education: Participation


IndicatorName: School enrollment, primary and secondary (gross), gender parity index (GPI)

Longdefinition: Gender parity index for gross enrollment ratio in primary and secondary education is the ratio of girls to boys enrolled at primary and secondary levels in public and private schools.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female gross enrollment ratio in primary and secondary education by male gross enrollment ratio in primary and secondary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, secondary (gross), gender parity index (GPI)

Longdefinition: Gender parity index for gross enrollment ratio in secondary education is the ratio of girls to boys enrolled at secondary level in public and private schools.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female gross enrollment ratio in secondary education by male gross enrollment ratio in secondary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, tertiary (gross), gender parity index (GPI)

Longdefinition: Gender parity index for gross enrollment ratio in tertiary education is the ratio of women to men enrolled at tertiary level in public and private schools.

Statisticalconceptandmethodology:
This indicator is calculated by dividing female gross enrollment ratio in tertiary education by male gross enrollment ratio in tertiary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Preprimary education, duration (years)

Longdefinition: Preprimary duration refers to the number of grades (years) in preprimary school.

Topic: Education: Inputs


Developmentrelevance: The pupil-teacher ratio is often used to compare the quality of schooling across countries, but it is often weakly related to student learning and quality of education.

IndicatorName: Pupil-teacher ratio, preprimary

Limitationsandexceptions: The comparability of pupil-teacher ratios across countries is affected by the definition of teachers and by differences in class size by grade and in the number of hours taught, as well as the different practices countries employ such as part-time teachers, school shifts, and multi-grade classes. Moreover, the underlying enrollment levels are subject to a variety of reporting errors.

Longdefinition: Preprimary school pupil-teacher ratio is the average number of pupils per teacher in preprimary school.

Source: UNESCO Institute for Statistics (http://uis.unesco.org/). Data as of February 2020.

Statisticalconceptandmethodology:
Pupil-teacher ratio is calculated by dividing the number of students at the specified level of education by the number of teachers at the same level of education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


Developmentrelevance: Gross enrollment ratios indicate the capacity of each level of the education system, but a high ratio may reflect a substantial number of overage children enrolled in each grade because of repetition or late entry rather than a successful education system. The net enrollment rate excludes overage and underage students and more accurately captures the system's coverage and internal efficiency. Differences between the gross enrollment ratio and the net enrollment rate show the incidence of overage and underage enrollments.

IndicatorName: School enrollment, preprimary (% gross)

Limitationsandexceptions: Enrollment indicators are based on annual school surveys, but do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs across countries and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase the rate; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where registration of births is not strictly enforced.

Longdefinition: Gross enrollment ratio is the ratio of total enrollment, regardless of age, to the population of the age group that officially corresponds to the level of education shown. Preprimary education refers to programs at the initial stage of organized instruction, designed primarily to introduce very young children to a school-type environment and to provide a bridge between home and school.

Statisticalconceptandmethodology:
Gross enrollment ratio for pre-primary school is calculated by dividing the number of students enrolled in pre-primary education regardless of age by the population of the age group which officially corresponds to pre-primary education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: School enrollment, preprimary, female (% gross)


IndicatorName: School enrollment, preprimary, male (% gross)


Developmentrelevance:
Trained teachers refer to teaching force with the necessary pedagogical skills to teach and use teaching materials in an effective manner. The share of trained teachers reveals a country's commitment to investing in the development of its human capital engaged in teaching.

Teachers are important resource, especially for children who are the first-generation of receiving education in their families and heavily rely on teachers in acquiring basic literacy skills. However, rapid increase in enrollments may cause the shortage of trained teachers. Education finance is a key for appropriate teacher allocations, since teacher salaries account for a large share of education budgets. The shortage of trained teacher may result in low qualified teachers in more disadvantaged area.

IndicatorName: Trained teachers in preprimary education, female (% of female teachers)

Limitationsandexceptions: This indicator does not take into account differences in teachers' experiences and status, teaching methods, teaching materials, and classroom conditions - all factors that affect the quality of teaching and learning. Some teachers without formal training may have acquired equivalent pedagogical skills through professional experience. In addition, national standards regarding teacher qualifications and pedagogical skills may vary.

Longdefinition: Trained teachers in preprimary education are the percentage of preprimary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.

Statisticalconceptandmethodology:
Share of trained teachers is calculated by dividing the number of trained teachers of the specified level of education by total number of teachers at the same level of education, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Trained teachers in preprimary education, male (% of male teachers)


IndicatorName: Trained teachers in preprimary education (% of total teachers)


Developmentrelevance: The World Bank and the UNESCO Institute for Statistics jointly developed the primary completion rate indicator. Increasingly used as a core indicator of an education system's performance, it reflects an education system's coverage and the educational attainment of students.

IndicatorName: Primary completion rate, female (% of relevant age group)

Limitationsandexceptions:
Data limitations preclude adjusting for students who drop out during the final year of primary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual primary completion rate.

There are many reasons why the primary completion rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of primary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of primary education.

Longdefinition: Primary completion rate, or gross intake ratio to the last grade of primary education, is the number of new entrants (enrollments minus repeaters) in the last grade of primary education, regardless of age, divided by the population at the entrance age for the last grade of primary education. Data limitations preclude adjusting for students who drop out during the final year of primary education.

Statisticalconceptandmethodology:
Primary completion rate is calculated by dividing the number of new entrants (enrollment minus repeaters) in the last grade of primary education, regardless of age, by the population at the entrance age for the last grade of primary education and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Primary completion rate, male (% of relevant age group)


IndicatorName: Primary completion rate, total (% of relevant age group)


Developmentrelevance: A relative high concentration of the adult population in a given level of education reflects the capacity of the educational system in the corresponding level of education. Educational attainment is closely related to the skills and competencies of a country's population, and could be seen as a proxy of both the quantitative and qualitative aspects of the stock of human capital.

IndicatorName: Educational attainment, at least completed primary, population 25+ years, male (%) (cumulative)

Limitationsandexceptions: Caution is required when using this indicator for cross-country comparison, since the countries do not always classify degrees and qualifications at the same International Standard Classification of Education (ISCED) levels, even if they are received at roughly the same age or after a similar number of years of schooling. Also, certain educational programmes and study courses cannot be easily classified according to ISCED. This indicator only measures educational attainment in terms of level of education attained, i.e. years of schooling, and do not necessarily reveal the quality of the education (learning achievement and other impacts).

Longdefinition: The percentage of population ages 25 and over that attained or completed primary education.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed primary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Primary education, duration (years)

Longdefinition: Primary duration refers to the number of grades (years) in primary school.


IndicatorName: Pupil-teacher ratio, primary

Longdefinition: Primary school pupil-teacher ratio is the average number of pupils per teacher in primary school.


IndicatorName: Over-age students, primary, female (% of female enrollment)

Longdefinition: Over-age students are the percentage of those enrolled who are older than the official school-age range for primary education.

Statisticalconceptandmethodology:
The percentage of over-age students is calculated by dividing the number of students who are older than the official school-age range for primary education by primary school enrollment, and multiplying by 100.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).

Topic: Education: Efficiency


IndicatorName: Over-age students, primary, male (% of male enrollment)


IndicatorName: Over-age students, primary (% of enrollment)


IndicatorName: Trained teachers in primary education, female (% of female teachers)

Longdefinition: Trained teachers in primary education are the percentage of primary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.


IndicatorName: Trained teachers in primary education, male (% of male teachers)


IndicatorName: Trained teachers in primary education (% of total teachers)


Aggregationmethod: Sum

Developmentrelevance: Large numbers of children out of school create pressure to enroll children and provide classrooms, teachers, and educational materials, a task made difficult in many countries by limited education budgets. However, getting children into school is a high priority for countries and crucial for achieving universal primary education.

IndicatorName: Children out of school, primary

Limitationsandexceptions: Due to different data sources for enrollment and population data, the number may not capture the actual number of children not attending in primary school.

Longdefinition: Children out of school are the number of primary-school-age children not enrolled in primary or secondary school.

Statisticalconceptandmethodology:
The number of out-of-school children is calculated by subtracting the number of primary school-age children enrolled in primary or secondary school from the total population of the official primary school-age children.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Children out of school, primary, female


IndicatorName: Children out of school, female (% of female primary school age)

Limitationsandexceptions: The administrative data used in the calculation of the rate of out-of-school children are based on enrolment at a specific date which can bias the results by either counting enrolled children who never attend school or by omitting those who enroll after the reference date for reporting enrolment data. Furthermore, children who drop out of school after the reference date are not counted as out of school. Discrepancies between enrolment and population data from different sources can also result in over- or underestimates of the rate. Lastly, the international comparability of this indicator can be affected by the use of different concepts of enrolment and out-of-school children across countries.

Longdefinition: Children out of school are the percentage of primary-school-age children who are not enrolled in primary or secondary school. Children in the official primary age group that are in preprimary education should be considered out of school.

Statisticalconceptandmethodology:
The rate of out-of-school children allows to compare across countries with different population sizes. It shows the share of official primary-school-age children who never attended school or dropped out to the population of official primary school age.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Children out of school, primary, male


IndicatorName: Children out of school, male (% of male primary school age)


IndicatorName: Children out of school (% of primary school age)


IndicatorName: Lower secondary completion rate, female (% of relevant age group)

Limitationsandexceptions:
Data limitations preclude adjusting for students who drop out during the final year of lower secondary education. Thus this rate is a proxy that should be taken as an upper estimate of the actual lower secondary completion rate.

There are many reasons why the rate can exceed 100 percent. The numerator may include late entrants and overage children who have repeated one or more grades of lower secondary education as well as children who entered school early, while the denominator is the number of children at the entrance age for the last grade of lower secondary education.

Longdefinition: Lower secondary education completion rate is measured as the gross intake ratio to the last grade of lower secondary education (general and pre-vocational). It is calculated as the number of new entrants in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.

Statisticalconceptandmethodology:
Lower secondary completion rate is calculated as the number of new entrants (enrollment minus repeaters) in the last grade of lower secondary education, regardless of age, divided by the population at the entrance age for the last grade of lower secondary education.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Lower secondary completion rate, male (% of relevant age group)


IndicatorName: Lower secondary completion rate, total (% of relevant age group)


IndicatorName: Educational attainment, at least completed lower secondary, population 25+, female (%) (cumulative)

Longdefinition: The percentage of population ages 25 and over that attained or completed lower secondary education.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed lower secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Educational attainment, at least completed lower secondary, population 25+, male (%) (cumulative)


IndicatorName: Educational attainment, at least completed lower secondary, population 25+, total (%) (cumulative)


IndicatorName: Educational attainment, at least completed post-secondary, population 25+, female (%) (cumulative)

Longdefinition: The percentage of population ages 25 and over that attained or completed post-secondary non-tertiary education.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed post-secondary non-tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Educational attainment, at least completed post-secondary, population 25+, male (%) (cumulative)


IndicatorName: Educational attainment, at least completed post-secondary, population 25+, total (%) (cumulative)


IndicatorName: Educational attainment, at least completed upper secondary, population 25+, female (%) (cumulative)

Longdefinition: The percentage of population ages 25 and over that attained or completed upper secondary education.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed upper secondary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Educational attainment, at least completed upper secondary, population 25+, male (%) (cumulative)


IndicatorName: Educational attainment, at least completed upper secondary, population 25+, total (%) (cumulative)


IndicatorName: Secondary education, duration (years)

Longdefinition: Secondary duration refers to the number of grades (years) in secondary school.

Statisticalconceptandmethodology:
Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Aggregate data are based on World Bank estimates.

The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Pupil-teacher ratio, lower secondary

Longdefinition: Lower secondary school pupil-teacher ratio is the average number of pupils per teacher in lower secondary school.


IndicatorName: Pupil-teacher ratio, secondary

Longdefinition: Secondary school pupil-teacher ratio is the average number of pupils per teacher in secondary school.


IndicatorName: Pupil-teacher ratio, upper secondary

Longdefinition: Upper secondary school pupil-teacher ratio is the average number of pupils per teacher in upper secondary school.


IndicatorName: Trained teachers in secondary education, female (% of female teachers)

Longdefinition: Trained teachers in secondary education are the percentage of secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.


IndicatorName: Trained teachers in lower secondary education, female (% of female teachers)

Longdefinition: Trained teachers in lower secondary education are the percentage of lower secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.


IndicatorName: Trained teachers in lower secondary education, male (% of male teachers)


IndicatorName: Trained teachers in lower secondary education (% of total teachers)


IndicatorName: Trained teachers in secondary education, male (% of male teachers)


IndicatorName: Trained teachers in upper secondary education, female (% of female teachers)

Longdefinition: Trained teachers in upper secondary education are the percentage of upper secondary school teachers who have received the minimum organized teacher training (pre-service or in-service) required for teaching in a given country.


IndicatorName: Trained teachers in upper secondary education, male (% of male teachers)


IndicatorName: Trained teachers in upper secondary education (% of total teachers)


IndicatorName: Trained teachers in secondary education (% of total teachers)


IndicatorName: Adolescents out of school, female (% of female lower secondary school age)

Longdefinition: Adolescents out of school are the percentage of lower secondary school age adolescents who are not enrolled in school.

Statisticalconceptandmethodology:
The rate of out-of-school adolescents allows to compare across countries with different population sizes. It shows the share of official lower secondary age adolescents who never attended school or dropped out to the population of official lower secondary school age.

Data on education are collected by the UNESCO Institute for Statistics from official responses to its annual education survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011. Population data are drawn from the United Nations Population Division. Using a single source for population data standardizes definitions, estimations, and interpolation methods, ensuring a consistent methodology across countries and minimizing potential enumeration problems in national censuses. The reference years reflect the school year for which the data are presented. In some countries the school year spans two calendar years (for example, from September 2010 to June 2011); in these cases the reference year refers to the year in which the school year ended (2011 in the example).


IndicatorName: Adolescents out of school, male (% of male lower secondary school age)


IndicatorName: Adolescents out of school (% of lower secondary school age)


IndicatorName: Educational attainment, at least Bachelor's or equivalent, population 25+, female (%) (cumulative)

Longdefinition: The percentage of population ages 25 and over that attained or completed Bachelor's or equivalent.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed Bachelor's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Educational attainment, at least Bachelor's or equivalent, population 25+, male (%) (cumulative)


IndicatorName: Educational attainment, at least Bachelor's or equivalent, population 25+, total (%) (cumulative)


IndicatorName: Educational attainment, Doctoral or equivalent, population 25+, female (%) (cumulative)

Longdefinition: The percentage of population ages 25 and over that attained or completed Doctoral or equivalent.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed Doctoral or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Educational attainment, Doctoral or equivalent, population 25+, male (%) (cumulative)


IndicatorName: Educational attainment, Doctoral or equivalent, population 25+, total (%) (cumulative)


IndicatorName: Educational attainment, at least Master's or equivalent, population 25+, female (%) (cumulative)

Longdefinition: The percentage of population ages 25 and over that attained or completed Master's or equivalent.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed Master's or equivalent by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Educational attainment, at least Master's or equivalent, population 25+, male (%) (cumulative)


IndicatorName: Educational attainment, at least Master's or equivalent, population 25+, total (%) (cumulative)


IndicatorName: Educational attainment, at least completed short-cycle tertiary, population 25+, female (%) (cumulative)

Longdefinition: The percentage of population ages 25 and over that attained or completed short-cycle tertiary education.

Statisticalconceptandmethodology:
It is calculated by dividing the number of population ages 25 and older who attained or completed short-cycle tertiary education by the total population of the same age group and multiplying by 100. The number 0 means zero or small enough that the number would round to zero.

Data are collected by the UNESCO Institute for Statistics mainly from national population census, household survey, and labour force survey. All the data are mapped to the International Standard Classification of Education (ISCED) to ensure the comparability of education programs at the international level. The current version was formally adopted by UNESCO Member States in 2011.


IndicatorName: Educational attainment, at least completed short-cycle tertiary, population 25+, male (%) (cumulative)


IndicatorName: Educational attainment, at least completed short-cycle tertiary, population 25+, total (%) (cumulative)