Developmentrelevance: The World Bank Group is committed to reducing extreme poverty to 3 percent or less, globally, by 2030. Monitoring poverty is important on the global development agenda as well as on the national development agenda of many countries. The World Bank produced its first global poverty estimates for developing countries for World Development Report 1990: Poverty (World Bank 1990) using household survey data for 22 countries (Ravallion, Datt, and van de Walle 1991). Since then there has been considerable expansion in the number of countries that field household income and expenditure surveys. The World Bank maintains a database that is updated annually as new survey data become available (and thus may contain more recent data or revisions) and conducts a major reassessment of progress against poverty every year. The Poverty and Inequality Platform (PIP) is an interactive computational tool that allows users to replicate these internationally comparable $1.90, $3.20 and $5.50 a day global, regional and country-level poverty estimates and to compute poverty measures for custom country groupings and for different poverty lines. PIP also provides access to user-friendly dashboards with graphs and interactive maps that visualize trends in key poverty and inequality indicators for different regions and countries.

IndicatorName: Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population)

Longdefinition: Poverty headcount ratio at $1.90 a day is the percentage of the population living on less than $1.90 a day at 2011 international prices. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

Statisticalconceptandmethodology:
International comparisons of poverty estimates entail both conceptual and practical problems. Countries have different definitions of poverty, and consistent comparisons across countries can be difficult. Local poverty lines tend to have higher purchasing power in rich countries, where more generous standards are used, than in poor countries.

Since World Development Report 1990, the World Bank has aimed to apply a common standard in measuring extreme poverty, anchored to what poverty means in the world's poorest countries. The welfare of people living in different countries can be measured on a common scale by adjusting for differences in the purchasing power of currencies. The commonly used $1 a day standard, measured in 1985 international prices and adjusted to local currency using purchasing power parities (PPPs), was chosen for World Development Report 1990 because it was typical of the poverty lines in low-income countries at the time. As differences in the cost of living across the world evolve, the international poverty line has to be periodically updated using new PPP price data to reflect these changes. The last change was in October 2015, when we adopted $1.90 as the international poverty line using the 2011 PPP. Prior to that, the 2008 update set the international poverty line at $1.25 using the 2005 PPP. Poverty measures based on international poverty lines attempt to hold the real value of the poverty line constant across countries, as is done when making comparisons over time. The $3.20 poverty line is derived from typical national poverty lines in countries classified as Lower Middle Income. The $5.50 poverty line is derived from typical national poverty lines in countries classified as Upper Middle Income.

Early editions of World Development Indicators used PPPs from the Penn World Tables to convert values in local currency to equivalent purchasing power measured in U.S dollars. Later editions used 1993, 2005, and 2011 consumption PPP estimates produced by the World Bank. The current extreme poverty line is set at $1.90 a day in 2011 PPP terms, which represents the mean of the poverty lines found in 15 of the poorest countries ranked by per capita consumption. The new poverty line maintains the same standard for extreme poverty - the poverty line typical of the poorest countries in the world - but updates it using the latest information on the cost of living in developing countries. As a result of revisions in PPP exchange rates, poverty rates for individual countries cannot be compared with poverty rates reported in earlier editions.

The statistics reported here are based on consumption data or, when unavailable, on income surveys.

Topic: Poverty: Poverty rates


Derivationmethod:
Official multidimensional poverty headcount is calculated by each country using different methodologies. The most commonly used method is Alkire Foster (AF) methodology which identifies dimensions, typically health, education and living standards and several indicators in each dimension. The individuals are considered as multidimensionally poor if they are deprived in multiple indicators exceeding certain thresholds. Details of the methodology can be found here (https://ophi.org.uk/research/multidimensional-poverty/). It is also important to note that a country-specific analysis is carried out by adjusting the dimensions, indicators and thresholds to better reflect each country’s context and so the results presented in one country are not comparable with the findings of other countries on multidimensional poverty headcount. On the other hand, EU countries and North Macedonia use a completely different approach to measure the multidimensional poverty using the concept of “people at risk of poverty or social exclusion” (AROPE). AROPE consists of three indicators, and people will be considered as “at risk of poverty or social exclusion” if they are “at risk of poverty” or “severely materially deprived” or “living in a household with a very low work intensity”.  Details of the methodology can be found here (https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:At_risk_of_poverty_or_social_exclusion_(AROPE)).
Official multidimensional poverty headcount is calculated by each country using different methodologies. The most commonly used method is Alkire Foster (AF) methodology which identifies dimensions, typically health, education and living standards and several indicators in each dimension. The individuals are considered as multidimensionally poor if they are deprived in multiple indicators exceeding certain thresholds. Details of the methodology can be found here (https://ophi.org.uk/research/multidimensional-poverty/). It is also important to note that a country-specific analysis is carried out by adjusting the dimensions, indicators and thresholds to better reflect each country’s context and so the results presented in one country are not comparable with the findings of other countries on multidimensional poverty headcount.

On the other hand, EU countries and North Macedonia use a slightly different approach to measure the multidimensional poverty using the concept of “people at risk of poverty or social exclusion” (AROPE). AROPE consists of three indicators, and people will be considered as “at risk of poverty or social exclusion” if they are “at risk of poverty” or “severely materially deprived” or “living in a household with a very low work intensity”.  Details of the methodology can be found here (https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:At_risk_of_poverty_or_social_exclusion_(AROPE)).

IndicatorName: Multidimensional poverty headcount ratio (% of total population)

License_Type: CC BY-4.0

Limitationsandexceptions:
It should be clearly noted that these multidimensional indicators are not comparable across countries. For instance, AF methodology and AROPE are different, and although both produce some headcount ratio of people who are considered as “multidimensionally poor”, their definition of multidimensionality of poverty is utterly different, and so should not be compared.

Besides, even when they use the same approach, the numbers are not comparable across countries, as the important parameters to calculate the figures such as the number of indicators and the weight allocated to each indicator are tailored depending on the country specific context.

Shortdefinition: The percentage of people who are multidimensionally poor

Source: Government statistical agencies. Data for EU countires are from the EUROSTAT

Topic: Poverty: Multidimensional poverty


Derivationmethod:
Official multidimensional poverty headcount is calculated by each country using different methodologies. The most commonly used method is Alkire Foster (AF) methodology which identifies dimensions, typically health, education and living standards and several indicators in each dimension. The individuals are considered as multidimensionally poor if they are deprived in multiple indicators exceeding certain thresholds. Details of the methodology can be found here (https://ophi.org.uk/research/multidimensional-poverty/). It is also important to note that a country-specific analysis is carried out by adjusting the dimensions, indicators and thresholds to better reflect each country’s context and so the results presented in one country are not comparable with the findings of other countries on multidimensional poverty headcount.

On the other hand, EU countries and North Macedonia use a slightly different approach to measure the multidimensional poverty using the concept of “people at risk of poverty or social exclusion” (AROPE). AROPE consists of three indicators, and people will be considered as “at risk of poverty or social exclusion” if they are “at risk of poverty” or “severely materially deprived” or “living in a household with a very low work intensity”.  Details of the methodology can be found here (https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:At_risk_of_poverty_or_social_exclusion_(AROPE)).

IndicatorName: Multidimensional poverty headcount ratio, children (% of child population)

Shortdefinition: The percentage of children who are multidimensionally poor


Derivationmethod: The Multidimensional poverty index for  children is calculated by multiplying the multidimensional  poverty headcount and the average share of weighted deprivations (intensity) of children.

IndicatorName: Multidimensional poverty index, children (scale 0-1)

Limitationsandexceptions: The MPI here is a national MPI reported by each country and differs from the global MPI collected by the UNDP. Unlike the global MPI which uses the same dimensional and indicators, the national MPI is calculated using different dimensions and indicators by each country, therefore, it is not comparable across countries.

Shortdefinition: Proportion of the child population that is multidimensionally poor adjusted by the intensity of the deprivations


IndicatorName: Multidimensional poverty headcount ratio, female (% of female population)

Shortdefinition: The percentage of female population who are multidimensionally poor


Derivationmethod: Official multidimensional poverty headcount for houesholds is calculated by each country using different methodologies. The most commonly used method is Alkire Foster (AF) methodology which identifies dimensions, typically health, education and living standards and several indicators in each dimension. The households are considered as multidimensionally poor if they are deprived in multiple indicators exceeding certain thresholds. Details can be found here (https://ophi.org.uk/research/multidimensional-poverty/).  It is also important to note that a country-specific analysis is carried out by adjusting the dimensions, indicators and thresholds to better reflect each country’s context and so the results presented in one country are not comparable with the findings of other countries on multidimensional poverty headcount.

IndicatorName: Multidimensional poverty headcount ratio, household (% of total households)

Limitationsandexceptions: It should be clearly noted that these multidimensional indicators are not comparable across countries as the important parameters to calculate the figures such as the number of indicators and the weight allocated to each indicator are tailored accoding to each country specific context.

Shortdefinition: The percentage of households who are multidimensionally poor


Derivationmethod: The multidimensional headcount is a useful measure, but it does not increase if poor people become more deprived. Because of that, we need a different set of measures, which is the average share of weighted deprivations, also known as intensity. Intensity is calculated by adding up the proportion of total deprivations each person suffers and dividing by the total number of poor persons.

IndicatorName: Multidimensional poverty intensity

Limitationsandexceptions: It should be noted that the intensity is not comparable across diffferent countries as it depends on the parameters used in the methodology such as what kind of dimensions and indicators are used, and how the weight is constructed, which varies significantly across countries.

Shortdefinition: The average share of weighted deprivations (intensity)


Derivationmethod:
Official multidimensional poverty headcount is calculated by each country using different methodologies. The most commonly used method is Alkire Foster (AF) methodology which identifies dimensions, typically health, education and living standards and several indicators in each dimension. The individuals are considered as multidimensionally poor if they are deprived in multiple indicators exceeding certain thresholds. Details can be found here (https://ophi.org.uk/research/multidimensional-poverty/). It is also important to note that a country-specific analysis is carried out by adjusting the dimensions, indicators and thresholds to better reflect each country’s context and so the results presented in one country are not comparable with the findings of other countries on multidimensional poverty headcount.

On the other hand, EU countries and North Macedonia use a completely different approach to measure the multidimensional poverty using the concept of “people at risk of poverty or social exclusion” (AROPE). AROPE consists of three indicators, and people will be considered as “at risk of poverty or social exclusion” if they are “at risk of poverty” or “severely materially deprived” or “living in a household with a very low work intensity”.  Details can be found here (https://ec.europa.eu/eurostat/statistics-explained/index.php/Glossary:At_risk_of_poverty_or_social_exclusion_(AROPE)).

IndicatorName: Multidimensional poverty headcount ratio, male (% of male population)

Limitationsandexceptions:
It should be clearly noted that these multidimensional indicators are not comparable across countries. For instance, AF methodology and AROPE are fundamentally very different, and although both produce some headcount ratio of people who are considered as “multidimensionally poor”, their definition of multidimensionality of poverty is utterly different, and so should not be compared.

Besides, even when they use the same approach, the numbers are not comparable across countries, as the important parameters to calculate the figures such as the number of indicators and the weight allocated to each indicator are tailored accoding to the country specific context.

Shortdefinition: The percentage of male population who are multidimensionally poor


Derivationmethod: The Multidimensional poverty index is calculated by multiplying multidimensional  poverty headcount and average number of deprivations (intensity).

IndicatorName: Multidimensional poverty index (scale 0-1)

Limitationsandexceptions: The MPI here is a national MPI reported by each country and differs from the global MPI collected by the UNDP. Unlike the global MPI which uses the same dimensions and indicators, the national MPI is calculated using different dimensions and indicators by each country, therefore, it is not comparable across countries.

Shortdefinition: Proportion of the population that is multidimensionally poor adjusted by the intensity of the deprivations


Developmentrelevance: The poverty rate as defined by national poverty lines reflects the share of the population that fails to meet the standard a country thinks is necessarty to cover basic needs.

Generalcomments: This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. Due to differences in estimation methodologies and poverty lines, estimates should not be compared across countries.

IndicatorName: Poverty headcount ratio at national poverty lines (% of population)

Longdefinition: National poverty headcount ratio is the percentage of the population living below the national poverty line(s). National estimates are based on population-weighted subgroup estimates from household surveys. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year.

Periodicity: Annual

Relatedsourcelinks: World Bank, Poverty and Inequality Platform: https://pip.worldbank.org/

Source: World Bank, Poverty and Inequality Platform. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.

Statisticalconceptandmethodology:
Poverty headcount ratio among the population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.

Poverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income.

National poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies.

Almost all national poverty lines in developing economies are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years.

This series only includes estimates that to the best of our knowledge are reasonably comparable over time for a country. For economies for which the data are from EU-SILC, the reported year is the income reference year, which is the year before the survey year. For all other economies, the year reported is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which data collection started.


IndicatorName: Rural poverty headcount ratio at national poverty lines (% of rural population)

Longdefinition: Rural poverty headcount ratio is the percentage of the rural population living below the national poverty lines.

Source: World Bank, Global Poverty Working Group. Data are compiled from official government sources or are computed by World Bank staff using national (i.e. country–specific) poverty lines.

Statisticalconceptandmethodology:
Poverty headcount ratio among the rural population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.

Poverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income.

National poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies.

Almost all national poverty lines are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years. The data is based on the two most recent years for which survey data are available.

Survey year is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected.


IndicatorName: Urban poverty headcount ratio at national poverty lines (% of urban population)

Longdefinition: Urban poverty headcount ratio is the percentage of the urban population living below the national poverty lines.

Statisticalconceptandmethodology:
Poverty headcount ratio among the urban population is measured based on national (i.e. country-specific) poverty lines. A country may have a unique national poverty line or separate poverty lines for rural and urban areas, or for different geographic areas to reflect differences in the cost of living or sometimes to reflect differences in diets and consumption baskets.

Poverty estimates at national poverty lines are computed from household survey data collected from nationally representative samples of households. These data must contain sufficiently detailed information to compute a comprehensive estimate of total household income or consumption (including consumption or income from own production), from which it is possible to construct a correctly weighted distribution of per capita consumption or income.

National poverty lines are the benchmark for estimating poverty indicators that are consistent with the country's specific economic and social circumstances. National poverty lines reflect local perceptions of the level and composition of consumption or income needed to be non-poor. The perceived boundary between poor and non-poor typically rises with the average income of a country and thus does not provide a uniform measure for comparing poverty rates across countries. While poverty rates at national poverty lines should not be used for comparing poverty rates across countries, they are appropriate for guiding and monitoring the results of country-specific national poverty reduction strategies.

Almost all national poverty lines are anchored to the cost of a food bundle - based on the prevailing national diet of the poor - that provides adequate nutrition for good health and normal activity, plus an allowance for nonfood spending. National poverty lines must be adjusted for inflation between survey years to remain constant in real terms and thus allow for meaningful comparisons of poverty over time. Because diets and consumption baskets change over time, countries periodically recalculate the poverty line based on new survey data. In such cases the new poverty lines should be deflated to obtain comparable poverty estimates from earlier years. The data is based on the two most recent years for which survey data are available.

Survey year is the year in which the underlying household survey data were collected or, when the data collection period bridged two calendar years, the year in which most of the data were collected.


Developmentrelevance: Reducing the cost of remittance transactions has a direct impact on development by freeing additional resources that, instead of being paid as transaction cost, will remain with the senders and receivers of the flows. Remittance cost is highlighted in Sustainable Development Goal 10. Target 10.c calls for reducing to less than 3 percent the transaction costs of migrant remittances and ensure that in no corridor remittance senders are required to pay more than 5 percent by 2030.

IndicatorName: Average transaction cost of sending remittances to a specific country (%)

Limitationsandexceptions: Remittance service providers (RSPs) are excluded when they do not disclose the exchange rate applied to the transaction

Longdefinition: Average transaction cost of sending remittance to a specific country is the average of the total transaction cost in percentage of the amount sent for sending USD 200 charged by each single remittance service provider (RSP) included in the Remittance Prices Worldwide (RPW) database to a specific country.

Periodicity: Quarterly (represented as Annual)

Source: World Bank, Remittance Prices Worldwide, available at http://remittanceprices.worldbank.org

Statisticalconceptandmethodology: The World Bank calculates and tracks the global average cost for sending remittances following each iteration of Remittance Prices Worldwide (RPW). This is intended to provide a tool to track the trend of remittance prices by various policy makers, including measuring progress towards the commitment by the G8 member countries to reduce the cost of remittances by five percentage points over five years (the “5x5 Objective”), as well as the commitment by the G20 member countries to also reduce the global average to 5 percent. The Global Average Total Cost is calculated as the average total cost for sending USD 200 with all remittance service providers (RSPs) worldwide. In other terms, the global average total cost is the simple average of the total cost for sending USD 200 charged by each single RSP included in the RPW database, expressed as the percentage of the amount sent. The regional and national average total costs are calculated using the same methodology used to calculate the Global Average Total Cost. These represent the simple average total cost for sending USD 200 with every single RSP to a specific region of the world (regional), or to a specific country (national). The reference years reflect third quarter data here; for example, data for 2016 refers to data in the third quarter of the year. For all quarterly data, visit http://remittanceprices.worldbank.org.

Topic: Financial Sector: Access


IndicatorName: Average transaction cost of sending remittances from a specific country (%)

Limitationsandexceptions: Remittance service providers (RSPs) are excluded when they do not disclose the exchange rate applied to the transaction.

Longdefinition: Average transaction cost of sending remittance from a specific country is the average of the total transaction cost in percentage of the amount sent for sending USD 200 charged by each single remittance service provider (RSP) included in the Remittance Prices Worldwide (RPW) database from a specific country.

Statisticalconceptandmethodology: The World Bank calculates and tracks the global average cost for sending remittances following each iteration of Remittance Prices Worldwide (RPW). This is intended to provide a tool to track the trend of remittance prices by various policy makers, including measuring progress towards the commitment by the G8 member countries to reduce the cost of remittances by five percentage points over five years (the “5x5 Objective”), as well as the commitment by the G20 member countries to also reduce the global average to 5 percent. The Global Average Total Cost is calculated as the average total cost for sending USD 200 with all remittance service providers (RSPs) worldwide. In other terms, the global average total cost is the simple average of the total cost for sending USD 200 charged by each single RSP included in the RPW database, expressed as the percentage of the amount sent. The regional and national average total costs are calculated using the same methodology used to calculate the Global Average Total Cost. These represent the simple average total cost for sending USD 200 with every single RSP from a specific region of the world (regional), or from a specific country (national). The same applies to other averages such as the G8 average, which calculates the average cost of sending USD 200 from the G8 member countries, or the bank average, which represent the average cost of sending USD 200 with a bank worldwide. The reference years reflect third quarter data here; for example, data for 2016 refers to data in the third quarter of the year. For all quarterly data, visit http://remittanceprices.worldbank.org.


Developmentrelevance: The World Bank Group's goal of promoting shared prosperity has been defined as fostering income growth of the bottom 40 per cent of the welfare distribution in every country.

Generalcomments: The comparability of welfare aggregates (consumption or income) for the chosen years T0 and T1 is assessed for every country. If comparability across the two surveys is a major concern for a country, the selection criteria are re-applied to select the next best survey year(s). Annualized growth rates are calculated between the survey years, using a compound growth formula. The survey years defining the period for which growth rates are calculated and the type of welfare aggregate used to calculate the growth rates are noted in the footnotes.

IndicatorName: Annualized average growth rate in per capita real survey mean consumption or income, bottom 40% of population (%)

Limitationsandexceptions:
The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See the Poverty and Inequality Platform (http://www.pip.worldbank.org) for detailed explanations.

Because household surveys are infrequent in most countries and are not aligned across countries, comparisons across countries or over time should be made with a high degree of caution.

Longdefinition:
The growth rate in the welfare aggregate of the bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the population in  the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1.  The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered.

The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See the Poverty and Inequality Platform for detailed explanations.

Shortdefinition: The growth rate in the welfare aggregate of bottom 40% is computed as the annualized average growth rate in per capita real consumption or income of the bottom 40% of the income distribution in a country from household surveys over a roughly 5-year period.

Source: World Bank, Global Database of Shared Prosperity (GDSP) (http://www.worldbank.org/en/topic/poverty/brief/global-database-of-shared-prosperity).

Topic: Poverty: Shared prosperity


IndicatorName: Annualized average growth rate in per capita real survey mean consumption or income, total population (%)

Longdefinition:
The growth rate in the welfare aggregate of the total population is computed as the annualized average growth rate in per capita real consumption or income of the total population in  the income distribution in a country from household surveys over a roughly 5-year period. Mean per capita real consumption or income is measured at 2011 Purchasing Power Parity (PPP) using the Poverty and Inequality Platform (http://www.pip.worldbank.org). For some countries means are not reported due to grouped and/or confidential data. The annualized growth rate is computed as (Mean in final year/Mean in initial year)^(1/(Final year - Initial year)) - 1.  The reference year is the year in which the underlying household survey data was collected. In cases for which the data collection period bridged two calendar years, the first year in which data were collected is reported. The initial year refers to the nearest survey collected 5 years before the most recent survey available, only surveys collected between 3 and 7 years before the most recent survey are considered.

The coverage and quality of the 2011 PPP price data for Iraq and most other North African and Middle Eastern countries were hindered by the exceptional period of instability they faced at the time of the 2011 exercise of the International Comparison Program. See the Poverty and Inequality Platform for detailed explanations.

Shortdefinition: The growth rate in the welfare aggregate of total population is computed as annualized average growth rate in per capita real consumption or income of total population from household surveys over a roughly 5-year period.


Aggregationmethod: Weighted average

Developmentrelevance:
Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas.

The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment.
Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries.

IndicatorName: Employment in agriculture, female (% of female employment) (modeled ILO estimate)

Limitationsandexceptions:
There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.

Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.

The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectorsdata.

Longdefinition: Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The agriculture sector consists of activities in agriculture, hunting, forestry and fishing, in accordance with division 1 (ISIC 2) or categories A-B (ISIC 3) or category A (ISIC 4).

Source: International Labour Organization, ILOSTAT database. Data as of January 2021.

Statisticalconceptandmethodology:
The International Labour Organization (ILO) classifies economic activity using the International Standard Industrial Classification (ISIC) of All Economic Activities, revision 2 (1968), revision 3 (1990), and revision 4 (2008). Because this classification is based on where work is performed (industry) rather than type of work performed (occupation), all of an enterprise's employees are classified under the same industry, regardless of their trade or occupation. The categories should sum to 100 percent. Where they do not, the differences are due to workers who are not classified by economic activity.

The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available.

Topic: Social Protection & Labor: Economic activity


IndicatorName: Employment in agriculture, male (% of male employment) (modeled ILO estimate)


IndicatorName: Employment in agriculture (% of total employment) (modeled ILO estimate)


Developmentrelevance: The indicator provides information on the proportion of women who are employed in decision-making and management roles in government, large enterprises and institutions.

IndicatorName: Female share of employment in senior and middle management (%)

Longdefinition: The proportion of females in total employment in senior and middle management. It corresponds to major group 1 in both ISCO-08 and ISCO-88 minus category 14 in ISCO-08 (hospitality, retail and other services managers) and minus category 13 in ISCO-88 (general managers), since these comprise mainly managers of small enterprises.

Source: International Labour Organization, ILOSTAT database. Data as of June 2022.


Developmentrelevance:
Breaking down employment information by status in employment provides a statistical basis for describing workers' behaviour and conditions of work, and for defining an individual's socio-economic group. A high proportion of wage and salaried workers in a country can signify advanced economic development. If the proportion of own-account workers (self-employed without hired employees) is sizeable, it may be an indication of a large agriculture sector and low growth in the formal economy. A high proportion of contributing family workers — generally unpaid, although compensation might come indirectly in the form of family income — may indicate weak development, little job growth, and often a large rural economy.

Each status group faces different economic risks, and contributing family workers and own-account workers are the most vulnerable - and therefore the most likely to fall into poverty. They are the least likely to have formal work arrangements, are the least likely to have social protection and safety nets to guard against economic shocks, and often are incapable of generating sufficient savings to offset these shocks.

IndicatorName: Wage and salaried workers, female (% of female employment) (modeled ILO estimate)

Limitationsandexceptions: Data are drawn from labor force surveys and household surveys, supplemented by official estimates and censuses for a small group of countries. Due to differences in definitions and coverage across countries, there are limitations for comparing data across countries and over time even within a country. Estimates of women in employment are not comparable internationally, reflecting that demographic, social, legal, and cultural trends and norms determine whether women's activities are regarded as economic.

Longdefinition: Wage and salaried workers (employees) are those workers who hold the type of jobs defined as "paid employment jobs," where the incumbents hold explicit (written or oral) or implicit employment contracts that give them a basic remuneration that is not directly dependent upon the revenue of the unit for which they work.

Statisticalconceptandmethodology:
The indicator of status in employment distinguishes between two categories of the total employed. These are: (a) wage and salaried workers (also known as employees); and (b) self-employed workers. Self-employed group is broken down in the subcategories: self-employed workers with employees (employers), self-employed workers without employees (own-account workers), members of producers' cooperatives and contributing family workers (also known as unpaid family workers). Vulnerable employment refers to the sum of contributing family workers and own-account workers.

The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available.


IndicatorName: Wage and salaried workers, male (% of male employment) (modeled ILO estimate)


IndicatorName: Wage and salaried workers, total (% of total employment) (modeled ILO estimate)


IndicatorName: Contributing family workers, female (% of female employment) (modeled ILO estimate)

Longdefinition: Contributing family workers are those workers who hold "self-employment jobs" as own-account workers in a market-oriented establishment operated by a related person living in the same household.


IndicatorName: Contributing family workers, male (% of male employment) (modeled ILO estimate)


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.

GDP per person employed is a key measure to monitor whether a country is on track to achieve the Sustainable Development Goal of promoting sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all. [SDG Indicator 8.2.1]

IndicatorName: GDP per person employed (constant 2017 PPP $)

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 in both national currencies and purchasing power parity dollars is not easily available, especially in developing countries, because the definition, coverage, and methodology are not always consistent across countries. For example, countries employ different methodologies for estimating the missing values for the nonmarket service sectors and use different definitions of the informal sector.

Longdefinition: GDP per person employed is gross domestic product (GDP) divided by total employment in the economy. Purchasing power parity (PPP) GDP is GDP converted to 2017 constant international dollars using PPP rates. An international dollar has the same purchasing power over GDP that a U.S. dollar has in the United States.

Source: Derived using data from International Labour Organization, ILOSTAT database. The data retrieved on June 15, 2021.

Statisticalconceptandmethodology: GDP per person employed represents labor productivity — output per unit of labor input. To compare labor productivity levels across countries, GDP is converted to international dollars using purchasing power parity rates which take account of differences in relative prices between countries.


Developmentrelevance:
Sectoral information is particularly useful in identifying broad shifts in employment and stages of development. In the textbook case of economic development, labour flows from agriculture and other labour-intensive primary activities to industry and finally to the services sector; in the process, workers migrate from rural to urban areas.

The breakdown of the indicator by sex allows for analysis of gender segregation of employment by specific sector. Women may be drawn into lower-paying service activities that allow for more flexible work schedules thus making it easier to balance family responsibilities with work life. Segregation of women in certain sectors may also result from cultural attitudes that prevent them from entering industrial employment.

Segregating one sex in a narrow range of occupations significantly reduces economic efficiency by reducing labor market flexibility and thus the economy's ability to adapt to change. This segregation is particularly harmful for women, who have a much narrower range of labor market choices and lower levels of pay than men. But it is also detrimental to men when job losses are concentrated in industries dominated by men and job growth is centered in service occupations, where women have better chances, as has been the recent experience in many countries.

IndicatorName: Employment in industry, female (% of female employment) (modeled ILO estimate)

Limitationsandexceptions:
There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.

Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.

The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of the three broad sectors data.

Longdefinition: Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The industry sector consists of mining and quarrying, manufacturing, construction, and public utilities (electricity, gas, and water), in accordance with divisions 2-5 (ISIC 2) or categories C-F (ISIC 3) or categories B-F (ISIC 4).


IndicatorName: Employment in industry, male (% of male employment) (modeled ILO estimate)


IndicatorName: Employment in industry (% of total employment) (modeled ILO estimate)


Generalcomments: Harmonized series

IndicatorName: Informal employment, female (% of total non-agricultural employment)

Limitationsandexceptions: There are limitations for comparing data across countries and over time even within a country, due to differences in definitions and methodology of data collection. For example, informal sector enterprises refer to non-registered enterprises in some countries but registration requirements can vary from country to country. Others apply the employment size criterion only (which may vary from country to country). For detailed information on definitions and coverage, see footnotes.

Longdefinition: Employment in the informal economy as a percentage of total non-agricultural employment. It basically includes all jobs in unregistered and/or small-scale private unincorporated enterprises that produce goods or services meant for sale or barter. Self-employed street vendors, taxi drivers and home-base workers, regardless of size, are all considered enterprises. However, agricultural and related activities, households producing goods exclusively for their own use (e.g. subsistence farming, domestic housework, care work, and employment of paid domestic workers), and volunteer services rendered to the community are excluded.

Source: International Labour Organization, ILOSTAT database. Data as of September 2020.

Statisticalconceptandmethodology: There are wide variations in definitions and methodology of data collection. In addition to employment in the informal economy, informal employment within the formal sector should be also taken into account. Casual, short term, and seasonal workers, for example, could be informally employed — lacking social protection, health benefits, legal status, rights and freedom of association. Some countries now provide data according to the guidelines, adopted by the 17th International Conference of Labour Statisticians (2003); Informal employment as the total number of informal jobs, whether carried out in formal sector enterprises, informal sector enterprises, or households, during a given reference period.


IndicatorName: Informal employment, male (% of total non-agricultural employment)


IndicatorName: Informal employment (% of total non-agricultural employment)


IndicatorName: Employment in services, female (% of female employment) (modeled ILO estimate)

Limitationsandexceptions:
There are many differences in how countries define and measure employment status, particularly members of the armed forces, self-employed workers, and unpaid family workers. Where members of the armed forces are included, they are allocated to the service sector, causing that sector to be somewhat overstated relative to the service sector in economies where they are excluded. Where data are obtained from establishment surveys, data cover only employees; thus self-employed and unpaid family workers are excluded. In such cases the employment share of the agricultural sector is severely underreported. Caution should be also used where the data refer only to urban areas, which record little or no agricultural work. Moreover, the age group and area covered could differ by country or change over time within a country. For detailed information, consult the original source.

Countries also take different approaches to the treatment of unemployed people. In most countries unemployed people with previous job experience are classified according to their last job. But in some countries the unemployed and people seeking their first job are not classifiable by economic activity. Because of these differences, the size and distribution of employment by economic activity may not be fully comparable across countries.

The ILO reports data by major divisions of the ISIC revision 2, revision 3, or revision 4. Broad classification such as employment by agriculture, industry, and services may obscure fundamental shifts within countries' industrial patterns. A slight majority of countries report economic activity according to the ISIC revision 3 instead of revision 2 or revision 4. The use of one classification or the other should not have a significant impact on the information for the employment of three broad sectors data.

Longdefinition: Employment is defined as persons of working age who were engaged in any activity to produce goods or provide services for pay or profit, whether at work during the reference period or not at work due to temporary absence from a job, or to working-time arrangement. The services sector consists of 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, in accordance with divisions 6-9 (ISIC 2) or categories G-Q (ISIC 3) or categories G-U (ISIC 4).


IndicatorName: Employment in services, male (% of male employment) (modeled ILO estimate)


IndicatorName: Employment in services (% of total employment) (modeled ILO estimate)


Developmentrelevance: In most countries more boys are involved in employment, or the gender difference is small. However, girls are often more present in hidden or underreported forms of employment such as domestic service, and in almost all societies girls bear greater responsibility for household chores in their own homes, work that lies outside the System of National Accounts production boundary and is thus not considered in estimates of children's employment.

IndicatorName: Children in employment, female (% of female children ages 7-14)

Limitationsandexceptions: Although efforts are made to harmonize the definition of employment and the questions on employment in survey questionnaires, significant differences remain in the survey instruments that collect data on children in employment and in the sampling design underlying the surveys. Differences exist not only across different household surveys in the same country but also across the same type of survey carried out in different countries, so estimates of working children are not fully comparable across countries. For detailed source information, see footnotes at each data point.

Longdefinition: Children in employment refer to children involved in economic activity for at least one hour in the reference week of the survey.

Source: Understanding Children's Work project based on data from ILO, UNICEF and the World Bank.

Statisticalconceptandmethodology:
Data are from household surveys by the International Labor Organization (ILO), the United Nations Children's Fund (UNICEF), the World Bank, and national statistical offices. The surveys yield data on education, employment, health, expenditure, and consumption indicators related to children's work. Since children's work is captured in the sense of "economic activity," the data refer to children in employment, a broader concept than child labor (see ILO 2009a for details on this distinction).

Household survey data generally include information on work type - for example, whether a child is working for payment in cash or in kind or is involved in unpaid work, working for someone who is not a member of the household, or involved in any type of family work (on the farm or in a business).

In line with the definition of economic activity adopted by the 13th International Conference of Labour Statisticians, the threshold set by the 1993 UN System of National Accounts for classifying a person as employed is to have been engaged at least one hour in any activity relating to the production of goods and services during the reference period. Children seeking work are thus excluded. Economic activity covers all market production and certain nonmarket production, including production of goods for own use. It excludes unpaid household services (commonly called "household chores") - that is, the production of domestic and personal services by household members for a household's own consumption.

Country surveys define the ages for child labor as 5-17. The data here have been recalculated to present statistics for children ages 7-14.


IndicatorName: Children in employment, male (% of male children ages 7-14)


IndicatorName: Children in employment, total (% of children ages 7-14)


Developmentrelevance:
Paradoxically, low unemployment rates can disguise substantial poverty in a country, while high unemployment rates can occur in countries with a high level of economic development and low rates of poverty. In countries without unemployment or welfare benefits people eke out a living in vulnerable employment. In countries with well-developed safety nets workers can afford to wait for suitable or desirable jobs. But high and sustained unemployment indicates serious inefficiencies in resource allocation.

Youth unemployment is an important policy issue for many economies. Young men and women today face increasing uncertainty in their hopes of undergoing a satisfactory transition in the labour market, and this uncertainty and disillusionment can, in turn, have damaging effects on individuals, communities, economies and society at large. Unemployed or underemployed youth are less able to contribute effectively to national development and have fewer opportunities to exercise their rights as citizens. They have less to spend as consumers, less to invest as savers and often have no "voice" to bring about change in their lives and communities. Widespread youth unemployment and underemployment also prevents companies and countries from innovating and developing competitive advantages based on human capital investment, thus undermining future prospects.

Unemployment is a key measure to monitor whether a country is on track to achieve the Sustainable Development Goal of promoting sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all. [SDG Indicator 8.5.2]

Generalcomments: The series for ILO estimates is also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

IndicatorName: Unemployment, youth female (% of female labor force ages 15-24) (national estimate)

Limitationsandexceptions:
The criteria for people considered to be seeking work, and the treatment of people temporarily laid off or seeking work for the first time, vary across countries. In many cases it is especially difficult to measure employment and unemployment in agriculture. The timing of a survey can maximize the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.

There may be also persons not currently in the labour market who want to work but do not actively "seek" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. The exclusion of people who want to work but are not seeking work (often called the "hidden unemployed" or "discouraged workers") is a criterion that will affect the unemployment count of both women and men.

However, women tend to be excluded from the count for various reasons. Women suffer more from discrimination and from structural, social, and cultural barriers that impede them from seeking work. Also, women are often responsible for the care of children and the elderly and for household affairs. They may not be available for work during the short reference period, as they need to make arrangements before starting work. Further, women are considered to be employed when they are working part-time or in temporary jobs, despite the instability of these jobs or their active search for more secure employment.

Longdefinition: Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.

Statisticalconceptandmethodology:
The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or who have voluntarily left work. Persons who did not look for work but have an arrangements for a future job are also counted as unemployed.

Some unemployment is unavoidable. At any time some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. It is the labour force or the economically active portion of the population that serves as the base for this indicator, not the total population.

Topic: Social Protection & Labor: Unemployment


Generalcomments: National estimates are also available in the WDI database. Caution should be used when comparing ILO estimates with national estimates.

IndicatorName: Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate)

Longdefinition: Youth unemployment refers to the share of the labor force ages 15-24 without work but available for and seeking employment.

Statisticalconceptandmethodology:
The standard definition of unemployed persons is those individuals without work, seeking work in a recent past period, and currently available for work, including people who have lost their jobs or who have voluntarily left work. Persons who did not look for work but have an arrangements for a future job are also counted as unemployed.

Some unemployment is unavoidable. At any time some workers are temporarily unemployed between jobs as employers look for the right workers and workers search for better jobs. It is the labour force or the economically active portion of the population that serves as the base for this indicator, not the total population.

The series is part of the ILO estimates and is harmonized to ensure comparability across countries and over time by accounting for differences in data source, scope of coverage, methodology, and other country-specific factors. The estimates are based mainly on nationally representative labor force surveys, with other sources (population censuses and nationally reported estimates) used only when no survey data are available.


IndicatorName: Unemployment, youth male (% of male labor force ages 15-24) (national estimate)


IndicatorName: Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate)


IndicatorName: Unemployment, youth total (% of total labor force ages 15-24) (national estimate)


IndicatorName: Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate)


Developmentrelevance:
Unemployment and total employment are the broadest indicators of economic activity as reflected by the labor market. The International Labour Organization(ILO) defines the unemployed as members of the economically active population who are without work but available for and seeking work, including people who have lost their jobs or who have voluntarily left work. Some unemployment is unavoidable. At any time some workers are temporarily unemployed - between jobs as employers look for the right workers and workers search for better jobs. Such unemployment, often called frictional unemployment, results from the normal operation of labor markets.

Youth unemployment is an important policy issue for many economies. Young men and women today face increasing uncertainty in their hopes of undergoing a satisfactory transition in the labour market, and this uncertainty and disillusionment can, in turn, have damaging effects on individuals, communities, economies and society at large. Unemployed or underemployed youth are less able to contribute effectively to national development and have fewer opportunities to exercise their rights as citizens. They have less to spend as consumers, less to invest as savers and often have no "voice" to bring about change in their lives and communities. Widespread youth unemployment and underemployment also prevents companies and countries from innovating and developing competitive advantages based on human capital investment, thus undermining future prospects.

The NEET group is particularly at risk of both labour market and social exclusion, because this group is neither improving their future employability through investment in skills nor gaining experience through employment, . In addition, the NEET group is already in a disadvantaged position due to lower levels of education and lower household incomes. In view of the fact that the NEET group includes unemployed youth as well as economically inactive youth, the NEET rate provides important complementray information to labour force participation rates and unemploymenent rates. For example, if youth participation rates decrease during an economic downturn due to discouragement, this may be reflected in an upward movement in the NEET rate. More generally, a high NEET rate and a low youth unemployment may indicate significant discouragement of young people. A high NEET rate for young women suggests their engagement in household chores, and/or the presence of strong institutional barriers limiting female participation in labour markets.

IndicatorName: Share of youth not in education, employment or training, female (% of female youth population)

Limitationsandexceptions: Data should be used cautiously because of differences in age coverage.

Longdefinition: Share of youth not in education, employment or training (NEET) is the proportion of young people who are not in education, employment, or training to the population of the corresponding age group: youth (ages 15 to 24); persons ages 15 to 29; or both age groups.

Statisticalconceptandmethodology:
The standard definition of unemployed persons is those individuals without work in a recent past period, and currently available for and seeking for employment. But there may be persons who do not actively "seek" work because they view job opportunities as limited, or because they have restricted labour mobility, or face discrimination, or structural, social or cultural barriers. NEET rates capture more broadly untapped potential youth, including such individuals who want to work but are not seeking work (often called the "hidden unemployed" or "discouraged workers").

Youth are defined as persons ages 15 to 24; young adults are those ages 25 to 29; and adults are those ages 25 and above. However, countries vary somewhat in their operational definitions. In particular, the lower age limit for young people is usually determined by the minimum age for leaving school, where this exists. When data are available for more than two age groups in a given year, one value for persons ages 15 to 29 is taken, considering that not all people complete their education by the age of 24.


IndicatorName: Share of youth not in education, employment or training, male (% of male youth population)


IndicatorName: Share of youth not in education, employment or training, total (% of youth population)


IndicatorName: Unemployment, female (% of female labor force) (national estimate)

Longdefinition: Unemployment refers to the share of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country.


IndicatorName: Unemployment, female (% of female labor force) (modeled ILO estimate)

Longdefinition: Unemployment refers to the share of the labor force that is without work but available for and seeking employment.


IndicatorName: Unemployment, male (% of male labor force) (national estimate)


IndicatorName: Unemployment, male (% of male labor force) (modeled ILO estimate)


IndicatorName: Unemployment, total (% of total labor force) (national estimate)


IndicatorName: Unemployment, total (% of total labor force) (modeled ILO estimate)


Developmentrelevance: Good nutrition is the cornerstone for survival, health and development. Well-nourished children perform better in school, grow into healthy adults and in turn give their children a better start in life. Well-nourished women face fewer risks during pregnancy and childbirth, and their children set off on firmer developmental paths, both physically and mentally (UNICEF www.childinfo.org).

Generalcomments: This is the Sustainable Development Goal indicator 2.1.1[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Prevalence of undernourishment (% of population)

Limitationsandexceptions: From a policy and program standpoint, this measure has its limits. First, food insecurity exists even where food availability is not a problem because of inadequate access of poor households to food. Second, food insecurity is an individual or household phenomenon, and the average food available to each person, even corrected for possible effects of low income, is not a good predictor of food insecurity among the population. And third, nutrition security is determined not only by food security but also by the quality of care of mothers and children and the quality of the household's health environment (Smith and Haddad 2000).

Longdefinition: Prevalence of undernourishments is the percentage of the population whose habitual food consumption is insufficient to provide the dietary energy levels that are required to maintain a normal active and healthy life. Data showing as 2.5 may signify a prevalence of undernourishment below 2.5%.

Source: Food and Agriculture Organization (http://www.fao.org/faostat/en/#home).

Statisticalconceptandmethodology: Data on undernourishment are from the Food and Agriculture Organization (FAO) of the United Nations and measure food deprivation based on average food available for human consumption per person, the level of inequality in access to food, and the minimum calories required for an average person.

Topic: Health: Nutrition


Developmentrelevance:
Food insecurity at moderate levels of severity is typically associated with the inability to regularly eat healthy, balanced diets. As such, high prevalence of food insecurity at moderate levels can be considered a predictor of various forms of diet-related health conditions in the population, associated with micronutrient deficiency and unbalanced diets. Severe levels of food insecurity, on the other hand, imply a high probability of reduced food intake and therefore can lead to more severe forms of undernutrition, including hunger. FAO has identified the FIES as the tool with the greatest potential for becoming a global standard capable of providing comparable information on food insecurity experience across countries and population groups to track progress on reducing food insecurity and
hunger

IndicatorName: Prevalence of moderate or severe food insecurity in the population (%)

Longdefinition: The percentage of people in the population who live in households classified as moderately or severely food insecure. A household is classified as moderately or severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to low quality diets and might have been forced to also reduce the quantity of food they would normally eat because of a lack of money or other resources.

Source: Food and Agriculture Organization of the United Nations (FAO)

Statisticalconceptandmethodology: The assessment is conducted using data collected with the Food Insecurity Experience Scale or a compatible experience-based food security measurement questionnaire (such as the HFSSM). The probability to be food insecure is estimated using the one-parameter logistic Item Response Theory model (the Rasch model) and thresholds for classification are made cross country comparable by calibrating the metrics obtained in each country against the FIES global reference scale, maintained by FAO. The threshold to classify "moderate or severe" food insecurity corresponds to the severity associated with the item "having to eat less" on the global FIES scale. It is an indicator of lack of food access.The indicator is calculated as an average over 3 years (eg. data for 2015 is the average of 2014-2016 data).

Topic: Health


IndicatorName: Prevalence of severe food insecurity in the population (%)

Longdefinition: The percentage of people in the population who live in households classified as severely food insecure. A household is classified as severely food insecure when at least one adult in the household has reported to have been exposed, at times during the year, to several of the most severe experiences described in the FIES questions, such as to have been forced to reduce the quantity of the food, to have skipped meals, having gone hungry, or having to go for a whole day without eating because of a lack of money or other resources.

Statisticalconceptandmethodology: The assessment is conducted using data collected with the Food Insecurity Experience Scale or a compatible experience-based food security measurement questionnaire (such as the HFSSM). The probability to be food insecure is estimated using the one-parameter logistic Item Response Theory model (the Rasch model) and thresholds for classification are made cross country comparable by calibrating the metrics obtained in each country against the FIES global reference scale, maintained by FAO. The threshold to classify "severe" food insecurity corresponds to the severity associated with the item "having not eaten for an entire day" on the global FIES scale. It is an indicator of lack of food access.The indicator is calculated as an average over 3 years (eg. data for 2015 is the average of 2014-2016 data).


Generalcomments: This is the Sustainable Development Goal indicator 3.7.2 [https://unstats.un.org/sdgs/metadata/].

IndicatorName: Adolescent fertility rate (births per 1,000 women ages 15-19)

Longdefinition: Adolescent fertility rate is the number of births per 1,000 women ages 15-19.

Source: United Nations Population Division, World Population Prospects.

Statisticalconceptandmethodology:
Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. Means of achieving reproductive health include education and services during pregnancy and childbirth, safe and effective contraception, and prevention and treatment of sexually transmitted diseases. Complications of pregnancy and childbirth are the leading cause of death and disability among women of reproductive age in developing countries.

Adolescent fertility rates are based on data on registered live births from vital registration systems or, in the absence of such systems, from censuses or sample surveys. The estimated rates are generally considered reliable measures of fertility in the recent past. Where no empirical information on age-specific fertility rates is available, a model is used to estimate the share of births to adolescents. For countries without vital registration systems fertility rates are generally based on extrapolations from trends observed in censuses or surveys from earlier years.

Topic: Health: Reproductive health


Developmentrelevance: Although the legal age of marriage is defined as 18 years in most countries, the practice of child marriage remains widespread.  A women’s access to education and later her employment opportunities as well as the nature and terms of her work are often compromised by this practice.  Young married girls whose schooling is cut short often lack the knowledge and skills for formal work and are limited to occupations with lower incomes and inferior working conditions.  Sustainable Development Goal 5 commits to eliminate the practice of child marriage.

Generalcomments: This is the Sustainable Development Goal indicator 5.3.1[https://unstats.un.org/sdgs/metadata/].

IndicatorName: Women who were first married by age 15 (% of women ages 20-24)

Longdefinition: Women who were first married by age 15 refers to the percentage of women ages 20-24 who were first married by age 15.

Source: UNICEF Data; Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS), AIDS Indicator Surveys(AIS), Reproductive Health Survey(RHS), and other household surveys.

Topic: Gender: Agency


IndicatorName: Women who were first married by age 18 (% of women ages 20-24)

Longdefinition: Women who were first married by age 18 refers to the percentage of women ages 20-24 who were first married by age 18.


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: Researchers in R&D (per million people)

Limitationsandexceptions: Estimates of the resources allocated to R&D are affected by national characteristics such as the periodicity and coverage of national R&D surveys across institutional sectors and industries; and the use of different sampling and estimation methods. R&D typically involves a few large performers, hence R&D surveys use various techniques to maintain up-to-date registers of known performers, while attempting to identify new or occasional performers.

Longdefinition: The number of researchers engaged in Research &Development (R&D), expressed as per million. Researchers are professionals who conduct research and improve or develop concepts, theories, models techniques instrumentation, software of operational methods. R&D covers basic research, applied research, and experimental development.

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

Statisticalconceptandmethodology:
Researchers are professionals engaged in the conception or creation of new knowledge, products, processes, methods and systems, as well as in the management of these projects. Students studying at the master’s or doctoral level (ISCED2011 level 7 or 8) engaged in R&D are included.

The OECD's Frascati Manual defines research and experimental development as "creative work undertaken on a systemic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications." R&D covers basic research, applied research, and experimental development.

(1) Basic research - Basic research is experimental or theoretical work undertaken primarily to acquire new knowledge of the underlying foundation of phenomena and observable facts, without any particular application or use in view.

(2) Applied research - Applied research is also original investigation undertaken in order to acquire new knowledge; it is, however, directed primarily towards a specific practical aim or objective.

(3) Experimental development - Experimental development is systematic work, drawing on existing knowledge gained from research and/or practical experience, which is directed to producing new materials, products or devices, to installing new processes, systems and services, or to improving substantially those already produced or installed.

The fields of science and technology used to classify R&D according to the Revised Fields of Science and Technology Classification are:
1. Natural sciences;
2. Engineering and technology;
3. Medical and health sciences;
4. Agricultural sciences;
5. Social sciences;
6. Humanities and the arts.

Data are for full-time equivalent (FTE); the FTE of R&D personnel is defined as the ratio of working hours actually spent on R&D during a specific reference period (usually a calendar year) divided by the total number of hours conventionally worked in the same period by an individual or by a group.

The data are obtained through statistical surveys which are regularly conducted at national level covering R&D performing entities in the private and public sectors.

Topic: Infrastructure: Technology


IndicatorName: Completeness of birth registration, female (%)

Longdefinition: Completeness of birth registration is the percentage of children under age 5 whose births were registered at the time of the survey. The numerator of completeness of birth registration includes children whose birth certificate was seen by the interviewer or whose mother or caretaker says the birth has been registered.

Source: UNICEF's State of the World's Children based mostly on household surveys and ministry of health data.

Statisticalconceptandmethodology:
Health systems - the combined arrangements of institutions and actions whose primary purpose is to promote, restore, or maintain health (World Health Organization, World Health Report 2000) - are increasingly being recognized as key to combating disease and improving the health status of populations. The World Bank's Healthy Development: Strategy for Health, Nutrition, and Population Results emphasizes the need to strengthen health systems, which are weak in many countries, in order to increase the effectiveness of programs aimed at reducing specific diseases and further reduce morbidity and mortality. To evaluate health systems, the World Health Organization (WHO) has recommended that key components - such as financing, service delivery, workforce, governance, and information - be monitored using several key indicators. The data are a subset of the key indicators. Monitoring health systems allows the effectiveness, efficiency, and equity of different health system models to be compared. Health system data also help identify weaknesses and strengths and areas that need investment, such as additional health facilities, better health information systems, or better trained human resources.

Numerous indicators have been proposed to assess a country's health information system.They can be grouped into two broad types: indicators related to data generation using core sources and methods (health surveys, civil registration, censuses, facility reporting, health system resource tracking) and indicators related to capacity for data synthesis, analysis, and validation. Indicators related to data generation reflect a country's capacity to collect relevant data at suitable intervals using the most appropriate data sources. Benchmarks include periodicity, timeliness, contents, and availability. Indicators related to capacity for synthesis, analysis, and validation measure the dimensions of the institutional frameworks needed to ensure data quality, including independence, transparency, and access. Benchmarks include the availability of independent coordination mechanisms and micro- and meta-data. Indicators related to data generation include completeness of birth registration.

Birth registration refers to the permanent and official recording of a child's existence by some administrative levels of the State that is normally coordinated by a particular branch of the government.

Completeness of birth registration indicator is related to the group of indictors of data generation.

Topic: Health: Population: Dynamics


IndicatorName: Completeness of birth registration, male (%)


IndicatorName: Completeness of birth registration, rural (%)


IndicatorName: Completeness of birth registration, urban (%)


IndicatorName: Completeness of birth registration (%)


Developmentrelevance:
Explosive growth of cities globally signifies the demographic transition from rural to urban, and is associated with shifts from an agriculture-based economy to mass industry, technology, and service.

In principle, cities offer a more favorable setting for the resolution of social and environmental problems than rural areas. Cities generate jobs and income, and deliver education, health care and other services. Cities also present opportunities for social mobilization and women's empowerment.

IndicatorName: Urban population growth (annual %)

Limitationsandexceptions:
There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.

Most countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries.

Estimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.

Because the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution.

Longdefinition: Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects.

Source: World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.

Statisticalconceptandmethodology:
Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. To estimate urban populations, UN ratios of urban to total population were applied to the World Bank's estimates of total population.

Countries differ in the way they classify population as "urban" or "rural." The population of a city or metropolitan area depends on the boundaries chosen.

Topic: Environment: Density & urbanization


Aggregationmethod: Sum

IndicatorName: Urban population

Limitationsandexceptions:
Aggregation of urban and rural population may not add up to total population because of different country coverage. There is no consistent and universally accepted standard for distinguishing urban from rural areas, in part because of the wide variety of situations across countries.

Most countries use an urban classification related to the size or characteristics of settlements. Some define urban areas based on the presence of certain infrastructure and services. And other countries designate urban areas based on administrative arrangements. Because of national differences in the characteristics that distinguish urban from rural areas, the distinction between urban and rural population is not amenable to a single definition that would be applicable to all countries.

Estimates of the world's urban population would change significantly if China, India, and a few other populous nations were to change their definition of urban centers.

Because the estimates of city and metropolitan area are based on national definitions of what constitutes a city or metropolitan area, cross-country comparisons should be made with caution.

Longdefinition: Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.


IndicatorName: Urban population (% of total population)

Longdefinition: Urban population refers to people living in urban areas as defined by national statistical offices. The data are collected and smoothed by United Nations Population Division.

Source: United Nations Population Division. World Urbanization Prospects: 2018 Revision.

Statisticalconceptandmethodology:
Urban population refers to people living in urban areas as defined by national statistical offices. The indicator is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects.

Percentages urban are the numbers of persons residing in an area defined as ''urban'' per 100 total population. They are calculated by the Statistics Division of the United Nations Department of Economic and Social Affairs. Particular caution should be used in interpreting the figures for percentage urban for different countries.

Countries differ in the way they classify population as "urban" or "rural." The population of a city or metropolitan area depends on the boundaries chosen.


IndicatorName: Merchandise trade (% of GDP)

Longdefinition: Merchandise trade as a share of GDP is the sum of merchandise exports and imports divided by the value of GDP, all in current U.S. dollars.

Source: World Trade Organization, and World Bank GDP estimates.

Topic: Private Sector & Trade: Total merchandise trade


IndicatorName: Tariff rate, applied, simple mean, manufactured products (%)

Longdefinition: Simple mean applied tariff is the unweighted average of effectively applied rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of simple mean tariffs. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68.

Shortdefinition: Simple mean applied tariff is the unweighted average of effectively applied rates for all products subject to tariffs calculated for all traded goods. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68.

Source: World Bank staff estimates using the World Integrated Trade Solution system, based on data from United Nations Conference on Trade and Development's Trade Analysis and Information System (TRAINS) database and the World Trade Organization’s (WTO) Integrated Data Base (IDB) and Consolidated Tariff Schedules (CTS) database.

Topic: Private Sector & Trade: Tariffs


IndicatorName: Tariff rate, applied, weighted mean, manufactured products (%)

Longdefinition: Weighted mean applied tariff is the average of effectively applied rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of weighted mean tariffs. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68.

Shortdefinition: Weighted mean applied tariff is the average of effectively applied rates weighted by the product import shares corresponding to each partner country. Manufactured products are commodities classified in SITC revision 3 sections 5-8 excluding division 68.


Developmentrelevance:
Poor people in developing countries work primarily in agriculture and labor-intensive manufactures, sectors that confront the greatest trade barriers. Removing barriers to merchandise trade could increase growth in these countries - even more if trade in services were also liberalized.

In general, tariffs in high-income countries on imports from developing countries, though low, are twice those collected from other high-income countries. But protection is also an issue for developing countries, which maintain high tariffs on agricultural commodities, labor-intensive manufactures, and other products and services.

Countries use a combination of tariff and nontariff measures to regulate imports. The most common form of tariff is an ad valorem duty, based on the value of the import, but tariffs may also be levied on a specific, or per unit, basis or may combine ad valorem and specific rates. Tariffs may be used to raise fiscal revenues or to protect domestic industries from foreign competition - or both. Nontariff barriers, which limit the quantity of imports of a particular good, include quotas, prohibitions, licensing schemes, export restraint arrangements, and health and quarantine measures. Because of the difficulty of combining nontariff barriers into an aggregate indicator, they are not included in the data.

Some countries set fairly uniform tariff rates across all imports. Others are selective, setting high tariffs to protect favored domestic industries. The effective rate of protection - the degree to which the value added in an industry is protected - may exceed the nominal rate if the tariff system systematically differentiates among imports of raw materials, intermediate products, and finished goods.

IndicatorName: Tariff rate, applied, simple mean, all products (%)

Longdefinition: Simple mean applied tariff is the unweighted average of effectively applied rates for all products subject to tariffs calculated for all traded goods. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of simple mean tariffs.

Statisticalconceptandmethodology: Simple averages are often a better indicator of tariff protection than weighted averages, which are biased downward because higher tariffs discourage trade and reduce the weights applied to these tariffs.


IndicatorName: Tariff rate, applied, weighted mean, all products (%)

Longdefinition: Weighted mean applied tariff is the average of effectively applied rates weighted by the product import shares corresponding to each partner country. Data are classified using the Harmonized System of trade at the six- or eight-digit level. Tariff line data were matched to Standard International Trade Classification (SITC) revision 3 codes to define commodity groups and import weights. To the extent possible, specific rates have been converted to their ad valorem equivalent rates and have been included in the calculation of weighted mean tariffs. Import weights were calculated using the United Nations Statistics Division's Commodity Trade (Comtrade) database. Effectively applied tariff rates at the six- and eight-digit product level are averaged for products in each commodity group. When the effectively applied rate is unavailable, the most favored nation rate is used instead.