Name: Gender Statistics
Creator: World Bank Group
Published: 2010-07-19

The BOOST initiative is a Bank-wide collaborative effort launched in 2010 to facilitate access to budget data and promote effective use for improved decision-making processes, transparency and accountability.

BOOST - Public Expenditure Database

This collection contains datasets that may be useful for analysis, response or modelling for the Coronavirus (COVID-19) pandemic.

Coronavirus (COVID-19) Related Datasets

The Data360 initiative aims to integrate high-value data and knowledge curated in the Bank’s verticals into a user-centered data platform. 

Data 360

The Development Data Partnership platform facilitates formation of public-private partnerships for solving development challenges with technology. Specifically, the Development Data Partnership Working Group organizes opportunities for WBG staff to work with technology companies who offer pro-bono data and resources.

Development Data Partnership

This collection contains discrepancy indexes for UN COMTRADE data that aims to capture both the frequency of missed reporting and its impact on overall recorded trade value

Discrepancy Index

A collection of datasets produced through partnership between the World Bank and the European Space Agency (ESA) Earth Observation for Sustainable Development (EO4SD) initiative.

Earth Observation for Sustainable Development

Open data and analytics for a sustainable energy future.

Energy Data Info

This collection features datasets to support building policies, institutions and investments for inclusive and sustainable growth.

Equitable Growth, Finance and Institutions

Project Page: https://worldbank.github.io/GEEST/README.html 

As part of the “Geospatial Assessment of Women Employment and Business Opportunities in the Energy Sector” project, open-source Gender-related spatial data was collected for 31 Small Island Developing States (SIDS) across the globe, resulting in curated and thoroughly documented geodatabases (GDBs) that are now ready to be explored! 
Fifty-nine spatial layers were identified and then researched for each country, covering the following categories: Demographics and Population | Renewable Energy | Energy Access | Education | Jobs and Finance | Digital Inclusion | Transportation | Safety | Amenities | Climate/Earth | Law/Policy/Government. 


However, not every country GDB contains all 59 data layers, as this was dependent on the availability of open-source data in each SIDS. Users are encouraged to check the accompanying metadata excel file for more information on the datasets in each GDB, the vintage, and the

Gender Spatial Data - Small Island States

A collection of datasets that contain geospatial data. These datasets have one or more resources in a geospatial data format.

Geospatial Datasets

Collection of useful datasets from IMF made available to Bank staff via <a href=http://mydatabank.worldbank.org>myDataBank</a>

IMF Dataset

A collection of datasets to help finance the global infrastructure gap.

Infrastructure Finance Datasets

Data and dataset subscriptions managed by the Library Network on agriculture, business, economics, energy, finance, health, risk, water, and more..

Library Databases

The LinkedIn-World Bank partnership offers data to help governments and researchers understand rapidly evolving labor markets with detailed and dynamic data. It allows leaders to benchmark and compare labor markets across the world; analyze skills, occupations, migration, and industries; and leverage real-time data to make policy changes.Visualizations for many of these data are available at <a href=https://linkedindata.worldbank.org/>linkedindata.worldbank.org</a>

LinkedIn Data for Development

Collection of merchandise trade data available to World Bank staff.

Merchandise Trade Data

This collection includes datasets associated with research organized under the Bank, <a href=http://prwp.worldbank.org target='_blank' title='Opens in a new window'>Policy Research Working Papers</a>.

Policy Research Working Papers

This collection contains data on disaster and climate risk assessments curated by the Global Facility for Disaster Reduction and Recovery (GFDRR).

Risk Data Library

This collection presents software tools and models developed by the World Bank to support monitoring, planning, programming and the economic evaluation of roads and highways works.

Road Software Tools

This spatial database, a product of the South Asia Region Chief Economist's (SARCE) Office, presents data collected from official sources and harmonized into different spatial levels. Data includes economic and environmental data across 12 topic areas, and includes data from four countries in South Asia (Bangladesh, Bhutan, India, and Nepal) for both 2001 and 2011.

SARCE Spatial Database

A collection of country Small Area Estimation (SAE) and Poverty Mapping that contains papers, shapefiles, and datasets produced through partnerships between the World Bank and country statistics offices.

Small area estimates / Poverty mapping

This collection consists of datasets compiled and created by the World Bank Data Lab in response to a request by the Syria Economic Monitor Team to explore alternative data sources to better understand changing trends in trade and economic activity, focusing on: surface cross-border transport routes, changes in observed agricultural production, observed nighttime lights, and reported conflict.

Syria Economic Monitor

A collection of relevant datasets to support operations in Ukraine.

Ukraine datasets

Catalogue lists all the data produced under the partnership contracts between the World Bank Group and the European Space Agency

World Bank (WBG) - European Space Agency (ESA) Database

A collection of datasets to help achieve universal access to reliable and fast internet services for all.

World Bank Digital Development Data

A collection of datasets to help achieve sustainable energy for all.

World Bank Energy Datasets

A collection of datasets to help achieve sustainable mobility for all.

World Bank Transport Data

From Data to a Water-Secure World for All. World Bank Water Data surrounding the three pillars of Sustain Water Resources, Deliver Services and Build Resilience.

World Bank Water Data

The World Development Report 2021: Data for Better Lives explores the tremendous potential of the changing data landscape to improve the lives of poor people, while also acknowledging its potential to open back doors that can harm individuals, businesses, and societies. To address this tension between the helpful and harmful potential of data, this Report calls for a new social contract that enables the use and reuse of data to create economic and social value, ensures equitable access to that value, and fosters trust that data will not be misused in harmful ways. The data used in the WDR2021 are curated as a collection here.

World Development Report 2021

The World Development Report 2022: Finance for an Equitable Recovery examines the central role of finance in the economic recovery from the COVID-19 pandemic. In doing so, it looks into the consequences of the crisis most likely to affect emerging economies and proposes a set of policies to mitigate the interconnected financial risks stemming from the pandemic and to steer economies toward a sustainable and equitable recovery. The data used in the WDR2022 are curated as a collection here.

World Development Report 2022

The World Settlement Footprint Collection includes country datasets describing the evolution of the built-area across the globe at a ~30m resolution.

World Settlement Footprint

Resources, family organization, and domestic violence against married women in Minya, Egypt

Promoting gender equality in the context of Nigerian cultural and religious expression: beyond increasing female access to education

Gender equity and womens contraception use

Universal womens rights since 1970: The centrality of autonomy and agency

Asian families at the crossroads: A meeting of east, west, tradition, modernity, and gender

Can concern for the long-term care of older parents explain son preference at birth in India?

Feminizing leadership in Arab societies: the perspectives of Omani female leaders

Womens family power and gender preference in Minya, Egypt

Community Services and Out-Migration

Foreign banks: executive jobs for Turkish women?

Domestic violence in urban Filipino families

Couples joint decision-making: the construction and validation of a key proxy for understanding gender relations in contemporary families

Gender, aging, and the evolving Arab patriarchal contract

Gender Analysis of the Policy Responses to High Oil Prices: A Case Study of South Africa

The percentage of respondents who report borrowing any money for health or medical purposes in the past 12 months, female (% age 15+).

The percentage of respondents who report borrowing any money to start, operate, or expand a farm or business in the past 12 months, male (% age 15+).

The percentage of respondents who report borrowing any money to start, operate, or expand a farm or business in the past 12 months, female (% age 15+)

The percentage of respondents who report borrowing any money from a store by using installment credit or buying on credit in the past 12 months

The percentage of respondents who report borrowing any money for education or school fees in the past 12 months

The percentage of respondents who report borrowing any money for education or school fees in the past 12 months, male (% age 15+).

The percentage of respondents who report borrowing any money from a bank or another type of financial institution in the past 12 months

The percentage of respondents who report borrowing any money from a bank or another type of financial institution in the past 12 months, male (% age 15+).

The percentage of respondents who report borrowing any money from a bank or another type of financial institution, or using a credit card, in the past 12 months, male (% age 15+).

The percentage of respondents who report borrowing any money from a bank or another type of financial institution, or using a credit card, in the past 12 months, female (% age 15+)

The percentage of respondents who report borrowing any money from family, relatives, or friends in the past 12 months, male (% age 15+).

The percentage of respondents who report borrowing any money from family, relatives, or friends in the past 12 months, female (% age 15+)

The percentage of respondents who report borrowing any money (by themselves or together with someone else) for any reason and from any source in the past 12 months, female (% age 15+)

The percentage of respondents who report that in case of an emergency it is possible for them to come up with 1/20 of gross national income (GNI) per capita in local currency within the next month

The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution.

The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution, male (% age 15+).

The percentage of respondents who report having an account (by themselves or together with someone else) at a bank or another type of financial institution,female (% age 15+).

The percentage of respondents who report using the internet to pay bills in the past 12 months, female (% age 15+).

The percentage of respondents who report using the internet to pay bills or buy something online in the past 12 months, male (% age 15+).

The percentage of respondents who report using the internet to buy something online in the past 12 months, male (% age 15+).

The percentage of respondents who report saving or setting aside any money at a bank or another type of financial institution in the past 12 months.

The percentage of respondents who report saving or setting aside any money in the past 12 months by using an informal savings club or a person outside the family.

The percentage of respondents who report saving or setting aside any money in the past 12 months by using an informal savings club or a person outside the family, male (% age 15+).

The percentage of respondents who report saving or setting aside any money in the past 12 months by using an informal savings club or a person outside the family, female (% age 15+).

The percentage of respondents who report saving or setting aside any money in the past 12 months for education or school fee.

The percentage of respondents who report saving or setting aside any money in the past 12 months for education or school fee, male (% age 15+).

The percentage of respondents who report personally saving or setting aside any money for any reason and using any mode of saving in the past 12 months., female (% age 15+).

The percentage of respondents who report having an outstanding loan (by themselves or together with someone else) from a bank or another type of financial institution to purchase a home, an apartment, or land, female (% age 15+).

Male rural population is the percentage males who live in rural areas to total population.

Rural population refers to people living in rural areas as defined by national statistical offices. It is calculated as the difference between total population and urban population.

Female urban population is the percentage of females who live in urban areas to total population.

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.

Male urban population is the percentage of males who live in urban areas to total population.

Unmet need for contraception is the percentage of fertile, married women of reproductive age who do not want to become pregnant and are not using contraception.

Number of female vocational education students at the lower secondary level expressed as a percentage of the total number of vocational education students (male and female) at the lower secondary level in a given school year.

Number of female vocational education students at the upper secondary level expressed as a percentage of the total number of vocational education students (male and female) at the upper secondary level in a given school year.

Number of female vocational education students at the post-secondary non-tertiary level expressed as a percentage of the total number of vocational education students (male and female) at the post-secondary non-tertiary level in a given school year.

Female share of graduates in the given field of education, tertiary is the number of female graduates expressed as a percentage of the total number of graduates in the given field of education from tertiary education.

Total number of students enrolled in vocational programmes at the upper secondary education level, expressed as a percentage of the total number of students enrolled in all programmes (vocational and general) at the upper secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.

Total number of female students enrolled in vocational programmes at the upper secondary education level, expressed as a percentage of the total number of female students enrolled in all programmes (vocational and general) at the upper secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.

Total number of male students enrolled in vocational programmes at the upper secondary education level, expressed as a percentage of the total number of male students enrolled in all programmes (vocational and general) at the upper secondary level. Vocational education is designed for learners to acquire the knowledge, skills and competencies specific to a particular occupation or trade or class of occupations or trades. Vocational education may have work-based components (e.g. apprenticeships). Successful completion of such programmes leads to labour-market relevant vocational qualifications acknowledged as occupationally-oriented by the relevant national authorities and/or the labour market.

Number of males of official upper secondary school age who are not enrolled in upper secondary school expressed as a percentage of the male population of official upper secondary school age.

Intentional homicides, female are estimates of unlawful female homicides purposely inflicted as a result of domestic disputes, interpersonal violence, violent conflicts over land resources, intergang violence over turf or control, and predatory violence and killing by armed groups. Intentional homicide does not include all intentional killing; the difference is usually in the organization of the killing. Individuals or small groups usually commit homicide, whereas killing in armed conflict is usually committed by fairly cohesive groups of up to several hundred members and is thus usually excluded.

Male population between the ages 70 to 74.

Female population between the ages 75 to 79.

Male population between the ages 75 to 79.

Age population, female refers to female population at the specified age level. The geographical areas included in the data are the same as the data source.

Age population, male refers to male population at the specified age level. The geographical areas included in the data are the same as the data source.

Sex ratio at birth refers to male births per female births. The data are 5 year averages.

Female population is the percentage of the population that is female. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Male population is based on the de facto definition of population, which counts all male residents regardless of legal status or citizenship.

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.

Female population between the ages 5 to 9.

Female population between the ages 10 to 14.

Total population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Female population between the ages 20 to 24.

Male population between the ages 25 to 29.

Male population between the ages 30 to 34.

Male population between the ages 35 to 39.

Female population between the ages 40 to 44.

Male population between the ages 40 to 44.

Male population between the ages 45 to 49.

Male population between the ages 50 to 54.

Female population between the ages 55 to 59.

Female population between the ages 60 to 64.

Female population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Male population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Total population 65 years of age or older. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Population ages 65 and above as a percentage of the total population. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Life expectancy at birth indicates the number of years a newborn infant would live if prevailing patterns of mortality at the time of its birth were to stay the same throughout its life.

Mean age at marriage, female shows the average length of single life expressed in years among those females who marry before age 50. It is a synthetic indicator calculated from marital status categories of men and women aged 15 to 54 at the census or survey date.

Mean age at marriage, male shows the average length of single life expressed in years among those males who marry before age 50. It is a synthetic indicator calculated from marital status categories of men and women aged 15 to 54 at the census or survey date.

Wanted fertility rate is an estimate of what the total fertility rate would be if all unwanted births were avoided.

Female headed households shows the percentage of households with a female head.

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

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

Female population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Male population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Total population between the ages 0 to 14. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Population between the ages 0 to 14 as a percentage of the total population. Population is based on the de facto definition of population.

Labor force comprises people ages 15 and older who supply labor for the production of goods and services during a specified period. It includes people who are currently employed and people who are unemployed but seeking work as well as first-time job-seekers. Not everyone who works is included, however. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. Labor force size tends to vary during the year as seasonal workers enter and leave.

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.

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

Ratio of female to male youth unemployment is the percentage of female to male youth unemployment rates.

The percentage of the labor force with an advanced level of education who are unemployed. Advanced education comprises short-cycle tertiary education, a bachelor’s degree or equivalent education level, a master’s degree or equivalent education level, or doctoral degree or equivalent education level according to the International Standard Classification of Education 2011 (ISCED 2011).

The percentage of the labor force with a basic level of education who are unemployed. Basic education comprises primary education or lower secondary education according to the International Standard Classification of Education 2011 (ISCED 2011).

The percentage of the labor force with an intermediate level of education who are unemployed. Intermediate education comprises upper secondary or post-secondary non tertiary education according to the International Standard Classification of Education 2011 (ISCED 2011).

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.

Bulk Download File (Excel)

The Gender Data Portal is the World Bank Group’s comprehensive source for the latest sex-disaggregated data and gender statistics covering demography, education, health, economic opportunities, public life and decision-making, and agency. The database is updated four times a year (April, July, September, and December).

Gender Statistics

Metadata