Overview
Indicators for education, health, jobs, population, and gender help capture the quality of people’s lives and provide a multidimensional portrait of the progress of societies. These data also support many of the Sustainable Development Goals (SDGs), such as Goal 3 on health, Goal 4 on education, Goal 5 on gender equality, Goal 6 on water and sanitation, and Goal 8 on decent work and economic growth.
Population is unique among these indicators, because an important indicator in itself, it is also necessary for constructing other indicators. For instance, it serves as the denominator for many per capita measures including per capita GNI estimates that are, in part, used to by the World Bank to determine the lending rates and credit terms for country operations. The World Bank publishes statistics on the size, growth, composition, and distribution of the population for over 200 economies and groups.
Which indicators are new?
Important indicators related to sustainable development are added to the WDI. Human Capital Index (HCI), released by the World Bank last year, quantifies the contribution of health and education to the productivity of the next generation of workers. Investing in human capital is crucial for sustainable growth and poverty reduction. Increasing their ability, knowledge, skills and health can make people more productive and innovative. HCI, expressed as a score ranging from zero to one, provides the national as well as sex-disaggregated data for each country.
Other new important indicators are gender-related indicators. To achieve gender equality and all women’s empowerment targeted in SDG 5, gender-related indicators are crucial to be collected, analyzed and used. This year, four health SDG indicators disaggregated by sex are included in Population Section. Sex-disaggregated data present discrepancies of the situation or well-being between women and men. Mortality rate attributed to household and ambient air pollution by women and men (3.9.1) estimates the deaths due to exposure to household and ambient air pollution. The majority of the burden occurs in low and middle-income countries. Mortality from cardiovascular disease, cancer, diabetes or chronic respiratory disease between exact ages 30 and 70 by both women and men (3.4.1) measures the disease burden from main non-communicable diseases among adults. Suicide mortality rate by women and men (3.4.2) measures the number of suicide deaths. The WHO estimates that there are around 800,000 suicide deaths in the world. Total alcohol consumption by women and men (3.5.1) estimates the total amount of alcohol consumed per adult ages 15+.
What’s special? Unpacking the data
Data for indicators are collected, estimated and compiled by national authorities and international development agencies like the World Bank. Although WDI data are typically national averages, many of the indicators are disaggregated by sex, age, wealth quintile, and urban or rural location. Because national averages often conceal differences between population subgroups disaggregated data can better inform decision-making.
For example, estimates of malnutrition, poverty, and population at subnational levels over time can be found online, as can gender-disaggregated data on financial inclusion, employment law, and business regulations—areas where the World Bank is leading collaborative efforts to collect those data.
Featured Indicators
A selection of relevant indicators is presented below. The table shows, for each featured indicator, time coverage per year, for all countries, for each decade since the 1960s, and regional coverage for each World Bank geographical region since 2010. For detailed thematic lists please refer to the World Development Indicators Statistical Tables.
| Population dynamics | ||||
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| Indicator | Code | Time coverage | Region coverage | Get data |
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Population, total
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SP.POP.TOTL |
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Population growth (annual %)
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SP.POP.GROW |
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Birth rate, crude (per 1,000 people)
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SP.DYN.CBRT.IN |
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Death rate, crude (per 1,000 people)
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SP.DYN.CDRT.IN |
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Fertility rate, total (births per woman)
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SP.DYN.TFRT.IN |
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Life expectancy at birth, male (years)
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SP.DYN.LE00.MA.IN |
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Life expectancy at birth, female (years)
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SP.DYN.LE00.FE.IN |
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Age dependency ratio, young (% of working-age population)
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SP.POP.DPND.YG |
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Age dependency ratio, old (% of working-age population)
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SP.POP.DPND.OL |
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| Education | ||||
| Indicator | Code | Time coverage | Region coverage | Get data |
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Government expenditure on education, total (% of GDP)
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SE.XPD.TOTL.GD.ZS |
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School enrollment, primary (% gross)
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SE.PRM.ENRR |
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School enrollment, secondary (% gross)
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SE.SEC.ENRR |
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School enrollment, tertiary (% gross)
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SE.TER.ENRR |
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Progression to secondary school (%)
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SE.SEC.PROG.ZS |
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Primary completion rate, total (% of relevant age group)
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SE.PRM.CMPT.ZS |
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Literacy rate, youth total (% of people ages 15-24)
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SE.ADT.1524.LT.ZS |
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| Labor | ||||
| Indicator | Code | Time coverage | Region coverage | Get data |
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Labor force participation rate, total (% of total population ages 15+) (modeled ILO estimate)
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SL.TLF.CACT.ZS |
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Employment in agriculture (% of total employment) (modeled ILO estimate)
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SL.AGR.EMPL.ZS |
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Employment in industry (% of total employment) (modeled ILO estimate)
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SL.IND.EMPL.ZS |
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Employment in services (% of total employment) (modeled ILO estimate)
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SL.SRV.EMPL.ZS |
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Employment to population ratio, 15+, total (%) (modeled ILO estimate)
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SL.EMP.TOTL.SP.ZS |
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Unemployment, total (% of total labor force) (modeled ILO estimate)
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SL.UEM.TOTL.ZS |
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Children in employment, total (% of children ages 7-14)
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SL.TLF.0714.ZS |
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| Health | ||||
| Indicator | Code | Time coverage | Region coverage | Get data |
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Prevalence of stunting, height for age (% of children under 5)
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SH.STA.STNT.ZS |
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Maternal mortality ratio (modeled estimate, per 100,000 live births)
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SH.STA.MMRT |
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Mortality rate, under-5 (per 1,000 live births)
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SH.DYN.MORT |
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Incidence of HIV (% of uninfected population ages 15-49)
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SH.HIV.INCD.ZS |
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Mortality from CVD, cancer, diabetes or CRD between exact ages 30 and 70 (%)
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SH.DYN.NCOM.ZS |
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Mortality caused by road traffic injury (per 100,000 people)
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SH.STA.TRAF.P5 |
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Adolescent fertility rate (births per 1,000 women ages 15-19)
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SP.ADO.TFRT |
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Proportion of population spending more than 10% of household consumption or income on out-of-pocket health care expenditure (%)
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SH.UHC.OOPC.10.ZS |
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| Gender | ||||
| Indicator | Code | Time coverage | Region coverage | Get data |
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School enrollment, primary and secondary (gross), gender parity index (GPI)
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SE.ENR.PRSC.FM.ZS |
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Women who were first married by age 18 (% of women ages 20-24)
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SP.M18.2024.FE.ZS |
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Demand for family planning satisfied by modern methods (% of married women with demand for family planning)
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SH.FPL.SATM.ZS |
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Ratio of female to male labor force participation rate (%) (modeled ILO estimate)
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SL.TLF.CACT.FM.ZS |
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Female share of employment in senior and middle management (%)
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SL.EMP.SMGT.FE.ZS |
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Proportion of women subjected to physical and/or sexual violence in the last 12 months (% of women age 15-49)
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SG.VAW.1549.ZS |
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Proportion of seats held by women in national parliaments (%)
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SG.GEN.PARL.ZS |
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About the data
Population
World Bank population estimates are compiled from three main sources: (1) the United Nations Population Division’s World Population Prospects (WPP), (2) census reports and other publications from national statistical offices (NSOs), and (3) Eurostat Demographic Statistics, which collects data directly from European NSOs. The WPP is the primary source for World Bank population estimates because for many countries it provides the most reliable, comprehensive, and internally consistent population and demographic datasets.
Population estimates are usually based on national population censuses. More countries conducted a census in the 2010 census round (2005–14) than in previous rounds, with about 93 percent of the estimated world population enumerated in that period. Recency and quality of a census and of complementary data available from vital registration systems or surveys are important for high quality population and demographic estimates.
Errors and undercounting in censuses occur even in high-income countries; in some low- and middle-income countries the errors may be substantial. Census-year population estimates for low- and middle-income countries that lack reliable recent census data are provided by the United Nations Population Division. Those estimates are derived from demographic modeling based on a cohort component method, a standard method for estimating and projecting population that draws on fertility, mortality, and net migration data, often collected from sample surveys. A similar approach is used to calculate pre- and post-census (“intercensal”) estimates for all countries, even those whose census data are reliable.
The growth rate of the total population conceals age-group differences in growth rates. In many low- and middle-income countries, the growth rate of the once rapidly growing under-15 population is now slower, and a share of its total population is declining. The previously high fertility rates and declining mortality rates now find expression in the fact that the working-age population comprises a larger share of total population.
Crude birth rate and crude death rate are the numbers of births and deaths per 1,000 people. These crude rates are not adjusted for the age structure of the population and can reflect, for example, higher death rates in aging than in younger populations, even if the age-specific mortality rates are lower. Crude birth rate minus crude death rate shows whether there has been an increase or a decrease in the population without taking into account any migration.
Total fertility rate is the number of children that would be born to a woman if she were to live to the end of her childbearing years and bear children in accordance with the age-specific fertility rates of a given year. The total fertility rate is therefore adjusted by the age structure of women of reproductive age. Fertility rates are based on data on registered live births from vital registration systems or, where there are no such reliable systems, from censuses or sample surveys.
Life expectancy at birth shows overall mortality in a population; this indicator is often used to illustrate the socioeconomic development across countries. Typically, it is calculated in a life table applying age specific death rates of a given population for a given year.
Dependency ratios capture variations in the proportions of children, elderly people, and working-age people in a population that suggest the burden the working-age population must carry to support the society’s children and elderly. But dependency ratios show only the age composition of a population, not economic dependency. Some children and elderly people are part of the labor force, and many working-age people are not.
Health
Long and healthy lives can help people to fulfill their potential and also contribute to the economy. Health statistics, which help to monitor their progress, assess health services and identify emerging trends in mortality and fertility, nutrition and malnutrition, the prevalence of diseases, and people's lifestyle choices.
Child malnutrition
Good nutrition is paramount for survival, health, and development. Well-nourished children perform better in school, grow into healthy adults, and give their own children a better start in life; well-nourished women face fewer risks during pregnancy and childbirth.
Undernourished children have less resistance to infection and are more likely to die from common childhood ailments like diarrheal diseases and respiratory infections. Frequent illness saps the health of those who survive, locking them into a vicious cycle of recurring sickness and faltering growth.
The World Health Assembly’s Global Nutrition Targets 2025 and the 2030 Sustainable Development Goals (SDGs) give priority to countering stunting (low height for age), wasting (low weight for height), and the prevalence of overweight (high weight for height) in children under age 5. Estimates of wasting and severe wasting can show large fluctuations across surveys within countries. Better estimates would be based on annual incidence, but the national or regional data to support them often do not exist. Because estimates of stunting are more reliable, trends are easier to derive. Childhood stunting is a largely irreversible outcome of inadequate nutrition and repeated bouts of infection during the first 1,000 days of a child’s life. Stunting has long-term effects on individuals (and ultimately societies) in terms of diminished cognitive and physical development, reduced productive capacity, poor health generally, and higher risk of degenerative diseases like diabetes. Data on prevalence of stunting are from the WHO’s Global Database on Child Growth and Malnutrition.
Under-5 mortality
At every age, mortality rates are important indicators of health status. When data on the incidence and prevalence of diseases are unavailable, mortality rates may be used to identify vulnerable populations, and under-5 mortality rates are among the indicators most frequently used to compare socioeconomic development across countries.
The main sources of mortality data are vital registration systems and direct or indirect estimates based on sample surveys or censuses. A complete vital registration system—covering at least 90 percent of vital events in the population—is the best source of age-specific mortality data, but in low- and middle-income countries complete vital registration systems tend to be rare. Thus, estimates must be obtained from sample surveys or derived by applying indirect estimation techniques to census, or survey data. (Note that survey data are subject to recall bias.)
To ensure the comparability and consistency of estimates produced by different agencies, the UN Inter-agency Group for Child Mortality Estimation, which comprises the United Nations Children’s Fund (UNICEF), the World Health Organization (WHO), the World Bank, the United Nations Population Division, and universities and research institutes, has adopted a statistical method that uses relevant available information to reconcile differences. Trend lines are obtained by fitting a country-specific regression model of mortality rates against their reference dates.
Maternal mortality
Measurements of maternal mortality are subject to many types of errors. In countries with incomplete vital registration systems, deaths of women of reproductive age or their pregnancy status may not be reported, or the cause of death may not be known. Even in high-income countries with reliable vital registration systems, misclassification of maternal deaths has been found to cause serious underestimation. Surveys and censuses can be used to measure maternal mortality by asking respondents about survivorship of sisters, but the estimates are retrospective, referring to a period approximately five years before the survey, and may be affected by recall bias. Further, they reflect pregnancy-related deaths (deaths while pregnant or within 42 days of pregnancy termination, irrespective of the cause of death) and need to be adjusted to conform to the strict definition of maternal death which is the death of a woman while pregnant or within 42 days of termination of pregnancy from any cause related to or aggravated by the pregnancy or its management.
Maternal mortality ratios are available for both national estimates and modeled estimates based on work by the WHO, UNICEF, the UN Population Fund, the World Bank, and the UN Population Division. For countries that do not have complete vital registration data but do have other types of data, and for countries with no data, maternal mortality is estimated with a multilevel regression model using any national maternal mortality data available and socioeconomic information, including fertility, birth attendants, and gross domestic product. Because the methodology differs from that used for previous estimates, data presented here should not be compared across editions (UN Maternal Mortality Estimation Inter-agency Group 2015).
Adolescent fertility
Reproductive health is a state of physical and mental well-being in relation to the reproductive system and its functions and processes. It can be supported by 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 for women of reproductive age in low- and middle-income countries.
Adolescent pregnancies are high-risk for both mother and child. They are more likely to result in premature delivery, low birthweight, delivery complications, and death. Many adolescent pregnancies are unintended, but young girls may continue their pregnancies, giving up opportunities for education and employment, or seek unsafe abortions. Estimates of adolescent fertility rates are based on vital registration systems or, if there are no reliable systems, censuses or sample surveys. 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 previous censuses or surveys. Data are from the United Nations Population Division, with annual data linearly interpolated by the World Bank Development Data Group.
Incidence of human immunodeficiency virus (HIV)
HIV weakens the immune system and ultimately leads to acquired immune deficiency syndrome (AIDS). Its incidence is the rate of new HIV infections among an uninfected population during a certain time period. People infected before that period are not part of the incidence. Incidence reflects the current rate of HIV transmission and provides a measure of progress toward preventing onward transmission.
Data on incidence of HIV are from the Joint United Nations Programme on HIV/AIDS, which helps countries produce global, regional, and national estimates annually. Because of challenges in collecting direct measures of HIV incidence, modelled estimates are used. The models incorporate data on HIV prevalence from surveys of the general population, antenatal clinic attendees, and populations at increased risk of contracting HIV (such as sex workers, men who have sex with men, and people who inject drugs) and on the number of people receiving antiretroviral therapy, which will increase the prevalence of HIV because people living with HIV now survive longer. In countries with high-quality health information systems the models are also informed by case reporting and vital registration data.
The estimates include plausibility bounds, available at metadata in World Development Indicators database, which reflect the degree of certainty associated with each estimate. The wider the bounds of an estimate, the greater the uncertainty.
Education
Many governments publish statistics showing how well their education systems are working and improving, with data on enrollment, graduates, and financial and human resources and such efficiency indicators as repetition rates, pupil–teacher ratios, and cohort progression. Data on education are sourced primarily from the UNESCO Institute for Statistics (UIS), and household surveys such as Demographic and Health Surveys by ICF, Multiple Indicator Cluster Surveys by UNICEF and World Bank Living Standards Measurement Surveys. Monitoring progress toward national and global education targets helps allocate resources more efficiently and make quality learning opportunities accessible to all. Better-quality education leads to an empowered citizenry and a more productive labor force.
Financial and human resources
Knowing how much a country is spending on education makes it possible to assess its commitment to building human capital. The share of government expenditure on education demonstrates the priority a government assigns to education relative to other public investments. Countries with younger populations may spend more on education than on other sectors, such as health or social security, and vice versa.
By measuring government expenditure spending on education relative to GDP, it is possible to compare countries or the same country at different times: spending a high percentage of GDP suggests a high priority for education and a capacity for raising revenues for public spending. Because it can take a long time before children currently enrolled can productively contribute to the national economy, returns on investment in education cannot be measured simply by comparing current education indicators with national income.
Data on human resources are also important measures. For example, the share of trained teachers reveals a country’s commitment to investing in the development of its teachers, but it does not take into account differences in their experiences and status, teaching methods, teaching materials, and classroom conditions—all factors that affect the quality of teaching and learning.
School enrollment
Gross enrollment ratios indicate the capacity at each level of the education system, but a high ratio may reflect not a successful education system but instead a substantial number of overage children enrolled in each grade because of repetition or late entry. The net enrollment rate excludes over-age and under-age students and more accurately captures a system's coverage and internal efficiency. Differences between gross and net enrollment rates show the incidence of over-age and under-age enrollments.
Enrollment indicators are based on annual school surveys; they do not necessarily reflect actual attendance or dropout rates during the year. Also, the length of education differs by country and can influence enrollment rates, although the International Standard Classification of Education (ISCED) tries to minimize the difference. For example, a shorter duration for primary education tends to increase enrollment; a longer one to decrease it (in part because older children are more at risk of dropping out). Moreover, age at enrollment may be inaccurately estimated or misstated, especially in communities where birth registration is not strictly enforced.
Progression
Students’ progress through school gives a picture of how successful the education system is in reaching students and how efficiently it moves them from one grade to the next. The gross intake ratio into the first grade of primary education indicates capacity to provide access to primary education. The cohort survival rate to grade 5 or the last grade of primary education measures the system’s holding power and internal efficiency. Data on repeaters are also used to indicate an education system’s internal efficiency: repeaters not only increase the cost of education for the family and the school system but also use up limited school resources.
The effective transition rate from primary to secondary education conveys the degree of access, or transition between, the two levels. Since completing primary education is a prerequisite for participating in lower secondary education, growing numbers of primary completers will inevitably create pressure for more secondary places. A low effective transition rate can signal such problems as inadequate examination and promotion or insufficient secondary education capacity.
Completion
Completion, measured by the gross intake ratio to last grade of education, is a core indicator of education system performance in terms of coverage and how well students learn. In the World Development Indicators database, completion rates are available for two levels: the primary cycle—which typically lasts six years (with a range of four to seven) and the lower secondary cycle.
The completion rate is a proxy that should be taken as an upper bound estimate of the actual completion rate, since data limitations preclude adjusting for students who drop out during the final year of primary education. The completion rate may exceed 100 percent because, for instance, the numerator includes late entrants and over-age children who have repeated one or more grades and children who entered school early, and the denominator is the number of children at the entrance age for the last grade.
Youth literacy
The youth literacy rate for ages 15–24 is a standard measure of recent progress in student achievement. It reflects the cumulative outcomes of primary and secondary education by indicating the proportion of the youth population that has acquired basic literacy and numeracy skills in the previous 10 years or so.
Conventional literacy statistics that divide the population into literate and illiterate are widely available and useful for tracking global progress toward universal literacy, but in practice literacy is not easy to measure. Estimating literacy rates accurately requires census or survey measurements made under controlled conditions. Many countries report the number of literate or illiterate people from self-reported data. Some use educational attainment as a proxy but apply different lengths of school attendance or levels of completion. There is also a trend among recent national and international surveys of using direct reading to test literacy skills. Because national definitions and methods of data collection differ, data should be used cautiously. Generally, literacy also encompasses numeracy, the ability to make simple arithmetic calculations.
Labor
Labor statistics are compiled by the International Labour Organization (ILO) ILOSTAT database typically from labor force surveys, which are the most comprehensive source for internationally comparable labor data, supplemented by population censuses, establishment censuses, and administrative records. Among factors that affect comparability are source, collection, conceptual variation, and collection tools and methodology. ILO-modeled estimates largely address these issues. In the World Development Indicator database, both ILO-modeled and national estimates are available.
Labor force structure
The labor force participation rate is the ratio of the supply of labor available for producing goods and services in an economy (the labor force) to the working-age population, expressed as a percentage. The labor force comprises both people who are currently employed and people who are unemployed but seeking work. However, not everyone who works is included. Unpaid workers, family workers, and students are often omitted, and some countries do not count members of the armed forces. The size of a country’s labor force tends to vary during the year as seasonal workers enter and leave. Average annual percentage growth of the labor force is available at WDI online table 2.2; it is calculated using the exponential endpoint method (see the Sources and Methods).
Employment by sector
ILO classifies economic activity using the International Standard Industrial Classification of All Economic Activities (ISIC). Although classification by three broad groups—agriculture, industry, and services—may obscure fundamental shifts within a country, the major sectoral information is still useful for identifying the country’s stage of economic development. The distribution of economic wealth in the world is closely correlated with employment by economic activity; in wealthier economies services employ the largest share of total employment, in poorer countries most jobs are in agriculture. The labor shift also suggests workers migrate from rural to urban areas. However, 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 within the same industry, regardless of their trade or occupation.
Full and productive employment
Full and productive employment is the main route for escape from poverty. Both employment and unemployment rates indicate how well an economy provides jobs for those who wish to work. A high employment-to-population ratio means that a large proportion of the population is employed. But a lower employment-to-population ratio can be a positive sign, if it is caused by young people getting more education rather than seeking jobs.
The unemployed are members of the working-age population who are without jobs but seeking work. Some unemployment within an economy is unavoidable: at any one time some workers are temporarily unemployed as employers look for suitable workers, and workers search for better jobs. Paradoxically, low unemployment can disguise substantial poverty in a country. In countries without unemployment or welfare benefits people must eke out a living in the informal economy or in informal work arrangements, while in many middle- or high-income 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 how resources are allocated.
The criteria for people considered to be seeking employment, and the treatment of people temporarily laid off or seeking employment for the first time, vary by country. It can be especially difficult to measure agricultural employment and unemployment. The timing of a survey can minimize or exacerbate the effects of seasonal unemployment in agriculture. And informal sector employment is difficult to quantify where informal activities are not tracked.
Labor productivity is used to assess a country's 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 improvements, but without them—and the economic growth they bring—improvements are highly unlikely. GDP per person employed is a key measure of SDG Indicator 8.2.1.
Children who are employed
Many children are economically active. Some perform simple tasks within the family; others endure long hours working in harsh and damaging conditions. Children’s work obligations can interfere with their education and with their physical and mental development, reducing their prospects for leading healthy and productive lives.
Children are considered to be employed if they are engaged for at least one hour in any activity relating to the production of goods and services during the reference week of the survey. Children seeking work are thus not counted, as are children performing household chores (see here for more details). Data are from household surveys by the International Labour Organization (ILO), the United Nations Children’s Fund (UNICEF), the World Bank, and national statistical offices. Children aged 7–14 are counted. While country surveys define the ages for child labor as 5–17, not all surveys collect data for the age group and children over 15 may work, according to both international standards and national law.
Economic activity covers all market and certain nonmarket production. For example, household services in a third-party household, paid or unpaid, is included, while it is excluded when it refers to unpaid household services (“household chores”) by household members for the household’s own consumption. The classification of sector and status is based on the ISIC. The WDI online table 2.6 highlights indicators regarding children at work.
In most countries more boys are employed than girls, or the gender difference is small. However, girls are often more active in hidden or underreported forms of employment, such as domestic service, and in almost all societies girls bear greater responsibility for 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.
Gender
Gender equality and women’s empowerment are essential to sustainable and inclusive development. Despite much progress in recent decades, gender inequalities are still pervasive. For that reason, World Bank Group Gender Strategy (FY16-23): Gender Equality, Poverty Reduction and Inclusive Growth identifies four strategic objectives for gender parity:
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Improve human endowments,
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Remove obstacles to accessing more and better jobs.
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Remove barriers to women&'s ownership and control of assets.
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Enhance women's voices and agency and engage men and boys.
Where gender inequalities exist, whether in legislation or in access to resources and funds, the well-being of the total populace is affected, as is the productivity and social and economic growth of a country. The WDI online table WV.5 highlights indicators to monitor progress toward gender equality and women’s empowerment.
Human endowments
The concept of human endowments incorporates health, education, and social protection. For example, indicators like Life expectancy at birth and Maternal Mortality Ratio help capture women’s general mortality. Eliminating gender disparities in education would help increase the status and capabilities of women, but there are many such disparities, as seen in School enrollment, primary and secondary (gross), gender parity index (GPI).
Economic opportunities
Women are less likely than men to be working or looking for work, according to the ratio of female to male labor force participation rate. However, women tend to be excluded from employment and unemployment counts for a variety of reasons. In many low-income countries women often work without pay on farms or in other family enterprises, and others work in or near their homes, mixing work and family activities during the day. Women may 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. In many high-income economies, women’s participation in higher education has led to better-compensated, longer-term careers rather than lower-skilled, shorter-term jobs. However, access to good-paying occupations for women is more limited in many occupations and countries around the world.
Women’s ownership of, and control over, assets
Financial accounts and land ownership help women escape poverty and protect them from economic shocks. Having an account ownership at a financial institution or with a mobile-money-service provider is a measure of women’s access to financial services. Women often trail men in account ownership.
Voice and agency
Many women are prevented from making their own decisions about family planning and health. Child marriage can lead to early pregnancy, which puts the health of teenage girls, and their children, at risk. It also substantially reduces their educational opportunities. Demand for family planning satisfied by modern methods monitors the share of women who desire either to have no children or to postpone childbirth and who are currently using modern contraceptive methods. And though nearly a third of all women have experienced some form of physical or sexual violence from an intimate partner (WHO, 2017) in 2017 forty five countries (Women, Business and the Law, 2018) still failed to protect women from domestic violence through laws. Proportion of women subjected to physical and/or sexual violence in the last 12 months throws light on both the prevalence of and the tolerance for domestic violence.
In many countries, women are still underrepresented in managerial positions and government. Without representation at this level, it is difficult for women to influence managerial and policy decisions. Female share of employment in senior and middle management provides information on the proportion of women who are employed in decision-making and management roles in government, large enterprises, and institutions. And Proportion of seats held by women in national parliaments presents the level of women’s political participation.