1 Insights from Disaggregating the Human Capital INDEX 2 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX  i Insights from Disaggregating the Human Capital INDEX ii Acknowledgments This booklet was prepared by Ciro Avitabile, Ritika D’Souza, Roberta Gatti, and Emily Weedon under the strategic direction of Annette Dixon (Vice President, Human Development Practice Group) and with inputs from Nicola Dehnen, Alexander Leipziger, and Juan Elias Mejalenko. Section 2 of this report builds on D’Souza, Gatti, and Kraay (2019), and section 3 synthesizes the country geographical disaggregation exercises led by the World Bank teams in Angola, Burkina Faso, Chad, Indonesia, Mali, Niger, Peru, Romania, Sierra Leone, Sri Lanka, and Vietnam. The socioeconomic Human Capital Index country profiles were produced by Raul Andres Castaneda Aguilar, Zelalem Debebe and Martin De Simone. The authors are particularly grateful for ana- lytical inputs provided by Harsha Aturupane, Reena Badiani-Magnusson, Kathleen Beegle, Livia Benavides, Carmen Carpio, Mohamed Coulibaly, Gabriel Demombynes, Emily Gardner, Antonio Giuffrida, Daniel Halim, Hideki Higashi, Veronica Hinostroza, Camilla Holmemo, Keiko Inoue, Leonardo Lucchetti, Kevin Macdonald, Emma Monsalve Montiel, Obert Pimhidzai, Sharon Piza, Manal Quota, Aly Sanoh, Jigyasa Sharma, Changqing Sun, and Sailesh Tiwari. They thank Kavita Watsa for her valuable feedback and Aart Kraay, Deon Filmer, and Halsey Rogers for useful comments. iii Contents Acknowledgments........................................................................................................................................... ii 1. DISAGGREGATING THE HUMAN CAPITAL INDEX FOR POLICY INSIGHTS.................2 2. SOCIOECONOMIC DISAGGREGATION ...........................................................................8 Understanding socioeconomic gaps in human capital..................................................................11 Human capital outcomes and income within and across countries......................................... 18 3. SPATIAL DISAGGREGATION ........................................................................................... 20 Subnational inequality is substantial .................................................................................................. 21 What dimensions of human capital drive these inequalities?....................................................24 Looking within the HCI.......................................................................................................................... 26 How are these findings informing action?........................................................................................ 26 4. REALIZING CHANGE: A WHOLE-OF-GOVERNMENT APPROACH .......................... 28 Staying the course: Long-term commitment to equity............................................................... 29 Working together: Coordination across and beyond government.......................................... 30 Using evidence: Undertaking reforms and allocating resources based on data .................. 32 What’s Next? An ongoing commitment............................................................................................ 33 5. USING DATA TO DESIGN RESPONSIVE POLICIES ..................................................... 36 References...................................................................................................................................................... 40 Appendix 1: Differences between the SES-HCI and HCI....................................................................... 46 Appendix 2: Data Sources for the SES-HCI............................................................................................. 49 Appendix 3: Data Sources for the GEO-HCI ........................................................................................... 52 Appendix 4: SES-HCI Country Profiles ..................................................................................................... 54 Albania.................................................................................................................................................................55 Armenia................................................................................................................................................................56 Azerbaijan........................................................................................................................................................... 57 Benin.....................................................................................................................................................................58 Burkina Faso.......................................................................................................................................................59 iv INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Burundi........................................................................................................................................................ 60 Cameroon.....................................................................................................................................................61 Chad..............................................................................................................................................................62 Colombia......................................................................................................................................................63 Comoros.......................................................................................................................................................64 The Democratic Republic of Congo....................................................................................................65 The Republic of Congo............................................................................................................................66 Côte d’Ivoire................................................................................................................................................67 Dominican Republic.................................................................................................................................68 The Arabic Republic of Egypt................................................................................................................69 El Salvador..................................................................................................................................................70 Eswatini.........................................................................................................................................................71 Ethiopia........................................................................................................................................................72 Gabon...........................................................................................................................................................73 The Gambia................................................................................................................................................74 Ghana...........................................................................................................................................................75 Guatemala...................................................................................................................................................76 Haiti............................................................................................................................................................... 77 Honduras.....................................................................................................................................................78 India...............................................................................................................................................................79 Jordan.......................................................................................................................................................... 80 Kazakhstan..................................................................................................................................................81 Kenya............................................................................................................................................................82 Kyrgyz Republic..........................................................................................................................................83 Lesotho.........................................................................................................................................................84 Madagascar................................................................................................................................................85 Malawi..........................................................................................................................................................86 Mali................................................................................................................................................................87 Moldova.......................................................................................................................................................88 Mozambique...............................................................................................................................................89 Myanmar..................................................................................................................................................... 90 Namibia.........................................................................................................................................................91 Niger..............................................................................................................................................................92 Paraguay.....................................................................................................................................................93 Peru...............................................................................................................................................................94 Senegal........................................................................................................................................................95 Tajikistan......................................................................................................................................................96 Tanzania.......................................................................................................................................................97 Togo...............................................................................................................................................................98 Turkey...........................................................................................................................................................99 Uganda......................................................................................................................................................100 Vietnam....................................................................................................................................................... 101 West Bank and Gaza.............................................................................................................................102 Zambia....................................................................................................................................................... 103 Zimbabwe.................................................................................................................................................. 104 C ontents 1 2 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX 1 Disaggregating the Human Capital Index for POLICY INSIGHTS D isaggregating the Human Capital I ndex for Policy I nsights 3 A t the 2018 Annual Meetings, the World in future worker productivity deriving from gaps Bank Group launched the Human Capital in human capital across countries, the HCI under- Project, an unprecedented global effort scores the urgency of improving human capital to support human capital development as a core outcomes. This is particularly pressing in the con- element of the overall strategies of countries to text of the rapidly changing nature of work, which increase productivity and growth. The main objec- is associated with an increasing demand for higher- tive of the HCP is rapid progress toward a world in order skills.2 which all children can achieve their full potential. For that to happen, children need to reach school The global HCI is calculated for 157 countries well-nourished and ready to learn, attain real using national averages of the component data. learning in the classroom, and enter the job mar- While the cross-country comparison of human ket as healthy, skilled, and productive adults. capital outcomes is important, national averages mask significant differences along dimensions Central to this effort has been the Human Capital such as gender, ethnicity, socioeconomic status, Index (HCI), a cross-country metric measuring the and geographic location, which are likely associ- human capital that a child born today can expect ated with gaps in productivity. to attain by her 18th birthday, given the risks of poor health and poor education prevailing in her This report quantifies some of these human capital country.1 The HCI brings together measures of dif- inequalities, with a special focus on socioeconomic ferent dimensions of human capital: health (child and subnational spatial differences. The socioeco- survival, stunting, and adult survival rates) and the nomic analysis covers 50 low- and middle-income quantity and quality of schooling (expected years countries where the data permit comparable dis- of school and international test scores). Using esti- aggregation. The spatial analysis covers 11 low- and mates of the economic returns to education and middle-income countries where the global HCI health, these components are combined into an release sparked demand for analysis at the sub- index that captures the expected productivity of a national level. As a result, rather than describing child born today as a future worker, relative to a comprehensive trends, this booklet highlights the benchmark of complete education and full health. potential of detailed disaggregation for the design of well-targeted policies. The index ranges from zero to one, so that an HCI value of, for instance, 0.57—the global aver- age—implies that a child born today will only be Disaggregation of the HCI complements 57 percent as productive as a future worker as she poverty and other metrics to inform would be if she enjoyed complete education and evidence-based reforms. full health (box 1.1). By benchmarking shortfalls 1. The HCI was introduced in World Bank (2018a, 2018b), and the methodology of the HCI is detailed in Kraay (2019). 2. World Bank (2019a). 4 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX The association between a household’s socio- economic divergences between urban communi- economic status and investments in children is ties, with high levels of human capital and vibrant well-documented, especially for high- and mid- labor markets, and rural areas with low levels of dle-income countries. This literature indicates that 3 human capital and stagnating economies.5 skills formed early in life matter significantly and explain a substantial part of lifetime inequalities. Low-skilled individuals who grow up in rural For example, evidence shows that half the inequal- areas have limited opportunities to improve their ity in lifetime earnings in the United States is estab- prospects, even if they decide to migrate. Again, lished by age 18. In a process where skills beget skills, the evidence shows that investing early has the closing human capital differences early in life is greatest results. Children born in disadvantaged one of the most cost-effective strategies to reduce households can reduce the gap with more afflu- income gaps. 4 ent in terms of both future education and labor market outcomes if their families move to areas Disaggregating the HCI by different socioeco- with high quality schools and health facilities.6 nomic levels can help countries quantify these In the United States, it is estimated that moving early inequalities and identify policy priorities for early in life to a high-opportunity area reduces the most disadvantaged. The disaggregation of the the persistence of income across generations by HCI components can also provide useful insights 25 percent.7 because the benefits and costs of different types of human capital investments vary by socioeconomic Improving the quality of human capital in disad- status. For instance, in contexts where differences vantaged regions can have potentially long-lasting in malnutrition between the rich and the poor are effects.8 Yet, identifying areas where the returns limited, while differences in learning outcomes to human capital investment are higher is not are large, early childhood interventions might pri- always simple because measures of current mon- oritize cognitive and socioemotional stimulation etary poverty might not fully signal these returns. over nutrition. Disaggregating the HCI spatially can help govern- ments prioritize social sector spending, comple- Job polarization is also linked to inequality, con- menting not only poverty maps but also spend- tributing to the widening earnings gap between ing data and measures of the quality of services, high- and low-skilled individuals. Urbanization has such as those collected by the Service Delivery possibly exacerbated this inequality. Highly skilled Indicators initiative.9 It might also improve the workers tend to concentrate in densely populated efficiency of other types of government spending. urban areas. Young and educated women and men For instance, regions where levels of human capital prefer to be surrounded by peers with similar char- are low might not be the most suitable to receive acteristics and many firms, especially the most incentives for research and development because innovative ones, locate where young and skilled people in these regions are not properly prepared workers are. This sorting process fuels further to maximize the potential of these opportunities. 3. See for example Cunha and Heckman (2009) and Schady et al. (2015). 4. Cunha and Heckman (2006); Cunha and Heckman (2007); Cunha and Heckman (2009). 5. Ferreyra and Roberts (2018); Moretti (2013). 6. Bergman et al. (2019); Chetty and Hendren (2018). 7. Bergman et al. (2019). 8. Valencia Caicedo (2018). 9. See SDI (Service Delivery Indicators) (database), World Bank, Washington, DC, https://www.sdindicators.org/. D isaggregating the Human Capital I ndex for Policy I nsights 5 BOX 1.1  The Human Capital Index The Human Capital Index (HCI) measures the amount of human capital that a child born today can expect to attain by age 18, given the risks of poor health and poor education that prevail in the country where she lives. The HCI consists of three components: • Component 1: Child Survival. This component reflects the fact that not all children born today will survive until age 5, when the process of human capital accumulation through formal education begins. • Component 2: Expected Learning-Adjusted Years of School. This component combines information on the quantity and quality of education. The quantity of education is mea- sured as the number of years of school that a child can expect to obtain by age 18. The quality of education draws on work at the World Bank to harmonize test scores from major international student achievement testing programs into a common yardstick of learning. • Component 3: Health. Two proxies for the overall health environment are used to inform this component: (i) adult survival rates, defined as the fraction of 15-year-olds that sur- vive until age 60 and (ii) the rate of stunting for children under age 5. Adult survival rates can also be interpreted as a proxy for the range of non-fatal health outcomes that a child born today would experience as an adult. Children are defined as stunted if their height- for-age is more than two standard deviations below the World Health Organization Child Growth Standards median. Stunting is broadly accepted as a proxy for the prenatal, infant, and early childhood health environment. The HCI formulation has theoretical underpinnings in the development accounting litera- ture. Specifically, it uses micro-econometric estimates of the returns to education and health to measure the contributions of these components to the productivity of a child born today as a future worker. The index ranges between 0 and 1, where the index takes the value 1 only if the average worker in the country will achieve both full health (defined as the absence of stunting and an adult survival rate of 100 percent) and full education potential (14 years of high-quality school by age 18). Therefore, if a country scores 0.70 in the HCI, this indicates that the productivity of the average worker is 30 percent below what she could have achieved with complete education and full health. Thanks to its structure, the index can be directly linked to scenarios for future income. If a country has a score of 0.50, then gross domestic product (GDP) per worker could be twice as high if the country reached the benchmark of complete education and full health. This is because human capital leads workers to become more productive and earn more, and in turn save more, providing the economy with more physical capital. The global HCI reports country averages as well as country scores disaggregated by gender (box 1.2). This booklet presents analytical work to disaggregate the index by socioeconomic group and at the subnational level for selected countries where the required data are available. Source: Kraay 2019; World Bank 2018a, 2018b. 6 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Unlocking the Potential of Human Capital Investments through BOX 1.2  Gender Equality Achieving gender equality is essential for countries to realize their economic and social potential and meet the challenges of the changing nature of work. Losses from gender inequality because of differences in lifetime labor earnings are large.a Human capital provides opportunities and underpins economic empowerment; gender equity is a prerequisite for this. However, countries also need to become galvanized into removing barriers faced by women and girls in utilizing their human capital to capture pro- ductivity gains fully. Much progress has been made in closing gender gaps at the global and regional levels, but some challenges remain. Sex disaggregation—available for 126 out of the 157 coun- tries in the global HCI—shows that scores are slightly higher among girls than boys in most countries with available data. Indeed, an emerging trend shows that girls are not merely catching up to but outperforming boys in expected years of school and learning outcomes in some regions. In Tunisia, girls are expected to complete one additional year of school- ing compared with boys. In Saudi Arabia, the average learning outcomes for girls is 57 points higher than for boys. Yet, in 40 percent of low-income countries with sex-disaggregated data, boys outperform girls in expected years of schooling. Within countries, disaggregation of outcomes shows further nuance. In Romania, girls have higher expected years of school in 35 of 41 counties and the average advantage for girls is considerably larger than the average advantage for boys. Conversely, in Angola, scores for girls and students in rural areas are lower on average in almost all provinces. Even if the HCI overall shows that girls do as well or slightly better than boys, girls continue to face unique challenges in accumulating human capital that are not captured in the HCI, such as child marriage, early childbearing, and gender-based violence—not only in general but also in school specifically. Often, these are exacerbated by additional challenges within the countries. In Vietnam, for example, roughly three times as many adolescent girls in eth- nic minorities are married compared with the national average, and almost five times as many have children before they reach age 19 as in the Kinh ethnic majority.b These observations come with two important caveats. First, gender gaps can only be observed if the relevant data are available. One in five countries in the 2018 global HCI rank- ing are missing sex-disaggregated HCI data. This is driven by gaps in the data on expected years of school and learning outcomes. Second, while gender gaps in human capital are closing in terms of the flow (youth), the gaps are quite wide in the stock (adults). Globally, males born between 1961 and 1970 were on average 9.4 percentage points more likely to be literate than the corresponding females. This gap drops to 3.1 percentage points among cohorts born between 1991 and 2000.c Despite improvement in the human capital of girls, women continue to face unique barriers in converting their human capital into economic opportunities. Adult labor force participa- tion worldwide is 27 percentage points lower among women than men. Globally, only one D isaggregating the Human Capital I ndex for Policy I nsights 7 firm in five has women top managers.d Women are paid less, more likely to work in the infor- mal sector, and less likely to move up the career ladder. Turning human capital investments into economic potential means addressing the barriers to women’s economic empowerment, such as occupational sex-segregation, disadvanta- geous social norms on household and market roles, lack of childcare, inadequate parental leave policies, sexual harassment, unsafe transportation, differential constraints in access to finance and markets, and legal and regulatory barriers to work and to start and grow firms. a. Wodon and de la Brière (2018). b. Mbuya, Atwood and Huynh (2019). c. Statistics calculated from data of DataBank, World Bank, Washington, DC, http://databank.worldbank.org/data. d. Statistics calculated from data of Gender Data Portal (database), World Bank, Washington, DC, https://datatopics.world- bank.org/gender/. 8 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX 2 Socioeconomic DISAGGREGATION S ocioeconomic Disaggregation 9 A large body of evidence, especially from and progressive Sweden, one additional year of high- and middle-income countries, education of a great-grand-parent is associated shows that children in poor households with 0.15 years more education of the grandchild.16 have worse human capital outcomes compared with children in rich households.10 The size of the human capital gap between rich and poor households varies considerably across Several factors, which often reinforce one another, countries, and underlying drivers can also differ can contribute to these rich-poor gaps in human depending on the context. In many upper-middle- capital. The lack of monetary resources, com- income countries, children in different socioeco- bined with the reduced ability to borrow, prevents nomic groups display differences in cognitive abili- the poor from accessing health and education ties but not in nutritional outcomes. This is not the services. 11 In the absence of insurance, external case in low-income countries where socioeconomic shocks, such as those caused by weather, may differences are often dramatic for both health and force children in poor households to drop out education outcomes.17 of school or adversely impact their learning out- comes. Evidence from Uganda shows that girls Governments have a vital role to play in building are likely to be the most affected.12 Households human capital— directly financing and delivering may lack information about the returns to human or regulating the private delivery of social services capital or face significant opportunity costs in while ensuring equitable access to opportunities. A acquiring human capital. And social norms about 13 socioeconomic disaggregation of the HCI can shed women’s roles, which can be harder for the poor light on inequalities within countries and allow to challenge, shape many critical decisions related policy makers to formulate and target interven- to human capital such as fertility, breastfeeding, or tions more effectively for the most disadvantaged. schooling. 14 While the global HCI cannot readily be disaggre- These early inequalities in human capital are gated by socioeconomic group, comparable data amplified over the life cycle and investments to from Demographic and Health Surveys (DHS) remediate them become costlier the older chil- and Multiple Indicator Cluster Surveys (MICS) dren get. Moreover, their effects are often inher- allow the measurement of child survival, school ited by subsequent generations. Even in well-off 15 enrollment, and stunting rates at the individual 10 This section is largely based on D’Souza, Gatti, and Kraay (2019). 11. Barrera-Osorio, Linden and Urquiola (2007). 12. Björkman-Nyqvist (2013). 13. Dupas (2011); Jensen (2010). 14. Jayachandran and Kuziemko (2011); Kahn and Ginther (2017); La Ferrara, Chong, and Duryea (2012). 15. Chetty et al. (2018). 16. Lindahl et al. (2015). 17. Wagstaff, Bredenkamp and Buisman (2014). 10 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX and household levels, as well as by socioeconomic contribution to productivity, a socioeconomically quintile. The harmonized student test scores disaggregated HCI (SES-HCI) can be constructed underlying the global HCI can also be organized for a set of 50 mostly low- and middle-income by socioeconomic quintile (box 2.1). 18 Using the countries, slightly under one-third of the 157 HCI methodology to translate these data into their countries covered by the global HCI.19 Constructing a Socioeconomically Disaggregated HCI (SES-HCI) BOX 2.1  The SES-HCI sheds light on inequalities in human capital accumulation across socio- economic groups. It is computed using the same methodology as the calculation of the global HCI, described in Kraay (2019), but relies on different data sources to allow for a disaggregation by socioeconomic status (SES). Mortality and stunting rates among children under age 5 and school enrollment rates for ages 6 to 17 come from nationally representa- tive DHS and MICS. These are drawn from two existing compilations of SES-disaggregated DHS-MICS data–the Health Equity and Financial Protection Indicators (HEFPI) database, described in Wagstaff et al. ,(2019), and the household wealth and educational attainment dataset, first described in Filmer and Pritchett (1999). SES-disaggregated harmonized test scores are obtained from Abdul-Hamid and Iqbal (2019), who in turn draw on the same data- base of student-level harmonized test scores used in the 2018 HCI, as described in Patrinos and Angrist (2018). The DHS and MICS contain information on household characteristics and asset ownership that can be used to create a wealth index. Similarly, Abdul-Hamid and Iqbal (2019) develop proxies for the SES of the households in which each student resides based on data collected by the testing program on the home possessions of students, as well as parental education and occupation. In the DHS-MICS context, these indexes are usually referred to as wealth or asset indexes. International testing program databases construct conceptually similar indexes, but use terms such as economic, social, and cultural status. For terminological con- venience, all these measures are referred to here as SES indexes. To create the sample of countries for the SES-HCI, data from DHS-MICS surveys are aligned with test score data to account for the fact that the positions of students in the SES distribu- tion in the test score data cover only the households of children who are attending school (because the harmonized test scores are measured using school-based tests), while the DHS-MICS data cover all households, including those in which children do not attend school. Consider, for example, a country where the test scores are taken from the Programme for International Student Assessment (PISA), which is administered to 15-year-olds. Enrollment rates for 15-year-olds by SES quintile in the DHS-MICS are used to calculate the fraction of students attending school associated with each SES quintile in the DHS-MICS. For instance, if students in the bottom SES quintile are more likely to drop out of school, then students in the bottom quintile might, for example, represent only 15 percent of test takers even 18. Data sources for the SES-HCI are detailed in appendix 2. The SES-HCI has a more limited country coverage than the global HCI (50 vs 157 countries) because it requires a DHS or 19  MICS to be available, as well as student-level data on harmonized learning outcomes taken from a test carried out reason- ably close in time to the DHS or MICS S ocioeconomic Disaggregation 11 though they account for 20 percent of households. In this case, the average harmonized test score for the poorest 15 percent of test-takers (according to the SES-HCI in the test score data) is assigned to the households in the poorest quintile in the DHS-MICS. A similar approach is applied for each quintile to arrive at average harmonized test scores for each DHS-MICS quintile. This process creates a single cross-section of 50 countries, using the most recent-available DHS-MICS and testing data. Although the SES-HCI uses the same methodology as the global HCI, it differs in several key respects. First, the SES-HCI uses household survey-based measures of school attendance, which can differ considerably from the administrative data used in the global index. Second, because of data limitations, the SES-HCI measures expected years of school between ages 6 and 17, while the global HCI relies on administrative data covering the 4 to 17 age range. Third, because household survey data do not provide estimates of adult mortality, the health component of the SES-HCI is based only on stunting rates, unlike the global HCI, which uses stunting rates and adult survival rates. Taken together, these differences imply that the SES- HCI data at the quintile level and averaged to the national level are not fully comparable or consistent with the global HCI, and country scores and relative positions can differ between the SES-HCI and the global index. However, the SES-HCI can still prove informative about gaps in human capital outcomes across quintiles. (Appendix 1 provides a more detailed description of these differences). Source: D’Souza, Gatti, and Kraay 2019. UNDERSTANDING SOCIOECONOMIC GAPS country-average SES-HCI values. These gaps are IN HUMAN CAPITAL illustrated in figure 2.1, where quintiles of the The SES-HCI varies considerably, ranging between SES-HCI are plotted for each country relative to 0.3 to 0.4 in the least well-performing countries, per capita GDP and against the background of the such as Chad, Mali, and Niger, to around 0.7 in the global HCI (light grey dots). top-performing countries, such as Armenia and Vietnam. Socioeconomic gaps in human capital outcomes within countries are large and Across countries, as with the global HCI, the SES- HCI increases with per capita income. And, within account for nearly one-third of the total countries, rich households have better outcomes variation in the SES-HCI. than poor ones. These rich-poor gaps are appar- ent across the whole income spectrum. For exam- The differences in human capital between rich ple, in Madagascar, the SES-HCI ranges from and poor people contribute substantially to 0.40 in the poorest quintile to 0.58 in the richest overall differences in human capital around the quintile, while, in much richer Vietnam, the gap world. Nearly one-third of the total variation in ranges from 0.58 to 0.85. In the latter, the with- human capital consists of within-country differ- in-country difference between the top and bottom ences across socioeconomic quintiles. Differences quintiles is roughly half the size of the cross-coun- in child survival and test scores across quintiles try difference between the highest and lowest within countries account for a relatively small 12 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX FIGURE 2.1  Socioeconomically Disaggregated Human Capital Index Source: D’Souza, Gatti, and Kraay 2019. Notes: The figure plots the HCI disaggregated by quintiles of socioeconomic status (on the vertical axis) against log real GDP per capita (on the horizontal axis) for the most recent cross-section of 50 countries in the SES-HCI dataset. A solid dot indicates the average across quintiles, and the top (bottom) end of the vertical bar indicates the value for the top (bottom) quintile. The light grey data points show the global HCI for countries for which the SES- HCI is not available. share of the overall variation in these outcomes: 21 convergence in rich-poor gaps reflects the bene- percent and 23 percent, respectively. Instead, with- fits of improved access to health care for pregnant in-country rich-poor gaps in expected years of women, newborns, and young children, as well as schooling and stunting account for a considerably better nutrition and sanitation. This is partly attrib- larger share of the overall variation in these out- utable to the increased coverage of several key comes, at 31 percent and 33 percent, respectively. interventions over the last two decades that have particularly benefited children from the most dis- As countries get richer, the rich-poor gap in the advantaged backgrounds, including antenatal care SES-HCI decreases, albeit slightly. This is captured visits with skilled health personnel, facility-based in figure 2.1 by the length of the vertical bars and in labor and childbirth care, vitamin A supplementa- figure 2.2, which plots the difference in outcomes tion, immunization, and safe drinking water.20 between the top and bottom socioeconomic quin- tiles against per capita GDP. Despite these gains, poor countries and poor house- holds continue to bear a disproportionate burden The rich-poor gap decreases as countries get richer of child mortality. For example, a child in the poor- in all but one component of the SES-HCI: learning est households in Burundi has an 84 percent chance outcomes. For child survival, the cross-country of surviving to age 5, compared with 92 percent in 20. Chao et al. (2018); Liu et al. (2016). S ocioeconomic Disaggregation 13 FIGURE 2.2  Rich-Poor Gaps in Human Capital across Countries Source: D’Souza, Gatti, and Kraay 2019. Notes: The figure plots gaps in human capital outcomes between the top and bottom quintiles (on the vertical axis) against log GDP per capita (on the horizontal axis) for the most recent cross-section of 50 countries in the SES-HCI dataset. The Q5- Q1 gaps are defined as (a) the difference between the top and bottom quintiles (for expected years of schooling, harmonized test scores, quality-adjusted years of school, and the not-stunted rate) and (b) the log-difference between the top and bottom quintiles for child survival and for the overall HCI. 14 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX the most affluent families. In contrast, in Armenia, However, this progress materialized in an uneven children in both poor and rich households can way across and within countries. Consider hope to reach age 5 with near certainty. This is in Guatemala and Madagascar. Notwithstanding a tandem with a global trend whereby coverage of significant difference in per capita income, both key interventions among the richest far exceeds countries have among the highest stunting rates in that among the poor. Infectious diseases, such as the world; nearly half of all children are stunted. pneumonia and diarrhea, affect children in poor In Madagascar, stunting is uniformly high across households more compared with their rich coun- all socioeconomic groups, while in Guatemala, a terparts as they continue to lack access to effective child in the bottom socioeconomic group is more treatments, appropriate nutrition, safe water, and than three times as likely to be stunted than a child sanitation facilities. Likewise, the burden of new- in the top quintile. born deaths, a key contributor to poor child sur- vival, is disproportionately high among the poor. Moreover, the poor in poorer countries continue Unlike other HCI components, stunting to fare worse than the poor in richer countries. does not necessarily decrease among wealthier households In countries with the largest socio- economic gaps, young children in the Moreover, in many countries, stunting does not poorest households still face a significant decrease in lock step with income.23 Figure 2.3 risk of not making it to their 5th birthday. reports the fraction of children not stunted for a selection of countries in which the gap between Nevertheless, countries such as Malawi, Tanzania, the poorest households (the 1st quintile) and the and Uganda have succeeded in improving child 4th quintile is smaller than the gap between the 4th survival significantly, while narrowing the differ- quintile and the richest households (the 5th quin- ences between the rich and the poor. These exam- tile). This likely reflects the complexity of the basic ples indicate that supporting the improved cov- and underlying determinants of undernutrition, erage and quality of key reproductive, maternal, including environmental, economic, and cultural newborn, and child health interventions, with a factors. The need to respond through multi-sectoral focused attention on socioeconomically disad- programs that simultaneously address these multi- vantaged groups, is critical in addressing these ple drivers has been recognized internationally.24 disparities.21 Over the last 50 years, schooling has expanded The benefits brought about by higher income are dramatically in most low- and middle-income also evident in other markers of child well-being. countries. In some countries, this expansion has Globally, stunting rates decline with increasing per been at historically unprecedented rates, both in capita income and stunting prevalence fell from primary and secondary education.25 Unfortuna- 40 percent to 22 percent between 1990 and 2017.22 tely, children in marginalized groups continue 21. Requejo et al. (2015). de Onis and Branca (2016) for 1990 data; Galasso and Wagstaff (2017); WDI (World Development Indicators) (database), 22.  World Bank, Washington, DC, https://datacatalog.worldbank.org/dataset/world-development-indicators for 2017 data. 23. de Onis and Branca (2016). 24. World Bank (2018a). 25. World Bank (2018c). S ocioeconomic Disaggregation 15 FIGURE 2.3  Socioeconomic Gradient in Nonstunting Rates by Income Level Source: World Bank calculations based on DHS-MICS data as reported in Wagstaff et al. 2019. to face significant barriers in accessing and com- quintiles—here captured by an estimate of pleting primary education and in transitioning to wealth  —across a selection of countries. The y-axis 27 higher grades, all of which translates into a per- shows the proportion of the population ages 10–19 sistent association between schooling and socio- that has succeeded (that is, survived) to each grade economic status. (grades 1–9).28 There are striking differences in the grade survival patterns across and within countries Figure 2.4, which is drawn from the World Bank comparing children in the richest quintile (repre- educational attainment database, depicts these sented by the red continuous line in the panels) to patterns and their heterogeneity.26 It details those in the poorest quintile (represented by the grade survival trajectories by socioeconomic blue continuous line). 26. See Educational Attainment (database), World Bank, Washington, DC, http://iresearch.worldbank.org/edattain/. Wealth status is captured by a proxy based on the assets owned by members of the household. 27.  To accommodate the fact that the full school trajectory until grade 9 is not observed among younger children, the proba- 28.  bility of completing future grades is estimated using a hazard function. 16 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Especially in the poorest countries and benchmarking progress and quantifying learning gaps across socioeconomic groups.29 The evidence for poorer households, a large portion of shows that better learning continues to be associ- children never start school or fail to stay ated with higher socioeconomic status across and in school as they get older. within countries, signaling differences in access to quality education.30 In Chad—the country that scored the lowest in the global HCI—as of 2015, only 60 percent of chil- In the SES-HCI sample of low- and middle-income dren ages 10–19 from the bottom four socioeco- countries, learning inequality increases as coun- nomic groups had completed grade 1, and barely tries get richer. This can be due to many factors, 30 percent had completed grade 9. This is in sharp and more research is needed to disentangle them contrast with the 80 percent of 10- to 19-year-olds fully.31 Yet, emerging evidence suggests that this in the top quintile who had completed grade 1 and pattern disappears above a certain income level. were significantly more likely to stay in school This is consistent with the experience in high- until grade 9. income countries, such as Germany and Poland, that have been able to increase their overall perfor- In Pakistan, moving from a lower to a higher socio- mance in student assessments by improving learn- economic quintile is associated with a progressive ing among children at low levels of achievement, improvement in both access to school and grade often those with more marginalized backgrounds.32 survival. In 2012, only 44 percent of children from For example, following the unexpectedly poor the lowest wealth quintile were enrolled in grade 1, results in the 2000 Programme for International and only 20 percent of these children graduated to Student Assessment (PISA), the German govern- grade 9. In other countries, gaps emerge only later in ment implemented a series of reforms, including the school system, for example, in Thailand, where reduced tracking and segregation, standardization the wealth gap becomes evident only in grades 6 of curricula, expansion and strengthening of the and 7. educational content of pre-primary schools, that effectively reduced the gap between children with Furthermore, being in school does not necessarily advantaged and disadvantaged educational back- translate into learning. International and national grounds and improved the country’s overall per- student assessments have been instrumental in formance in subsequent PISA assessments.33 29. Crouch and Gustafsson (2018). 30. Martins and Veiga (2010). On the one hand, this pattern could be due to underlying factors such as the fact that tests in the poorer countries in this 31.  sample tend to focus on primary school, while tests in richer countries are more likely to cover secondary school-aged children. If individual differences in learning ability accumulate over time, this could contribute to the observed regular- ity of greater dispersion in test scores in rich countries. It could also reflect selection, if the children in school in poorer countries come from a more homogenous background than the children in school in richer countries. On the other hand, this pattern is also to some extent a consequence of the test score harmonization methodology. Tests are harmonized by (a) first rescaling testing data from individual testing programs to have mean 500 and standard deviation 100 across all students taking that test in all countries and (b) then developing a multiplicative exchange rate between testing programs that reflects the ratio of the average performance of students in countries participating in two testing programs. This ratio is smaller than one for the testing programs in poorer countries. For example, for Early Grade Reading Assessment test (EGRA), the scaling factor is 0.73 relative to the benchmark. This multiplicative adjustment factor reduces both the mean and the dispersion in harmonized test scores in EGRA relative to the benchmark. This contributes to the pattern of lower dispersion in harmonized test scores in the poorer countries relative to the richer countries in the sample. There is ample debate on the policies that can be effective in improving education outcomes. See, for example, Glewwe 32.  and Muralidharan (2016). 33. Davoli and Entorf (2018). S ocioeconomic Disaggregation 17 FIGURE 2.4  Proportion of 10- to 19-Year-Olds Who Have Attained Each Grade, by Wealth Quintile Source: Educational Attainment (database), World Bank, Washington, DC, http://iresearch.worldbank.org/edattain/; Filmer 2018. 18 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX HUMAN CAPITAL OUTCOMES AND INCOME WITHIN AND ACROSS COUNTRIES average, the rate at which human capital improves with income within countries is similar to the rate Countries differ greatly both by the level of human at which human capital improves with income capital acquired by the poorest and by how quickly between countries.34 This suggests that, on aver- human capitalincreases if one shifts attention age, governments have not been more successful from households in the bottom income quintile to in reducing inequalities in human capital than the those at the top. Figure 2.5 shows the relationship effect that getting richer has across countries. between SES-HCI and log income across quintiles across different regions. This human capital-in- National governments have the ability and often come gradient is depicted as an upward sloping the mandate to reduce inequalities in health line for each country, while the five data points and education outcomes across income groups. correspond to the five socioeconomic quintiles. The analysis in this section reveals an unfinished agenda: with low average human capital outcomes In countries with steeper slopes (illustrated in red), and considerable gaps between the rich and the the income distribution is relatively more com- poor. The extent of these gaps varies across human pressed than the distribution of human capital. In capital dimensions and country income. these countries, a small increase in income is asso- ciated with significant increases in human capital. On the whole, rich-poor gaps in the SES-HCI tend Green lines highlight countries in which the dis- to decrease slightly as countries get richer, and tribution of human capital is relatively egalitarian, government redistributive policies do not seem to which results in flatter slopes. do a better job of reducing human capital inequal- ity than the effect of increased national income. At For example, in the top-left panel, the fairly flat the same time, the heterogeneity of the slopes in green line for Haiti shows that the country exhib- figure 2.5 indicates that individual countries have its relatively small differences in human capital different degrees of success in decoupling human outcomes across socioeconomic quintiles despite capital outcomes among children from the income quite large income differences across quintiles. differences among their households. Conversely, the steep red line for Guatemala high- lights that country’s large differences in human Addressing these rich-poor gaps in human capital capital outcomes across quintiles given the level of must remain a priority for governments because, in income inequality. many cases, the returns to investment in the human capital of disadvantaged groups, especially early in These relationships reflect both the historical life, are the highest. distribution of income within countries and the cumulative effectiveness of policies that redistri- buted human capital across different socioeco- nomic groups. Regression results show that, on Pooling the quintile level data on the SES-HCI and log income per capita for all countries allows a between and a within 34.  regression of the former on the latter to be estimated and thus answer the question, how the within-country relationships between human capital outcomes and income levels compare with the corresponding pattern across countries. Both for the SES-HCI and for all but one of its components, the slope of the relationship between countries is similar to the with- in-country slope. The one exception to this pattern is child survival rates, where the within-country gradient with income is consistently smaller than the between-country gradient with income. The results are described in detail in D’Souza, Gatti and Kraay (2019). S ocioeconomic Disaggregation 19 FIGURE 2.5  Human Capital: Income Gradients within Countries Source: D’Souza, Gatti, and Kraay 2019. Notes: The figure reports the within-country relationship across quintiles between the SES-HCI and log per capita income. Per capita income in each quintile is approximated using the quintile share in income or consumption as reported in the PovcalNet tool for the survey nearest to the SES-HCI data, together with GDP per capita as the mean. The upward sloping lines in each panel trace the five quintile values for each country. The heavy solid green line (heavy dashed red line) shows the country in each group with the flattest (steepest) within-country gradient between the SES-HCI and log income per capita. See PovcalNet (online analysis tool), World Bank, Washington, DC, http://iresearch.worldbank.org/PovcalNet/. 20 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX 3 Spatial DISAGGREGATION S PAT I A L DI SAG G R EGAT ION 21 W hile inequality between countries has reflect differences in human capital now more decreased in the past decades, increa- than ever. However, migration from rural to urban sed inequality within countries and areas does not always level the playing field among especially the urban-rural disconnect are growing unskilled workers. Evidence from the United concerns for many.35 This phenomenon reflects States shows that non–college educated workers important and interrelated global trends such as who live in urban areas are employed in occupa- urbanization and technological change. tions that require lower skills and pay lower real wages than in the past.37 Irrespective of a country’s Across countries, a 1 percentage point increase in income level, these trends are likely to increase the the share of the urban population is associated importance of the quality of the schools and health with a 3.8 percent increase in GDP per capita.36 facilities in the places where individuals grow up. This exemplifies a trend that is common to many countries around the world: urban regions are There is growing consensus among economists growing much more quickly than rural ones. that place-based policies should be tailored around the skills of the people who live in the places. For Spatial inequalities are increasing, example, the benefits that a community obtains from major infrastructure relative to a targeted reflecting urbanization and the skill- welfare program or research and development biased nature of technological change. incentives depend on the skills of the residents.38 Geographically disaggregated measures of human Technological change and automation exacerbate capital can provide a useful lens to identify areas this rural-urban divide. Skill-based technologi- where governments can target their resources cal change—innovation that is complementary most effectively to invest in the human capital of to higher-order skills—has contributed to the the young. increase in monetary and non-monetary returns for highly skilled individuals who opt to live in urban areas relative to those who are less well edu- SUBNATIONAL INEQUALITY IS SUBSTANTIAL cated or live in rural areas. Moreover, because of The HCI offers a natural starting point to help pol- agglomeration externalities, well-educated work- icy makers identify policies that can reduce with- ers become more productive and attract the most in-country disparities. The evidence that follows dynamic and innovative firms if they are sur- reflects the ongoing work of country teams at the rounded by peers with similar characteristics. As World Bank and showcases findings from 11 coun- a result, disparities between urban and rural areas tries: Angola, Burkina Faso, Chad, Indonesia, Mali, 35. World Bank (2016). 36. Ferreyra and Roberts (2018). 37. Autor (2019). 38. Austin, Glaeser and Summers (2018); Hendrickson, Muro and Galston (2018). 22 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Spatial Disaggregation Conducted by World Bank Country Teams BOX 3.1  The 11 disaggregations of the HCI (GEO-HCI) featured in this section were computed by World Bank country teams. The level of disaggregation varies by country: the GEO-HCI for Angola, Burkina Faso, Indonesia, Sierra Leone, and Sri Lanka is disaggregated by region; for Chad, Mali, Niger, and Peru by province; and for Romania at the county- level. In addition, data for Vietnam are disaggregated by ethnic group. The GEO-HCI illustrates disparities in human capital outcomes within countries. The differences in levels of disaggregation pre- clude cross-country comparisons of these gaps. For example, the range between best and worst performers is likely to be larger in countries that disaggregate at a lower subnational unit. Like the SES-HCI, the GEO-HCI is based on the same methodology as the global HCI but uses different data sources in the calculation of disaggregated HCI scores at the subnational level. Some country teams also modify the complete education benchmark of 14 years used in the global HCI to reflect more closely the standard duration of the country’s education system. As a result, the GEO-HCI data at the subnational level, and averaged to the national level, are not fully comparable or consistent with the global HCI, and country scores and relative positions can differ between the GEO-HCI and the HCI. Accordingly, comparisons between the two should be made recognizing these differences. Because the analysis of these 11 countries reflects country interest and demand in analyzing regional inequality, this is not a representative or purposefully selected sample and patterns should be interpreted with caution. This grouping, however, covers each global region and is split among low-, lower-middle-, and upper-middle-income brackets, including two frag- ile states according to the World Bank classification. Nonetheless, because of the sample limitations, the analysis is not conducive to generalizations and is more akin to a case study approach, which highlights the potential of the methodology. Niger, Peru, Romania, Sierra Leone, Sri Lanka, bottom-performing regions are significant, but and Vietnam (box 3.1). 39 they are especially large in middle-income coun- tries, such as Indonesia and Peru. Capital regions Overall, in this sample, richer regions within are typically the top performers (see figure 3.1), countries have better human capital outcomes, a trend that is particularly pronounced in the mirroring the pattern across countries. Figure 3.1 low-income countries. However, the relationship shows the GEO-HCI and per capita income for between the GEO-HCI and per capita income is eight countries on which subnational GDP per not always linear. For example, in Sri Lanka, the capita data were available. best and worst performers are neither the richest region nor the poorest and most conflict affected In the 11 countries studied here, within-country region, respectively. differences in the GEO-HCI between the top and 39. Data sources for the GEO-HCI are detailed in Appendix 3. S PAT I A L DI SAG G R EGAT ION 23 FIGURE 3.1  The Relationship between Income and the GEO-HCI Varies with Country income Source: World Bank calculations based on GEO-HCI and GDP data provided by World Bank country teams. See appendix 3 for details. Notes: Prices adjusted at 2011 purchasing power parity. To calculate subnational GDP per capita for Burkina Faso, Chad, Indonesia, Mali, and Niger, national GDP per capita is multiplied by the ratio of subnational per capita consumption to mean per capita consumption. 24 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX FIGURE 3.2  The Spatial Gaps in Harmonized Test Scores Are Large in Romania Source: Lucchetti, Badiani-Magnusson, and Ianovici 2019. No matter the income level of the country, human relative to their peers, whether in rural or in urban capital within regions can differ along many areas. The stunting rate among children under- dimensions, such as rural-urban status and ethnic- 5-year-olds is three times higher among urban ity. For example, the urban-rural divide in learn- indigenous children than among urban nonin- ing outcomes in Romania is significant. In Vaslui digenous children, and 10 points higher between County, there are urban areas that score as high rural indigenous and rural non-indigenous.40 as Ukraine, while there are rural areas that rank at par with Senegal (figure 3.2). WHAT DIMENSIONS OF HUMAN CAPITAL DRIVE THESE INEQUALITIES? Within regions, minority group status also cor- relates with differences in human capital out- Like the global HCI, where both the quality and comes. In the global HCI, Vietnam ranks close to the quantity of schooling constitute an important the high-income country average and well above driver of the variation across countries, education the average among lower middle-income coun- outcomes are clear drivers of regional inequality tries (its own income group). However, disaggre- in the GEO-HCI. Romania, Peru, and Sri Lanka— gation of 2014 data shows that ethnic minori- middle-income countries with relatively higher ties score 0.62 in the GEO-HCI, compared with HCI scores—show large variations in learning out- 0.75 for the ethnic-majority Kinh. At 32 percent, comes, but little differences in expected years of stunting rates are two times larger among ethnic school. Conversely, countries with lower overall minorities than among the Kinh majority. School HCI scores show little variations in learning out- enrollment also lags among ethnic minorities comes, but relatively large variations in expected relative to their Kinh peers by 30 percentage points. years of school. In Peru, indigenous populations underperform 40. Marini and Rokx (2017). S PAT I A L DI SAG G R EGAT ION 25 FIGURE 3.3  Spatial Disaggregation of Learning Outcomes and Years of Schooling, Select Countries Source: World Bank calculations based on GEO-HCI data provided by World Bank country teams. Notes: Countries are ordered from the poorest to the richest. Within the small group of countries analyzed variation in learning observed in these countries here, the variation in learning outcomes versus despite high enrollment. In low-income countries, years of schooling seems to suggest that access to with more limited access to school, it is possible schooling does not necessarily translate into real- that the group of test-takers is more homogenous ized learning (figure 3.3). In middle-income coun- in terms of school readiness, although at lower tries, the systematic improvements in enrollment levels. This may explain why Angola, Mali, and and completion rates, especially in regions that Niger display relatively high within-country varia- started from low levels, may have led to an inflow tion in expected years of school and little differen- of students with different levels of school readi- tiation in terms of learning outcomes.41 ness. This is likely to account, in part, for the large As discussed in section 2, some of the differences in the patterns of learning dispersion between rich and poor countries 41.  are related to the statistical process of the harmonization of various test scores from different student assessments. 26 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX In countries with less human capital, regional dif- FIGURE 3.4  Range of Stunting Outcomes, by ferences in stunting are large and play a key role Region, Select Low-Income Countries in explaining within-country variations in the overall rate. For example, figure 3.4 shows that, in Niger, stunting ranges from 18 percent to 43 per- cent across regions. Similarly, in Angola, the stunt- ing rate is more than two times higher in some regions than in others, ranging from less than 25 percent to roughly 50 percent. In Mali, the spread is also substantial, 24 percent to 41 percent. Some of these outcomes are stubbornly difficult to modify, particularly in the case of typically mar- ginalized groups. Although the rate of stunting was reduced in Peru by more than half between 2008 and 2016, stunting remains high, at nearly 26 percent, in rural areas. By contrast, even with high levels of poverty in large cities such as Lima, the Source: World Bank calculations based on GEO-HCI data urban stunting rate is only 8 percent.42 In Vietnam, provided by World Bank country teams. the prevalence of stunting among ethnic minority groups compared with the majority Kinh is widen- country such as Chad, which, with a score of .29, ing. Between 2010 and 2015, stunting among eth- ranks at the bottom of the global HCI. The GEO- nic minorities dropped by 5 percent, to 31 percent, HCI shows minimal variation within the country. affecting nearly one-third of all minority children. However, within regions, index components vary By contrast, the rate of stunting among Kinh chil- quite substantially and, in some cases, in ways that dren was only 15 percent and dropped by 7 percent are negatively correlated to each other. For exam- over the same period.43 ple, regions with more schooling have relatively lower learning outcomes. Understanding how dif- ferent factors drive poor human capital outcomes LOOKING WITHIN THE HCI in different regions of a country can help deter- Resource-constrained countries may need to mine priority areas for intervention. relevant efforts not only across different regions, but also across different types of interventions. The degree of regional variation of the health and Information on region-specific HCI education components of the HCI can provide outcomes can help in tailoring locally guidance for policy action. Reducing class sizes relevant policies. in education might be less urgent than nutrition interventions in those areas where there are high rates of stunting, especially because addressing nutrition is likely to have important repercussions on school readiness. This might be the case in a 42. Section 4 discusses the current reforms in Peru. 43. Mbuya, Atwood, and Huynh (2019). S PAT I A L DI SAG G R EGAT ION 27 HOW ARE THESE FINDINGS INFORMING The GEO-HCI also complements other available ACTION? data and, through triangulation, can deepen the picture of the constraints on human capital accu- In the absence of adequate policy responses, mulation. Vietnam’s interest in further disaggre- high rates of poverty, when combined with low gation of outcomes among ethnic minorities has levels of human capital, can compromise the prompted a change in methodology in national hopes of many generations. The challenges of surveys. The Peruvian government uses different poverty, the urban-rural disconnect, and poor human capital indicators at the subnational level human capital outcomes can be mutually—and to monitor policy implementation and inform negatively—reinforcing. results-based budgeting. Measuring different outcomes—both Matching GEO-HCI data with information of the in the HCI overall and its component Service Delivery Indicators Initiative, which tracks parts—across regions can help target the variation in skills and the efforts of providers within health and education systems, can provide those most in need. insights into capacity delivery. In Angola, regions found through the initiative to have higher rates Emerging evidence shows that targeting based of teacher absenteeism and fewer textbooks in on multiple methodologies, such as poverty, geo- schools also have worse human capital outcomes graphical, and community approaches, appears to in the GEO-HCI data. Moreover, as in the GEO- be most effective in reaching the vulnerable and HCI, urban-rural divides in initiative data reveal typically marginalized. Combining the GEO-HCI 44 significant differences in the diagnostic accuracy with measures of monetary poverty can also help and adherence to clinic guidelines among health governments achieve the better equity-efficiency providers. For example, health providers in Sierra trade-offs implied by various alternative policy Leone were significantly more likely to be absent options. For instance, in two equally poor regions, in urban facilities. the government might differentiate the types of firms that receive tax benefits and grants accord- The GEO-HCI helps build an evidence base that ing to the average level of human capital in the governments can use to design, target, and moni- regions. Disaggregation on additional dimensions tor better responses to address the needs of those highlights the need for nuance. For example, the falling farthest behind. evidence in Romania shows that rural populations, even within one region, are disadvantaged com- pared with urban ones. In Vietnam, the HCI disag- gregation shows that ethnic minorities fare worse than the Kinh majority even in the same areas. 44. World Bank (2016). 28 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX 4 REALIZING CHANGE: A Whole-of-Government Approach R ealiz ing C hange: A Whole - of- G ov ernment A pproach 29 B ecause of the large shortfalls in human cap- Countries that have seen the most ital and the persistent inequality, empower- dramatic gains have achieved continuity ing disadvantaged populations is an urgent priority. The experiences of countries such as of reforms across political cycles. Bangladesh, India, and Peru show that it is possible to bring about change through concerted govern- gains have achieved continuity in reforms across ment action to deliver not only marked improve- political cycles. Improving outcomes among the ment in national outcomes linked to human capital poor and reducing inequality in outcomes requires but also convergence in terms of equity. a similarly enduring effort. The success stories in this section span a wide In India, the government’s drive for universal pri- array of critical issues. The rate of stunting was mary education began with a flagship program, halved in Peru in less than a decade, and prog- Sarva Shiksha Abhiyan (education for all move- ress was more rapid among the poorest house- ment), which was launched in 2001 and codified into holds. At the beginning of the 20th century, uni- law in 2009 and which has remained a priority. The versal primary education became a goal in India program has sought to universalize quality educa- and, in 2015, 99 percent gross net enrollment tion for children ages 6–14. By 2007, the number was achieved, including a focus on gender parity of out-of-school children had fallen from 32.0 mil- and access among typically marginalized groups. lion to 13.5 million, with significantly better access Since independence, Bangladesh has seen one of among girls and typically marginalized groups. the most dramatic reductions in fertility globally, Recognizing the need for ongoing attention to this from nearly seven births per woman to approxi- critical area, the government continued to priori- mately two. tize funding for the flagship program and signaled its commitment to universal primary education by A common theme across these country examples adopting the 2009 Right to Free and Compulsory is a whole-of-government approach that com- Education Act, which became effective in April bines sustained political commitment, coordina- 2010. In 2015, the gross enrollment rate reached 99 tion across sectors, and the use of evidence-based percent. As a result of the government’s commit- policies.45 ment to equality in outcomes, in the 2016/17 school year, the shares of girls, scheduled caste, scheduled tribe, and Muslim children enrolled in primary STAYING THE COURSE: LONG-TERM school was greater than the respective shares in the COMMITMENT TO EQUITY overall population.46 The progress in access and Building human capital requires sustained commit- in the eventual reduction in inequality in years of ment. Countries that have seen the most dramatic school is represented in figure 4.1. The whole-of-government concept is explored in a series of briefs published by the World Bank. For instance, see World 45.  Bank (2019b); see also “Human Capital Project,” World Bank, Washington, DC, https://www.worldbank.org/en/publication/ human-capital. 46. World Bank (2018d). 30 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX FIGURE 4.1  Progress in School Access in India Source: World Bank calculations based on DHS-MICS data reported in Filmer and Pritchett 1999 and subsequent updates. Notes: The figure plots expected years of school disaggregated by quintiles of socioeconomic status (on the vertical axis) against log real GDP per capita (on the horizontal axis) for the most recent cross-section of 50 countries in the SES-HCI dataset. A solid dot indicates the average across quintiles, and the top (bottom) end of the vertical bar indicates the value for the top (bottom) quintile. Orange bars show the spread of expected years of school in India over time, and grey bars show the spread by income across countries on which data are available. In Bangladesh, a commitment to pro-equity WORKING TOGETHER: COORDINATION development policies undertaken at indepen- ACROSS AND BEYOND GOVERNMENT dence in 1971 and has been maintained into the present.47 In successive national plans, the govern- Peru’s national strategy for early childhood devel- ment identified clear priorities linked to women’s opment, Crecer, created a holistic framework that empowerment, from family planning to maternal helped reduce the rate of chronic malnutrition health and women’s education. In Peru, stunting from 28 percent in 2005 to 13 percent in 2016 featured as a priority issue in all presidential elec- and saw an even pace of change among rural and tion campaigns from 2006 to 2016. Four succes- urban children. As illustrated in figure 4.2, the sive governments maintained the continuity of change in stunting rates also has seen convergence the effective public policies put in place by their in outcomes across socioeconomic status. While predecessors, but with each administration setting stunting remains correlated to household socio- its own new and ambitious targets.48 economic status, the gap between the poorest and 47 World Bank (forthcoming). 48. Marini and Rokx (2017). R ealiz ing C hange: A Whole - of- G ov ernment A pproach 31 FIGURE 4.2  Rates of Nonstunting, by Income, Peru Source: World Bank calculations based on DHS-MICS data as reported in Wagstaff et al. 2019. Notes: The figure plots nonstunting rates disaggregated by quintile of socioeconomic status (vertical axis) against log real GDP per capita (horizontal axis) for the most recent cross-section of 50 countries in the SES-HCI dataset. The solid dot indicates the average across quintiles, and the top (bottom) end of the vertical bar indicates the value for the top (bottom) quintile. Orange bars show the spread of nonstunting rates in Peru over time, and grey bars show the spread by income across countries on which data are available. richest households nearly halved, from 48 percent- sector, international development agencies, and age points to 26 percentage points between 2000 grassroots organizations. The government coor- and 2016. dinated horizontally across ministries and pub- lic bodies as well as vertically among national, Launched in 2007, Crecer coordinated across var- regional, and municipal authorities. Moreover, ious actors to deliver diverse services targeted at 1 there was reliance on a strong commitment to million children under age 5. It focused first on the measurement, including fielding DHS surveys on poorest areas of the country. The national strategy a continuous basis beginning in 2000 rather than acknowledged that good nutrition alone could not at the typical five-year intervals. reduce stunting and therefore involved multiple areas, such as water, sanitation, access to health ser- Change requires coordination across vices, education, and the empowerment of women government, as well as crowding-in the in poor, remote, and rural communities. To imple- ment this vision, Crecer allied national, regional, private sector, development partners, and municipal governments alongside the private and civil society. 32 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX The government also adopted an effective condi- As part of the comprehensive strategy, the govern- tional cash transfer program and a comprehensive ment’s Family Planning Program built on concrete public insurance scheme that increased health evidence of how community health workers could coverage among Peru’s poor and vulnerable pop- help implement changes in household family ulation from 32 percent to 75 percent in slightly planning and maternal and child health. Launched less than a decade. in 1977, the Family Planning and Maternal Child Health Program in Matlab Subdistrict began with Similarly, following independence, the govern- biweekly household visits focused on contracep- ment of Bangladesh worked across a range of stake- tion options and then expanded to include infor- holders to achieve a reproductive revolution and mation on related health services. By 1982, cen- wide-ranging successes in health and education sus data showed a 15 percent decrease in fertility outcomes. Local and national government entities, compared with neighboring administrative areas. the formal and informal private sector, private Building from this evidence, the government and nonprofit nongovernmental organizations, launched the national Family Planning Program and donors engaged in improving services and the to provide multidimensional maternal and child uptake of services, particularly in poor areas, which health services at the household level. At its peak, involved religious and community leaders playing the program employed 28,000 married women a key role in supporting behavior change. across the country as family welfare assistants.49 USING EVIDENCE: UNDERTAKING REFORMS Evidence can help countries identify and AND ALLOCATING RESOURCES BASED reach those segments of the population ON DATA that are most in need. Setting policies and allocating resources based on evidence of a country’s human capital challenges Similarly, a nongovernmental organization, the can help drive higher returns to investment. It also Bangladesh Association for Community Education, can help countries identify and reach those seg- started the Secondary School Stipend Program ments of its population that are most in need. in six districts in 1982 and witnessed positive out- comes. While still low overall, the pilot areas saw In the early 1970s, Bangladesh had high population an increase in average female secondary-school density, a high poverty rate, and low food produc- enrollment from under 8 percent to 14 percent. tion. A total fertility rate of over six children per In 1994, the government launched the program woman only compounded these challenges, and nationally, and, from 1999 to 2005, an average the government set an ambitious target of reduc- of nearly 3.5 million girls received stipends each ing this number by two-thirds by 1985. While this year. This contributed to a jump in female second- was not achieved as quickly as hoped, the gov- ary-school enrollment from 1.1 million in 1991 to ernment maintained a commitment to this goal, 3.9 million in 2005.50 and, in 2017, the total fertility rate was 2.1. Map 4.1 shows that, in realizing this goal, the regions that In Peru, the adoption of results-based budgeting— had begun with the highest rates registered the tying financing allocations to needs and perfor- most significant progress. mance—was a watershed reform in the country’s 49. Schultz and Joshi (2007) and see https://www.dgfpbd.org/. 50. Schurmann (2009). R ealiz ing C hange: A Whole - of- G ov ernment A pproach 33 MAP 4.1  The Total Fertility Rate, Bangladesh, 1994 and 2014 Source: World Bank, forthcoming. WHAT’S NEXT? AN ONGOING COMMITMENT drive to improve child health. Adopted in 2008, results-based budgeting changed the way resources The data are unambiguous: despite progress, were allocated to local government. Rather than much work remains to be done to improve human determinations based on previous levels of spend- capital globally and ensure that the improvements ing, the approach determined the cost to adminis- benefit those most in need. ter a full package of immunizations to children and then calculated the budgets based on the number But there are important signs of commitment to of children health clinics planned to vaccinate. This transformational change. Together, Indonesia, helped shift resources to regions with greater need. Nigeria, and Pakistan account for nearly a 10th Regions could also increase their budget allocations of the world’s population. Recognizing the chal- by 50 percent if they met specified targets in related lenges they face in preparing their populations to areas, such as nutrition, sanitation, and water. The achieve full potential, they have embarked on con- government’s commitment to regular monitoring crete actions. was instrumental in the success of results-based budgeting. Regular surveys that accurately mea- In March 2019, Pakistan launched a flagship pro- sured malnutrition across the country’s depart- gram, Ehsaas, focused on investing in people, ments provided timely feedback and allowed for reducing inequality, and lifting lagging districts, the evidence-based allocation of resources. with an emphasis on timely data and modern 34 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX technology to deliver results. Ehsaas involves a for vocational training, raising the size of the whole-of-government response to the challenges benefit and the number of eligible food items in four central areas: addressing elite capture and under a food assistance program, and doubling focusing the government system on establishing the number of government scholarships available equality; creating safety nets for disadvantaged for poor and talented students. segments of the population; fostering jobs and livelihoods; and developing human capital. In Nigeria, the government has set an ambitious objective of reducing the under-5 mortality rate by In Indonesia, among its many programs and ini- half in a decade. To this end, it is adopting reforms tiatives, the government is using fiscal policy to aimed at improving the utilization of immuni- promote equity of outcomes in human capital. zation, antimalaria, maternal, and neonatal ser- The proposed budget for 2020 highlights signifi- vices, initially in selected states. The program has cant human capital expenditures, one of which is a a strong evidence-based agenda, and activities in planned increase of 3 percent and 10 percent in the later phases will involve the application of the les- 2019 education and health budgets, respectively, sons learned during earlier phases to states that in real terms. Notable new policies include target- continue to lag. ing nearly 2 million current workers or job-seekers R ealiz ing C hange: A Whole - of- G ov ernment A pproach 35 36 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX 5 USING DATA to Design Responsive Policies Using Data to Design R esponsi v e Policies 37 T he powerful economic message of the efficient countries would only raise life expectancy global HCI first published in October by two months, but improving outcomes among 2018 and the response of the 65 countries the poorest performers could raise life expectancy that have joined the Human Capital Project as of by about five years.53 October 2019 underscores the urgency of acceler- ating the progress in human capital and to provide With its launch, the global HCI drew attention governments with additional data and analyses to to the scale of opportunities lost because of poor help address barriers to human capital develop- human capital outcomes. Now, the HCI disaggrega- ment in countries. tion provides insights that can inform government policies and reforms in responding to the chal- Effecting change in human capital outcomes lenges ahead. depends on the unique context of each country. In some low-income contexts, spending more and Section 2 of this report reveals substantial differ- strengthening governance and institutions repre- ences in the human capital outcomes of children in sent necessary first steps to improving human cap- rich and poor households within the same country. ital. Niger and Sierra Leone, included in the spa- The gaps can be as large as those between coun- tial analysis here, are examples of countries with tries. About a third of the total variation in the SES- limited resources and implementation capacity in HCI is driven by these large within-country gaps. the face of urgent needs.51 Governments have an important role to play in implementing redistributive policies and programs In other contexts, spending more does not neces- that address these large inequalities and improve sarily translate into better outcomes, and the chal- the outcomes among the most disadvantaged. lenge centers much more on the efficiency and effectiveness of spending. For instance, research The spatial disaggregation of the HCI in section in Indonesia, where social sector expenditures are 3 showcases the insights to be gained from com- substantial, finds that an unconditional doubling plementing monetary measures of poverty and in teacher salary did not improve teacher effort or inequality. Lower income or wealth is associated learning outcomes. 52 with less human capital accumulation, but certain aspects of human capital, stunting foremost among For governments facing budget constraints, under- them, are not strictly correlated with wealth. standing who within a country is falling farthest Geography, rural and urban divides, and ethnicity behind and targeting marginalized groups rep- can also help determine human capital formation. resent one option for realizing efficiency gains. International Monetary Fund analysis suggests that While revealing stark within-country inequali- increasing health spending by 10 percent in the least ties, this analysis does offer a positive message. 51. World Bank (2018a). 52. de Ree et al. (2017). 53. Grigoli and Kapsoli (2013). 38 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX As governments work to improve the outcomes Efforts to realize universal health care highlight the among the most disadvantaged, they can look role of progressive universalism—prioritizing poor to top performers, particularly better perform- and underperforming populations in expanding ing regions, and the systems and institutions basic services and protections.54 Not only does this within the country that contribute to higher lev- respond to budget constraints, it can help capture els of human capital. These homegrown solutions the benefits of shared prosperity by narrowing the can potentially be replicated in other parts of human capital gap in a country. the country. Strengthening systems while effectively target- In designing reforms to improve human capi- ing the most disadvantaged is a daunting task. In tal outcomes, governments can also draw inspi- high-income countries, civil registries, and social ration from the experiences of other countries. insurance, databases cover nearly all people, but Bangladesh, India, and Peru have realized major they cover less than half the people in low-in- progress in diverse human capital outcomes and come countries.55 In these contexts, targeting reduced the inequality in these outcomes as a key based on imprecise measures of poverty, such as part of national reforms. While implementing proxy-means testing, can miss those most in need. a whole-of-government approach, these coun- Geographical targeting provides an alternative tries have adopted long-term, wide-ranging, evi- method to identify areas for intervention, though dence-based policies. They have taken concrete it has limitations. steps to tailor programming to the needs of mar- ginalized groups—the last mile of service deliv- HCI disaggregation is a way for low- and mid- ery. Separate sanitation facilities for girls, gender- dle-income countries to use existing household sensitive staffing, and household-based outreach data to complement these other approaches to can all promote the uptake of health and educa- targeting. It can provide insights into poverty-as- tion services by groups often left behind. sociated deprivations in human capital. It can also nuance geographical targeting, particularly by Targeting populations with weak human capi- highlighting uniformly poor outcomes in some tal outcomes is a fundamental step toward fairer low-income countries or helping identify last mile distributional impacts and is essential to the pro- populations that perform below relatively good gressive achievement of the universal coverage national averages despite living side-by-side with of social services. The Universal Declaration for majority groups. Human Rights established in 1948 included free elementary education. It also outlined the right to Changes in policies take time to translate into an adequate standard of living in terms of health better human capital outcomes. Acting quickly and well-being. More concretely, since the 2000s, to understand where human capital deficits are many countries have started on a path toward greatest and where returns to policy interventions universal health care. And now, universal basic are likely to be the highest will have profound income is gaining momentum in response to new implications for future income and well-being, and changing norms in work. national economic growth and competitiveness, and overall poverty reduction. The realities of constrained government resources require strategic reforms to achieve such goals. 54. Packard et al. (2019). 55. Packard et al. (2019). Using Data to Design R esponsi v e Policies 39 40 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX References Abdul-Hamid, H., and S. A. 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As is well known, these two measures of school participation can differ considerably.56 Second, because of data limitations, the SES-HCI gauges expected years of schooling between ages 6 and 17, while the HCI relies on administrative data on preprimary through upper-secondary enrollment, covering the 4–17 age range. Third, the household survey data used does not provide estimates of adult mortality and therefore does not allow calculation of adult survival rates by SES quintile. This means that the health compo- nent of the SES-HCI is based only on stunting rates, unlike the global HCI, which uses stunting rates and adult survival rates. Fourth, there are minor discrepancies between the SES-HCI and HCI data on child survival, stunting, and test scores. Taken together, these differences imply that the SES-HCI data by quintile and averaged to the national level are not fully comparable or consistent with the global HCI. The scores and relative positions of countries can differ in the SES-HCI and the HCI. Accordingly, compari- sons between the two should be made cautiously and recognizing these differences. The divergences between the global HCI and national averages of the SES-HCI are briefly summarized in figure A1.1. In the figure, the national average of the SES-HCI is calculated using the national averages of the four components.57 The national average SES-HCI is plotted (on the vertical axis) against the global HCI (on the horizontal axis). To isolate the first source of difference between the two, the global HCI on the horizon- tal axis is calculated using only stunting as the proxy for health, as is the case of the SES- HCI. The national averages of child survival and stunting and the test scores used in the SES-HCI are similar to their counterparts in the global HCI. This means that the differ- ences between the SES-HCI and the global HCI displayed in figure A1.1 primarily arise because of differences in expected years of schooling as calculated from survey data (as in the SES-HCI) as opposed to administrative data (as in the global HCI).58 These differ- ences are manifested in two ways in figure A1.1. First, although the correlation across countries between the SES-HCI and the global HCI is high, at 0.93, it is not perfect. This reflects the less-than-perfect correlation between expected years of schooling based on survey versus administrative data. Second, because the SES-HCI calculates 56. For example, see Urquiola and Calderón (2006). The Human Capital Index is a convex function of the index components. As a result, the SES-HCI 57.  evaluated at the national averages of the component data differs slightly from the average of the SES-HCI across quintiles because of Jensen’s inequality. For a detailed discussion of the differences between the global HCI and the SES-HCI component 58  data, see D’Souza, Gatti, and Kraay (2019). 48 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX expected years of schooling over a shorter 12-year age range (ages 6–17), while the HCI considers a 14-year age range (ages 4–17), the dispersion in expected years of schooling across countries is smaller in the SES-HCI because it does not capture cross-country differences in preprimary-school participation. Because the index values reflect gaps in human capital relative to the benchmarks of complete education and full health, these gaps are also smaller in the SES-HCI, in which the education benchmark is 12 learning-adjusted years of school, compared with 14 in the global HCI. This means that the average values of the SES-HCI are larger than the average values of the global HCI, as can be seen from the fact that nearly all countries are above the 45-degree line in figure A1.1. FIGURE A1.1  Comparing the SES-HCI and the Global HCI Source: D’Souza, Gatti, and Kraay 2019. Notes: The figure compares the overall HCI disaggregated by quintile of socioeconomic status (on the vertical axis) with the global HCI (on the horizontal axis) for the 42 countries in the most recent cross- section of countries in the SES-HCI dataset for which the SES-HCI data refer to 2010 or later. The dashed line is the 45-degree line. For purposes of comparison, the global HCI is calculated excluding adult survival rates (ASRs) as a proxy for health to be more consistent with the SES-HCI, which does not include the ASR. A ppendix 2 : Data S ources for the S ES - HCI 49 APPENDIX 2 Data Sources for the SES-HCI 50 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Expected Years of Harmonized Test Year in Child Survival Stunting Schooling Scores PovcalNet SES-HCI Country Dataset Year Source Year Source Year Source Year Source Year Albania 2008 2008 DHS 2008 DHS 2005 MICS 2009 PISA 2008 Armenia 2015 2015 DHS 2015 DHS 2015 DHS 2011 TIMSS 2015 Azerbaijan 2006 2006 DHS 2006 DHS 2006 DHS 2006 PISA 2005 Benin 2014 2014 MICS 2014 MICS 2014 MICS 2014 PASEC 2015 Burkina Faso 2010 2010 DHS 2010 DHS 2010 DHS 2014 PASEC 2009 Burundi 2010 2010 DHS 2010 DHS 2010 DHS 2014 PASEC 2014 Cameroon 2014 2014 MICS 2014 MICS 2014 MICS 2014 PASEC 2014 Chad 2014 2014 DHS 2014 DHS 2014 DHS 2014 PASEC 2011 Colombia 2009 2009 DHS 2009 DHS 2010 DHS 2009 PISA 2009 Comoros 2000 1996 DHS 2000 MICS 1996 DHS 2006 PASEC 2004 Congo, Dem. Rep. 2013 2013 DHS 2013 DHS 2013 DHS 2012 EGRA 2012 Congo, Rep. 2014 2014 MICS 2014 MICS 2014 MICS 2014 PASEC 2011 Côte d'Ivoire 2016 2016 MICS 2016 MICS 2016 MICS 2014 PASEC 2015 Dominican Republic 2013 2013 DHS 2013 DHS 2013 DHS 2015 PISA 2013 Egypt, Arab Rep. 2014 2014 DHS 2014 DHS 2014 DHS 2015 TIMSS/PIRLS 2015 El Salvador 2014 2014 MICS 2014 MICS 2014 MICS 2007 TIMSS 2014 Eswatini 2014 2014 MICS 2014 MICS 2014 MICS 2007 SACMEQ 2009 Ethiopia 2016 2016 DHS 2016 DHS 2016 DHS 2010 EGRA 2016 Gabon 2012 2012 DHS 2012 DHS 2012 DHS 2006 PASEC 2017 Gambia, The 2013 2013 DHS 2013 DHS 2013 DHS 2011 EGRA 2015 Ghana 2014 2014 DHS 2014 DHS 2014 DHS 2013 EGRA 2017 Guatemala 2014 2014 DHS 2014 DHS 2014 DHS 2013 LLECE 2014 Haiti 2012 2012 DHS 2012 DHS 2012 DHS 2013 EGRA 2012 Honduras 2011 2011 DHS 2011 DHS 2011 DHS 2013 LLECE 2011 India 2015 2015 DHS 2015 DHS 2015 DHS 2009 PISA 2012 Jordan 2012 2012 DHS 2012 DHS 2012 DHS 2012 PISA 2010 Kazakhstan 1999 1999 DHS 1999 DHS 1999 DHS 2009 PISA 2001 Kenya 2014 2014 DHS 2014 DHS 2014 DHS 2007 SACMEQ 2016 Kyrgyz Republic 2014 2014 MICS 2014 MICS 2014 MICS 2009 PISA 2014 Lesotho 2014 2014 DHS 2014 DHS 2014 DHS 2007 SACMEQ 2010 Madagascar 2008 2008 DHS 2008 DHS 2008 DHS 2006 PASEC 2010 Malawi 2015 2015 DHS 2015 DHS 2015 DHS 2012 EGRA 2016 Mali 2015 2015 MICS 2015 MICS 2015 MICS 2015 EGRA 2010 Moldova 2005 2005 DHS 2005 DHS 2005 DHS 2007 PIRLS 2005 Mozambique 2011 2011 DHS 2011 DHS 2011 DHS 2007 SACMEQ 2009 Myanmar 2015 2015 DHS 2015 DHS 2015 DHS 2014 EGRA 2015 A ppendix 2 : Data S ources for the S ES - HCI 51 Expected Years of Harmonized Test Year in Child Survival Stunting Schooling Scores PovcalNet SES-HCI Country Dataset Year Source Year Source Year Source Year Source Year Namibia 2013 2013 DHS 2013 DHS 2013 DHS 2007 SACMEQ 2015 Niger 2012 2012 DHS 2012 DHS 2012 DHS 2014 PASEC 2011 Paraguay 2016 2016 MICS 2016 MICS 2016 MICS 2013 LLECE 2016 Peru 2012 2012 DHS 2012 DHS 2012 DHS 2015 PISA 2012 Senegal 2014 2014 DHS 2014 DHS 2014 DHS 2014 PASEC 2011 Tajikistan 2012 2012 DHS 2012 DHS 2012 DHS 2016 EGRA 2009 Tanzania 2015 2015 DHS 2015 DHS 2015 DHS 2013 EGRA 2012 Togo 2013 2013 DHS 2013 DHS 2013 DHS 2014 PASEC 2015 Turkey 2003 2003 DHS 2003 DHS 2003 DHS 2012 PISA 2003 Uganda 2016 2016 DHS 2016 DHS 2016 DHS 2007 SACMEQ 2017 Vietnam 2013 2013 MICS 2010 MICS 2013 MICS 2015 PISA 2014 West Bank and Gaza 2014 2014 MICS 2014 MICS 2014 MICS 2011 TIMSS 2017 Zambia 2013 2013 DHS 2013 DHS 2013 DHS 2011 EGRA 2015 Zimbabwe 2015 2015 DHS 2015 DHS 2015 DHS 2007 SACMEQ 2011 Note: The SES-HCI analysis in this booklet draws on D’Souza, Gatti, and Kraay (2019). The analysis uses a sample of 50 countries, drawing data from the latest available DHS-MICS surveys in the past two decades. Data presented in section 2 of this booklet are derived from the surveys and years detailed in this table. 52 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX APPENDIX 3 Data Sources for the GEO-HCI Expected Years of Harmonized Test Child Survival Stunting Adult Survival Schooling Scores GDP Data Country Year Source Year Source Year Source Year Source Year Source Year Source Angola 2015/16 DHS 2015/16 DHS n/a n/a 2017/18 EMIS 2011 EGRA n/a n/a Burkina Faso 2010 DHS 2010 DHS n/a n/a 2014 LSMS 2014 PASEC 2014 LSMS-ISA* Chad 2014/15 DHS 2014/15 DHS n/a n/a 2011 LSMS 2014 PASEC 2011 Chad Household Consumption and Informal Sector Survey (ECOSIT 3)* Indonesia 2015 Survei 2013 Riskesdas 2015 Survei 2017 Survei Sosial 2017 Ujian Akhir 2016 Indonesia Penduduk (Basic Health Penduduk Ekonomi Nasional Nasional Central Bureau Antar Sensus Survey) Antar Sensus (SUSENAS) (national of Statistics (SUPAS) (SUPAS) assessment) (BPS)* Mali 2012 DHS 2012 DHS n/a n/a 2014 LSMS 2014 PASEC 2014 LSMS-ISA* Niger 2012 DHS 2012 DHS n/a n/a 2014 LSMS 2014 PASEC 2014 LSMS-ISA* Peru 2016/17 Instituto 2018 Instituto n/a n/a 2016 Estadistica de la 2015 PISA 2014 OECD Regional Nacional de Nacional de Calidad Educativa Database Estadistica e Estadistica e (ESCALE) Informatica Informatica Romania 2017 National n/a n/a 2017 National 2017 National Institute 2017 Integrated 2015 OECD Regional Institute for Institute for for Statistics Education Database Statistics Statistics (TEMPO database) Information (TEMPO (TEMPO for enrollment System (SIIIR) database) database) rates/ Integrated Education Information System (SIIIR) for repetition rates Sierra Leone 2017 MICS 2017 MICS n/a n/a 2017 MICS 2017 MICS n/a n/a Sri Lanka 2016 DHS 2016 DHS 2016 Sri Lanka 16 HIES 16 SL-TIMSS n/a n/a Department (National of Census assesment and Statistics linked to TIMSS) Vietnam 2013/14 MICS 2013/14 MICS 2013/14 MICS 2013/14 MICS 2015 PISA n/a n/a Note: Data sources provide per capita consumption data. To calculate GDP per capita for each subnational unit, national GDP per capita is multiplied by the ratio of subnational per capita consumption to mean per capita consumption. For some countries with large differences between household income and consumption, variations in per capita A ppendix 3 : Data S ources for the G EO- HCI consumption may imperfectly reflect variations in income. 53 54 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX APPENDIX 4 SES-HCI Country Profiles 54 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Albania Albania Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Albania was ranked 56 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Albania, the productivity as a future worker of a child born today in the richest 20 percent of households is 64 percent while it is 50 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 14 percentage points. This gap is slightly smaller than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Demographic and Health Survey 2008 • Probability of Survival to Age 5. In Albania, the proba- bility of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 99 percent while it is 97 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 2 percentage points. This gap is smaller than the typical Source: Multiple Indicator Cluster Survey 2005 gap across the 50 countries (4 percentage points). • Expected Years of School. In Albania, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 10.4 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Programme for International Student Assessment 2009 can expect to complete 8.7 years of school, a gap of 1.6 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Albania score 437 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 356, a gap of Source: Demographic and Health Survey 2008 81 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Albania, the percentage of children in the top 20 percent of house- holds who are not stunted is 87 percent while it is 73 percent among the poorest 20 percent, a gap of 13 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is smaller than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 55 Armenia 56 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Armenia Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Armenia was ranked 78 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Armenia, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 77 percent while it is 66 percent for a child born .2 .4 .6 .8 1 in the poorest 20 percent, a gap of 11 percentage points. This gap is smaller than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Demographic and Health Survey 2015 • Probability of Survival to Age 5. In Armenia, the prob- ability of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 100 percent while it is 99 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 1 percentage points. This gap is smaller than the typical Source: Demographic and Health Survey 2015 gap across the 50 countries (4 percentage points). • Expected Years of School. In Armenia, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11.7 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Trends in International Mathematics and Science Study 2011 can expect to complete 11.3 years of school, a gap of .5 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Armenia score 483 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 417, a gap of 67 Source: Demographic and Health Survey 2015 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is larger than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Armenia, the percentage of children in the top 20 percent of house- holds who are not stunted is 94 percent while it is 88 percent among the poorest 20 percent, a gap of 6 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is smaller than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 56 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Azerbaijan Azerbaijan Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Azerbaijan was ranked 69 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Azerbaijan, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 65 percent while it is 54 percent for a child born .2 .4 .6 .8 1 in the poorest 20 percent, a gap of 11 percentage points. This gap is smaller than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Demographic and Health Survey 2006 • Probability of Survival to Age 5. In Azerbaijan, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 96 percent while it is 94 percent for a child born in the poorest 20 percent, a gap of 2 percentage points. This gap is slightly smaller Expected Years of School than the typical gap across the 50 countries (4 percent- Source: Demographic and Health Survey 2006 age points). • Expected Years of School. In Azerbaijan, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Programme for International Student Assessment 2006 can expect to complete 10.1 years of school, a gap of 1 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Azerbaijan score 441 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 410, a gap of Source: Demographic and Health Survey 2006 31 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Azerbaijan, the percentage of children in the top 20 percent of house- holds who are not stunted is 84 percent while it is 67 percent among the poorest 20 percent, a gap of 17 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is smaller than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 57 Benin 58 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Benin Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Benin was ranked 127 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Benin, the productivity as a future worker of a child born today in the richest 20 percent of households is 59 percent while it is 37 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 23 percentage points. This gap is larger than the typical gap across the 50 countries Probability of Survival to Age 5 (15 percentage points). Source: Multiple Indicator Cluster Survey 2014 • Probability of Survival to Age 5. In Benin, the proba- bility of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 93 percent while it is 86 per- cent for a child born in the poorest 20 percent, a gap of 7 percentage points. This gap is larger than the typical Expected Years of School Source: Multiple Indicator Cluster Survey 2014 gap across the 50 countries (4 percentage points). • Expected Years of School. In Benin, a child in the rich- est 20 percent of households who starts school at age 2 4 6 8 10 12 14 6 can expect to complete 10.6 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores can expect to complete 5.6 years of school, a gap of 4.9 Source: Programme for the Analysis of Education Systems 2014 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Benin score 423 while those from the poorest 20 percent score 365, a gap of 59 Fraction of Children Under 5 Not Stunted Source: Multiple Indicator Cluster Survey 2014 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is about the same as the typical gap across the 50 countries (55 .2 .4 .6 .8 1 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Benin, the per- centage of children in the top 20 percent of households who are not stunted is 82 percent while it is 54 percent The Human Capital Project is a global effort to accelerate the among the poorest 20 percent, a gap of 28 percentage amount and quality of investments in people. points. This gap is larger than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 58 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Burkina Faso Burkina Faso Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Burkina Faso was ranked 144 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Burkina Faso, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 52 percent while it is 32 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 20 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Demographic and Health Survey 2010 • Probability of Survival to Age 5. In Burkina Faso, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 90 percent while it is 83 percent for a child born in the poorest 20 percent, a gap of 8 percentage points. This gap is larger than the typi- Expected Years of School Source: Demographic and Health Survey 2010 cal gap across the 50 countries (4 percentage points). • Expected Years of School. In Burkina Faso, a child in 2 4 6 8 10 12 14 the richest 20 percent of households who starts school at age 6 can expect to complete 8.5 years of school by her 18th birthday while a child from the poorest 20 per- Harmonized Test Scores cent can expect to complete 2.9 years of school, a gap Source: Programme for the Analysis of Education Systems 2014 of 5.6 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Burkina Faso score 421 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 390, a gap of Source: Demographic and Health Survey 2010 30 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Burkina Faso, the percentage of children in the top 20 percent of households who are not stunted is 82 percent while it is 58 percent among the poorest 20 percent, a gap of 25 The Human Capital Project is a global effort to accelerate the percentage points. This gap is larger than the typical amount and quality of investments in people. gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 59 Burundi 60 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Burundi Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Burundi was ranked 138 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Burundi, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 51 percent while it is 37 percent for a child born .2 .4 .6 .8 1 in the poorest 20 percent, a gap of 14 percentage points. This gap is smaller than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Demographic and Health Survey 2010 • Probability of Survival to Age 5. In Burundi, the prob- ability of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 92 percent while it is 85 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 7 percentage points. This gap is larger than the typical Source: Demographic and Health Survey 2010 gap across the 50 countries (4 percentage points). • Expected Years of School. In Burundi, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 9.4 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Programme for the Analysis of Education Systems 2014 can expect to complete 7.1 years of school, a gap of 2.3 years of school. This gap is about the same as the typi- cal gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Burundi score 430 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 422, a gap of Source: Demographic and Health Survey 2010 8 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Burundi, the percentage of children in the top 20 percent of house- holds who are not stunted is 59 percent while it is 31 percent among the poorest 20 percent, a gap of 28 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is larger than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 60 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Cameroon Cameroon Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Cameroon was ranked 132 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Cameroon, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 63 percent while it is 38 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 26 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Multiple Indicator Cluster Survey 2014 • Probability of Survival to Age 5. In Cameroon, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 94 percent while it is 83 percent for a child born in the poorest 20 percent, a gap of 12 percentage points. This gap is larger than the typ- Expected Years of School Source: Multiple Indicator Cluster Survey 2014 ical gap across the 50 countries (4 percentage points). • Expected Years of School. In Cameroon, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11.4 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores can expect to complete 7.4 years of school, a gap of 4 Source: Programme for the Analysis of Education Systems 2014 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Cameroon score 418 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 336, a gap of Source: Multiple Indicator Cluster Survey 2014 82 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Cameroon, the percentage of children in the top 20 percent of house- holds who are not stunted is 86 percent while it is 58 percent among the poorest 20 percent, a gap of 27 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is larger than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 61 Chad 62 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Chad Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Chad was ranked 157 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Chad, the productivity as a future worker of a child born today in the richest 20 percent of households is 45 percent while it is 35 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 11 percentage points. This gap is smaller than the typical gap across the 50 coun- Probability of Survival to Age 5 tries (15 percentage points). Source: Demographic and Health Survey 2014 • Probability of Survival to Age 5. In Chad, the proba- bility of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 86 percent while it is 84 percent for a child born in the poorest 20 percent, a gap of 2 percentage points. This gap is slightly smaller Expected Years of School Source: Demographic and Health Survey 2014 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Chad, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 9.4 years of school by her 18th Harmonized Test Scores birthday while a child from the poorest 20 percent can Source: Programme for the Analysis of Education Systems 2014 expect to complete 5.4 years of school, a gap of 4 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Chad score 357 while those Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2014 from the poorest 20 percent score 322, a gap of 35 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is smaller than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Chad, the per- centage of children in the top 20 percent of households who are not stunted is 68 percent while it is 59 percent The Human Capital Project is a global effort to accelerate the among the poorest 20 percent, a gap of 9 percentage amount and quality of investments in people. points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 62 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Colombia Colombia Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Colombia was ranked 70 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Colombia, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 69 percent while it is 53 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 16 percentage points. This gap is slightly larger than the typical gap Probability of Survival to Age 5 across the 50 countries (15 percentage points). Source: Demographic and Health Survey 2009 • Probability of Survival to Age 5. In Colombia, the prob- ability of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 99 percent while it is 97 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 2 percentage points. This gap is smaller than the typical Source: Demographic and Health Survey 2010 gap across the 50 countries (4 percentage points). • Expected Years of School. In Colombia, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 10.5 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Programme for International Student Assessment 2009 can expect to complete 9 years of school, a gap of 1.5 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Colombia score 464 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 366, a gap of Source: Demographic and Health Survey 2009 98 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Colombia, the percentage of children in the top 20 percent of house- holds who are not stunted is 93 percent while it is 80 percent among the poorest 20 percent, a gap of 13 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is smaller than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 63 Comoros 64 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Comoros Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Comoros was ranked 123 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In the Comoros, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 49 percent while it is 35 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 14 percentage points. This gap is slightly smaller than the typical gap Probability of Survival to Age 5 across the 50 countries (15 percentage points). Source: Demographic and Health Survey 1996 • Probability of Survival to Age 5. In the Comoros, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 91 percent while it is 87 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is slightly larger Expected Years of School than the typical gap across the 50 countries (4 percent- Source: Demographic and Health Survey 1996 age points). • Expected Years of School. In the Comoros, a child in 2 4 6 8 10 12 14 the richest 20 percent of households who starts school at age 6 can expect to complete 9 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Programme for the Analysis of Education Systems 2006 can expect to complete 4.6 years of school, a gap of 4.4 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in the Comoros score 408 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 376, a gap of Source: Multiple Indicator Cluster Survey 2000 33 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In the Comoros, the percentage of children in the top 20 percent of households who are not stunted is 61 percent while it is 50 percent among the poorest 20 percent, a gap of 11 The Human Capital Project is a global effort to accelerate the percentage points. This gap is smaller than the typical amount and quality of investments in people. gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 64 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX The Democratic Republic of Congo The Democratic Republic of Congo Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. The Democratic Republic of Congo was ranked 146 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In the Democratic Republic of Congo, the productivity as a future worker of a child born today in the richest 20 percent of households is 52 percent while it is 40 per- .2 .4 .6 .8 1 cent for a child born in the poorest 20 percent, a gap of 11 percentage points. This gap is smaller than the typi- cal gap across the 50 countries (15 percentage points). Probability of Survival to Age 5 Source: Demographic and Health Survey 2013 • Probability of Survival to Age 5. In the Democratic Re- public of Congo, the probability of survival of a child born today in the richest 20 percent of households is .8 .85 .9 .95 1 92 percent while it is 88 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is about the same as the typical gap across the 50 Expected Years of School countries (4 percentage points). Source: Demographic and Health Survey 2013 • Expected Years of School. In the Democratic Repub- lic of Congo, a child in the richest 20 percent of house- 2 4 6 8 10 12 14 holds who starts school at age 6 can expect to complete 10.8 years of school by her 18th birthday while a child from the poorest 20 percent can expect to complete 8.9 Harmonized Test Scores years of school, a gap of 1.9 years of school. This gap is Source: Early Grade Reading Assessment 2012 smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in the Democratic Republic of Congo score 326 while those from the poorest 20 Fraction of Children Under 5 Not Stunted percent score 311, a gap of 16 points on a scale that Source: Demographic and Health Survey 2013 ranges from 300 (minimal attainment) to 625 (high at- tainment). This gap is smaller than the typical gap .2 .4 .6 .8 1 across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In the Democratic Republic of Congo, the percentage of children in the top 20 percent of households who are not stunted is 79 percent while it is 50 percent among the poorest The Human Capital Project is a global effort to accelerate the 20 percent, a gap of 30 percentage points. This gap amount and quality of investments in people. is larger than the typical gap across the 50 countries (19 For more information on the Human Capital Project, please percentage points). visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 65 The Republic of Congo 66 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX The Republic of Congo Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. The Republic of Congo was ranked 120 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In the Republic of Congo, the productivity as a future worker of a child born today in the richest 20 percent of households is 65 percent while it is 49 percent for .2 .4 .6 .8 1 a child born in the poorest 20 percent, a gap of 16 per- centage points. This gap is about the same as the typical gap across the 50 countries (15 percentage points). Probability of Survival to Age 5 Source: Multiple Indicator Cluster Survey 2014 • Probability of Survival to Age 5. In the Republic of Congo, the probability of survival of a child born today in the richest 20 percent of households is 97 percent .8 .85 .9 .95 1 while it is 92 percent for a child born in the poorest 20 percent, a gap of 5 percentage points. This gap is Expected Years of School slightly larger than the typical gap across the 50 coun- Source: Multiple Indicator Cluster Survey 2014 tries (4 percentage points). • Expected Years of School. In the Republic of Congo, 2 4 6 8 10 12 14 a child in the richest 20 percent of households who starts school at age 6 can expect to complete 11.7 years of school by her 18th birthday while a child from the Harmonized Test Scores poorest 20 percent can expect to complete 10.1 years of Source: Programme for the Analysis of Education Systems 2014 school, a gap of 1.6 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in the Republic of Congo score 410 while those from the poorest 20 percent score 343, Fraction of Children Under 5 Not Stunted Source: Multiple Indicator Cluster Survey 2014 a gap of 67 points on a scale that ranges from 300 (min- imal attainment) to 625 (high attainment). This gap is larger than the typical gap across the 50 countries (55 .2 .4 .6 .8 1 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In the Republic of Congo, the percentage of children in the top 20 percent of households who are not stunted is 86 percent while it The Human Capital Project is a global effort to accelerate the is 70 percent among the poorest 20 percent, a gap of 16 amount and quality of investments in people. percentage points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 66 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Côte d’Ivoire Côte d’Ivoire Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Côte d’Ivoire was ranked 149 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Côte d’Ivoire, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 58 percent while it is 40 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 18 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Multiple Indicator Cluster Survey 2016 • Probability of Survival to Age 5. In Côte d’Ivoire, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 93 percent while it is 88 percent for a child born in the poorest 20 percent, a gap of 5 percentage points. This gap is slightly larger Expected Years of School than the typical gap across the 50 countries (4 percent- Source: Multiple Indicator Cluster Survey 2016 age points). • Expected Years of School. In Côte d’Ivoire, a child in 2 4 6 8 10 12 14 the richest 20 percent of households who starts school at age 6 can expect to complete 10 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Programme for the Analysis of Education Systems 2014 can expect to complete 6.2 years of school, a gap of 3.8 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Côte d’Ivoire score 400 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 350, a gap of Source: Multiple Indicator Cluster Survey 2016 50 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Côte d’Ivoire, the percentage of children in the top 20 percent of households who are not stunted is 91 percent while it is 70 percent among the poorest 20 percent, a gap of The Human Capital Project is a global effort to accelerate the 21 percentage points. This gap is larger than the typical amount and quality of investments in people. gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 67 Dominican Republic 68 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Dominican Republic Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Dominican Republic was ranked 101 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Dominican Republic, the productivity as a future worker of a child born today in the richest 20 percent of households is 66 percent while it is 53 percent for .2 .4 .6 .8 1 a child born in the poorest 20 percent, a gap of 13 per- centage points. This gap is smaller than the typical gap across the 50 countries (15 percentage points). Probability of Survival to Age 5 Source: Demographic and Health Survey 2013 • Probability of Survival to Age 5. In Dominican Repub- lic, the probability of survival of a child born today in the richest 20 percent of households is 98 percent while .8 .85 .9 .95 1 it is 96 percent for a child born in the poorest 20 per- cent, a gap of 3 percentage points. This gap is slightly Expected Years of School smaller than the typical gap across the 50 countries (4 Source: Demographic and Health Survey 2013 percentage points). • Expected Years of School. In Dominican Republic, 2 4 6 8 10 12 14 a child in the richest 20 percent of households who starts school at age 6 can expect to complete 11.4 years of school by her 18th birthday while a child from the Harmonized Test Scores poorest 20 percent can expect to complete 9.9 years of Source: Programme for International Student Assessment 2015 school, a gap of 1.5 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Dominican Republic score 398 while those from the poorest 20 percent score 322, Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2013 a gap of 75 points on a scale that ranges from 300 (min- imal attainment) to 625 (high attainment). This gap is larger than the typical gap across the 50 countries (55 .2 .4 .6 .8 1 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Dominican Re- public, the percentage of children in the top 20 percent of households who are not stunted is 96 percent while The Human Capital Project is a global effort to accelerate the it is 89 percent among the poorest 20 percent, a gap of amount and quality of investments in people. 7 percentage points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 68 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX The Arabic Republic of Egypt The Arabic Republic of Egypt Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. The Arabic Republic of Egypt was ranked 104 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In the Arabic Republic of Egypt, the productivity as a future worker of a child born today in the richest 20 percent of households is 63 percent while it is 50 per- .2 .4 .6 .8 1 cent for a child born in the poorest 20 percent, a gap of 13 percentage points. This gap is smaller than the typi- cal gap across the 50 countries (15 percentage points). Probability of Survival to Age 5 Source: Demographic and Health Survey 2014 • Probability of Survival to Age 5. In the Arabic Repub- lic of Egypt, the probability of survival of a child born today in the richest 20 percent of households is 98 per- .8 .85 .9 .95 1 cent while it is 96 percent for a child born in the poor- est 20 percent, a gap of 2 percentage points. This gap is slightly smaller than the typical gap across the 50 coun- Expected Years of School tries (4 percentage points). Source: Demographic and Health Survey 2014 • Expected Years of School. In the Arabic Republic of Egypt, a child in the richest 20 percent of households 2 4 6 8 10 12 14 who starts school at age 6 can expect to complete 11.2 years of school by her 18th birthday while a child from the poorest 20 percent can expect to complete 10 years Harmonized Test Scores of school, a gap of 1.2 years of school. This gap is Source: Trends in International Mathematics and Science Study/Progress in International Reading Literacy Study 2015 smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in the Arabic Republic of Egypt score 417 while those from the poorest 20 percent score Fraction of Children Under 5 Not Stunted 301, a gap of 116 points on a scale that ranges from 300 Source: Demographic and Health Survey 2014 (minimal attainment) to 625 (high attainment). This gap is larger than the typical gap across the 50 countries .2 .4 .6 .8 1 (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In the Arabic Re- public of Egypt, the percentage of children in the top 20 percent of households who are not stunted is 77 percent while it is 76 percent among the poorest 20 percent, a The Human Capital Project is a global effort to accelerate the gap of 1 percentage points. This gap is smaller than amount and quality of investments in people. the typical gap across the 50 countries (19 percentage For more information on the Human Capital Project, please points). visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 69 El Salvador 70 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX El Salvador Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. El Salvador was ranked 97 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In El Salvador, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 64 percent while it is 50 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 14 percentage points. This gap is slightly smaller than the typical gap Probability of Survival to Age 5 across the 50 countries (15 percentage points). Source: Multiple Indicator Cluster Survey 2014 • Probability of Survival to Age 5. In El Salvador, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 99 percent while it is 97 percent for a child born in the poorest 20 percent, a gap of 2 percentage points. This gap is smaller than the typ- Expected Years of School ical gap across the 50 countries (4 percentage points). Source: Multiple Indicator Cluster Survey 2014 • Expected Years of School. In El Salvador, a child in the richest 20 percent of households who starts school 2 4 6 8 10 12 14 at age 6 can expect to complete 10.7 years of school by her 18th birthday while a child from the poorest 20 per- Harmonized Test Scores cent can expect to complete 8.7 years of school, a gap of Source: Trends in International Mathematics and Science Study 2007 1.9 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in El Salvador score 403 while those from the poorest 20 percent score 344, a gap of Fraction of Children Under 5 Not Stunted 59 points on a scale that ranges from 300 (minimal at- Source: Multiple Indicator Cluster Survey 2014 tainment) to 625 (high attainment). This gap is about the same as the typical gap across the 50 countries (55 .2 .4 .6 .8 1 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In El Salvador, the percentage of children in the top 20 percent of house- holds who are not stunted is 95 percent while it is 76 percent among the poorest 20 percent, a gap of 18 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is slightly smaller than the typ- amount and quality of investments in people. ical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 70 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Eswatini Eswatini Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Eswatini was ranked 124 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Eswatini, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 66 percent while it is 55 percent for a child born .2 .4 .6 .8 1 in the poorest 20 percent, a gap of 11 percentage points. This gap is smaller than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Multiple Indicator Cluster Survey 2014 • Probability of Survival to Age 5. In Eswatini, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 95 percent while it is 90 percent for a child born in the poorest 20 percent, a gap of 5 percentage points. This gap is slightly larger Expected Years of School Source: Multiple Indicator Cluster Survey 2014 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Eswatini, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11.2 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Southern and Eastern Africa Consortium for Monitoring Educational Quality 2007 can expect to complete 11 years of school, a gap of .2 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Eswatini score 436 while Fraction of Children Under 5 Not Stunted Source: Multiple Indicator Cluster Survey 2014 those from the poorest 20 percent score 408, a gap of 28 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Eswatini, the percentage of children in the top 20 percent of house- holds who are not stunted is 91 percent while it is 70 The Human Capital Project is a global effort to accelerate the percent among the poorest 20 percent, a gap of 21 per- amount and quality of investments in people. centage points. This gap is larger than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 71 Ethiopia 72 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Ethiopia Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Ethiopia was ranked 135 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Ethiopia, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 52 percent while it is 39 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 13 percentage points. This gap is smaller than the typical gap across Probability of Survival to Age 5 the 50 countries (15 percentage points). Source: Demographic and Health Survey 2016 • Probability of Survival to Age 5. In Ethiopia, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 93 percent while it is 91 percent for a child born in the poorest 20 percent, a gap of 2 percentage points. This gap is slightly smaller Expected Years of School Source: Demographic and Health Survey 2016 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Ethiopia, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 9.3 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Early Grade Reading Assessment 2010 can expect to complete 5.9 years of school, a gap of 3.4 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Ethiopia score 388 while Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2016 those from the poorest 20 percent score 347, a gap of 41 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Ethiopia, the percentage of children in the top 20 percent of house- holds who are not stunted is 75 percent while it is 55 The Human Capital Project is a global effort to accelerate the percent among the poorest 20 percent, a gap of 20 per- amount and quality of investments in people. centage points. This gap is slightly larger than the typi- cal gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 72 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Gabon Gabon Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Gabon was ranked 110 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Gabon, the productivity as a future worker of a child born today in the richest 20 percent of households is 71 percent while it is 57 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 14 percentage points. This gap is slightly smaller than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Demographic and Health Survey 2012 • Probability of Survival to Age 5. In Gabon, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 95 percent while it is 92 percent for a child born in the poorest 20 percent, a gap of 3 percentage points. This gap is slightly smaller Expected Years of School Source: Demographic and Health Survey 2012 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Gabon, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 11.3 years of school by her 18th Harmonized Test Scores birthday while a child from the poorest 20 percent can Source: Programme for the Analysis of Education Systems 2006 expect to complete 10.4 years of school, a gap of 1 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Gabon score 474 while those Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2012 from the poorest 20 percent score 434, a gap of 40 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is smaller than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Gabon, the per- centage of children in the top 20 percent of households who are not stunted is 95 percent while it is 70 percent The Human Capital Project is a global effort to accelerate the among the poorest 20 percent, a gap of 24 percentage amount and quality of investments in people. points. This gap is larger than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 73 The Gambia 74 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX The Gambia Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. The Gambia was ranked 130 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In the Gambia, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 56 percent while it is 42 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 14 percentage points. This gap is smaller than the typical gap across Probability of Survival to Age 5 the 50 countries (15 percentage points). Source: Demographic and Health Survey 2013 • Probability of Survival to Age 5. In the Gambia, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 97 percent while it is 93 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is about the same Expected Years of School as the typical gap across the 50 countries (4 percentage Source: Demographic and Health Survey 2013 points). • Expected Years of School. In the Gambia, a child in 2 4 6 8 10 12 14 the richest 20 percent of households who starts school at age 6 can expect to complete 9 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Early Grade Reading Assessment 2011 can expect to complete 6.3 years of school, a gap of 2.7 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in the Gambia score 402 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 332, a gap of Source: Demographic and Health Survey 2013 71 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In the Gambia, the percentage of children in the top 20 percent of households who are not stunted is 85 percent while it is 72 percent among the poorest 20 percent, a gap of 13 The Human Capital Project is a global effort to accelerate the percentage points. This gap is smaller than the typical amount and quality of investments in people. gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 74 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Ghana Ghana Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Ghana was ranked 116 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Ghana, the productivity as a future worker of a child born today in the richest 20 percent of households is 50 percent while it is 43 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 7 percentage points. This gap is smaller than the typical gap across the 50 coun- Probability of Survival to Age 5 tries (15 percentage points). Source: Demographic and Health Survey 2014 • Probability of Survival to Age 5. In Ghana, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 94 percent while it is 91 percent for a child born in the poorest 20 percent, a gap of 3 percentage points. This gap is slightly smaller Expected Years of School Source: Demographic and Health Survey 2014 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Ghana, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 8.7 years of school by her 18th Harmonized Test Scores birthday while a child from the poorest 20 percent can Source: Early Grade Reading Assessment 2013 expect to complete 7.4 years of school, a gap of 1.3 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Ghana score 317 while those Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2014 from the poorest 20 percent score 307, a gap of 9 points on a scale that ranges from 300 (minimal attainment) to 625 (high attainment). This gap is smaller than the .2 .4 .6 .8 1 typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Ghana, the per- centage of children in the top 20 percent of households who are not stunted is 92 percent while it is 75 percent The Human Capital Project is a global effort to accelerate the among the poorest 20 percent, a gap of 17 percentage amount and quality of investments in people. points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 75 Guatemala 76 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Guatemala Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Guatemala was ranked 109 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Guatemala, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 62 percent while it is 40 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 22 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Demographic and Health Survey 2014 • Probability of Survival to Age 5. In Guatemala, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 98 percent while it is 94 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is about the same Expected Years of School as the typical gap across the 50 countries (4 percentage Source: Demographic and Health Survey 2014 points). • Expected Years of School. In Guatemala, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 9.8 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Latin American Laboratory for Assessment of the Quality of Education 2013 can expect to complete 6.8 years of school, a gap of 3 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Guatemala score 449 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 377, a gap of Source: Demographic and Health Survey 2014 72 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Guatemala, the percentage of children in the top 20 percent of house- holds who are not stunted is 82 percent while it is 34 percent among the poorest 20 percent, a gap of 48 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is larger than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 76 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Haiti Haiti Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Haiti was ranked 112 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Haiti, the productivity as a future worker of a child born today in the richest 20 percent of households is 58 percent while it is 45 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 13 percentage points. This gap is smaller than the typical gap across the 50 coun- Probability of Survival to Age 5 tries (15 percentage points). Source: Demographic and Health Survey 2012 • Probability of Survival to Age 5. In Haiti, the probabil- ity of survival of a child born today in the richest 20 per- .8 .85 .9 .95 1 cent of households is 94 percent while it is 90 percent for a child born in the poorest 20 percent, a gap of 4 per- Expected Years of School centage points. This gap is about the same as the typical Source: Demographic and Health Survey 2012 gap across the 50 countries (4 percentage points). • Expected Years of School. In Haiti, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 11.1 years of school by her 18th birthday while a child from the poorest 20 percent can Harmonized Test Scores Source: Early Grade Reading Assessment 2013 expect to complete 9 years of school, a gap of 2.1 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Haiti score 351 while those Fraction of Children Under 5 Not Stunted from the poorest 20 percent score 331, a gap of 20 Source: Demographic and Health Survey 2012 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is smaller than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Haiti, the per- centage of children in the top 20 percent of households who are not stunted is 94 percent while it is 70 percent among the poorest 20 percent, a gap of 24 percentage The Human Capital Project is a global effort to accelerate the points. This gap is larger than the typical gap across the amount and quality of investments in people. 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 77 Honduras 78 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Honduras Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Honduras was ranked 103 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Honduras, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 64 percent while it is 44 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 20 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Demographic and Health Survey 2011 • Probability of Survival to Age 5. In Honduras, the prob- ability of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 98 percent while it is 96 per- cent for a child born in the poorest 20 percent, a gap of 2 percentage points. This gap is smaller than the typical Expected Years of School gap across the 50 countries (4 percentage points). Source: Demographic and Health Survey 2011 • Expected Years of School. In Honduras, a child in the richest 20 percent of households who starts school at 2 4 6 8 10 12 14 age 6 can expect to complete 10.3 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores can expect to complete 6.8 years of school, a gap of 3.5 Source: Latin American Laboratory for Assessment of the Quality of Education 2013 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Honduras score 430 while those from the poorest 20 percent score 374, a gap of Fraction of Children Under 5 Not Stunted 56 points on a scale that ranges from 300 (minimal at- Source: Demographic and Health Survey 2011 tainment) to 625 (high attainment). This gap is about the same as the typical gap across the 50 countries (55 .2 .4 .6 .8 1 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Honduras, the percentage of children in the top 20 percent of house- holds who are not stunted is 93 percent while it is 58 percent among the poorest 20 percent, a gap of 35 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is larger than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 78 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX India India Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. India was ranked 115 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In India, the productivity as a future worker of a child born today in the richest 20 percent of households is 61 percent while it is 44 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 17 percentage points. This gap is larger than the typical gap across the 50 countries Probability of Survival to Age 5 (15 percentage points). Source: Demographic and Health Survey 2015 • Probability of Survival to Age 5. In India, the proba- bility of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 98 percent while it is 92 percent for a child born in the poorest 20 percent, a gap of 5 percentage points. This gap is slightly larger Expected Years of School Source: Demographic and Health Survey 2015 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In India, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 11.7 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Programme for International Student Assessment 2009 can expect to complete 9.3 years of school, a gap of 2.4 years of school. This gap is about the same as the typi- cal gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in India score 383 while those Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2015 from the poorest 20 percent score 335, a gap of 48 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is smaller than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In India, the per- centage of children in the top 20 percent of households who are not stunted is 78 percent while it is 49 percent The Human Capital Project is a global effort to accelerate the among the poorest 20 percent, a gap of 29 percentage amount and quality of investments in people. points. This gap is larger than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 79 Jordan 80 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Jordan Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Jordan was ranked 79 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Jordan, the productivity as a future worker of a child born today in the richest 20 percent of households is 74 percent while it is 60 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 14 percentage points. This gap is smaller than the typical gap across the 50 coun- Probability of Survival to Age 5 tries (15 percentage points). Source: Demographic and Health Survey 2012 • Probability of Survival to Age 5. In Jordan, the proba- bility of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 99 percent while it is 97 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 2 percentage points. This gap is smaller than the typical Source: Demographic and Health Survey 2012 gap across the 50 countries (4 percentage points). • Expected Years of School. In Jordan, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 11.7 years of school by her 18th birthday while a child from the poorest 20 percent can Harmonized Test Scores Source: Programme for International Student Assessment 2012 expect to complete 10.7 years of school, a gap of 1 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Jordan score 448 while those Fraction of Children Under 5 Not Stunted from the poorest 20 percent score 384, a gap of 64 Source: Demographic and Health Survey 2012 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is larger than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Jordan, the per- centage of children in the top 20 percent of households who are not stunted is 98 percent while it is 86 percent among the poorest 20 percent, a gap of 12 percentage The Human Capital Project is a global effort to accelerate the points. This gap is smaller than the typical gap across amount and quality of investments in people. the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 80 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Kazakhstan Kazakhstan Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Kazakhstan was ranked 31 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Kazakhstan, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 64 percent while it is 53 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 11 percentage points. This gap is smaller than the typical gap across Probability of Survival to Age 5 the 50 countries (15 percentage points). Source: Demographic and Health Survey 1999 • Probability of Survival to Age 5. In Kazakhstan, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 96 percent while it is 92 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is about the same Expected Years of School as the typical gap across the 50 countries (4 percentage Source: Demographic and Health Survey 1999 points). • Expected Years of School. In Kazakhstan, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 10.4 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Programme for International Student Assessment 2009 can expect to complete 10 years of school, a gap of .3 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Kazakhstan score 452 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 371, a gap of Source: Demographic and Health Survey 1999 81 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Kazakhstan, the percentage of children in the top 20 percent of house- holds who are not stunted is 90 percent while it is 81 percent among the poorest 20 percent, a gap of 9 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is smaller than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 81 Kenya 82 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Kenya Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Kenya was ranked 94 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Kenya, the productivity as a future worker of a child born today in the richest 20 percent of households is 66 percent while it is 50 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 16 percentage points. This gap is slightly larger than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Demographic and Health Survey 2014 • Probability of Survival to Age 5. In Kenya, the proba- bility of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 95 percent while it is 94 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 1 percentage points. This gap is smaller than the typical Source: Demographic and Health Survey 2014 gap across the 50 countries (4 percentage points). • Expected Years of School. In Kenya, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 10.7 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Southern and Eastern Africa Consortium for Monitoring Educational Quality 2007 can expect to complete 8.5 years of school, a gap of 2.2 years of school. This gap is about the same as the typi- cal gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Kenya score 467 while those Fraction of Children Under 5 Not Stunted from the poorest 20 percent score 404, a gap of 62 Source: Demographic and Health Survey 2014 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is larger than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Kenya, the per- centage of children in the top 20 percent of households who are not stunted is 86 percent while it is 64 percent among the poorest 20 percent, a gap of 22 percentage The Human Capital Project is a global effort to accelerate the points. This gap is larger than the typical gap across the amount and quality of investments in people. 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 82 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Kyrgyz Republic Kyrgyz Republic Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Kyrgyz Republic was ranked 76 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In the Kyrgyz Republic, the productivity as a future worker of a child born today in the richest 20 percent of households is 62 percent while it is 52 percent for a .2 .4 .6 .8 1 child born in the poorest 20 percent, a gap of 10 per- centage points. This gap is smaller than the typical gap across the 50 countries (15 percentage points). Probability of Survival to Age 5 Source: Multiple Indicator Cluster Survey 2014 • Probability of Survival to Age 5. In the Kyrgyz Repub- lic, the probability of survival of a child born today in the richest 20 percent of households is 99 percent while .8 .85 .9 .95 1 it is 96 percent for a child born in the poorest 20 per- cent, a gap of 3 percentage points. This gap is slightly Expected Years of School smaller than the typical gap across the 50 countries (4 Source: Multiple Indicator Cluster Survey 2014 percentage points). • Expected Years of School. In the Kyrgyz Republic, a 2 4 6 8 10 12 14 child in the richest 20 percent of households who starts school at age 6 can expect to complete 10.6 years of school by her 18th birthday while a child from the poor- Harmonized Test Scores est 20 percent can expect to complete 10.7 years of Source: Programme for International Student Assessment 2009 school, a gap of 0 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in the Kyrgyz Republic score 390 while those from the poorest 20 percent score 296, Fraction of Children Under 5 Not Stunted Source: Multiple Indicator Cluster Survey 2014 a gap of 94 points on a scale that ranges from 300 (min- imal attainment) to 625 (high attainment). This gap is larger than the typical gap across the 50 countries (55 .2 .4 .6 .8 1 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In the Kyrgyz Re- public, the percentage of children in the top 20 percent of households who are not stunted is 89 percent while The Human Capital Project is a global effort to accelerate the it is 82 percent among the poorest 20 percent, a gap of amount and quality of investments in people. 7 percentage points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 83 Lesotho 84 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Lesotho Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Lesotho was ranked 143 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Lesotho, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 59 percent while it is 46 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 13 percentage points. This gap is smaller than the typical gap across Probability of Survival to Age 5 the 50 countries (15 percentage points). Source: Demographic and Health Survey 2014 • Probability of Survival to Age 5. In Lesotho, the proba- bility of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 93 percent while it is 92 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 1 percentage points. This gap is smaller than the typical Source: Demographic and Health Survey 2014 gap across the 50 countries (4 percentage points). • Expected Years of School. In Lesotho, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11.2 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Southern and Eastern Africa Consortium for Monitoring Educational Quality 2007 can expect to complete 9.5 years of school, a gap of 1.7 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Lesotho score 384 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 348, a gap of Source: Demographic and Health Survey 2014 37 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Lesotho, the percentage of children in the top 20 percent of house- holds who are not stunted is 87 percent while it is 56 percent among the poorest 20 percent, a gap of 31 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is larger than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 84 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Madagascar Madagascar Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Madagascar was ranked 140 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Madagascar, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 58 percent while it is 41 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 18 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Demographic and Health Survey 2008 • Probability of Survival to Age 5. In Madagascar, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 95 percent while it is 89 percent for a child born in the poorest 20 percent, a gap of 6 percentage points. This gap is larger than the typi- Expected Years of School Source: Demographic and Health Survey 2008 cal gap across the 50 countries (4 percentage points). • Expected Years of School. In Madagascar, a child in the richest 20 percent of households who starts school 2 4 6 8 10 12 14 at age 6 can expect to complete 10.4 years of school by her 18th birthday while a child from the poorest 20 per- Harmonized Test Scores cent can expect to complete 6.2 years of school, a gap of Source: Programme for the Analysis of Education Systems 2006 4.2 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Madagascar score 467 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 427, a gap of Source: Demographic and Health Survey 2008 41 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Madagascar, the percentage of children in the top 20 percent of households who are not stunted is 56 percent while it is 52 percent among the poorest 20 percent, a gap of 4 The Human Capital Project is a global effort to accelerate the percentage points. This gap is smaller than the typical amount and quality of investments in people. gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 85 Malawi 86 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Malawi Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Malawi was ranked 125 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Malawi, the productivity as a future worker of a child born today in the richest 20 percent of households is 54 percent while it is 45 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 9 percentage points. This gap is smaller than the typical gap across the 50 coun- Probability of Survival to Age 5 tries (15 percentage points). Source: Demographic and Health Survey 2015 • Probability of Survival to Age 5. In Malawi, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 94 percent while it is 92 percent for a child born in the poorest 20 percent, a gap of 2 percentage points. This gap is slightly smaller Expected Years of School Source: Demographic and Health Survey 2015 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Malawi, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 11.2 years of school by her 18th Harmonized Test Scores birthday while a child from the poorest 20 percent can Source: Early Grade Reading Assessment 2012 expect to complete 9.7 years of school, a gap of 1.5 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Malawi score 338 while Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2015 those from the poorest 20 percent score 325, a gap of 13 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Malawi, the per- centage of children in the top 20 percent of households who are not stunted is 77 percent while it is 55 percent The Human Capital Project is a global effort to accelerate the among the poorest 20 percent, a gap of 22 percentage amount and quality of investments in people. points. This gap is larger than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 86 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Mali Mali Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Mali was ranked 154 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Mali, the productivity as a future worker of a child born today in the richest 20 percent of households is 50 percent while it is 32 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 18 percentage points. This gap is larger than the typical gap across the 50 countries Probability of Survival to Age 5 (15 percentage points). Source: Multiple Indicator Cluster Survey 2015 • Probability of Survival to Age 5. In Mali, the probabil- ity of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 95 percent while it is 88 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 6 percentage points. This gap is larger than the typical Source: Multiple Indicator Cluster Survey 2015 gap across the 50 countries (4 percentage points). • Expected Years of School. In Mali, a child in the richest 2 4 6 8 10 12 14 20 percent of households who starts school at age 6 can expect to complete 9.4 years of school by her 18th birth- day while a child from the poorest 20 percent can ex- Harmonized Test Scores Source: Early Grade Reading Assessment 2015 pect to complete 2.6 years of school, a gap of 6.8 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Mali score 313 while those Fraction of Children Under 5 Not Stunted from the poorest 20 percent score 309, a gap of 3 Source: Multiple Indicator Cluster Survey 2015 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is smaller than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Mali, the per- centage of children in the top 20 percent of households who are not stunted is 85 percent while it is 60 percent among the poorest 20 percent, a gap of 25 percentage The Human Capital Project is a global effort to accelerate the points. This gap is larger than the typical gap across the amount and quality of investments in people. 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 87 Moldova 88 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Moldova Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Moldova was ranked 75 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Moldova, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 74 percent while it is 61 percent for a child born .2 .4 .6 .8 1 in the poorest 20 percent, a gap of 13 percentage points. This gap is smaller than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Demographic and Health Survey 2005 • Probability of Survival to Age 5. In Moldova, the prob- ability of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 98 percent while it is 97 per- cent for a child born in the poorest 20 percent, a gap of 1 percentage points. This gap is smaller than the typical Expected Years of School Source: Demographic and Health Survey 2005 gap across the 50 countries (4 percentage points). • Expected Years of School. In Moldova, a child in the richest 20 percent of households who starts school at 2 4 6 8 10 12 14 age 6 can expect to complete 10.4 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores can expect to complete 9 years of school, a gap of 1.3 Source: Progress in International Reading Literacy Study 2007 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Moldova score 530 while those from the poorest 20 percent score 472, a gap of Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2005 58 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is about the same as the typical gap across the 50 countries (55 .2 .4 .6 .8 1 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Moldova, the percentage of children in the top 20 percent of house- holds who are not stunted is 93 percent while it is 85 The Human Capital Project is a global effort to accelerate the percent among the poorest 20 percent, a gap of 8 per- amount and quality of investments in people. centage points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 88 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Mozambique Mozambique Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Mozambique was ranked 148 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Mozambique, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 55 percent while it is 37 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 18 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Demographic and Health Survey 2011 • Probability of Survival to Age 5. In Mozambique, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 91 percent while it is 87 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is about the same Expected Years of School as the typical gap across the 50 countries (4 percentage Source: Demographic and Health Survey 2011 points). • Expected Years of School. In Mozambique, a child in 2 4 6 8 10 12 14 the richest 20 percent of households who starts school at age 6 can expect to complete 10.9 years of school by Harmonized Test Scores her 18th birthday while a child from the poorest 20 per- Source: Southern and Eastern Africa Consortium for Monitoring Educational Quality 2007 cent can expect to complete 6.6 years of school, a gap of 4.3 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Mozambique score 395 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 350, a gap of Source: Demographic and Health Survey 2011 45 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Mozambique, the percentage of children in the top 20 percent of households who are not stunted is 76 percent while it is 49 percent among the poorest 20 percent, a gap of The Human Capital Project is a global effort to accelerate the 27 percentage points. This gap is larger than the typical amount and quality of investments in people. gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 89 Myanmar 90 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Myanmar Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Myanmar was ranked 107 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Myanmar, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 62 percent while it is 43 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 20 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Demographic and Health Survey 2015 • Probability of Survival to Age 5. In Myanmar, the prob- ability of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 97 percent while it is 90 per- cent for a child born in the poorest 20 percent, a gap of 7 percentage points. This gap is larger than the typical Expected Years of School Source: Demographic and Health Survey 2015 gap across the 50 countries (4 percentage points). • Expected Years of School. In Myanmar, a child in the richest 20 percent of households who starts school at 2 4 6 8 10 12 14 age 6 can expect to complete 10.1 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores can expect to complete 6.7 years of school, a gap of 3.4 Source: Early Grade Reading Assessment 2014 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Myanmar score 438 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 396, a gap of Source: Demographic and Health Survey 2015 42 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Myanmar, the percentage of children in the top 20 percent of house- holds who are not stunted is 85 percent while it is 63 percent among the poorest 20 percent, a gap of 22 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is larger than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 90 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Namibia Namibia Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Namibia was ranked 117 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Namibia, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 65 percent while it is 49 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 16 percentage points. This gap is about the same as the typical gap Probability of Survival to Age 5 across the 50 countries (15 percentage points). Source: Demographic and Health Survey 2013 • Probability of Survival to Age 5. In Namibia, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 97 percent while it is 93 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is about the same Expected Years of School Source: Demographic and Health Survey 2013 as the typical gap across the 50 countries (4 percentage points). • Expected Years of School. In Namibia, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 10.8 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Southern and Eastern Africa Consortium for Monitoring Educational Quality 2007 can expect to complete 9.4 years of school, a gap of 1.4 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Namibia score 427 while Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2013 those from the poorest 20 percent score 346, a gap of 81 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Namibia, the percentage of children in the top 20 percent of house- holds who are not stunted is 90 percent while it is 71 The Human Capital Project is a global effort to accelerate the percent among the poorest 20 percent, a gap of 20 per- amount and quality of investments in people. centage points. This gap is slightly larger than the typi- cal gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 91 Niger 92 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Niger Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Niger was ranked 155 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Niger, the productivity as a future worker of a child born today in the richest 20 percent of households is 41 percent while it is 31 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 11 percentage points. This gap is smaller than the typical gap across the 50 coun- Probability of Survival to Age 5 tries (15 percentage points). Source: Demographic and Health Survey 2012 • Probability of Survival to Age 5. In Niger, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 89 percent while it is 86 percent for a child born in the poorest 20 percent, a gap of 3 percentage points. This gap is slightly smaller Expected Years of School Source: Demographic and Health Survey 2012 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Niger, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 7.5 years of school by her 18th Harmonized Test Scores birthday while a child from the poorest 20 percent can Source: Programme for the Analysis of Education Systems 2014 expect to complete 2.6 years of school, a gap of 5 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Niger score 321 while those Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2012 from the poorest 20 percent score 281, a gap of 40 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is smaller than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Niger, the per- centage of children in the top 20 percent of households who are not stunted is 66 percent while it is 54 percent The Human Capital Project is a global effort to accelerate the among the poorest 20 percent, a gap of 12 percentage amount and quality of investments in people. points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 92 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Paraguay Paraguay Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Paraguay was ranked 90 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Paraguay, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 71 percent while it is 56 percent for a child born .2 .4 .6 .8 1 in the poorest 20 percent, a gap of 16 percentage points. This gap is about the same as the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Multiple Indicator Cluster Survey 2016 • Probability of Survival to Age 5. In Paraguay, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 100 percent while it is 97 percent for a child born in the poorest 20 percent, a gap of 2 percentage points. This gap is slightly smaller Expected Years of School Source: Multiple Indicator Cluster Survey 2016 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Paraguay, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11.4 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Latin American Laboratory for Assessment of the Quality of Education 2013 can expect to complete 9.8 years of school, a gap of 1.7 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Paraguay score 429 while Fraction of Children Under 5 Not Stunted Source: Multiple Indicator Cluster Survey 2016 those from the poorest 20 percent score 359, a gap of 69 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Paraguay, the percentage of children in the top 20 percent of house- holds who are not stunted is 99 percent while it is 87 The Human Capital Project is a global effort to accelerate the percent among the poorest 20 percent, a gap of 12 per- amount and quality of investments in people. centage points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 93 Peru 94 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Peru Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Peru was ranked 72 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Peru, the productivity as a future worker of a child born today in the richest 20 percent of households is 68 percent while it is 48 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 20 percentage points. This gap is larger than the typical gap across the 50 countries Probability of Survival to Age 5 (15 percentage points). Source: Demographic and Health Survey 2012 • Probability of Survival to Age 5. In Peru, the probabil- ity of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 99 percent while it is 96 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 2 percentage points. This gap is smaller than the typical Source: Demographic and Health Survey 2012 gap across the 50 countries (4 percentage points). • Expected Years of School. In Peru, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 10.3 years of school by her 18th birthday while a child from the poorest 20 percent can Harmonized Test Scores Source: Programme for International Student Assessment 2015 expect to complete 9.2 years of school, a gap of 1.1 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Peru score 464 while those Fraction of Children Under 5 Not Stunted from the poorest 20 percent score 348, a gap of 116 Source: Demographic and Health Survey 2012 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is larger than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Peru, the per- centage of children in the top 20 percent of households who are not stunted is 96 percent while it is 61 percent among the poorest 20 percent, a gap of 35 percentage The Human Capital Project is a global effort to accelerate the points. This gap is larger than the typical gap across the amount and quality of investments in people. 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 94 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Senegal Senegal Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Senegal was ranked 121 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Senegal, the productivity as a future worker of a child born today in the richest 20 percent of households is 62 percent while it is 41 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 22 percentage points. This gap is larger than the typical gap across the 50 countries Probability of Survival to Age 5 (15 percentage points). Source: Demographic and Health Survey 2014 • Probability of Survival to Age 5. In Senegal, the proba- bility of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 97 percent while it is 91 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 6 percentage points. This gap is larger than the typical Source: Demographic and Health Survey 2014 gap across the 50 countries (4 percentage points). • Expected Years of School. In Senegal, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 9.6 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Programme for the Analysis of Education Systems 2014 can expect to complete 5.4 years of school, a gap of 4.3 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Senegal score 440 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 370, a gap of Source: Demographic and Health Survey 2014 71 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Senegal, the percentage of children in the top 20 percent of house- holds who are not stunted is 91 percent while it is 72 percent among the poorest 20 percent, a gap of 20 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is slightly larger than the typi- amount and quality of investments in people. cal gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 95 Tajikistan 96 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Tajikistan Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Tajikistan was ranked 89 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Tajikistan, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 61 percent while it is 55 percent for a child born .2 .4 .6 .8 1 in the poorest 20 percent, a gap of 6 percentage points. This gap is smaller than the typical gap across the 50 Probability of Survival to Age 5 countries (15 percentage points). Source: Demographic and Health Survey 2012 • Probability of Survival to Age 5. In Tajikistan, the prob- ability of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 96 percent while it is 94 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 2 percentage points. This gap is smaller than the typical Source: Demographic and Health Survey 2012 gap across the 50 countries (4 percentage points). • Expected Years of School. In Tajikistan, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 10.1 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Early Grade Reading Assessment 2016 can expect to complete 9.7 years of school, a gap of .4 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Tajikistan score 449 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 428, a gap of Source: Demographic and Health Survey 2012 22 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Tajikistan, the percentage of children in the top 20 percent of house- holds who are not stunted is 79 percent while it is 68 percent among the poorest 20 percent, a gap of 11 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is smaller than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 96 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Tanzania Tanzania Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Tanzania was ranked 128 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Tanzania, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 54 percent while it is 39 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 15 percentage points. This gap is about the same as the typical gap Probability of Survival to Age 5 across the 50 countries (15 percentage points). Source: Demographic and Health Survey 2015 • Probability of Survival to Age 5. In Tanzania, the prob- ability of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 93 percent while it is 92 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 0 percentage points. This gap is smaller than the typical Source: Demographic and Health Survey 2015 gap across the 50 countries (4 percentage points). • Expected Years of School. In Tanzania, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 9.4 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Early Grade Reading Assessment 2013 can expect to complete 5.4 years of school, a gap of 3.9 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Tanzania score 407 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 331, a gap of Source: Demographic and Health Survey 2015 76 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Tanzania, the percentage of children in the top 20 percent of house- holds who are not stunted is 81 percent while it is 61 percent among the poorest 20 percent, a gap of 20 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is slightly larger than the typi- amount and quality of investments in people. cal gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 97 Togo 98 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Togo Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Togo was ranked 122 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Togo, the productivity as a future worker of a child born today in the richest 20 percent of households is 63 percent while it is 45 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 18 percentage points. This gap is larger than the typical gap across the 50 countries Probability of Survival to Age 5 (15 percentage points). Source: Demographic and Health Survey 2013 • Probability of Survival to Age 5. In Togo, the proba- bility of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 95 percent while it is 88 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 7 percentage points. This gap is larger than the typical Source: Demographic and Health Survey 2013 gap across the 50 countries (4 percentage points). • Expected Years of School. In Togo, a child in the rich- 2 4 6 8 10 12 14 est 20 percent of households who starts school at age 6 can expect to complete 10.6 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Programme for the Analysis of Education Systems 2014 can expect to complete 8.9 years of school, a gap of 1.8 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Togo score 425 while those Fraction of Children Under 5 Not Stunted from the poorest 20 percent score 356, a gap of 69 Source: Demographic and Health Survey 2013 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is larger than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Togo, the per- centage of children in the top 20 percent of households who are not stunted is 90 percent while it is 67 percent among the poorest 20 percent, a gap of 23 percentage The Human Capital Project is a global effort to accelerate the points. This gap is larger than the typical gap across the amount and quality of investments in people. 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 98 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Turkey Turkey Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Turkey was ranked 53 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Turkey, the productivity as a future worker of a child born today in the richest 20 percent of households is 77 percent while it is 49 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 29 percentage points. This gap is larger than the typical gap across the 50 countries Probability of Survival to Age 5 (15 percentage points). Source: Demographic and Health Survey 2003 • Probability of Survival to Age 5. In Turkey, the proba- bility of survival of a child born today in the richest 20 .8 .85 .9 .95 1 percent of households is 98 percent while it is 92 per- cent for a child born in the poorest 20 percent, a gap of Expected Years of School 6 percentage points. This gap is larger than the typical Source: Demographic and Health Survey 2003 gap across the 50 countries (4 percentage points). • Expected Years of School. In Turkey, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11.1 years of school by her 18th birthday while a child from the poorest 20 percent Harmonized Test Scores Source: Programme for International Student Assessment 2012 can expect to complete 7.9 years of school, a gap of 3.2 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Turkey score 521 while those Fraction of Children Under 5 Not Stunted from the poorest 20 percent score 426, a gap of 94 Source: Demographic and Health Survey 2003 points on a scale that ranges from 300 (minimal attain- ment) to 625 (high attainment). This gap is larger than .2 .4 .6 .8 1 the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Turkey, the per- centage of children in the top 20 percent of households who are not stunted is 96 percent while it is 69 percent among the poorest 20 percent, a gap of 27 percentage The Human Capital Project is a global effort to accelerate the points. This gap is larger than the typical gap across the amount and quality of investments in people. 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 99 Uganda 100 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Uganda Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Uganda was ranked 137 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Uganda, the productivity as a future worker of a child born today in the richest 20 percent of households is 55 percent while it is 45 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 10 percentage points. This gap is smaller than the typical gap across the 50 coun- Probability of Survival to Age 5 tries (15 percentage points). Source: Demographic and Health Survey 2016 • Probability of Survival to Age 5. In Uganda, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 95 percent while it is 91 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is about the same Expected Years of School Source: Demographic and Health Survey 2016 as the typical gap across the 50 countries (4 percentage points). • Expected Years of School. In Uganda, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 9.5 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Southern and Eastern Africa Consortium for Monitoring Educational Quality 2007 can expect to complete 8.3 years of school, a gap of 1.2 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Uganda score 399 while Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2016 those from the poorest 20 percent score 355, a gap of 44 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is smaller .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Uganda, the percentage of children in the top 20 percent of house- holds who are not stunted is 83 percent while it is 67 The Human Capital Project is a global effort to accelerate the percent among the poorest 20 percent, a gap of 16 per- amount and quality of investments in people. centage points. This gap is smaller than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 100 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Vietnam Vietnam Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Vietnam was ranked 48 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Vietnam, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 85 percent while it is 58 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 27 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Multiple Indicator Cluster Survey 2013 • Probability of Survival to Age 5. In Vietnam, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 99 percent while it is 96 percent for a child born in the poorest 20 percent, a gap of 3 percentage points. This gap is slightly smaller Expected Years of School Source: Multiple Indicator Cluster Survey 2013 than the typical gap across the 50 countries (4 percent- age points). • Expected Years of School. In Vietnam, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11.6 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Programme for International Student Assessment 2015 can expect to complete 9.6 years of school, a gap of 2.1 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Vietnam score 560 while Fraction of Children Under 5 Not Stunted Source: Multiple Indicator Cluster Survey 2010 those from the poorest 20 percent score 487, a gap of 73 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Vietnam, the percentage of children in the top 20 percent of house- holds who are not stunted is 94 percent while it is 59 The Human Capital Project is a global effort to accelerate the percent among the poorest 20 percent, a gap of 35 per- amount and quality of investments in people. centage points. This gap is larger than the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 101 West Bank and Gaza 102 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX West Bank and Gaza Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. West Bank and Gaza was ranked 82 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In the West Bank and Gaza, the productivity as a future worker of a child born today in the richest 20 percent of households is 72 percent while it is 61 percent for a .2 .4 .6 .8 1 child born in the poorest 20 percent, a gap of 11 per- centage points. This gap is smaller than the typical gap across the 50 countries (15 percentage points). Probability of Survival to Age 5 Source: Multiple Indicator Cluster Survey 2014 • Probability of Survival to Age 5. In the West Bank and Gaza, the probability of survival of a child born today in the richest 20 percent of households is 98 percent .8 .85 .9 .95 1 while it is 98 percent for a child born in the poorest 20 percent, a gap of 1 percentage points. This gap is Expected Years of School smaller than the typical gap across the 50 countries (4 Source: Multiple Indicator Cluster Survey 2014 percentage points). • Expected Years of School. In the West Bank and Gaza, a child in the richest 20 percent of households who 2 4 6 8 10 12 14 starts school at age 6 can expect to complete 11.5 years of school by her 18th birthday while a child from the Harmonized Test Scores poorest 20 percent can expect to complete 10.9 years Source: Trends in International Mathematics and Science Study 2011 of school, a gap of .6 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). • Harmonized Test Scores. Students from the richest 20 250 350 450 550 625 percent of households in the West Bank and Gaza score 458 while those from the poorest 20 percent score 372, Fraction of Children Under 5 Not Stunted a gap of 86 points on a scale that ranges from 300 (min- Source: Multiple Indicator Cluster Survey 2014 imal attainment) to 625 (high attainment). This gap is larger than the typical gap across the 50 countries (55 .2 .4 .6 .8 1 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In the West Bank and Gaza, the percentage of children in the top 20 per- cent of households who are not stunted is 94 percent while it is 93 percent among the poorest 20 percent, The Human Capital Project is a global effort to accelerate the a gap of 1 percentage points. This gap is smaller than amount and quality of investments in people. the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 102 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Zambia Zambia Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Zambia was ranked 131 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Zambia, the productivity as a future worker of a child born today in the richest 20 percent of households is 50 percent while it is 39 percent for a child born in the .2 .4 .6 .8 1 poorest 20 percent, a gap of 11 percentage points. This gap is smaller than the typical gap across the 50 coun- Probability of Survival to Age 5 tries (15 percentage points). Source: Demographic and Health Survey 2013 • Probability of Survival to Age 5. In Zambia, the prob- ability of survival of a child born today in the richest .8 .85 .9 .95 1 20 percent of households is 94 percent while it is 90 percent for a child born in the poorest 20 percent, a gap of 4 percentage points. This gap is about the same Expected Years of School Source: Demographic and Health Survey 2013 as the typical gap across the 50 countries (4 percentage points). • Expected Years of School. In Zambia, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 10.7 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Early Grade Reading Assessment 2011 can expect to complete 7.4 years of school, a gap of 3.3 years of school. This gap is larger than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Zambia score 313 while those Fraction of Children Under 5 Not Stunted Source: Demographic and Health Survey 2013 from the poorest 20 percent score 310, a gap of 3 points on a scale that ranges from 300 (minimal attainment) to 625 (high attainment). This gap is smaller than the .2 .4 .6 .8 1 typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Zambia, the percentage of children in the top 20 percent of house- holds who are not stunted is 71 percent while it is 53 The Human Capital Project is a global effort to accelerate the percent among the poorest 20 percent, a gap of 19 per- amount and quality of investments in people. centage points. This gap is about the same as the typical gap across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople A ppendix 4 : S ES - HC I C ountry Profiles 103 Zimbabwe 104 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX Zimbabwe Insights from Disaggregating the Human Capital Index The launch of the World Bank Human Capital Index (HCI) in October 2018 highlighted large gaps in human capital outcomes across 157 countries around the world. The global HCI shows how shortfalls in health and education among children today will reduce the productivity of the next generation of workers. Zimbabwe was ranked 114 out of 157 countries in the global HCI. Gaps in human capital outcomes within countries across socioeconomic groups are large as well. This country profile docu- ments these within-country gaps using a newly-developed version of the HCI disaggregated by socioeconomic status (SES- HCI). It presents data on key indicators of human capital outcomes among children (child survival, expected years of school, harmonized test scores, and the fraction of children under 5 who are not stunted), together with a version of the SES-HCI, for 50 low- and middle-income countries where data are available. This version of the SES-HCI relies on the same general methodology as the global HCI, but uses different data sources in order to allow for this disaggregation, and so is not directly comparable with the global HCI. For details on the data and methodology of the SES-HCI, see A Socioeconomic Disaggregation of the World Bank Human Capital Index, by D’Souza, Gatti and Kraay (2019). HOW DO HUMAN CAPITAL OUTCOMES DIFFER BY SOCIOECONOMIC STATUS? HCI By Quintile of Socioeconomic Status SES-Disaggregated Human Capital Index (SES-HCI) Source: World Bank Staff Calculations • SES-Disaggregated Human Capital Index (SES-HCI). In Zimbabwe, the productivity as a future worker of a child born today in the richest 20 percent of house- holds is 66 percent while it is 47 percent for a child .2 .4 .6 .8 1 born in the poorest 20 percent, a gap of 19 percentage points. This gap is larger than the typical gap across the Probability of Survival to Age 5 50 countries (15 percentage points). Source: Demographic and Health Survey 2015 • Probability of Survival to Age 5. In Zimbabwe, the probability of survival of a child born today in the rich- .8 .85 .9 .95 1 est 20 percent of households is 95 percent while it is 90 percent for a child born in the poorest 20 percent, a gap of 5 percentage points. This gap is slightly larger Expected Years of School than the typical gap across the 50 countries (4 percent- Source: Demographic and Health Survey 2015 age points). • Expected Years of School. In Zimbabwe, a child in the 2 4 6 8 10 12 14 richest 20 percent of households who starts school at age 6 can expect to complete 11 years of school by her Harmonized Test Scores 18th birthday while a child from the poorest 20 percent Source: Southern and Eastern Africa Consortium for Monitoring Educational Quality 2007 can expect to complete 9 years of school, a gap of 1.9 years of school. This gap is smaller than the typical gap across the 50 countries (2.4 years). 250 350 450 550 625 • Harmonized Test Scores. Students from the richest 20 percent of households in Zimbabwe score 462 while Fraction of Children Under 5 Not Stunted those from the poorest 20 percent score 369, a gap of Source: Demographic and Health Survey 2015 94 points on a scale that ranges from 300 (minimal at- tainment) to 625 (high attainment). This gap is larger .2 .4 .6 .8 1 than the typical gap across the 50 countries (55 points). Poorest quintile 2nd quintile 3rd quintile 4th quintile Richest quintile • Healthy Growth (Not Stunted Rate). In Zimbabwe, the percentage of children in the top 20 percent of house- holds who are not stunted is 85 percent while it is 68 percent among the poorest 20 percent, a gap of 17 per- The Human Capital Project is a global effort to accelerate the centage points. This gap is smaller than the typical gap amount and quality of investments in people. across the 50 countries (19 percentage points). For more information on the Human Capital Project, please visit www.worldbank.org/humancapitalproject #investinPeople 104 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX A ppendix 4 : S ES - HC I C ountry Profiles 105 106 INSIG HTS FROM D ISAGGRE GAT IN G T H E HUM A N CA PI TA L I N DEX