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4
Progress Toward Education for All: Trends and Current Challenges for sub-Saharan Africa

Paul C. Hewett and Cynthia B. Lloyd




At the turn of the twenty-first century, significant challenges remain for sub-Saharan African countries attempting to provide universal schooling for their children and youth. We estimate for the region that 20.8 million or 25 percent of young adolescents ages 10 to 14 have never enrolled in school (11.5 million girls and 9.3 million boys). Fully 28.4 million (15.1 million girls and 13.3 million boys) have not completed four grades of schooling. Furthermore, 37.2 million or 45 percent will never complete primary school. This latter number is nearly twice the entire population of children ages 10 to 14 in the United States, virtually all of whom will complete a primary education.1 Indeed, the level of educational participation and attainment in sub-Saharan Africa falls significantly below all other regions in the developing world (Chapter 3). Furthermore, in many countries, rates of growth in primary completion have flattened out or even declined since the mid- to late 1980s.

1  

The estimates for sub-Saharan Africa are derived from nationally representative Demographic and Health Surveys (DHS) from 24 countries, collectively representing 81 percent of the total sub-Saharan youth population. The estimates are conservative because they are based on the assumption that the 19 percent of the sub-Saharan African population not represented by our data has the same levels of schooling participation and attainment as the 81 percent of the sub-Saharan population that is represented. Given that much of the missing population lives in countries that are in the midst of armed conflict and civil disruption, it is likely that their schooling performance will be lower than the performance in our sample population. The population estimate for the United States is 20.9 million in July 2001 (Table US-EST2001-ASRO-01, resident population estimates of the United States by age and sex, Population Division, U.S. Census Bureau).



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The Changing Transitions to Adulthood in Developing Countries: Selected Studies 4 Progress Toward Education for All: Trends and Current Challenges for sub-Saharan Africa Paul C. Hewett and Cynthia B. Lloyd At the turn of the twenty-first century, significant challenges remain for sub-Saharan African countries attempting to provide universal schooling for their children and youth. We estimate for the region that 20.8 million or 25 percent of young adolescents ages 10 to 14 have never enrolled in school (11.5 million girls and 9.3 million boys). Fully 28.4 million (15.1 million girls and 13.3 million boys) have not completed four grades of schooling. Furthermore, 37.2 million or 45 percent will never complete primary school. This latter number is nearly twice the entire population of children ages 10 to 14 in the United States, virtually all of whom will complete a primary education.1 Indeed, the level of educational participation and attainment in sub-Saharan Africa falls significantly below all other regions in the developing world (Chapter 3). Furthermore, in many countries, rates of growth in primary completion have flattened out or even declined since the mid- to late 1980s. 1   The estimates for sub-Saharan Africa are derived from nationally representative Demographic and Health Surveys (DHS) from 24 countries, collectively representing 81 percent of the total sub-Saharan youth population. The estimates are conservative because they are based on the assumption that the 19 percent of the sub-Saharan African population not represented by our data has the same levels of schooling participation and attainment as the 81 percent of the sub-Saharan population that is represented. Given that much of the missing population lives in countries that are in the midst of armed conflict and civil disruption, it is likely that their schooling performance will be lower than the performance in our sample population. The population estimate for the United States is 20.9 million in July 2001 (Table US-EST2001-ASRO-01, resident population estimates of the United States by age and sex, Population Division, U.S. Census Bureau).

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Despite the enormous challenges of overcoming such widespread lack of educational opportunities, the international community remains committed to the goals of providing universal access to, and assuring completion of, a basic level of schooling of good quality. Originally set forth in the “World Declaration on Education for All,” signed by more than 150 countries and international organizations in Jomtien, Thailand, in 1990, a target date for achieving universal access to primary schooling was set for 2000. Although this target date was ultimately not met, the international community reaffirmed the Education for All (EFA) framework at the World Education Forum in Dakar, Senegal, in 2000. Specifying six EFA goals, the Dakar conference set a new target date of 2015 for “all children, particularly girls, children in difficult circumstances, and those belonging to ethnic minorities, to have access to and complete free and compulsory primary education of good quality” (Dakar Framework for Action, 2000). Currently, however, only 13 of the 24 sub-Saharan African countries evaluated in this chapter have constitutional guarantees of compulsory schooling and, of these, only 10 guarantee free schooling. The key features of educational systems for 24 sub-Saharan African countries are presented in Table 4-1. Specific targets for education are also embedded within the Millennium Declaration adopted by the United Nations General Assembly in 2001. The Millennium Declaration set forth eight Millennium Development Goals (MDG) relating to poverty, health, the environment, economic development, and education. The two targets directly related to education state: “by the year 2015, children everywhere, boys and girls alike, will be able to complete a full course of primary schooling and that by 2005 gender disparities in primary and secondary education will be eliminated” (United Nations General Assembly, 2001). The EFA and MDG efforts reflect the fact that investments in basic schooling have received a heightened level of attention from donors, governments, and the media because they are seen as a means of alleviating poverty and jump starting development in many parts of the developing world. The purposes of the chapter are three-fold: (1) to highlight the value of consistent and comparable population-based data on educational participation and attainment levels for program planning and target setting, (2) to deepen our knowledge of trends in educational participation and achievement among youth in sub-Saharan Africa, and (3) to identify current priorities based on a more in-depth exploration of schooling differentials by gender and household wealth. In the first part of the chapter we review two often-used indicators for monitoring educational progress, the net primary enrollment ratio (NPER) and the survival rate to grade five, and compare them with similar measures from the nationally representative household data generated from the Demographic and Health Surveys (DHS). In the

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 4-1 Key Features of Educational Systems in sub-Saharan Africa, 2000   Constitutional Guarantee Age of Entry Years of Primary Compulsory Free Benin   6 6 Burkina Faso 7 6 Cameroon 6 6 Central African Republic 6 6 Chad 6 6 Comoros 6 6 Côte d’Ivoire 6 6 Ethiopia 7 6 Ghana 6 6 Guinea 7 6 Kenya 6 7 Madagascar 6 5 Malawi 6 6 Mali 7 6 Mozambique 6 5 Niger 7 6 Nigeria 6 6 Rwanda 7 6 South Africa 7 7 Tanzania 7 7 Togo a a 6 6 Uganda a   6 7 Zambia     7 7 Zimbabwe a a 6 7 aTo be progressively introduced. SOURCES: UNESCO (2002, 2003) and Tomasevski (2001). second part of the chapter, we use DHS education data to explore longer term trends in schooling performance. In the final part of the chapter, we evaluate what is likely the biggest challenge for the next 10 years in achieving education for all in sub-Saharan Africa. MONITORING PROGRESS IN SCHOOLING International efforts to improve educational participation and attainment have put a premium on the development of indicators to monitor progress and to assess whether countries will meet the targets set by the EFA framework and the MDG. Two principal indicators that have been used by UNESCO and UNICEF to monitor progress toward universal education have been the NPER and the survival rate to grade 5 (UNESCO,

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies 2002, 2003; UNICEF, 2003c).2 The logic behind the use of these measures is that the attainment of both would imply that the completion of primary school, which typically runs 1 to 3 years beyond grade 4, would shortly follow. In addition, such indicators represent the basic levels of schooling needed for the long-term acquisition of basic literacy and numeracy skills. The NPER captures, at a moment in time, the percentage of children of primary school age who are currently enrolled in primary school. The NPER is derived from two different statistical sources. The numerator is obtained from beginning of the year registrations as officially reported by schools throughout the country to national ministries of education. These enrollment numbers are then divided by United Nations estimates of the population for the year and ages in question to derive the NPER. An NPER of 100 percent would indicate that all children within the eligible ages of primary school are currently enrolled. Although often used to monitor progress and trends over time, a variety of limitations are associated with the NPER measure. In a context in which many children start and finish primary school late, it is possible for a country to have achieved universal primary completion while having an NPER below 100. This situation would occur if a significant percentage of students in a particular age cohort completed primary school beyond the standard age of completion. The NPERs are also not strictly comparable across countries due to variations in the duration of the primary school cycle as defined by UNESCO. Table 4-1 shows that two countries have a primary cycle of 5 years, sixteen have 6 years, and six have 7 years. Countries are free to design their own school systems and international standards have not been established for the length of a primary school cycle. Using the MDG for primary schooling, countries with a longer primary cycle are currently judged by a tougher standard than countries with a shorter primary cycle. 2   The gross primary enrollment ratio (GPER) is a more familiar measure, but its use as a marker for progress is problematic. The GPER includes in the numerator all children enrolled in school regardless of age and, in the denominator, only those in the primary school age range. Thus, it often yields values over 100 percent due to factors such as late entry and grade repetition. Primary completion rates, generated by the World Bank (Bruns, Mingat, and Rakotomalala, 2003), are also now utilized to monitor progress in attainment. Although these statistics benefit from being conceptually closer to the notion of universal primary completion, they are based on the same data sources as the NPER and survival rate to grade 5 and, hence, suffer from some of the same limitations (see also UNESCO, 2003, p. 59 for a critical evaluation). In addition, a proxy-primary completion rate, must be used when end-year enrollment data are not available; in only 7 of the 24 countries in this analysis is an actual primary completion rate available for the most recent period. The proxy indicator requires fairly strong assumptions about repetition and dropout rates that occur from year to year, assumptions that are particularly problematic for sub-Saharan Africa.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies This is because the denominator of the ratio is customized to the actual number of years in the primary cycle in each country. The NPER is also set according to the recommended starting ages in each country even if these ages are poorly promoted or enforced. Fifteen of the 24 countries have recommended starting ages of 6, while the other nine have recommended starting ages of 7. Countries with earlier recommended starting ages may have more difficulty achieving a particular NPER than countries with later recommended starting ages. Furthermore, assessments of UNESCO data have raised questions about their comparability and quality (Behrman and Rosenzweig, 1994; Lloyd, Kaufman, and Hewett, 2000). The enrollment data obtained from the ministries of education vary in quality according to the management information system (MIS) capacity within each country. The development of a good MIS is a continuing challenge in many parts of Africa (Moulton et al., 2001). Where financial flows to schools are a function of the level of enrollment, there is substantial motivation on the part of local education offices to inflate these numbers. Changes in systems of reporting that make current data more accurate, often introduced as part of school reform measures, may compromise comparability over time. Alternative indicators to monitor progress toward EFA and the MDGs can be developed using data on schooling collected in nationally representative surveys. Data collected since 1995 for 24 sub-Saharan African countries are currently available from the DHS. Based on United Nations population estimates, these surveys represent 81 percent of the population of young people (ages 10 to 24) living in the region.3 As indicated in Table 4-2, sample sizes in the DHS for the 10- to 24-year age group range from approximately 4,600 to more than 22,000. The median date for these surveys is 1999. In each of these nationally representative surveys, educational participation and attainment information is collected for all household members, while current schooling status is obtained for those ages 5 to 24.4 Arguably, the DHS estimate of attendance is likely to be more accurate in assessing actual school participation than the UNESCO NPER estimate, given that the NPER captures those that may have enrolled, but never actually attended school (UNESCO, 2002). Additional benefits of the DHS 3   Data on school participation and attainment of household members is drawn from a household questionnaire, which asks a series of questions of an informed adult, typically the household head, about each household member. 4   Attendance data from DHS presented in this chapter are from responses to the following question on the household survey: “Is ‘name’ still in school?” While the UNESCO enrollment ratio measures opening day enrollments, attendance rates from the DHS data will reflect actual school participation during the phase of the school year when the survey was in the field.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 4-2 Sub-Saharan African Countries Participating in the Demographic and Health Surveys (DHS) Since 1995 Country Year of Most Recent DHS DHS Sample Size of Population Ages 10-24 U.N. Estimated Population Ages 10-24 in 2000 (in thousands) Benin 2001 9,257 2,115 Burkina Faso 1998-1999 10,243 3,976 Cameroon 1998 8,833 4,996 Central African Republic 1994-1995 8,529 1,199 Chad 1996-1997 11,149 2,491 Comoros 1996 4,852 240 Côte d’Ivoire 1998-1999 4,654 5,595 Ethiopia 1999 22,769 19,988 Ghana 1998-1999 6,991 6,581 Guinea 1999 10,097 2,637 Kenya 1998 13,021 11,306 Madagascar 1997 11,080 5,025 Malawi 2000 20,884 3,722 Mali 2001 19,329 3,652 Mozambique 1997 14,730 5,848 Niger 1998 11,052 3,505 Nigeria 1999 11,589 37,637 Rwanda 2000 16,679 2,689 South Africa 1998-2000 17,276 13,715 Tanzania 1999 6,115 11,845 Togo 1998 14,041 1,496 Uganda 2000-2001 12,742 7,757 Zambia 2001-2002 12,788 3,521 Zimbabwe 1999 10,374 4,489 SOURCES: DHS household data, United Nations Population Division estimates, 2000 (United Nations, 2001). indicator are that the numerator and denominator are derived from the same population base and can be presented for separate sample subpopulations of interest. Furthermore, while UNESCO presents annual data on trends in NPER for those countries reporting enrollment data by age, such data are not available for all countries. In the case of sub-Saharan Africa, only 15 of the 24 countries covered in this chapter have recent net enrollment data as reported by UNESCO. By contrast, attendance rates can be derived for all 24 countries with DHS data. The DHS does have disadvantages. Because a survey can extend over several months, it may capture some households at different phases of the annual school cycle. Thus, surveys that take place when schools are not in

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies session may lead to an underestimation of current attendance, because some respondents may not report students on vacation as currently attending. Certainly the DHS question wording was intended to capture all who are still enrolled in school, even if they were not currently attending due to illness, school vacation, or other mitigating circumstances. However, to address this concern, the DHS has specifically added a question to their most recent surveys that asks if—during the current school year—the household member attended school at any time.5 Table 4-3 presents the most recent UNESCO NPER and attendance rates from the DHS for boys and girls using the same primary school age ranges for each country.6 Figures 4-1a and 4-1b combine these two indicators in scatter plots, pairing estimates with a 45-degree line representing complete equality between the measures. Although a majority of points are reasonably close to the diagonal line, there is a tendency for the UNESCO estimates to be higher than those of the DHS.7 This is highlighted in Figures 4-1a and 4-1b by the larger number of cases falling, and sometimes significantly so, below the 45-degree line. These comparisons reinforce suspicions about the inflation of ministry reporting of enrollment and the likelihood that many children are enrolled in, but never actually attend, school (UNESCO, 2002). Table 4-3 also provides two alternative estimates of the gender parity ratio. By comparing the gender ratios, it is clear that UNESCO estimates are systematically lower than those of the DHS. These results can be explained by the higher reported enrollments for boys in the UNESCO data 5   This question was added to measure enrollment in cases where surveys encompassed more than one school year or encompassed a school year and a vacation period. Note that current attendance rates generated from this question may improperly capture those who have dropped out during the current school year. These changes were initiated so DHS data could become more directly comparable to UNESCO data. The additional question is available for only 9 of the 24 countries. To maintain our comparisons across all 24 countries, we have used the original question wording for attendance: “Is ‘name’ still in school?” For six of the nine countries, the difference between estimates of attendance generated from the different measures is less than 3 percent. Attendance is 27 percent lower in Rwanda and 12 percent lower in Guinea using only the original question. In Tanzania, attendance is 5 percent higher using only the original question. 6   Sahn and Stifel (2003) recently assessed progress toward the Millennium Development Goals in Africa during the 1990s using attendance rates among 6- to 14-year-olds. This is problematic because the measure ranges over 9 years of age, whereas the net enrollment rate ranges over 4 to 7 years, depending on the country. Thus, the Sahn and Stifel indicator is, in fact, a much higher standard to meet than is implied by the MDG target. 7   Similar findings were highlighted in comparisons between UNESCO’s NPER and National Attendance Ratios using a smaller selection of the DHS and UNICEF’s Multiple Indicator Cluster Surveys (Huebler and Loaizia, 2002, as cited in UNESCO, 2002, p. 49; UNESCO, 2003, Table 2.6). These differences persist if the alternative measure of attendance is used; see footnote 5.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 4-3 Comparison of NPER (UNESCO) and Primary Attendance Rates (DHS) Country Age Ranges Year of Data Boys Girls Gender Parity Ratioa UNESCO DHS UNESCO DHS UNESCO DHS UNESCO DHS Benin 6-11 — 2001 79.5 60.5 48.3 46.6 .61 .77 Burkina Faso 7-12 1998 1998-1999 40.2 33.0 27.5 22.8 .68 .69 Cameroon 6-11 — 1998 — 74.7 — 72.8 — .97 C.A.R. 6-11 — 1994-1995 — 64.0 — 49.5 — .77 Chad 6-11 1996 1996-1997 59.0 36.7 32.8 24.2 .56 .66 Comoros 6-11 1998 1996 53.7 49.2 45.5 44.6 .85 .91 Côte d’Ivoire 6-11 1998-1999 1998 67.5 58.4 50.8 46.4 .75 .79 Ethiopia 7-12 1998 1999 40.8 32.4 29.8 27.2 .73 .84 Ghana 6-11 — 1998-1999 — 76.8 — 76.1 — .99 Guinea 7-12 1999-2000 1999 56.4 31.3 41.4 23.9 .73 .76 Kenya 6-12 — 1998 — 87.2 — 86.9 — .99 Madagascar 6-10 1998 1997 62.1 58.2 63.5 60.2 1.02 1.03 Malawi 6-11 — 2000 — 73.1 — 76.0 — 1.04 Mali 7-12 — 2001 — 45.0 — 33.5 — .74 Mozambique 6-10 1998 1997 45.2 54.0 36.8 47.1 .81 .87 Niger 7-12 1998 1998 31.9 31.2 20.4 21.1 .64 .68 Nigeria 6-11 — 1999 — 65.5 — 61.3 — .94 Rwanda 7-12 1999-2000 2000 97.1 43.6 97.5 45.4 1.01 1.04 South Africa 7-13 1997 1998 100.0 88.5 100.0 89.9 1.00 1.02 Tanzania 7-13 1999-2000 1999 45.8 51.6 47.6 56.0 1.04 1.09 Togo 6-11 1998 1998 98.6 74.2 78.3 64.7 .79 .87 Uganda 6-12 — 2000-2001 — 74.2 — 75.8 — 1.02 Zambia 7-13 2000-2001 2001-2002 80.0 65.6 80.0 65.7 1.00 1.00 Zimbabwe 6-12 1999-2000 1999 79.9 80.9 80.4 82.3 1.01 1.02 aCalculated as females divided by males. SOURCES: UNESCO (2002, Table 6), World Bank (2002), and DHS household data.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies FIGURE 4-1 Comparison of UNESCO NPER and DHS attendance rate. SOURCE: Table 4-3, this volume.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies (Figure 4-1a). These findings suggest the potential for a differential inflation of enrollment by gender, with either structural elements built into some management information systems that lead to this type of performance inflation and/or the fact that boys are more likely than girls to be enrolled in, yet never attend, school. It is possible that while norms about the importance of enrolling boys are pervasive, norms about the enrollment of girls are less strongly held. As a result, the registration of girls on the first day of school may reflect a stronger commitment on the part of parents to support their daughters’ regular attendance, whereas, in the case of boys, the act of first day enrollment may be more routine and therefore less indicative of parental commitment. Regardless of how we interpret these discrepancies, UNESCO enrollment data imply much larger gender gaps in schooling in these countries than DHS attendance data. Given late starting ages and different lengths of the primary cycle, it is also interesting to compare UNESCO’s survival rate to grade 5 and the DHS grade 4 completion rate among those ever enrolled, two alternative indicators of grade progression. UNESCO has developed an indicator of the survival rate to grade 5 using a ratio of the number of children officially enrolled in grade 5 in a given year relative to the number of children who officially enrolled in first grade 4 years earlier. This rate may or may not capture the actual percentage of any cohort that completes grade 4, because it does not allow for any repetition or temporary withdrawal and it does not restrict the measure to children of a common age. In countries with high repetition or withdrawal, this statistic would underestimate the percentage of children who would eventually complete grade 4. An alternative measure to assess progress toward EFA, which can be easily derived from the DHS and does not have these limitations, is the percentage of 15- to 19-year-olds who have completed 4 or more years of schooling among those who have ever attended. This measure accommodates late starters and allows comparisons across age cohorts. Table 4-4 presents a comparison of estimates of the survival to grade 5 derived from UNESCO and the grade 4 completion rate among those who ever attended from the DHS, separately for boys and girls. In only 14 of the 24 countries are such data available from UNESCO. Figures 4-2a and 4-2b present scatter plots of points derived from data in Table 4-4. As can be seen in the figures, with the exception of Chad and Guinea (for boys) and Chad (for girls), the UNESCO estimates are lower than the comparable DHS data. If the UNESCO enrollment numbers are inflated by students who enroll, but never attend school—as is suggested above—the grade 5 survival rates would be lower than would otherwise be expected. The differences between estimates are also likely a function of the fact that the grade 4 completion rates calculated from the DHS data are not bounded by age and include children who spend more than 4 years to complete grade 4.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 4-4 Comparison of UNESCO Survival Rates to Grade 5 and DHS Grade 4 Completion Rates Given Enrollment Country Year of Data Boys Girls Gender Parity Ratioa UNESCO DHS UNESCO DHS UNESCO DHS UNESCO DHS Benin — 2001 — 83.2 — 75.5 — .91 Burkina Faso 1998-1999 1998-1999 66.9 80.3 70.4 84.5 1.05 1.05 Cameroon — 1998 — 86.8 — 88.0 — 1.01 C.A.R. — 1994-1995 — 66.7 — 57.1 — .86 Chad 1997 1996-1997 62.0 57.8 53.0 42.7 .85 .74 Comoros — 1996 — 75.2 — 74.9 — .99 Côte d’Ivoire 1997 1998 77.0 87.0 71.0 81.6 .92 .94 Ethiopia 1997 1999 51.0 54.8 50.0 54.3 .98 .99 Ghana — 1998-1999 — 93.5 — 92.8 — .99 Guinea 1998-1999 1999 92.5 87.8 79.1 80.7 .86 .92 Kenya — 1998 — 93.1 — 93.8 — 1.01 Madagascar 1997 1997 49.0 52.0 33.0 55.1 .67 1.06 Malawi — 2000 — 75.9 — 77.8 — 1.03 Mali — 2001 — 86.4 — 84.7 — .98 Mozambique 1997 1997 52.0 64.2 39.0 50.3 .75 .78 Niger 1998-1999 1998 62.1 87.2 60.2 86.0 .97 .99 Nigeria — 1999 — 96.5 — 95.2 — .99 Rwanda 1998-1999 2000 47.9 67.0 42.8 66.5 .89 .99 South Africa 1998-1999 1998 75.1 97.4 76.7 98.8 1.02 1.01 Tanzania 1998-1999 1999 78.6 83.0 83.3 88.0 1.06 1.06 Togo 1998-1999 1998 54.2 77.3 48.4 68.0 .89 .88 Uganda 1998-1999 2000-2001 43.9 85.5 45.5 82.3 1.04 .96 Zambia — 2001-2002 — 84.8 — 84.5 — 1.00 Zimbabwe 1997 1999 78.0 96.3 79.0 97.2 1.01 1.00 aCalculated as females divided by males. SOURCES: UNESCO (2002, Table 10), World Bank (2002), and DHS household data.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Ages 25-29 Ages 35-39 Change for Most Recent Decade Change for Earlier Decade Boys Girls Boys Girls Boys Girls Boys Girls .46 .22 .47 .18 34.5 66.0 −1.7 17.5 .21 .10 .13 .08 41.5 84.9 62.7 31.8 .82 .65 .73 .54 −5.2 10.3 13.1 20.9 .58 .32 .52 .18 −3.6 7.9 10.6 82.7 .34 .08 .29 .07 7.4 83.1 16.2 8.9 .63 .44 .35 .15 2.3 12.2 79.3 189.3 .59 .43 .50 .27 −3.2 −5.9 16.9 59.3 .37 .20 .29 .08 −16.1 6.7 24.9 145.9 .84 .62 .77 .60 1.5 26.7 8.7 3.8 .35 .15 .31 .12 38.7 65.9 13.5 25.5 .93 .89 .91 .72 −2.5 2.3 2.3 22.5 .57 .56 .55 .42 −28.1 −22.4 4.4 32.1 .70 .48 .66 .38 3.3 49.2 4.8 25.6 .25 .14 .25 .15 41.1 64.3 −1.2 −5.8 .50 .30 .52 .18 13.0 13.9 −5.0 67.4 .27 .15 .16 .07 33.1 21.1 69.4 108.9 .79 .64 .76 .48 4.9 14.5 5.0 33.5 .65 .62 .52 .37 −12.1 −8.2 25.2 69.0 .93 .91 .89 .84 3.3 6.6 4.7 8.8 .64 .33 .61 .27 7.7 44.3 4.9 22.7 .78 .58 .71 .46 6.1 27.1 9.7 25.6 .83 .78 .85 .54 −10.9 −9.2 −2.7 43.3 .85 .78 .87 .71 −5.5 −1.3 −2.1 10.3 .97 .94 .91 .72 −2.0 1.0 6.7 30.7

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies TABLE 4-6c Trends in Percentage Completed Primary, by Age Group: 24 sub-Saharan African Countries Country Survey Date Ages 10-24 Ages 20-24 2000 Population Boys Girls Benin 2001 2,115 .38 .17 Burkina Faso 1998-1999 3,976 .25 .12 Cameroon 1998 4,996 .69 .60 Central African Republic 1994-1995 1,199 .40 .22 Chad 1996-1997 2,491 .29 .07 Comoros 1996 240 .51 .41 Côte d’Ivoire 1998-1999 5,595 .46 .34 Ethiopia 1999 19,988 .23 .14 Ghana 1998-1999 6,581 .80 .62 Guinea 1999 2,637 .36 .15 Kenya 1998 11,306 .70 .62 Madagascar 1997 5,025 .31 .32 Malawi 2000 3,722 .44 .26 Mali 2001 3,652 .24 .12 Mozambique 1997 5,848 .18 .08 Niger 1998 3,505 .30 .14 Nigeria 1999 37,637 .79 .65 Rwanda 2000 2,689 .40 .36 South Africa 1998-2000 13,715 .86 .90 Togo 1998 1,496 .50 .22 Uganda 2000-2001 7,757 .47 .32 United Republic of Tanzania 1999 11,845 .71 .67 Zambia 2001-2002 3,521 .68 .54 Zimbabwe 1999 4,489 .88 .86 SOURCE: United Nations (2001); DHS household data.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies Ages 30-34 Ages 35-44 Change for Most Recent Decade Change for Earlier Decade Boys Girls Boys Girls Boys Girls Boys Girls .34 .16 .26 .10 13.4 5.8 29.2 64.2 .15 .06 .12 .04 72.4 89.2 24.2 61.4 .67 .43 .57 .31 2.9 39.7 17.9 40.5 .38 .18 .26 .06 5.1 24.5 45.6 210.8 .21 .04 .17 .02 40.8 72.2 22.8 123.1 .48 .26 .20 .07 5.3 58.3 140.1 290.0 .44 .27 .37 .28 6.5 27.0 16.8 −3.7 .25 .08 .16 .03 −7.6 75.6 51.7 209.9 .74 .51 .73 .49 7.0 21.8 1.6 5.1 .31 .11 .27 .09 14.4 31.3 14.7 23.3 .81 .65 .73 .41 −13.1 −4.7 10.4 60.5 .45 .39 .30 .22 −30.8 −17.5 47.8 75.4 .37 .15 .33 .11 18.7 69.9 12.9 34.8 .19 .09 .21 .07 27.3 25.6 −12.3 28.1 .20 .08 .13 .02 −6.9 10.8 51.0 309.8 .20 .09 .11 .04 49.9 57.6 79.3 122.7 .72 .52 .60 .31 9.4 24.8 19.0 69.3 .41 .31 .31 .19 −3.4 15.6 35.0 67.4 .78 .73 .65 .61 10.3 22.4 19.8 20.6 .53 .19 .42 .14 −5.0 15.3 27.2 34.8 .44 .24 .44 .21 7.9 34.9 .0 11.4 .75 .62 .51 .30 −5.6 8.7 48.6 108.2 .75 .53 .78 .46 −8.7 1.5 −4.1 15.2 .88 .74 .68 .41 .6 16.4 29.6 79.1

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies 1993; Nieuwenhuis, 1996). The effect of these recent trends are particularly pronounced for the most recent cohort of boys, with a recent drop off in attendance and the projected stagnation in grade 4 and primary completion rates. For girls, these trends are only beginning to be revealed in attendance rates for the youngest cohort. With continual progress in girls’ schooling in the past 10 years and increasing gender parity ratios in levels of attainment, questions remain as to how the international community can focus its limited resources and attention to maximize the possibility of attaining the EFA goals and MDG. Since the Jomtien Conference in 1990, the international community has placed a great degree of weight on investments in girls’ schooling, given gender gaps that have historically favored boys in most of the developing world (UNESCO, 2003; UNICEF, 2003a, 2003b, 2003c). The trends in education for girls provide some evidence that those investments have had the intended impact. With the potential closing of the gender gap in sub-Saharan Africa in the near future, albeit at levels significantly below universal primary completion, remaining disadvantaged groups need to be identified, and policies developed, for achieving further progress in educational participation and attainment. Household surveys from the DHS provide an opportunity for focusing attention on the critical remaining challenges in achieving education for all. Although the UNESCO data do not allow us to explore differential educational attainment by household living standards, this is possible with DHS data. The DHS data are particularly advantageous in this way for EFA monitoring, given that many current reform efforts, in the presence of resource constraints, are attempting to target resources where they are most needed. Based on a methodology for generating a household wealth index utilizing Principal Components analysis (Filmer and Pritchett, 1999)16 and the indicator of grade 4 completion, we develop an index of educational 16   The living standards or wealth index is generated from the DHS and is based on two sets of indicators, the ownership of a set of consumer durables (e.g., a radio, bike, car) and various quality of housing indicators, including the availability of piped water, electricity, and finished flooring. To generate a single measure of household living standards using these indicators, the individual variables are included in a Principal Components analysis that generates weights for each item that represent the variable’s overall importance in capturing household wealth. The score of the first principal component is generated from a linear extrapolation of the weights and the variable score. The scores are then weighted by household size, with somewhat arbitrary percentile cutoffs of 40, 40, and 20 used to delineate low, middle, and high household wealth. This index measures relative inequality, not absolute inequality. Thus, the wealth index is not comparable across countries, and in the poorest countries, many in the middle, or even sometimes the highest wealth category will still be poor in an absolute sense. It should also be noted that the wealth delineations are strongly related to urban or rural residence. The preponderant percentage of the poor live in rural areas while the wealthier most often reside in urban areas.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies inequality by household wealth.17 The inequality index is calculated as 1 minus the ratio of the grade 4 attainment of the poorest 40 percent of households, relative to the wealthiest 20 percent of households. This measure of educational inequality ranges from 0 to 1, with 0 representing complete parity of attainment between the wealthiest 20 percent and the poorest 40 percent in each country and a value of 1 indicating a complete lack of educational opportunities for the poor. A measure of 0.5 implies that the poor have obtained 50 percent of the levels of attainment of the wealthiest. Figure 4-4 presents the inequality index for grade 4 completion by wealth status and gender. The countries are ordered from low to high inequality using the index for boys. The index varies across the full range of possible values among the 24 countries. Roughly half the countries have indices for both boys and girls that exceed 50 percent, suggesting wide differentials in educational attainment by household socioeconomic status in sub-Saharan Africa. These include Central African Republic, Mozambique, Niger, Chad, Guinea, Benin, Ethiopia, Madagascar, Burkina Faso, and Mali. In many of these countries, the inequality index takes on extreme values ranging from 70 to 90 percent, indicating almost a complete lack of educational opportunities for the poor. A few additional countries have levels of inequality that exceed 50 percent only for girls, including Comoros, Togo, and Côte d’Ivoire. On the other hand, we see that certain countries have achieved near universal schooling even for the poor. These include Kenya, Zimbabwe, and South Africa. Relatively low inequality, in the 0 to 0.25 range, can be seen for both sexes in Ghana and Rwanda and for boys in Tanzania. In many countries, the index of inequality is substantially higher for girls than boys, supporting the widely held belief that gender inequalities in educational attainment are compounded among the poor. Differences of 10 percentage points or more in the index between boys and girls can be found in 13 of the 24 countries. Such gender differences tend to be greatest in countries where overall wealth inequalities are greatest. It is interesting to note, however, that this pattern is not universal. In a substantial minority of countries, representing the full range in terms of schooling inequalities by household wealth status, we find similar levels of inequality for both boys and girls. These include Kenya, Zimbabwe, South Africa, Ghana, Rwanda, Malawi, Zambia, Cameroon, Madagascar, Burkina Faso, and Mali. We 17   Of the three indicators, grade 4 completion rates were selected because, relative to attendance rates, they provide a measure basic schooling attainment. Also, because grade 4 completion can be calculated for those 15- to 19-year-olds, it is more contemporaneous to current household living standards than primary completion rates for 20- to 24-year-olds.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies FIGURE 4-4 Index of inequality in grade 4 completion, 15- to 19-year-olds, by household wealth status and gender. SOURCE: DHS household data. find a few countries where inequalities for boys are greater than inequalities for girls: South Africa, Ghana, Rwanda, Zambia, and Madagascar. Figure 4-5 shows levels of grade 4 completion currently achieved by the wealthiest 20 percent of 10- to 14-year-olds in each country, graded from low to high according to the achievement of boys. We see that for many countries at the turn of the century, near universal grade 4 completion has already been achieved for the economically better off. For many others, such an achievement is likely within the next 15 years. For a few countries, however, even the wealthiest 20 percent have a long way to go. This group would include some of the poorest countries: Chad, Ethiopia, Niger, Burkina Faso, and Mali. While in the majority of countries, the gender gap among children from the wealthiest households has narrowed or almost disappeared, this is not the case in much of francophone Africa, including Burkina Faso, Niger, Chad, Mali, Benin, Guinea, Côte d’Ivoire, and Togo. Gender gaps among the wealthy remain large in Ethiopia and Mozambique as well.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies FIGURE 4-5 Grade 4 completion, 15- to 19-year-olds. SOURCE: DHS household data.

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies These results suggest that educational reform measures need to be tailored carefully to each country’s situation based on recent and accurate measures of the performance of different subgroups of the population. At the country level, DHS data permit other breakdowns as well, including provincial and rural-urban breakdowns. Although many of these breakdowns could be developed within a well-designed MIS, this would not be the case for indicators that require data that are collected at the household level, such as living standards. Given the enormous financial and organizational mobilization that will be required to achieve the millennium goals, resources will need to be targeted to the particular population subgroups that are lagging behind. As is illustrated here, a proper monitoring program will require information on the relative progress of the poor. CONCLUSIONS At the turn of the twenty-first century, we estimate that 37.2 million young adolescents ages 10 to 14 in sub-Saharan Africa will not complete primary. Reducing the number of uneducated African youth is a primary objective of signatories of the Education for All framework, as well as the United Nations MDG for education (United Nations, 2001). Achieving these goals in the time frame desired will require a level of resources and commitment not previously seen; it will also require more effective tools for monitoring progress. We conclude from our assessment of UNESCO’s two indicators for monitoring progress toward EFA and the MDG that UNESCO data may provide a potentially misleading picture of current progress. Not only are rates of enrollment significantly higher relative to attendance data from nationally representative DHS surveys, but gender parity ratios suggest a greater remaining gap in attendance than comparable DHS data. Part of the problem arises from UNESCO’s reliance on management information systems to make cross-country comparisons. This results in the publication of data of variable quality, with limited comparability across countries and over time. Reliance on such data to track progress toward the millennium goals should be carefully weighed. At a minimum, UNESCO data should be consistently evaluated vis-à-vis alternative data sources and indicators. Although UNESCO will likely remain committed to the net primary enrollment ratio and survival to grade 5 indicators, strides have already been made in utilizing a wider array of attainment data (UNESCO, 2003, Table 2.13). Nationally representative household data provide a useful baseline from which to build. UNICEF’s Multiple Indicator Cluster Survey and the DHS, both of which collect information on the educational participation and attainment of household members, are collected in a large enough number

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies of countries for cross-national and regional comparisons of educational progress. Since 2000, DHS household questionnaires have been expanded to allow the possibility of creating additional schooling indicators, including some which are directly comparable to commonly used UNESCO indicators. This is part of a relatively new project undertaken by the DHS with support from the USAID’s Office of Human Capacity Development, which includes the production of country-level fact sheets of education indicators. Furthermore, as part of the same project, the DHS is beginning to launch a series of in-depth surveys on education in sub-Saharan Africa in conjunction with its regular surveys. The first report was recently published on Uganda; results for Malawi and Zambia will follow shortly. This effort would require substantial expansion if it were to take on EFA monitoring throughout the world. Even with the limited education data already collected in the traditional DHS, much can be learned about past trends and the current status of schooling in sub-Saharan Africa. The trends in primary schooling completion for sub-Saharan Africa implied by these data raise serious questions about the feasibility of achieving the EFA goals and MDG in the foreseeable future. It is even possible that some earlier gains could be lost, given recent declines in attendance rates among the youngest boys and the tapering off in attendance rates among the youngest cohort of girls in many countries. It would also appear that, for the indicators utilized in this chapter, the gap between boys and girls is closing rapidly for the region as a whole. These trends in gender parity ratios are occurring despite huge variations in overall levels of educational attainment. Consequently, these findings raise doubts about the likelihood that EFA goals can be achieved with a strategy limited to an emphasis on girls’ schooling. The education gap between girls and boys has declined largely because of the impressive improvement in schooling for girls in sub-Saharan Africa. Although a large portion of this change occurred decades ago, growth continued in girls’ education in the 1980s and 1990s, despite significant economic setbacks. A thorough understanding of the reasons for disparate trends in boys’ and girls’ education over the past 30 years will require more research. Our data do not allow us to tease out the many possibilities, including rising returns to the education of girls (either market or nonmarket), the diffusion of global cultural values relating to the importance of girls’ schooling, and the effects of school reform. The schooling gap that remains most significant is the gap between the poorest and wealthiest households. Others have also posited the importance of household wealth in relation to schooling. Filmer and Pritchett (1999) provided documentation of the differential in educational attainment by household wealth status using data from many of the DHS available a few years ago. Even earlier, Knodel and Jones (1996), using school-

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The Changing Transitions to Adulthood in Developing Countries: Selected Studies ing data from Vietnam and Thailand, raised questions about the heavy emphasis on girls’ schooling in the international community given the much wider gaps in schooling by household wealth. This chapter offers a new comparison of the size of gender gaps and wealth gaps across most of the countries of sub-Saharan Africa using several widely accepted schooling indicators. With the gender gap closing in many cases at levels of educational attainment that fall far short of universal primary schooling, new strategies will need to be devised to reach the poorest parents and their children. REFERENCES Behrman, J.R., and Rosenzweig, M.R. (1994). Caveat emptor: Cross-country data on education and the labor force. Journal of Development Economics, 44(1), 147-171. Bruns, B., Mingat, A., and Rakotomalala, R. (2003) Achieving universal primary education by 2015: A chance for every child. Washington, DC: World Bank. Dakar Framework for Action. (2000). Education for all: Meeting our collective commitments. Text adopted by the World Education Forum, April 26-28, Dakar, Senegal. de Walque, D. (2002). How does the impact of an HIV/AIDS information campaign vary with educational attainment? Evidence from rural Uganda. (Population Research Center, Discussion Paper Series, No. 2002-16.) Chicago, IL: University of Chicago Press. Donors to African Education. (1994). A statistical profile of education in sub-Saharan Africa in the 1980s. Paris, France: Author, International Institute for Education Planning. Filmer, D., and Pritchett, L. (1999). The effect of household wealth on educational attainment: Evidence from 35 countries. Population and Development Review, 25(1), 85-120. Glynn, J.R., Carael, M., Buve, A., Anagonou, S., Zekeng, L., Kahindo, M., and Musonda, R. (2004). Does increased general schooling protect against HIV infection? A study in four African cities. Tropical Medicine and International Health, 9(1), 4-14. Hargreaves, J.R., and Glynn, J.R. (2002). Educational attainment and HIV-1 infection in developing countries: A systematic review. Tropical Medicine and International Health, 7(6), 489-498. Hodd, M. (1989). A survey of the African economies. In S. Moroney (Ed.), Handbooks to the modern world: Africa (pp. 787-809). New York: Oxford University Press. Kinyanjui, K. (1993). Enhancing women’s participation in the science-based curriculum: The case of Kenya. In J. Ker Conway and S.C. Bourque (Eds.), The politics of women’s education: Perspectives from Asia, Africa, and Latin America (pp. 133-148). Ann Arbor: University of Michigan Press. Knodel, J., and Jones, G.W. (1996). Post-Cairo population policy: Does promoting girls’ schooling miss the mark? Population and Development Review, 22(4), 683-702. Lloyd, C.B., Kaufman, C.E., and Hewett, P.C. (1999). The spread of primary schooling in sub-Saharan Africa: Implications for fertility change. (Policy Research Division Working Paper No. 127.) New York: Population Council. Lloyd, C.B., Kaufman, C.E., and Hewett, P.C. (2000). The spread of primary schooling in sub-Saharan Africa: Implications for fertility change. Population and Development Review, 26(3), 483-515. Lloyd, C.B., Mensch, B.S., and Clark, W.H. (2000). The effects of primary school quality on school dropout among Kenyan girls and boys. Comparative Education Review, 44(2), 113-147.

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