Chapter 2. Progress towards the EFA goals - Unesco

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0 1 0 CHAPTER 2 2 Education for All Global Monitoring Report Box 2.5: Children count — but counting children in school is difficult Data on enrolment by age are often treated uncritically as an accurate record of how many primary school age children are actually in primary school. The information passes from schools to education ministries and then to the UNESCO Institute for Statistics (UIS), which compiles the international data used to compare countries, monitor progress and inform international meetings. But is the information accurate? Research by the UIS compares enrolment figures generated by governments with data reported in Demographic and Health Surveys of households in twenty-nine countries (Figure 2.9). The analysis found that, when compared with household survey data, school registers tend to count more children within the official primary school age range. Correcting that bias would have the effect of reducing the net enrolment ratio — by significant margins in some countries. In the United Republic of Tanzania, the discrepancy was equivalent to twenty-five percentage points. It was over ten percentage points in ten of the twenty-nine countries covered. For nine other countries the bias was in the other direction. The study found that the main factor behind the differences was not the over-reporting of student numbers, but the misreporting of age. Household surveys actually report a greater number of total students attending than administrative data when all students, regardless of their age, are counted. Age-specific reporting is the main source of discrepancy. Consider the case of Senegal — a country that illustrates the broader pattern (Figure 2.10). For the 5 to 11 age group, administrative data reports an enrolment ratio consistently higher than the attendance rate for the same age group recorded in household survey data. The discrepancy is very large. For age 8, the net enrolment ratio is reported to be 77%, compared with 58% for the net attendance rate. At about age 11, the reporting lines cross: at older ages, household survey data register higher levels of attendance than net enrolment would imply. The consistent pattern to emerge from the UIS study can be briefly summarized. If the information in household surveys is accurate, net attendance rates covering children in the official primary school age range are lower than reported through net enrolment ratios based on administrative data. This would imply that there are more over-age children in school, and more primary school age children out of school, than indicated by official data. Simple comparisons between administrative and household survey data do not, however, provide a solid foundation for such conclusions to be drawn. There are many possible factors behind the discrepancies. One is demography. If national population data over- or under-report the size of the primary school age population, net enrolment ratios drawn from administrative data will mirror the inaccuracy. Uncertainty over the denominator (population size) can be compounded by education reporting systems. Registers may not provide an accurate picture of the age of students, instead treating the class that children are in as a proxy for their age. In some cases institutional incentives may play a role: if the number of students in the appropriate grade for their age determines the allocation of grants or teachers, schools and local governments might have a tendency to inflate the school register. Household survey exercises have problems as well. Apart from standard sampling errors, the timing of surveys can have a bearing on the results: for example, the data might be affected by the agricultural calendar, drought or major external shocks. The reference period and phrasing of questions can also cause complications. Household surveys examined in the analysis presented here ask whether children attended school at some point during the school year, not whether they are in school for the entire school year. Surveys can also systematically miss parts of the population that are difficult to reach. All these considerations caution against drawing sweeping policy conclusions. The UIS emphasizes that its technical work comparing household survey and administrative data does not provide a basis for revising estimates of out-of-school children. What is clear is that important issues are at stake — and that more work is needed to clarify the real picture with respect The model explores the importance of gender, income and location in determining whether or not children are in school. These categories of disadvantage interact with each other and with wider factors – such as language, ethnicity and disability – to create multiple barriers to school entry and survival. Chapter 3 explores the wider factors and their interactions in detail. Young girls. Disparities between boys and girls are narrowing, but females still accounted for 54% of the global out-of-school population in 2007. Gender parity would cut the number of girls out of school by over 6 million. Gender disadvantage is most pronounced in the Arab States, Central Asia, and South and West Asia. In Pakistan, girls accounted for 60% of out-ofschool children in 2006. Children from poor households. Parental wealth strongly influences prospects of being out of school. Low average income in many of the countries with large out-of-school populations means that poverty extends far beyond the poorest 20%. However, as evidence from household surveys shows, the poorest face distinctive problems. In India, children 58
PROGRESS TOWARDS THE EFA GOALS Universal primary education Figure 2.9: Different stories — administrative and household measurement of children in school can differ greatly Differences between net enrolment ratio (administrative data) and net attendance rate (household surveys), selected countries, latest available year U. R. Tanzania Guinea Mozambique Benin Mali Ethiopia Uganda Malawi India Zambia Senegal Madagascar Peru Rwanda Liberia Burkina Faso Niger Pakistan Philippines Zimbabwe Swaziland Kenya Nigeria Ghana Cameroon D. R. Congo Namibia Lesotho Congo Rates are lower for household survey data Rates are higher for household survey data -30 -20 -10 0 10 20 30 40 % point difference between household survey and administrative data Sources: Bruneforth (2009a). to the core issue in universal primary education: namely, how many children are really out of school. There is strong evidence that administrative data routinely overestimate net enrolment by a considerable margin. In a separate review of the twenty-nine countries covered by the UIS study, this Report estimates that, if the household survey data are accurate: Figure 2.10: In Senegal, estimates of children in school by age vary with data sources Age-specific enrolment and attendance rates, Senegal, 2006 Children in school (%) 90 80 70 60 50 40 30 20 10 0 77% 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Source: Bruneforth (2009a). 58% the out-of-school population in these countries would be 66 million, rather than the 44 million reported in administrative data; the out-of-school population in India would be 16 million higher, more than twice the administrative data total; in sub-Saharan Africa, Ethiopia and the United Republic of Tanzania would each have more than 1.8 million additional children out of school, Mozambique around 600,000 and Uganda over 800,000. Source: Bruneforth (2009a). 51% 33% Age in years Household survey Administrative data from the poorest 20% were over three times more likely to be out of school than children from the richest 20% in 2005 (Bruneforth, 2009b). Rural children. Living in a rural area often puts children at greater risk of being out of school. In Burkina Faso, Cameroon, Ethiopia, Malawi, the Niger, Senegal and Zambia, household survey data suggest that rural children are more than twice as likely not to be in school (Bruneforth, 2009b). Many of those currently not in primary school will probably never enrol. On the basis of past evidence and the UIS model, an estimated 44% of out-ofschool children are unlikely to make the transition into school (Figure 2.11). These 31 million children face the most acute disadvantages in education. The problem is most pronounced in sub-Saharan Africa, where 59% of the out-of-school population is unlikely to enrol. In South and West Asia, by contrast, dropout is a more serious problem. More than 60% of the out-of-school population has dropped out, while one-third is unlikely ever to enter. Almost half of the much smaller out-ofschool population in the Arab States is unlikely to enter. In East Asia and the Pacific, the problem is 59
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