Chapter 2. Progress towards the EFA goals - Unesco

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CHAPTER 2
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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
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