Asadullah et al-2017-development_policy_review

AcceptedArticle Enrolling Girls without Learning:
Evidence from Public Schools in Afghanistan
M. Niaz Asadullah1
, Abdul Alim2
and M. Anowar Hossain
Abstract
While more girls are now attending school in Afghanistan than a decade ago, there is a lack of evidence
on how school attendance is helping their cognitive development. We use data from a large sample of
all-girls public school students to estimate for the first time the ‘learning profile’ for Afghanistan.
Students enrolled in grades 4 to 9 were assessed using the Early Grade Reading Assessment (EGRA) and
the Early Grade Mathematics Assessment (EGMA) test items. We find that higher grade progression
(particularly in grades 6–9) leads to almost no gain in numeracy (addition and subtraction) skills that
should have been achieved in early grades. Similar results follow from the analysis of student
performance in EGRA test, particularly in oral reading fluency (correct words read per minute) and oral
reading comprehension (number of correct answers out of 12). These findings warn that simply enrolling
girls in school without improving the relationship between grade completion and learning is unlikely to
transform the lives of women in Afghanistan.
Key words: Cognitive ability; gender development; school quality; Afghanistan.
1. Introduction
Investment in girls’ education is often singled out as the most potent strategy for social transformation
in low-income countries such as Afghanistan and Pakistan. Educating girls and women is considered the
key to dismantling the systemic oppression of women based on gender. Arguably, school provides girls
with tools that enable them to both succeed economically outside the domestic sphere, and also to
challenge the justifications for women’s subordination to men. Educated women are better able to
1
Dept. of Development Studies, Faculty of Economics, University of Malaya, Malaysia; Department of Economics,
University of Reading, UK; Centre on Skills, Knowledge and Organisational Performance (SKOPE), University of
Oxford, UK; IZA Institute of Labor Economics, Bonn, Germany; School of Education, Environment and
Development (SEED), University of Manchester, UK; BRAC International, Afghanistan. Corresponding author.
Email: m.niaz@um.edu.my
2
BRAC International, Afghanistan.
This article has been accepted for publication and undergone full peer review but has not been
through the copyediting, typesetting, pagination and proofreading process, which may lead to
differences between this version and the Version of Record. Please cite this article as
doi: 10.1111/dpr.12354
This article is protected by copyright. All rights reserved.

AcceptedArticleprovide for themselves and their families, contributing to the overall health of their communities and
the economic well-being and political stability of the country (Sen 1999). Greater access to schools is
therefore central to the process of women’s empowerment and establishing gender equality.
It is commonly assumed that schooling transforms the lives of women in countries like Afghanistan is by
improving cognitive skills and providing literacy. Studies on high-income countries confirm that extra
days of schooling improve learning outcomes (e.g. Carlsson et al. 2015). Most importantly, there is
growing evidence on the positive effects of cognitive attainment on outcomes in the labour market
(Currie and Thomas 2001; Chetty et al. 2011; Parinduri 2014) and other measures of well-being
(Grantham-McGregor et al. 2007). However, efforts to improve learning outcomes through demand-side
initiatives are complicated in Afghanistan by the ongoing conflict, violence against schoolgirls, and social
insecurity, which have also historically undermined mothers’ agency in Afghan society (Kissane 2012).3
Even in post-Taliban Afghanistan, schools have been physically attacked by conservative groups
opposing female education (The Economist 2016). Afghanistan remains one of the world’s most
challenging locations for adolescent girls and women – life expectancy is 51 years, and violence against
women is rising (Independent Human Rights Commission of Afghanistan 2013 (AIHRC)). Historically the
country has suffered various forms of gender inequality in socio-economic indicators. Public investment
in girls’ schooling has also been low. Households and communities in South Asia also impose constraints
on girls’ mobility and/or discriminate against girls with regard to their education. In rural India, for
instance, evidence suggests that boys receive more parental input than girls (e.g. childcare time, length
of breastfeeding), which translates into a gender gap in health status (Barcellos et al. 2014). Therefore,
international aid agencies rightly emphasize providing greater educational opportunities for girls, such
as building high-quality single-sex public schools. It is assumed that such initiatives can both empower
girls, and also contribute to the acquisition of critical human capital.
Recent research, however, questions the single-focus pursuit of schooling as a policy through which
women’s status can be improved. In rural India, for instance, few children enrolled in primary school
children are at the relevant grade level in terms of learning; most are two or more grades behind
(Bhattacharjea et al. 2013). In general, there is growing evidence on differences in cognitive
3
Evidence suggests that girls’ schooling suffers more in conflict-affected areas. For India, for instance, Roy and
Singh (2016) find that a doubling of average murders in a district-year leads to a 13% drop in girls’ enrolment rate.

AcceptedArticledevelopment by socioeconomic status (World Bank 2018), which often generates pre-school learnings
gaps (Schady et al. 2015; World Bank 2015). Evidence from the Young Lives project in Ethiopia, Peru,
Vietnam, and Andhra Pradesh, India indicates that the richest quartile makes more progress in
arithmetic than the poorest quartile between ages of five and eight. By the age of eight, a sizable gap
opens up also in reading skills between richer and poorer children (Rolleston et al. 2014). Skill formation
is a dynamic process – disparities in early grades are compounded through the schooling cycle, meaning
that sources of low learning must be tackled during early school years (Carneiro and Heckman 2003).
Learning inequalities are often visible before children start school, and persist during their school years
(Cunha et al. 2010). At the same time, recent evidence in South Asia also indicates a reversal of early
childhood learning advantage among upper-caste girls compared to boys after five years of age (Lopez
Boo and Canon, 2014). Therefore, in addition to examining pre-school gaps in learning, it is important to
understand how the level of learning evolves from early primary to secondary grades.
There is a growing academic interest in tracking progress in learning in and outside the school setting
(e.g. Das 2013; Muralidharan and Zieleniak 2013; Singh 2014). Ideally, one should use longitudinal data
and track a cohort of students over a school cycle to estimate the schooling-learning gradient.4
In the
absence of such data, one approach is to compare cross-sectional data on learning outcomes across
grades keeping the test standard constant. Greaney et al. (1998) and Asadullah and Chaudhury (2015)
follow this approach for Bangladesh. More recently, Alcott and Pauline (2017) use large-scale, nationally
representative household survey data sets to estimate grade-learning gradients for rural children in
India.
The general conclusion of studies on the level of learning across grades in developing countries is that
children in high grades do not acquire even the rudimentary knowledge that is expected after attending
one or two years of primary school. In other words, the school-enrolled children are several years
behind in terms of grade-specific learning outcomes. For instance, for East Africa, Jones and Schipper
(2012) find that the learning of children from poorer households is at least one year behind that of
children of the same age from wealthier households. For South Africa, Spaull and Kotze (2015) report
4
For a similar approach, see Muralidharan and Zieleniak (2013) who find that only 2.4% of grade 1 students achieve
the grade 1 standard in Andhra Pradesh, India. They document flat grade-learning profiles based on a rigorous multi-
year sample. According to the authors, only 60% of these students have achieved the grade 1 level by grade 5.
Moreover, only 8% of the students achieve the grade 5 level by grade 5.

AcceptedArticlesimilar evidence – by grade 3, the poorest 60% are three grade levels behind the wealthiest quintile,
which increases to four grade levels by grade 9. While the level of learning rises across grades, a sizeable
number of children fail to perform grade 3 tasks in grade 5.
South Asia is not only home to most of the world’s out-of-school children, but there is also significant
concern that those in school are not learning much (Dundar et al. 2014; UNESCO 2014). This concern is
consistent with growing micro evidence that low achievement is a problem throughout the schooling
cycle, so that school completion does not translate into learning outcomes (Pritchett 2013). In other
words, children’s learning in South Asia may be suffering irrespective of how far they progress through
the education system, meaning that the education system takes much longer to impart minimum
competency skills than in other regions. This is a serious problem for countries like Pakistan and
Afghanistan, where children from specific social groups, such as girls, drop out early. Available evidence
based on primary data suggests a very low level of learning in school in both countries. In Pakistan, for
instance, only 31% of the primary school children at the end of the third grade could correctly form a
sentence in the vernacular (Urdu) with the word ‘school’ (Das et al. 2012).5
In Afghanistan, more than
one-third of students in grade 6 cannot answer questions that require them to add two-digit numbers
(Lumley et al. 2013).6
More recently, based on their comprehensive analysis of women’s reading ability
in a large sample of countries in Asia and Africa, Pritchett and Sandefur (2016) find that 40% percent
women would be illiterate even if all women completed at least six years of primary school.
Kaffenberger and Pritchett (2016) provide further evidence on the weak relationship between schooling
and learning using the Financial Inclusions Insights (FIIs) survey data on Bangladesh, India, Pakistan and
seven other developing countries (Ghana, Indonesia, Kenya, Nigeria, Rwanda, Tanzania, and Uganda).
In sum, education deficits in South Asian countries seem even larger once actual cognitive skills acquired
for a given level of education are taken into account. Clear evidence on the low level of learning across
grades has been documented for Bangladesh (Asadullah and Chaudhury 2015) and more evidence on
‘flat learning profile’ – the weak empirical relationship between years of schooling completed and
5
Based on an additional school-based sample, Das et al. (2012) also report similar evidence of low achievement for
the state of Uttar Pradesh in India.
6
Lumley et al. (2013) also note the opposite situation in among Class 6 students in neighbouring countries. Based
on findings from TIMSS, a major international study on Class 4 students, the authors point out that Class 4 students
in Azerbaijan, Iran and Kazakhstan are performing at a similar or higher level compared to Class 6 students in
Afghanistan.

AcceptedArticlereading ability– is emerging for developing countries (e.g. Pritchett and Sandefur 2016), but is lacking for
Afghanistan.7
This paper, therefore, presents new evidence on the low level of cognitive skills among schooled
children as well as the shallow learning profile in Afghanistan. We use data from the baseline survey of
Girls’ Education Challenge (GEC) project, which aimed to improve the quality of girls’ single-sex public
schools in Afghanistan. Our analysis shows that public schools in Afghanistan are failing to ensure
minimal learning among girls in a country where only a small proportion of girls attend school. The
grade-learning profile is flat: moving a girl from grade 4 to grade 9 does not lead to significant gains in
learning even in rudimentary numeracy and/or language skills. In presenting these findings, our paper
makes a significant contribution to the larger literature on the low level of student learning across South
Asia. According to the Global Monitoring Report of UNESCO and the World Bank, there is an ongoing
learning crisis particularly affecting developing countries, where millions of children are failing to attain
their cognitive potential (UNESCO 2014; World Bank 2018). Available evidence suggests that the crisis is
most severe in South Asia. Not only, as mentioned above, does the region have the largest number of
out-of-school children, but it also does worse in ensuring minimum learning outcomes by those who
complete primary school. The evidence presented here confirms that Afghanistan is experiencing a
similar learning crisis.
Given the current quality of public schools, increasing girls’ school enrolment is unlikely to improve
female literacy and improve women’s socioeconomic status. Most importantly, given our evidence,
public investment to encourage girls to attend school in Afghanistan is unlikely to improve the cognitive
attainment of the next generation of mothers. Without addressing the question of school quality, better
educated mothers will not achieve higher status at home and in the community. In that sense, our
findings have implications for the impact of schooling on reducing poverty and inequality in Afghanistan,
and more generally in South Asia.
7
For recent reviews of the literature on what works in improving girls’ education in developing countries, see
Unterhalter et al. (2014).

AcceptedArticleThe rest of the paper is organized as follows. Section 2 explains the study context and presents some
basic facts about the education system in Afghanistan. Section 3 describes the data used. Section 4
presents the results, and conclusions and policy implications are discussed in section 5.
2. Study Background: Girls’ education in Afghanistan
The education system in Afghanistan comprises general stream schools, Islamic schools, TVET, teacher
training centres (TTC), literacy schools, and community-based education. This paper focuses on girls
enrolled in general schools since in 2016 they accounted for 94% of all school children. Table 1 describes
the size, structure, and composition of primary and secondary education in Afghanistan. There are
15,709 primary and secondary schools in total, most of which are government schools.8
Primary schools
offer a six-year cycle for children aged between 7 and 12 years. Boys and girls either attend single-sex
schools or attend in separate shifts in mixed schools; girls account for 23% of all secondary school
students compared to 12% in primary education. The pupil–teacher ratio is higher in primary schools,
and three out of ten teachers are women. In 2016, 8.7 million children were enrolled in the general
stream, of which 38% were girls.
Table 1: Size, structure, and composition of primary and secondary education in Afghanistan
Primary education
Grades 1-6
% of female teachers 34.55
Pupil–teacher ratio 44.33
Total number of schools 6546
Boys-only school 33%
Girls-only school 12%
Mixed school 55%
Secondary education
Grades 7-12
% of female teachers 33.25
Pupil–teacher ratio 37.72
Total number of schools 9163
Boys-only school 35.4%
Girls-only school 19.3%
8
There are 1,051 private schools in the general stream.

AcceptedArticle Mixed school 45.3%
Notes: (a) Data on female teachers and PTR from WDI and for 2015 and corresponds to all types of
school. (b) Data on the total number of schools is from the EMIS 2016 database and corresponds to
general education stream only. (c) Mixed schools operate in several shifts where each shift is either for
boys or girls only – not organized in the same class. (d) PTR for lower secondary (grades 7–9) is 43.90.
Afghanistan has seen an increase in the gross enrolment rates (GER) in primary and secondary education
over time (see Figure 1). Between 1993 and 2015, secondary school GER increased nearly five-fold. The
primary school GER today is more than 100%. Female enrolment also increased during this period,
although progress towards gender parity has been slow, particularly during the 1990s. Most girls’
schools were closed during the Taliban era (1996–2001) so that gross enrolment fell from 32% to just
6.4% (Jackson 2011).9
In the post-Taliban years, schemes such as the Back to School campaign
contributed to the sharp rise in female enrolment since 2000. The total number of schools also
increased from around 3,500 in 2001 to 14,600 in 2013. The average primary school completion rate
increased from 47% in 2009 to 52% in 2013 (Ministry of Education), even though many all-girls’ schools
were closed or burned down by the Taliban and its allies between 2007 and 2009 (Kissane 2012). By
2015, the ratio of female to male enrolment in primary and secondary school was 69: 56.
9
The Asian Development Bank (ADB) estimated in 2001 that the GER in primary education was 38% for boys and
only 3% for girls.

AcceptedArticleFigure 1: Trends in school enrolment and gender parity in enrolment in Afghanistan, 1993–2015
Source: Authors’ calculation based on the World Bank’s World Development Indicators (WDI) data base
(accessed 8 October 2017). Data for 1996 and 2002 were unavailable for all four indicators and hence
these years were excluded.
Figure 2: Total number of student enrolment and female share in enrolment (%) across grades in
Afghanistan

AcceptedArticle
Source: Authors’ calculation based on 2016 EMIS data.
In general, the enrolment rate for both sexes drops between primary and secondary level. A similar
pattern is noticeable in administrative data on enrolment across grades (Figure 2). The number of
students falls significantly after grade 4, along with the share of girls in the total enrolled population. A
sharp fall is also visible at the end of the primary schooling cycle (grade 6) when the percentage fall in
female enrolment is the largest. Girl’s school enrolment drops from 39% in grade 1 to 35% in grade 9
(i.e. the end of the lower secondary cycle).
The challenges for girls to attend school and gender disparities in education are particularly acute in
rural areas. In terms of provision, educational institutions are scarce in rural areas. For many families,
schools are inaccessible and even when they exist, children may have to walk as much as 10 km to
attend (Al-Qusdi 2003; Kristiansena and Pratiknob 2006; Adele 2008). Many parents in Afghanistan
prefer female teachers and single-sex classrooms for their adolescent daughters (Karlsson and Mansory
2007). Unsurprisingly, according to the Government of Afghanistan, the shortage of all-girls’ schools,
qualified female teachers, and inadequate facilities such as toilets, drinking water, boundary walls and

AcceptedArticledesks negatively affect girls’ participation and completion rate (Ministry of Education 2014).10
The cost
for girls to travel long distances is another contributory factor because girls face unique risks both to
their safety and chastity (Lloyd et al. 2005; Sutton 1998). Also, deficits in the educational infrastructure
such as the lack of separate sanitation facilities, female teachers, and sex-segregated classrooms are
considered to be a greater deterrence to girls’ enrolment than to boys’ (Al-Qudsi 2003; Kristiansena and
Pratiknob 2006; Adele 2008). Burde and Linden (2010) similarly demonstrate that many parents are
reluctant to send their children, especially their daughters, to remote government schools more because
of the security situation than because of ideology. Notable demand-side factors include household
poverty and child marriage (Ministry of Education 2014). Keeping girls in school beyond primary
education clashes with the custom of early marriage. Qualitative evidence also suggests a link between
attitudes towards girls’ secondary schooling and households’ socioeconomic status (Karlsson and
Mansory 2007).
Leaving aside the issue of low school participation and enrolment, the quality of education remains a
significant concern. According to one nationwide study, only 43% of a sample of children in grade 3
could read with comprehension (Mansory 2013). Another study using a curriculum-based test for a small
sample of students in grades 3 and 6 found a very low level of average achievement (Mansory 2010) –
52% and 53% respectively. Interestingly, this study does not report a large gender gap. Evidence on pre-
primary cognitive skills in Afghanistan does not suggest any significant gender difference (Pisani and
O’Grady, 2015), but other assessments confirm a sizable gender gap. According to the National Risk and
Vulnerability Assessment (NRVA), literacy skills of girls aged 12 to 16 is 37% and 62% of boys (Central
Statistics Organization 2014).
The reasons for poor learning are not fully understood. According to government education statistics,
most teachers lack the requisite qualifications and subject-specific training. Children also lack access to
textbooks (Ministry of Education 2014). Student–teacher contact hours are short in many schools,
particularly those with large number of students in several shifts, so that some students receive as little
as two hours of schooling per day. Schools are also under-funded. Most not do not have usable
buildings: 70% have no surrounding walls, 30% no drinking water, 60% no sanitation facilities, and 88%
10
In 21.9% of 364 districts, there are no female teachers. In most districts, particularly for secondary grades, there
are no qualified female teachers. This is believed to significantly contribute to girls’ dropout in the post-primary
cycle (Ministry of Education 2014).

AcceptedArticleno electricity (Ministry of Education 2014). In contrast, the role of demand-side factors is less
researched. One study on early childhood development among children between the ages of three and
six finds a strong influence of family background such as parental education and home environment
(Pisani and O’Grady, 2015).
3. Data and sample description
Data used in this study come from the baseline survey of the Girls’ Education Challenge (GEC) project.
The project is managed by BRAC, an international NGO that has been working in Afghanistan since 2002.
BRAC has various schemes including interventions that aim to improve children’s learning outcomes in
general stream government schools. The GEC’s primary goal is to ensure equitable access to quality
education for boys and girls in ten provinces of Afghanistan. Other objectives are to increase girls’
retention, and to improve the quality of education, especially in underserved areas. Moreover, under
this project, the mentoring support and stipend programme for girls (who had dropped out for financial
reasons) are being brought back to school and subject-based training is provided to the teachers (in
physics, English, mathematics, chemistry, and biology) in 200 government schools. The programme
areas are Kabul, Kapisa, Parwan, Baghlan, Balk, Samangan, Kunduz, Jawjzan, Herat, and Nangarhar.
The GEC baseline survey was administered in government schools in 2014. Based on a pre-baseline
survey of the schools, the project implementation team identified 250 eligible schools as the sample
frame. The survey was conducted in 75 schools (see Appendix 1) of which 40 were mixed schools. We
used multi-stage clustered sampling to select sample girls. Clusters were stratified across the district and
provinces. Although ten subjects per cluster were required for the statistical power 0.8 and other
relevant specifications, it was increased to 12 so that an equal number of subjects could be randomly
selected from the target grades 4, 6 and 8 in each cluster. Similarly, for to assess learning outcomes, 100
students from grades 5, 7 and 9 were selected. To avoid bias, class enrolment lists were used to select
students randomly. Thus, the total sample in the baseline survey comprised 1,182 girls in 75 schools. In
each school, some 15 to 16 interviews were conducted with girls.
Since we are interested in evaluating changes in learning outcomes across schooling cycles (from
primary to secondary), the students were assessed against the same instrument and based on test items

AcceptedArticlethat captured competency in lower-order cognitive skills. To this end, we implemented the Early Grade
Reading Assessment (EGRA) and Early Grade Mathematics Assessment (EGMA) test to the 1,182 girls
from 96 government schools. EGRA included letter-sound identification, invented word reading, oral
passage reading, and reading comprehension. EGMA included number identification, quantity
discrimination, missing number, addition, and subtraction and a written exercise. These are also called
subtasks of EGRA (four) and EGMA (six). Most importantly, EGRA is designed to measure foundational
literacy skills.11
Also, we administered one oral numeracy and one written numeracy test, both based on
four test items.12
Since EGRA, EGMA and the two basic numeracy tests assess students in primary school
equivalent competencies, any difference in learning across primary and secondary grades can be
attributed, at least partially, to the time spent in school.
The selection of schools was designed to reflect province ratios in the programme. The total number of
schools in a province was used to calculate the number to be selected (see Appendix Table 1). In light of
the government’s EMIS data for 2013, our study sample provinces vary considerably regarding the
presence of female school teachers. Women comprise at least half of the school teachers in Balkh and
Herat provinces, but less than 20% in Parwan, Nangarhar and Kapisa provinces. Women’s share in the
total number of teachers in Jawzjan, Kabul Province, Samangan, Kunduz, and Baghlan is 45%, 33%, 32%,
29% and 27% respectively. However, the sample lacks representation of provinces with a very small
proportion of women teachers.13
In general, the female share is very high in urban areas – 75% of the
school teachers in Kabul city are women, but the southern provinces and Pashtun-dominated parts of
Afghanistan (Kandahar, Helmand, Zabul, Paktia and Nimroz) have a more conservative culture and there
are fewer women teachers.
4. Main results
Table 2 reports the distribution of test scores by grade among girls in the sample. Irrespective of
whether we look at EGRA, EGMA, numeracy (with or without literacy), the improvements in test scores
are not large as we move from girls enrolled in grade 4 to those in grade 9. In the case of EGRA, the
11
For further details on the conceptual framework that underpins EGRA assessment, see Dubeck and Gove (2015).
12
The test items were originally developed by Greaney et al. (1998), and later adopted by Asadullah and Chaudhury
(2015), to measure basic competencies in rural Bangladesh.
13
There are nine provinces where female share is less than 10%. In Paktika, Khost, Kunar and Laghman women
account for as little as 1%, 3%, 5% and 7% of all teachers.

AcceptedArticleoverall level of learning is very low. On average, a student could correctly answer only 53% and 63% of
questions in the EGRA and EGMA tests. When exclusively focusing on grade 9 children, the percentage
of correct answers was 61% and 68% respectively. This implies that percentage gains across grades are
very small. Moving a girl from grade 4 to grade 9 would on average increase her EGRA (EMGA) test
scores by approximately 3 (2) percentage points.
Table 2: Learning outcomes by grade and test types
Grade enrolled Test Outcomes
EGRA EGMA
Numeracy w/o
literacy
Numeracy with
literacy
4 43.19 55.34 32.73 22.86
5 52.44 63.65 40.18 41.07
6 59.31 67.12 52.13 43.62
7 58.92 68.07 52.23 39.49
8 61.23 69.84 61.82 50.00
9 60.95 67.84 71.26 52.10
Total 53.72 63.56 48.31 37.31
The ratio of test scores in grades 4
and 9 1.41 1.22 2.17 2.27
% gain on average per grade
completed 2.96 2.08 6.42 4.87
Note: Data are from the baseline survey of Girls’ Education Challenge (GEC) project.
Table 2 also reports test outcomes relating to very rudimentary arithmetic questions that we fielded in
Bangladesh as part of another study. When exclusively focusing on grade 9 children, the percentage of
correct answers was 32% and 48% respectively. This implies that percentage gains across grades are
very small – there is no notable jump in the grade-learning relationship at five years of primary
schooling. Moving a girl from grade 4 to grade 9 would on average increase numeracy (with literacy) test
scores by approximately 6 (5) percentage points. Slightly higher gains with respect to EGRA/EGMA
reflects a low threshold of difficulty.14
Nonetheless, these numbers are still very low by regional
standards – in rural Bangladesh, one year of schooling on average raises numeracy scores by 6.3
14
For the distribution of these test outcomes among school children in rural Bangladesh, see Asadullah and
Chaudhury (2015).

AcceptedArticlepercentage points per year (when averaged over the five years; the figure is lower, 3.6% in the case of
oral maths).
Overall, the learning profile is very flat – children who just complete primary school (grade 5) are only
12% more likely to be competent in an oral assessment of arithmetic than those with no schooling at all,
and this rises to only 20% in a written assessment. So, getting children into school does not seem to
make a significant difference to their performance.
Given the patterns in Table 2, we formally test whether years spent in school result in basic mathematics
competency by estimating the schooling-learning profile. Table 3 presents OLS and fixed effects
estimates of the determinants of girls’ maths, reading and numeracy performance in sample
government schools. Once again, grade-level analysis shows clear learning gains for an additional year of
schooling up to grade 9. This is because a large number of children, despite being in higher grades, still
fail the test.
We find that each year spent in school is indeed positively correlated with the test outcome. However, it
takes children well beyond primary schooling to learn basic numeracy concepts that should have been
mastered in primary school: the relationship between schooling and primary-level mathematics
competency is statistically significant above and beyond primary school completion. Moreover, the
pattern of increase in the probability of passing the primary standard tests for each year of schooling is
linear up to grade 8. The estimated schooling-learning profile is not steep, suggesting limited learning
gains for each year spent in school. This finding confirms that education in countries such as Afghanistan
is inefficient and lends support to the literature on the superiority of cognitive skills rather than school
completion as a proxy measure of human capital (e.g. see Pritchett 2001; Filmer et al. 2006; Pritchett
2004; Hanushek and Woessmann 2015).

cceptedArticleTable 3: OLS and fixed effects estimates of the determinants of mathematics, reading and numeracy performance of girls in Afghanistan
VARIABLES
EGRA EGMA Numeracy Numeracy
with literacy
with literacy
with literacy
Age 8.086** -0.131 -10.99 -0.122 7.488** 0.0116 -8.350 2.754 10.23** 1.158 -10.83 -3.621
(2.556) (2.030) (8.268) (8.075) (2.597) (2.094) (8.711) (8.560) (2.880) (2.291) (9.655) (9.563)
Age 2 -0.266** 0.0349 0.557+ 0.0412 -0.238* 0.0425 0.464 0.00832 -0.337** -0.00480 0.599 0.194
(0.0968) (0.0769) (0.313) (0.306) (0.0989) (0.0797) (0.332) (0.326) (0.110) (0.0875) (0.369) (0.365)
Grade 5 7.535** 8.502** 9.153+ 17.93** 7.697** 9.320** 6.492 13.07* 6.365** 9.041** 9.177 16.17**
(1.692) (1.344) (5.474) (5.346) (1.649) (1.329) (5.531) (5.435) (1.883) (1.498) (6.313) (6.253)
Grade 6 12.43** 10.70** 17.33** 20.32** 11.46** 9.714** 15.40* 14.39* 11.75** 10.71** 19.19** 21.43**
(1.891) (1.501) (6.116) (5.973) (1.834) (1.479) (6.152) (6.045) (2.098) (1.669) (7.034) (6.967)
Grade 7 10.95** 10.74** 13.51** 16.13** 9.736** 9.369** 13.58* 9.272+ 11.53** 10.90** 13.74* 15.37*
(1.558) (1.237) (5.040) (4.923) (1.578) (1.272) (5.292) (5.200) (1.854) (1.474) (6.214) (6.155)
Grade 8 13.85** 12.07** 18.04** 24.53** 11.48** 10.37** 13.68+ 17.14* 10.33** 11.83** 4.731 24.94**
(2.074) (1.647) (6.709) (6.552) (2.082) (1.678) (6.982) (6.861) (2.455) (1.953) (8.232) (8.153)
Grade 9 15.11** 11.65** 22.60** 24.55** 13.89** 10.57** 17.64* 14.08* 15.39** 12.56** 18.48* 26.45**
(1.984) (1.576) (6.419) (6.269) (2.047) (1.650) (6.864) (6.745) (2.313) (1.840) (7.755) (7.681)
Language at home dari 1.843 3.058** 2.873 -2.403 -0.151 0.774 2.578 -5.596 -2.027 -0.915 2.737 -6.689
(1.343) (1.067) (4.345) (4.244) (1.496) (1.206) (5.016) (4.929) (1.771) (1.408) (5.936) (5.880)
Absent from school -0.591 -1.462 -3.627 0.380 -0.731 -1.531 -1.861 -1.380 -0.251 -0.527 -0.0914 0.776
(1.705) (1.354) (5.516) (5.387) (1.671) (1.347) (5.604) (5.507) (1.879) (1.494) (6.298) (6.238)
Community support for girls’ schooling -0.605 -4.678** -7.781 2.925 -2.545 -5.086** -11.20+ -5.616 -2.447 -5.393** 3.131 -1.582
(1.919) (1.524) (6.208) (6.063) (1.963) (1.582) (6.582) (6.468) (2.563) (2.039) (8.593) (8.511)
Constant -7.777 50.09** 58.17 27.63 3.751 57.80** 38.07 27.43 -9.217 49.17** 17.96 99.40
(16.36) (12.99) (52.93) (51.70) (17.15) (13.83) (57.53) (56.53) (20.30) (16.15) (68.07) (67.42)
Observations 1,120 1,120 1,120 1,120 1,120 1,120 1,120 1,120 1,120 1,120 1,120 1,120
Adjusted R-squared 0.320 0.366 0.127 0.113 0.412 0.435 0.188 0.165 0.409 0.446 0.184 0.147
F-test: joint significance of grade dummies 15.66 19.84 2.976 4.821 12.84 16.82 1.907 2.171 11.41 15.50 2.449 3.484
Prob > F 0 0 0.01 0.00 0 0 0.09 0.05 0.00 0 0.03 0.00
Province fixed effects Yes Yes Yes Yes No No No No No No No No
School fixed effects No No No No Yes Yes Yes Yes No No No No
Village fixed effects No No No No No No No No Yes Yes Yes Yes

cceptedArticleNotes: (a) ++
indicates dummy variables; (b) base category for schooling dummies is grade 4; (c) + significant at 10%; * significant at 5%; **
significant at 1%. (d) Each regression controls for village dummies.

AcceptedArticleFigure 3 plots years of schooling completed on the x-axis against students’ predicted maths competency
on the y-axis. The slope of the schooling-learning relationship is close to zero in the first four years of
schooling in case of oral maths and increases slowly by grade 5 onwards. In the case of written maths,
the slope becomes steeper after grade 5. But again the overall schooling-learning profile is far from
being S-shaped. We also estimated a regression, treating grade 6 completion as the structural
breakpoint, but our result does not show a significant break at grade 6.

cceptedArticle Figure 3: Grade-learning profile for Afghanistan
(based on raw probabilities)
Figure 6: Grade-learning profile controlling for community
fixed effects
Figure 5: Grade-learning profile controlling for
school fixed effects
Figure 4: Grade-learning profile (based on estimated
probabilities; controlling for differences in language &
province fixed effects

cceptedArticle

AcceptedArticleOur finding that girls perform less satisfactorily in maths is consistent with the literature that reports
girls to be weaker in mathematics but outperforming boys in language skills. The fact that we find the
learning profile to be flat irrespective of test subjects highlights the deep learning crisis in the country’s
public education system. It is particularly so given the rudimentary nature of our tests and the fact that
we also hold differences in some student background factors constant.
It is possible that there may be important non-schooling explanations for why girls underperform in
Afghanistan. Besides the lack of parental support and capacity, cultural factors are considered important
reasons for girls’ underperformance (Fatima 2013). Limited experience of market transactions can limit
the scope for attaining basic numeracy in a non-school setting. However, we also find a low level of
written numeracy skills, which means that the non-schooling channel does not fully explain girls’ low
level of numeracy. Second, both grade completion and school enrolment fall sharply in South Asia from
the younger to older cohort of school-age children. This is also true for girls in Afghanistan (see Figure 2).
This implies that the empirical schooling-learning profiles documented in Figures 3–6 are not capturing
causal schooling-learning profiles if girls with higher cognitive skills drop out from a higher grade. But
this would also imply that correcting for the endogenous nature of the relationship between schooling
and learning would further flatten the learning profile if girls who drop out prematurely are drawn from
the bottom part of the cognitive distribution. Moreover, in the context of Afghanistan, safety concerns
and girls’ young age at first marriage and early pregnancy, together with traditional seclusion practices,
restrict adolescent girls from conservative and low-income families from continuing school in higher
grades (Karlsson and Mansory 2007; Ministry of Education 2014). This would imply that girls retained in
higher grades come from families with a socioeconomic status that favours learning. Improved control
for such factors or selection based on such family characteristics would only lower the slope of the
learning profile corresponding to higher grades.
Third, the cross-sectional association between school completion and student achievement may suffer
from sample selection biases in other ways. To avoid this, we used survey data on the performance of
secondary school-age children in elementary tests that were designed to assess basic competence in
primary standard mathematics. However, there is still the possibility of a selection bias since we only
use the test scores of enrolled children to examine whether schooling leads to learning. Our approach
ignores the fact that some learning takes place in an informal setting at home and/or through work

AcceptedArticleexperience irrespective of schooling.15
Since our assessment of cognitive outcomes ignores learning
among unschooled children, we are likely to overstate the relationship between schooling and learning.
However, the implication of this limitation is less serious as the estimated learning profile we present for
Afghanistan is already very flat. Besides, the Bangladesh study (Asadullah and Chaudhury 2015) that
corrected for this bias did not lead to a larger estimated slope of the learning profile.
In sum, policy initiatives in South Asia have to look beyond measures that only aim to raise school
enrolment. Our analysis once again confirms that enrolment does not imply learning. This finding adds
to the recent evidence on South Asia and other developing countries on the ineffectiveness of
government schools in teaching numeracy and literacy and a shallow gradient in learning with respect to
school enrolment and grade (Asadullah, Chaudhury and Dar 2007; Asadullah and Chaudhury 2013;
Alcott and Rose 2015; Asadullah 2016; Dundar et al. 2014; Bold, Filmer, Martin, Molina, Stacy,
Rockmore, Svensson, and Wane, 2017; World Bank 2018). The findings are also consistent with Pritchett
and Sandefur (2016) who use Demographic and Health Surveys (DHS) data on reading ability among
adult women in 51 developing countries and conclude that universal female literacy is unlikely to be
achieved through girls’ universal completion of primary school.
5. Conclusion and policy implications
There are many well-documented social and personal benefits to educating women and girls in
developing countries. Despite frequent calls for universal primary education (UPE) and an end to gender
disparities in education, few developing countries have reached either goal. Too few children go to
school, and girls account for the majority of those who do not go. In this paper, we have highlighted the
additional challenge that arise from the failure to impart minimal learning to the small proportion of
girls who attend school in Afghanistan, where girls’ education has suffered historical neglect.
We find that among girls enrolled in grades 4 to 9, grade progression (particularly moving to secondary
grades) leads to almost no gain in basic numeracy (addition and subtraction) skills that should have been
15
For example, Asadullah and Chaudhury (2015) find that children with no schooling achieved 22.9% correct scores
on the written numeracy test. If Afghan girls never enrolled in school also have positive scores in numeracy, their
exclusion would artificially increase the overall slope of the learning profile by overstating returns to grade 4
schooling in our sample.

AcceptedArticleachieved in early primary school. Similar results follow from the analysis of student performance in the
EGRA test, particularly in oral reading fluency (correct words read per minute) and oral reading
comprehension (number of correct answers out of 12). These findings imply that Afghanistan faces a
huge challenge in educating girls. Some 3.5 million girls are not currently in the formal education
system. These girls need to be enrolled in school, although in itself this may not bring about the desired
change in the lives of future mothers and women’s social status given the weak relationship between
grade completion and learning – the quality of teaching and learning should receive just as much priority
as increasing enrolment and retention. Our findings also add to the growing international evidence on
the ineffectiveness of widening the education sector based on input-focused growth (Hanushek et al.
2008; Hanushek and Woessmann 2015). The results also lend support to the view that achieving the
Sustainable Development Goal (SDG) target of ensuring learning for all in primary and basic education
will require both achievement of universal schooling and rapid improvements in the learning profile in
developing countries (Pritchett and Sandefur 2016).
In a poor country like Afghanistan, children face challenging circumstances at birth. This, combined with
income inequalities, risks creating further inequalities that mean that learning outcomes diverge with
age and/or time spent in school. Girls’ flat learning profile in Afghanistan could also reflect families’ low
investment in children’s early life. Emerging evidence shows a significant gap in cognitive outcomes
between pre-school children depending on the level of education of their family, and these differences
tend to widen with age (World Bank 2015; Rubio-Codina et al. 2014). Future research should therefore
also look into cognitive development in pre-school years and also examine whether girls’ low level of
learning is a matter of low parental investment or largely reflects gender-based discrimination in the
allocation of household expenditure.
At the same time, supply-side reforms should be prioritized. The availability of qualified female teachers
may also be an important constraint in a country where there are so few educated women – 85% of
women in Afghanistan have no formal education. Training and governance-related issues could
undermine learning. There are cases of non-existent schools and ‘ghost’ students (The Economist 2016).
In neighbouring Pakistan, teacher absenteeism was in the order of 10% at primary level (Reimers 1993).
Moreover, the pace and rigidity of the curriculum may also be important contributory factors for the low
level of learning in countries like Afghanistan (Pritchett and Beatty 2015).

AcceptedArticleCurrent reform initiatives already include interventions to enhance student achievement. Notable
examples include the BRAC Afghanistan community-based education programme (in operation since
2002) and the PACE-A programme under which village-based community schools have been constructed
in rural north-western Afghanistan. Early evaluation of the PACE-A scheme shows that the intervention
succeeded in raising test scores of boys and girls (Burde and Linden 2012), but the programme’s impact
was achieved by reducing the cost and time of travel to attend traditional public schools, of which there
are few in rural communities. Reforms to improve the quality of public schools in the country are less
understood. Therefore, follow-up research into the origin of the flat grade-learning profile in
Afghanistan’s public schools may be critical to raising girls’ level of learning in the country.
first submitted November 2016
final draft accepted October 2017
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AcceptedArticle Appendix Table 1: Sample size for EGRA/EGMA tests
Province No. of
Intervention
Schools
% of all
schools in
program
No. of
schools
included
in
research
No. of EGRA/EGMA Interviews
G4 G5 G6 G7 G8 G9
Kabul 12 12.5 9 45 16 10 44 13 15
Parwan 8 8.3 6 30 8 8 30 8 7
Kapisa 8 8.3 6 26 12 8 30 8 8
Baghlan 6 6.2 5 27 5 5 25 6 5
Kunduz 7 7.3 6 30 7 7 30 7 7
Samangan 7 7.3 6 37 11 5 11 11 21
Balkh 14 14.6 11 59 21 15 27 16 51
Jawzjan 9 9.4 7 34 8 9 22 13 26
Hirat 13 13.5 10 50 14 14 50 13 13
Nangarhar 12 12.5 9 47 10 13 45 15 14
TOTAL 96 - 75 385 112 94 314 110 167

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