Ten-Year Impacts of Burkina Faso’s BRIGHT Program

I: INTRODUCTION MATHEMATICA POLICY RESEARCH
in 56 low- and middle-income countries found that the programs that improve attendance and
enrollment most consistently are those that reduce the cost of education by lowering fees or
reducing the costs of such complements to education as school uniforms (Murnane and
Ganimian 2014). The literature review conducted by Cuesta et al. (2015) found mixed results
regarding achievement, but found programs that expand resources such as textbooks and
flipcharts to be effective. This is consistent with the review of Murnane and Ganimian (2014),
who also found that these resources, as well as expanded amenities such as free daily meals, lead
to an increase in achievement. They found, however, that increased achievement was only seen
when these resources had an impact on the students’ daily experiences at school.
The evidence regarding the impacts of school quality on school enrollment and test scores
are less straightforward. Although the studies cited below are not strictly comparable because
they do not include a school construction component, they are relevant for this report because
they look broadly at education production. A literature review examining 79 studies published
between 1990 and 2010 (43 of which were deemed “high quality” in terms of the rigor of the
evaluation design used) investigated which specific school and teacher characteristics, if any,
appear to have strong positive impacts on learning and time in school (Glewwe et al. 2011). The
estimated impacts on time in school and learning of most school and teacher characteristics were
statistically insignificant, especially when limiting the evidence to “high quality” studies. The
few variables that were found to have significant effects on enrollment and student test scores
included availability of desks, teachers’ knowledge of the subjects they teach, and teacher
absence. These findings are further strengthened by another literature review of 77 randomized
experiments evaluating the effects of educational interventions on student learning which found
that the largest mean effect sizes could be seen in interventions that included teacher training,
contract or volunteer teachers, and instructional materials (McEwan 2015).
The 10-year BRIGHT evaluation also sought to assess the impact of education on child
labor and young adult outcomes. A literature review conducted to assess the impact of education
on child labor found that it is very difficult to define a straightforward relationship not only due
to a lack of programs targeting child labor as a primary outcome, but also because many factors
influence child labor and render results inconsistent and dependent on context (de Hoop and
Rosati 2013). This review did find that food for education programs (including take-home
rations) reduce child participation in economic activities and household chores and access to
preschools decreased child participation in economic activities other than household chores and
family care activities (de Hoop and Rosati 2013). Another study that evaluated the relationship
between child labor and distance from school in Tanzania found that although a one-kilometer
increase in distance to school is associated with a fall in attendance of approximately 0.4
percentage points, and child labor often prevents school attendance, children are frequently
attending school even while working for the same number of hours as those who do not attend
school (Kondylis and Manacorda 2012). Increased accessibility, therefore, does not necessarily
correlate with a decrease in child labor involvement.
Finally, studies indicate that increased enrollment is related to a variety of positive outcomes
for young adults, including an increase in the age at which girls marry, a decrease in the number
of children that families have, and a decrease in neonatal mortality. In a study assessing the
effect of school construction in Nepal from 1950 to 1960 on subsequent educational and health
outcomes, Shrestha (2014) found that one additional school per 1,000 square kilometers
14