offered scholarships have attained 0.6 more grades of completed schooling. Never- theless, we fi nd no evidence that scholarships had signifi cant effects on test scores,
employment, earnings, or the probability of getting married or having a child in ado- lescence. Because we focus on medium- term effects, our paper is closely related to a
recent paper that analyzes the medium- term effects of PROGRESA Behrman, Parker, and Todd 2011, and we discuss this in more detail in our conclusions.
The rest of the paper proceeds as follows. In Section II, we describe the CSP schol- arship program and the data. Section III discusses our identifi cation strategy. Section
IV presents our main results. We conclude in Section VI.
II. The Program and Data
3
A. Scholarships in Cambodia
Cambodia has a tradition of demand- side incentives that seek to raise school en- rollment and attendance at the secondary school level. There are several relatively
small- scale programs that distribute bicycles, uniforms, and school materials to chil- dren in order to lower the travel and other direct costs associated with schooling. In
addition, Cambodia has had a number of scholarship programs fi nanced by nongov- ernmental organizations NGOs, international donors, and the government.
The CSP scholarship program, which we analyze in this paper, works as follows. The government fi rst selected 100 lower secondary schools throughout the country from a
total of approximately 800 to participate in the program. These CSP- eligible schools were chosen because they served poor areas, as indicated by a poverty map, and because
there appeared to be high levels of school nonenrollment and dropout, as indicated by administrative data; schools covered by other scholarship programs were excluded.
Next, each primary “feeder” school was mapped to a CSP- eligible secondary school.
4
Finally, in every feeder school, all students in sixth grade, the last year of primary school, fi lled out an “application form” for the CSP scholarship program—regardless of
whether children or their parents had expressed an interest in attending secondary school. Application forms consisted of 26 questions that were easy for sixth graders to
answer and for other students and teachers to verify. In practice, the form elicited information on household size and composition; parental education; the characteristics
of the home; availability of a toilet, running water, and electricity; and ownership of a number of household durables. Forms were fi lled out in school on a single day. Stu-
dents and parents were not told beforehand of the questions on the forms nor were they ever told the scoring formula—both decisions designed to minimize the possibility
of strategic responses for example, by a student seeking to maximize her chances of receiving a scholarship. Head teachers in each school collected the completed forms
3. This section draws on Filmer and Schady 2009. 4. A primary school was designated a feeder school if it had sent graduates to a given secondary school in
recent years. In the rare cases where primary schools had sent students to more than one secondary school, the primary school was designated as a feeder to the secondary school where it had sent most students. In
principle, scholarships were not portable. To receive a scholarship, a student graduating from a given primary school had to attend the designated CSP school into which her primary school fed. In practice, if a student
moved to a secondary school within fi ve 5 kilometers of a program school, she could retain her scholarship. Given the low density of secondary schools in Cambodia at the time, this was a very rare occurrence.
and sent them to Phnom Penh, the capital. The median age of children when they completed the application survey was 14; the tenth percentile of the distribution was
12; and the 90
th
percentile 16. We worked closely with offi cials from the Ministry of Education in Cambodia to
design a process that assigned CSP scholarships on the basis of the information on the application forms. We hired an independent fi rm to digitize the information on the
application forms, and provided the weights used to aggregate responses on the form into a composite “dropout- risk score.”
5
Separately for each CSP school, applicants were then ranked by their dropout- risk score. As requested by the Ministry, in “large” CSP schools, with total enrollment
above 200, 50 students with the highest value of the score were then offered a scholar- ship for grades 7, 8, and 9; in “small” CSP schools, with total enrollment below 200
students, 30 students with the highest value of the score were offered scholarships. In total, just over 3,800 scholarships were offered.
6
The list of students offered scholarships was posted in each CSP school, as well as in the corresponding feeder schools. The program allowed for a complaints mecha-
nism if an applicant felt they had been wrongly denied a scholarship but there were virtually no revisions made as a result of this process. We closely monitored every step
in the process whereby application forms were fi lled out, dropout scores calculated, and schools given the list of scholarship recipients.
7
Children who were offered a scholarship were automatically eligible to receive it for grades 7, 8, and 9 unless they repeated a grade or dropped out of school, in which case
the scholarship was withdrawn. Two- thirds of the scholarships were given to girls; this is because girls were more likely than boys to drop out of school in Cambodia, which
was factored into the dropout- risk score. The value of the scholarship was equivalent to US 45.
8
This is roughly 2 percent of the total consumption of the average recipient
5. All of the variables in the scholarship application form had also been collected in previous nationally - representative household surveys. Using the most recently available Cambodia Socio- Economic Survey,
Demographic and Health Survey, and Cambodia Child Labor Survey, we ran regressions of grade 7 enroll- ment, conditional on grade 5 completion, in a sample of 12–17- year- olds, on the variables in the application
form. We used the coeffi cients from this regression to construct the weights given to individual responses on the application form. All application forms were double- entered. We verifi ed the code used by the fi rm to
code individual questions, and to calculate the aggregate dropout- risk score. 6. When there were tied scores at the eligibility cutoff all applicants with the tied score were offered a
scholarship. 7. The fi nal list of scholarship recipients was included in an offi cial government proclamation “Prakas”
for each CSP school. We cross- checked the list on the “Prakas” against a list that we produced independently based on the applicant database. There were no discrepancies allowing for a handful of adjustments based
on the public comment phase. 8. In practice, within every large school, the 25 students with the highest dropout- risk score were offered
a scholarship of 60, and the 25 students with the next highest scores were offered a scholarship of 45; in small schools, the comparable numbers were 15 students with scholarships of 60, and 15 students with
scholarships of 45. We do not focus on this distinction in this paper. Rather, we compare applicants who were offered a scholarship, regardless of the amount, with others that were not. Because the identifi cation
strategy is regression discontinuity, as discussed below, we are implicitly comparing applicants who were offered a 45 scholarship, with those who were offered no scholarship at all. Students who were offered a
60 scholarship help estimate the control function that relates outcomes for example, grades of completed schooling or test scores to the dropout- risk score. We have shown elsewhere that there is no evidence that
the short- term effect of the CSP on enrollment is larger among students who were offered the 60 scholarship rather than the 45 scholarship Filmer and Schady 2011.
household in Cambodia, and is almost exactly equal to the direct cost of schooling, including fees, uniforms, supplies, and transportation but excluding the opportunity
cost of going to school Ferreira, Filmer, and Schady 2009.
B. Data
