Sindh Education Foundation Pilot, New School Subsidy Program (Public-Private Partnership)

Last registered on September 02, 2017


Trial Information

General Information

Sindh Education Foundation Pilot, New School Subsidy Program (Public-Private Partnership)
Initial registration date
August 31, 2017

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 02, 2017, 7:01 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.



Primary Investigator

Vanderbilt University

Other Primary Investigator(s)

PI Affiliation
Washington University in St. Louis
PI Affiliation
World Bank
PI Affiliation
University of Texas at Austin
PI Affiliation
New York University - Abu Dhabi

Additional Trial Information

Start date
End date
Secondary IDs
This project experimentally evaluates the effects of public per-student subsidies to local partnering entrepreneurs to establish and operate tuition-free, coeducational private primary schools in educationally underserved rural communities in Sindh province, Pakistan. Two different subsidy structures were tested, one in which the subsidy amount did not differ by the student’s gender, and the other in which the subsidy amount was higher for female students.
The latter structure was motivated by the interest of the program administrators to correct for the existing gender disparity in school enrollment in the general setting. The program increased school enrollment by 30 percentage points in treated communities, for both boys and girls. The gender-differentiated subsidy structure did not produce a greater increase in female enrollment than the gender-uniform one. The program increased test scores by 0.67 standard deviations in treated communities. Program schools proved more effective in raising test scores than government schools in the geographic vicinity, with program students scoring 0.16 standard deviations higher, despite coming from more socioeconomically disadvantaged backgrounds. Structural estimations of the supply and demand for schooling suggest nearly efficient choices on school inputs by the program administrators and partnering entrepreneurs.
External Link(s)

Registration Citation

Barrera-Osorio, Felipe et al. 2017. "Sindh Education Foundation Pilot, New School Subsidy Program (Public-Private Partnership) ." AEA RCT Registry. September 02.
Former Citation
Barrera-Osorio, Felipe et al. 2017. "Sindh Education Foundation Pilot, New School Subsidy Program (Public-Private Partnership) ." AEA RCT Registry. September 02.
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Experimental Details


Funded by the provincial government, the Promoting Private Schooling in Rural Sindh (PPRS) program was designed and administered by the Sindh Education Foundation (SEF), a semi-autonomous organization established in 1992 by the provincial government to undertake education initiatives targeting less-developed areas and marginalized populations in Sindh province. The main, stated objectives of the PPRS program were to increase access to schooling in marginalized areas, to reduce the gender disparity in school enrollment, and
to increase student learning, in a cost-effective manner.

Based on a budgetary assessment, SEF supported coeducational, private primary schools in 200 villages in the selected districts. The main benefits that program-school operators received included a per-student cash subsidy; free school leadership and teacher training; and free textbooks, other teaching and learning materials, stationery, and bookbags

Two types of monthly per-student subsidies were provided: a gender-uniform subsidy, where the school received 350 rupees (approximately $5 in annualized 2008 US dollars) for each student; and a genderdifferentiated subsidy, where the school received 350 rupees for each male student and 450 rupees ($6.4) for each female student. A total of 100 schools received the gender-uniform subsidy, and another 100 schools, the gender-differentiated subsidy. All schools received the other benefits.

The subsidy amounts were set at less than one-half of the per-student cost in public primary and secondary government schools in the province, and were not adjusted for price inflation over the evaluation period.6 Provided on a quarterly basis, a school’s total subsidy was linked to the number of children in attendance multiplied by 1.25 to reflect an expected 20-percent student-absence rate. SEF gathered attendance information through periodic, unannounced monitoring visits to program schools. Local private entrepreneurs were invited to apply to the program through an open call in newspapers, and to propose educationally underserved villages in the selected districts to establish and operate schools.

The first phase of the program, which we evaluate in this study, was implemented in eight (out of, at that time, 23) districts in the province. SEF selected the districts based on how they ranked in terms of the size of the out-of-school child population, the gender disparity in school enrollment, and the percentage of households located at least 15 minutes away from the nearest primary school. The eight poorest-ranked districts were selected, excluding those that were viewed by the provincial government and SEF as experiencing heightened law-and-order concerns.

SEF vetted the applications (ultimately, through visits to shortlisted villages) based on several criteria, including written assent from the parents of at least 75 children of primary-school ages that they would enroll their children in the school, should it be established; a school site in the village that was located at least 1.5 kilometers from the nearest other school; a building of sufficient size; and the identification of teachers with a minimum of eight years of schooling (middle school completion), with at least two being female.7 Once in the program, school operators would continue to receive the subsidy and other benefits, as long as they provided free schooling to children, and provided and maintained school infrastructure and the schooling environment consistent with SEF guidelines. SEF strictly enforced the free-schooling condition, but was more lenient in enforcing the school infrastructural features and environmental conditions.
Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
Enrollment rates; standardized test scores; characteristics/inputs of the schools
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
The evaluation employed a prospective experimental design, where program-eligible localities were randomly assigned to three statuses: receive the gender-uniform subsidy subprogram (treatment 1), receive the gender-differentiated subsidy subprogram (treatment 2), receive neither subprogram (control).

The effect of the program on outcomes of interest involve comparing treatment localities to control localities before and after the onset of the treatment (double differences). For some outcomes, only the single cross-sectional difference were examined. Given random assignment to treatment status, the single differencing will yield valid estimates of the program impact. The effects of the two individual treatments (the gender-uniform subsidy and the gender-differentiated subsidy) was determined by applying the same empirical strategy.

The selection of localities and school operators and their random assignment to the program followed a stepwise process. First, applicants submitted applications to the program with one or more localities where they want to set up schools. Second, the applicants and proposed localities were vetted separately based on their respective qualification criteria. Third, all qualifying applicants were contacted with the full list of qualifying localities and asked to select which localities they would like to set up schools; qualifying applicants can choose more than locality from this list, and unpicked qualifying localities were dropped. This “relinked list” of qualifying localities was provided to the impact evaluation team. The team then randomly assigned each locality from the list to one of three statuses: treatment 1, treatment 2, and control.

SEF administered a vetting survey to determine whether proposed villages qualified for the program. This survey, which we refer to as the baseline survey, was conducted in February 2009. Following the baseline survey, 263 villages that qualified for the program were randomly assigned to the two subsidy treatments, or to the control group. However, after random assignment, SEF scaled down the original evaluation sample of 263 villages to 199 villages to correct for errors in determining whether a village qualified for the program. The decisions taken by SEF were orthogonal to the assigned program status of the village. Thus, the effective evaluation sample consisted of 82 villages under the gender-uniform subsidy treatment, 79 under
the gender-differentiated one, and 38 as controls.

Schools were established in summer 2009. Because the new school year normally commences in the spring, program-school students had an abbreviated first school year. A follow-up survey was conducted in April/May 2011, after the conclusion of the second school year under the program.
The baseline survey consisted of a village survey answered by village leaders, a school survey of all schools in the general vicinity of the village, and a household survey of 12 households randomly selected from the list submitted by the entrepreneur of 75 households that had agreed to send their children to the proposed program school. The household survey collected information on the household, the household head, and on each child aged 5–9. In each village, the baseline survey also consisted of a survey of the entrepreneur and proposed teachers, as well as physical checks by the survey interviewers of the proposed school site and building. GPS data were collected from all schools, the proposed program-school site, and surveyed households.

The follow-up survey consisted of three instruments: a school survey; a household survey; and a child survey, which included a test. The household and child surveys, and child tests, were administered at the child’s home. The household survey was administered to households with at least one child aged 5–9. In large villages, up to 42 randomly sampled households in the village were interviewed; in villages with fewer than 42 households, which comprised the majority, all households in the village were interviewed. The survey was multi-topic, and had extensive modules on past and current schooling and other activities for children aged 5–17, answered by the household head or another primary adult household member.

A child survey was administered to each child aged 5–9. It asked questions mainly on work activities performed inside and outside the home, past and current schooling, and aspirations.
Each child was then administered tests on language (either Urdu or Sindhi, as preferred) and mathematics.

The school survey gathered information from interviews of head teachers and all other teachers, and visual checks by the survey interviewers of school infrastructural and environmental conditions. The survey also collected student attendance information through a headcount, with the attendance lists used during the household survey to verify the child’s enrollment status reported by the household. GPS data was gathered from all surveyed households and schools.
Experimental Design Details
Same as above
Randomization Method
Randomization done by computer
Randomization Unit
Village level
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
199 schools
Sample size: planned number of observations
Villages: 200. Approx. 40 control, 160 Treated.
Sample size (or number of clusters) by treatment arms
Schools: 38 Control; 82 Treatment 1; 79 Treatment 2.
Baseline: Households: 445 Control; 1644 Treatment
Followup: Households: 1069 Control; 4897 Treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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Institutional Review Boards (IRBs)

IRB Name
Columbia University
IRB Approval Date
IRB Approval Number


Post Trial Information

Study Withdrawal

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Is the intervention completed?
Data Collection Complete
Data Publication

Data Publication

Is public data available?

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials