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Conditional Subsidies for School Attendance (“Subsidios Condicionados a la Asistencia Escolar”) in Bogota, Colombia
Last registered on January 23, 2017

Pre-Trial

Trial Information
General Information
Title
Conditional Subsidies for School Attendance (“Subsidios Condicionados a la Asistencia Escolar”) in Bogota, Colombia
RCT ID
AEARCTR-0001930
Initial registration date
January 23, 2017
Last updated
January 23, 2017 2:36 PM EST
Location(s)
Region
Primary Investigator
Affiliation
Harvard University
Other Primary Investigator(s)
PI Affiliation
University of Texas, Austin
Additional Trial Information
Status
Completed
Start date
2005-03-01
End date
2006-03-30
Secondary IDs
Abstract
Using a student level randomization, we compare three education based conditional cash transfers designs: a standard design, a design
where part of the monthly transfers are postponed until children have to re-enroll in school, and a design that lowers the reward for attendance but incentivizes graduation and tertiary enrollment. The two nonstandard designs significantly increase enrollment rates at both
the secondary and tertiary levels while delivering the same attendance gains as the standard design. Postponing some of the attendance
transfers to the time of re-enrollment appears particularly effective for the most at-risk children.

We show that three Colombian conditional cash transfer (CCT) programs for secondary school improve educational outcomes eight to twelve years after random assignment relative to a control group. Forcing families to save a portion of the transfers until they make enrollment decisions for the next academic year increases on-time enrollment in secondary school, reduces dropout rates, and promotes tertiary enrollment and completion in the long-term. Traditional stipends improve on-time enrollment and high school exit exam completion rates in the medium-term but do not affect tertiary outcomes in the long-term. A stipend that directly incentivizes tertiary enrollment promotes secondary school on-time enrollment and enrollment in lower quality tertiary institutions in the medium but not the long-term.
External Link(s)
Registration Citation
Citation
Barrera-Osorio, Felipe and Leigh Linden. 2017. "Conditional Subsidies for School Attendance (“Subsidios Condicionados a la Asistencia Escolar”) in Bogota, Colombia." AEA RCT Registry. January 23. https://doi.org/10.1257/rct.1930-1.0.
Former Citation
Barrera-Osorio, Felipe and Leigh Linden. 2017. "Conditional Subsidies for School Attendance (“Subsidios Condicionados a la Asistencia Escolar”) in Bogota, Colombia." AEA RCT Registry. January 23. https://www.socialscienceregistry.org/trials/1930/history/13330.
Experimental Details
Interventions
Intervention(s)
In 2005, the city of Bogota established the Conditional Subsidies for School Attendance (“Subsidios
Condicionados a la Asistencia Escolar”) program in an effort to improve student retention, lower drop-out rates and reduce child labor. In an effort to improve the program over the basic conditional cash transfer model, the Secretary of Education of the City (Secretaria de Educacion del Distrito, SED) decided to implemented a pilot study in two of the twelve localities in the city. The pilot was to run for a year, and then the results would be used to inform the design of the final program that would operate city-wide. Ultimately, three interventions were chosen for the pilot. First, operating as a reference is a basic intervention similar to that used in PROGRESSA/OPPORTUNIDADES. In this basic model, participants would receive 30,000 pesos (approximately US$ 15) as long as the child attended at least 80 percent of the days that month. The payments made bi-monthly through a dedicated debit card run by one of the major banks in Colombia. Students were removed from the program if they failed twice, failed to reach the attendance target in two successive bi-monthly periods, or were expelled from school. Finally, all payments were based on reports provided to the Secretary of Education by the students’ principals. The two additional treatments were experimental variants of this basic intervention aiming to better reach the goals of the program while keeping the cost of each intervention roughly equivalent to the basic intervention. Based on research that suggests that families may face difficulties saving money for students’ education (either because of intra-household bargaining, personal discounting issues, or simply high costs of savings), the second treatment (Savings Treatment) varied the timing of the distributions to students’ families. Instead of receiving
30,000 pesos a month for reaching the attendance target, students were paid two thirds of this amount on a bi-monthly basis (20,000 pesos or US$10) and the remaining third was held in account. The accumulated funds were then made available to students families during the period in which students enroll and prepare for the next school year. If students reached the attendance target every month, this treatment would make 100,000 pesos (US$ 50) available to them in December.

Rather than manipulate the timing of payments, the third treatment (Tertiary Treatment) changes the outcome students are being incentivized upon. Instead of providing an incentive to attend school, this treatment provides an incentive to graduate and then to matriculate to a higher education institution. Like in the Savings Treatment, in the short term, the monthly subsidy is reduced from 30,000 pesos per month to 20,000 pesos. However, upon graduating the students earn the right to receive a transfer of 600,000 pesos ($US 300), amounting to 73 percent of the average cost of the first year at a vocational school (823,000 pesos or $US 412). If the student graduates and enrolls in a tertiary institution, they receive the transfer immediately; if they fail to enroll, they can only request the transfer after a year has passed.

Due to constraints imposed on us by the SED, the assessment of the treatments was divided into two separate experiments located in two very similar localities in Bogota, San Cristobal and Suba. Both experiments were based on an over-subscription model. The city guaranteed enough funds to provide 10,000 with the subsidies, 7,000 in San Cristobal and 3,000 in Suba, for three years. To participate, a publicly advertised registration process would be held and if there were more interested children than subsidies, then the subsidies would be allocated to children based on a lottery in each locality.

The richness of the available data was one of the major strengths of that study. The data comes from five sources. These include general survey data on all eligible families, data collected specifically for the study, and administrative data collected by the SED. The first source is the original SISBEN surveys from 2003 and 2004 that contain information on all families eligible to register for the lottery. The second source is from the program registration process itself. We collected baseline data from the 68 schools with the largest number of registered children as well. The fourth source is data on students’ attendance through direct observation, the last source is a follow-up survey done in spring of 2006.
Intervention Start Date
2005-03-01
Intervention End Date
2006-03-30
Primary Outcomes
Primary Outcomes (end points)
I would add long-term longitudinal data to the existing data set. New data would allow us to assess the effect of the program on student’s participation a tertiary educational institution and employment. As stated earlier, long-term effects are of primary importance, and the interaction of the earlier data with long-term data benefit our investigation greatly. In addition to the data from the original experiment, we propose to use four sources of data:

a. Administrative data on secondary school enrollment provided by the Secretary of Education of Bogota, Colombia.
b. Three national Colombian administrative data sets that the government of Colombia makes available to researchers. This includes data from three data sets – the data from the Colombian national secondary-school exit exam, the SABER 11, the database on all students enrolled in tertiary educational institutions, the SPADIES data base, and employment records. The SABER 11 contains a record of whether or not a student took the exam and the student’s score. The SPADIES data base contains information on each student’s enrollment status in Colombian institutions. The employment records data base then provide information on students’ employment and earnings. These data sets are made available to researchers working on projects like ours and have been used for assessments of long-term outcomes for several existing researcher projects.
c. In order to access the employment records described above, we also propose to obtain a new identification numbers for the subjects in our sample from the National Registrar’s office (NRO) of Colombia. The NRO is a government office in charge of the personal identification records used by all overnment offices within Colombia. Within the system, people 17 years and younger are identified using a number called the “targeta de identidad.” When someone reaches 18, however, they receive an “adult” ide called the “cedula de ciudadania”. The two identification numbers are not related in any way. Our current data set was obtained when all of our subjects were 17 or younger, and as a result, we have the targeta de identidad number. Since our subjects are or will soon be 18, we are requesting that the NRO provide us with the subjects’ cedula de ciudadania. Once we obtain this number, we will then match our data set to another dataset that includes employment records of everyone in Colombia.

To analyze this data, we will use three basic models. First, we use a simple difference estimator. Second, we also use a difference estimator that includes controls for individual and family characteristics. And finally, we estimate the relationship between attendance and demographic characteristics for control students. We then use this model to estimate what attendance would have been for treatment students without the treatment and for unregistered students had they been observed. In all specifications, we are careful to re-weight the data when pooling results across localities to account for the different treatment assignment ratios.

The data that we have access for this project doesn’t include any individual identifiable information.
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
Assignment in both localities was contingent on over-subscription. To ensure oversubscription, the SED advertised the program through posters, newspapers ads, radio clips, loudspeakers in cars, churches and community leaders, including school principals and priests. Interested applicants had to register during a 15-day window between late February and early March 2005. Program registration took place in various schools at the two localities.
The SED guaranteed in 2005 funding for 7,984 students in total: 6,851 in the basic-savings experiment in San Cristobal and 1,133 in the tertiary experiment in Suba. In total, 13,433 eligible applicants registered in the two localities: 10,907 in San Cristobal and 2,526 in Suba. Barrera-Osorio et al. (2008, 2011) created a stratified randomization algorithm that SED implemented in publicly held lotteries in each locality on April 4 2005. The algorithm stratified by locality (San Cristobal, Suba), school type (Public/Private), grade (6th-11th) and gender. A team of economists from Universidad Nacional in Bogota verified the validity of the algorithm prior to its implementation as well as compliance with the (random) assignment results during the public lottery events.
Barrera-Osorio et al. (2011) document that one year after randomization of students into treatments, all treatments significantly increase school attendance relative to control conditions. In addition, the savings and tertiary treatments increased grade re-enrollment in secondary education relative to control, unlike the basic treatment, which had no effect. Similarly, the savings and tertiary treatments increased tertiary enrollment after one year of treatment for students who were enrolled in grade eleven at baseline.
Experimental Design Details
Randomization Method
The randomization was publicly conducted on April 4 in each locality. The
research team conducted the actual lottery, but in order to ensure transparency of
the process, the code was inspected prior to the exercise by researchers from the
National University. The randomizations were done publicly (projecting the code
onto a screen), with representatives of the community, school, and local authorities
present. The lists of beneficiaries were immediately printed, signed by local officials,
and made available to the communities so that parents were able to determine
if their children were included.
Randomization Unit
Individual level. The randomization was stratified on locality, type of school (public/private),
gender, and grade level
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
The SED guaranteed in 2005 funding for 7,984 students in total: 6,851 in the basic-savings experiment in San Cristobal and 1,133 in the tertiary experiment in Suba. In total, 13,433 eligible applicants registered in the two localities: 10,907 in San Cristobal and 2,526 in Suba.
Sample size: planned number of observations
Students within the study were spread across 251 schools, but the density was heavily skewed with the majority of students in a small number of schools. Given the budget constraints, we chose to collect baseline data and subsequent attendance data in only the 68 schools with the largest number of registered children. This implied a total possible sample of 7,569 children.
Sample size (or number of clusters) by treatment arms
Total students, saving-basic treatment: 4,056 control; 3,427 basic; 3,424 savings
Total students, tertiary treatment: 1,393 control; 1,133 tertiary
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Supporting Documents and Materials

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IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Study has received IRB approval. Details not available.
IRB Approval Date
Details not available
IRB Approval Number
Details not available
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
Yes
Intervention Completion Date
March 30, 2006, 12:00 AM +00:00
Is data collection complete?
Yes
Data Collection Completion Date
March 30, 2006, 12:00 AM +00:00
Final Sample Size: Number of Clusters (Unit of Randomization)
Students within the study were spread across 251 schools, but the density
was heavily skewed with the majority of students in a small number of schools.
Given the budget constraints, we chose to collect baseline data and subsequent
attendance data in only the 68 schools with the largest number of registered children.
This implied a total possible sample of 7,569 children.
Was attrition correlated with treatment status?
No
Final Sample Size: Total Number of Observations
Final Sample Size (or Number of Clusters) by Treatment Arms
Reports and Papers
Preliminary Reports
Relevant Papers
Abstract
Using a student level randomization, we compare three educationbased
conditional cash transfers designs: a standard design, a design
where part of the monthly transfers are postponed until children have
to re-enroll in school, and a design that lowers the reward for attendance
but incentivizes graduation and tertiary enrollment. The two
nonstandard designs significantly increase enrollment rates at both
the secondary and tertiary levels while delivering the same attendance
gains as the standard design. Postponing some of the attendance
transfers to the time of re-enrollment appears particularly
effective for the most at-risk children.
Citation
Barrera-Osorio, Felipe, Marianne Bertrand, Leigh L. Linden, and Francisco Perez-Calle. "Improving the design of conditional transfer programs: Evidence from a randomized education experiment in Colombia." American Economic Journal: Applied Economics 3, no. 2 (2011): 167-195.