Understanding low completion rates of high school in a developing country
Last registered on August 06, 2019


Trial Information
General Information
Understanding low completion rates of high school in a developing country
Initial registration date
August 04, 2019
Last updated
August 06, 2019 11:51 AM EDT
Primary Investigator
Brown University
Other Primary Investigator(s)
Additional Trial Information
In development
Start date
End date
Secondary IDs
This study comprises an RCT to evaluate the impact of information (returns to education and probabilities of graduation) on students attending the last year of high school (5th year/senior). Even though the analysis of school attainment is not novel in the economic literature, I analyze this topic in a context with free education, free transportation, and high attendance but low completion rates (50% of the students attending the last year graduate by the end of the academic year). The structure of the educational system, that allows postponing the attendance to examination periods for pending subjects (up to 2, from previous years), will allow me to study potential mechanisms. This research is important to determine which piece of information could be more relevant to increase probabilities of graduation in a vulnerable population for whom career paths are going to be determined in the short run, and having a high school diploma will condition most of their choices (attending college or finding a job in the formal sector).
External Link(s)
Registration Citation
Lopez, Carolina. 2019. "Understanding low completion rates of high school in a developing country." AEA RCT Registry. August 06. https://doi.org/10.1257/rct.4511-1.0.
Former Citation
Lopez, Carolina. 2019. "Understanding low completion rates of high school in a developing country." AEA RCT Registry. August 06. http://www.socialscienceregistry.org/trials/4511/history/51312.
Experimental Details
The full-scale randomized controlled trial will include a main intervention (I1): I will provide information on returns to education or aspects of the production function of getting the high school diploma to randomly selected schools/shifts (only students attending the senior year) and measure the effects on graduation, academic performance, and future decisions. Specifically, I will visit all the schools in my sample to offer free access to an online platform with math to remediate students' standing or improve their current academic performance, in addition, in randomly selected schools/shifts I’ll show a short presentation with statistics indicating returns to education and in other randomly selected schools/shifts I will show statistics to indicate the impact of the pending subjects on the probability of graduation. SMS will be sent to remind the contents of the intervention.
In addition, randomly selected schools/shifts will receive after school classes before the next examination period (I2), and randomly selected students will receive SMS to highlight the existence of fellowships to attend college (I3).
Intervention Start Date
Intervention End Date
Primary Outcomes
Primary Outcomes (end points)
Main outcomes: graduation rates (on time: by December), number failed subjects by the end of the academic year, average grade (from school administrative records), formal employment, and college enrollment (from social security administrative data).

Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Intermediate outcomes: attendance to examination periods (December, February), and over(under) confidence update (from baseline questionnaire), attendance to after-school classes, registration and use of the platform (data from program records), standardized test scores.
Experimental outcome: over-underconfidence.
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The eligible population for this study is students attending the senior year of public high schools (I exclude technical schools because they depend on a different office). Some schools can have more than one shift, I will only consider the morning and the afternoon shift due to logistic constraints.
There is no updated information on the current enrollment, so I use the information from the academic year 2018. There were 2933 enrolled students in the last year in 63 school/shifts, this is the unit of randomization given that at the individual and class level are more likely to contaminate the control group.
The assignment to treatments in (I1) will be randomly determined at the school/shift level stratifying by number of students and geographic zone. A third of the school/shifts will be the control group, a third will receive information on returns to education and the rest information on aspects of the production function of the high school diploma. Regarding (I2), 5 randomly selected schools/shifts in each arm (information treatments and control group) will receive after school classes before the examination period.
Finally, 50% of the students (I3) will be randomly selected to receive the SMS about the fellowships.
Experimental Design Details
The visit to each school/shift will imply the following scheme of activities: - A week before the intervention date, the research team will visit and deliver to school administrators sealed envelopes containing surveys to math teachers of the 5th year asking for estimations of probabilities of graduation of students [these answers will be used to estimate under-over confidence along with the self-estimation of students] - At a date agreed with the school administrators, all students of a school/shift will be reunited in a room. The research team will be introduced by school administrators as part of a team of UNSa and Brown University who will provide useful information to students. - The research team will deliver tablets to students and will ask them to fill out the questionnaire, a short presentation will be shown to show students not familiarized with the use of tablets how to use them, and at the same time a quick explanation of the questionnaire will be provided. I will incentivize questions about wages and probabilities of employment and the questions to measure time preferences (to incentivize effort and true reporting in their answers). - After that, the research team will show a presentation introducing the online platform. - If applicable, Intervention 1 or Intervention 2 (showing the dates of after-school classes) will be conducted. - After the presentation, the research team will ask students to answer an additional question about over-under confidence to test updates after hearing the information presented. - To remind the treatment received, the research team will send monthly SMS reminders to students’ cell phones.
Randomization Method
Randomization done in office by a computer.
Randomization Unit
Intervention 1/2: School/shift level
Intervention 3: Individual level
Was the treatment clustered?
Experiment Characteristics
Sample size: planned number of clusters
I plan to enroll 63 schools/shifts.
Sample size: planned number of observations
I plan to enroll 3000 students.
Sample size (or number of clusters) by treatment arms
Approximately, 21 schools/shifts will be the control group, 21 schools/shifts will receive information on returns to education and 21 schools/shifts will receive information on aspects of the production function of the high school diploma.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB Name
Human Research Protection Program, Brown University
IRB Approval Date
IRB Approval Number
Analysis Plan

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