Nº 285 (August, 2021). Francisco Haimovich, Emmanuel Vazquez & Melissa Adelman
“Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial”.
Across many low- and middle-income countries, a sizable share of young people drop out of school before completing a full course of basic education. Early warning systems that accurately identify students at risk of dropout and support them with targeted interventions have shown results and are in widespread use in high-income contexts. This paper presents impact evaluation results from an early warning system pilot program in Guatemala, a middle-income country where nearly 40 percent of sixth graders drop out before completing ninth grade. The pilot program, which was implemented in 17 percent of Guatemala’s primary schools and largely leveraging existing government resources, reduced the dropout rate in the transition from primary to lower secondary school by 4 percent (1.3 percentage points) among schools assigned to the program, and by 9 percent (3 percentage points) among program compliers. Although the effect size is relatively modest, the low cost of the program (estimated at less than US$3 per student) and successful implementation at scale make this a promising and cost-effective approach for reducing dropout in resource-constrained contexts like Guatemala. AEA RCT ID: AEARCTR-0004091
JEL codes: I2, I3, J24
Suggested citation: Haimovich, F., E. Vazquez & M. Adelman (2021). Scalable Early Warning Systems for School Dropout prevention: Evidence from a 4.000-School Randomized Controlled Trial. CEDLAS Working Papers Nº 285, August, 2021, CEDLAS-FCE-Universidad Nacional de La Plata.