The potential of smart matching platforms in teacher assignment: The case of Ecuador

This paper studies the potential of personalized smart information interventions to improve teacher assignment results in the context of a centralized choice and assignment system in Ecuador. Specifically, the paper focuses on the impact that a personalized non-assignment risk warning, coupled with a list of "achievable" teaching position recommendations, had on teacher applications in the “I Want to Become a Teacher” selection process. The causal effect of the intervention on teachers' school choices is analyzed, assessing its impact on the equilibrium probability of being assigned and on the overall results of the selection process, both in terms of the percentage of filled vacancies and the selection scores of assigned teachers. The study concludes that treated teachers, in equilibrium, are much more likely to modify their application and obtain an assignment. This result highlights the potential of similar information interventions in other contexts. The paper furthermore presents evidence that the intervention led to increased overall assignment rates and selection scores.