Application Mistakes and Information Frictions in College Admissions


We analyze the prevalence and relevance of application mistakes in a seemingly strategyproof centralized college admissions system. We use data from Chile and exploit institutional features to identify a common type of application mistake: applying to programs without meeting all requirements (admissibility mistakes). We find that the growth of admissibility mistakes over time is driven primarily by growth on active score requirements. However, this effect fades out over time, suggesting that students might adapt to the new set of requirements but not immediately. To analyze application mistakes that are not observed in the data, we design nationwide surveys and collect information about students’ true preferences, their subjective beliefs about admission probabilities, and their level of knowledge about admission requirements and admissibility mistakes. We find that between 2%-4% of students do not list their true most preferred program, even though they face a strictly positive admission probability, and only a fraction of this skipping behavior can be rationalized by biases on students’ subjective beliefs. In addition, we find a pull-to-center effect on beliefs, ie, students tend to attenuate the probability of extreme events and under-predict the risk of not being assigned to the system. We use these insights to design and implement a large-scale information policy to reduce application mistakes. We find that showing personalized information about admission probabilities has a causal effect on improving students’ outcomes, significantly reducing the risk of not being assigned to the centralized system and the incidence of admissibility mistakes.

  • Coauthors: Tomás Larroucau, Manuel Martínez, Ignacio Rios
  • Date: 2022
  • PDF