College Application Choices in a Repeated DA Setting

In the study presented in this Research Seminar the authors use a unique dataset from the centralized college admission system in Croatia for five different years to provide evidence for strategic application behavior in Deferred Acceptance (DA) mechanism. They track the application choices of more than 30,000 individuals per cohort over the course of close to a week in an application system that updates and publishes preliminary admission outcomes on an hourly basis. They show that applicants react to the information signals on admission probability exploiting the hourly changes of program cutoffs in an RDD setting. The authors find that applicants are more likely to adjust their application choices when they are right below the cutoff i.e. when they are temporarily not admitted to a particular college program than when they are just above the cutoff and receive a positive preliminary admission signal. Furthermore, they simulate the DA matching algorithm to obtain a measure of applicant- specific admission probability. They show how applicants strategic changes over time are related to their risk of remaining unmatched to any ranked program. To their knowledge, this is the first study to exploit within-individual changes in admission probability and application choices in a repeated DA college admission system.