Access the university. A spatial Heckman probit model [Data set & Code]

Dataset accompanying the publication "Equal opportunities to access the university in Chile? An application with a spatial Heckman probit model" (Mathematics 2022, 10, 280). This study contributes to the debate on accessibility of higher education in Chile, with a special focus on the geospatial dimension of access to university studies. This paper addresses the central question of whether geography (physical distance and neighborhood effects) plays a significant role in determining the accessibility of higher education to students in Chile. We use Heckman probit-type (Heckit) models to adjust for selection during application for higher education—that is, pre-selection among applications to study at university and, ultimately, admission (or denial) to a higher educational institution. Of all high school graduates who took the university selection test (PSU), only 37.9% were able to attend higher education. The results show that the geospatial elements—neighborhood characteristics and distance from the city of Santiago—have a significant local effect on the student’s application and access to Chilean universities. Specifically, the most significant local range for each candidate is 300 neighbors. We also find that, when distance to the capital city increases, the probability of applying to university increases to a threshold of 1400 km, at which point probability begins to decrease.