Impacts of COVID-19 on Public Universities in Brazil: A Machine Learning Counterfactual Analysis
Volume 22, Issue 4 (2024), pp. 621–630
Pub. online: 5 February 2024
Type: Data Science In Action
Open Access
Open Access
Received
29 September 2023
29 September 2023
Accepted
17 January 2024
17 January 2024
Published
5 February 2024
5 February 2024
Abstract
This study delves into the impact of the COVID-19 pandemic on the enrollment rates of on-site undergraduate programs within Brazilian public universities. Employing the Machine Learning Control Method, a counterfactual scenario was constructed in which the pandemic did not occur. By contrasting this hypothetical scenario with real-world data on new entrants, a variable was defined to characterize the impact of the COVID-19 pandemic on on-site undergraduate programs at Brazilian public universities. This variable reveals that the impact factor varies significantly when considering the geographical locations of the institutions offering these courses. Courses offered by institutions located in smaller population cities experienced a more pronounced impact compared to those situated in larger urban centers.
Supplementary material
Supplementary MaterialThe following files are included in the supplementary material: (1) Study code file; (2) URL to INEP census data; (3) IBGE population of each municipality data.
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