Abstract

This study delves into the intricate and multifaceted factors driving state-level college and university closures, leveraging publicly accessible variables through a Generalized Linear Model (GLM) analysis, in contrast to Multiple Discriminant Analysis (MDA). The analysis identifies key determinants of closures, including institutional endowment, tuition, and the percentage of in-state students. A pivotal contribution of this research is the development of a predictive Z-score model and ranges, offering robust and efficient tools for classifying higher education institution closures with enhanced applicability.

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