Nonparametric Methods and Higher Education

The chapter provides an overview of nonparametric methods, particularly Data Envelopment Analysis (DEA) and related frontier techniques, in the study of higher education systems and institutions. It explains how these approaches enable the evaluation of efficiency and performance without imposing restrictive functional forms, making them especially suitable for analyzing complex, multi-input and multi-output processes typical of universities. The chapter discusses methodological foundations, key model variants, and extensions that account for heterogeneity, environmental factors, and quality dimensions. It also highlights practical applications in benchmarking institutions, informing policy decisions, and improving resource allocation, while noting limitations related to data quality, model specification, and interpretation of results.