Measuring Efficiency of Public Higher Education Using DEA Model for Sichuan in China

Abstract

This study uses Data Envelopment Analysis (DEA) and the Malmquist method to investigate efficiency in Sichuan Province’s public undergraduate universities by employing a dynamic unbalanced panel data approach and Refining input-output indicators through the application of the Factorial Component Analysis (FCA) method. We find average comprehensive efficiency (0.6601), pure technical efficiency (0.8562), scale efficiency (0.7723), and total factor productivity progress (0.932) for 27 institutions from 2018 to 2022. Despite the increased investment, efficiency gains are modest. Hierarchical correlation with input-output efficiency is noted, and total factor productivity shows an upward trend influenced by financial resources and economies of scale. These findings provide insights for university administrators and policymakers to address inefficiencies and optimize education resources for sustainable development.