Measuring efficiency in higher education: an empirical study using a bootstrapped data envelopment analysis

This paper applies data envelopment analysis (DEA) to assess technical efficiency in a big public university. Particular attention has been paid to two main activities, teaching and research, and on two large groups, the Science and Technology (ST) sector and the Humanity and Social Science (HSS) sector. The findings, based to data from 2005 to 2009, suggest that the ST sector is more efficient in terms of quality of research than the HSS sector, that instead achieves higher efficiency in teaching activities. The efficiency estimates strongly depend on the output specification, given that the use of several quality proxies, such as three research and two student questionnaire-based teaching alternative indices, reduce performance and its differentials for both research and teaching activities. A bootstrap technique is also used to provide confidence intervals for efficiency scores and to obtain bias-corrected estimates. The Malmquist index is calculated to measure changes in productivity.