Unlocking university efficiency: a Bayesian stochastic frontier analysis

In this paper, we analyze the performance of the Spanish public university system over the 2010-2019 period, which was particularly turbulent due to the tight budget constraints imposed on universities. To disentangle the main sources of performance change, we adopt a dynamic approach by decomposing it into efficiency change (catching up) and technical change (shifts in the frontier). In contrast to many studies on higher education institutions (HEIs), we opt for stochastic frontier analysis, employing the ray production function proposed by L & ouml;thgren (1997) to account for the multiple-output nature of HEIs. Additionally, to offer a more detailed examination of uncertainty quantification, we conduct inference within the Bayesian paradigm. Broadly, results point to an overall positive performance change over the entire period, particularly for technical change during 2010-2014. However, there were notable discrepancies across universities, which could be unlocked with certain precision via the posterior distributions of performance and its components.