Explaining (in)efficiency in higher education: a comparison of parametric and non-parametric analyses to rank universities

In recent years more and more numerous are the rankings published in the newspapers or technical reports available, covering many aspects of higher education, but in many cases with very conflicting results between them, due to the fact that universities’ performances depend on the set of variables considered and on the methods of analysis employed. The aim of this study is to rank higher education institutions (HEIs) in Italy, comparing parametric and non-parametric approaches: we firstly apply a so-called double bootstrap Data Envelopment Analysis (DEA) to generate unbiased coefficients (Simar and Wilson, 2007) and then a Stochastic Frontier Analysis (SFA), modelling the production set through an output distance function, applying a within transformation to data as developed by Wang and Ho (2010), to evaluate which determinants have an impact on universities’ efficiencies. The findings reveal that, on average and among the macro-areas of the country, the level of efficiency does not change significantly among estimation methods which, instead, generate different rankings. This may guide universities’ managers and policymakers as rankings have a strong impact on academic decision-making and behaviour, on the structure of the institutions and also on students and graduates recruiters. Variables describing institution, market place and environment have an important role in explaining (in)efficiency.