Second stage DEA: Comparison of approaches for modelling the DEA score

Tobit regression is often encountered in second stage data envelopment analysis (DEA), i.e. when the relationship between exogenous factors (non-physical inputs) and DEA efficiency scores is assessed. It is however not obvious that tobit is the only, or optimal, approach to modelling DEA scores. This paper presents two alternative approaches to second stage DEA, the results of which are compared with the tobit approach through a case study for the Danish fishery. Furthermore the three models are compared to OLS regression, representing a linear approximation to the models. It is firstly concluded that the tobit approach will in most cases be sufficient in representing second stage DEA models. Secondly it is shown that OLS may actually in many cases replace tobit as a sufficient second stage DEA model.