A Bayesian approach to statistical inference in stochastic DEA

Stochastic DEA can deal effectively with noise in the non-parametric measurement of efficiency but unfortunately formal statistical inference on efficiency measures in not possible. In this paper, we provide a Bayesian approach to the problem organized around simulation techniques that allow for finite-sample inferences on efficiency scores. The new methods are applied to efficiency analysis of the Greek banking system for the period 1993–1999. The results show that the majority of the Greek banks operate close to best market practices.