We use the concept of coarsened posteriors to provide robust Bayesian inference via coarsening in order to robustify posteriors arising from stochastic frontier models. These posteriors arise from tempered versions of the likelihood when at most a pre-specified amount of data is used, and are...

The distinguishing feature of the Bayesian approach in performance evaluation is that parameter uncertainty of the various models is formally taken into account along with model uncertainty as well. The usual sampling-theory approach proceeds conditionally on the parameter estimates that have...