Parametric stochastic frontier models yield firm-level conditional distributions of inefficiency that are truncated normal. Given these distributions, how should one assess and rank firm-level efficiency? This study compares the techniques of estimating a) the conditional mean of inefficiency...

In certain circumstances, both researchers and policy makers are faced with the challenge of determining individual efficiency scores for each decision making unit (DMU) under consideration. In this study, we use a Monte Carlo experimentation to analyze the optimal approach to determining...

In this paper we compare two flexible estimators of technical efficiency in a cross-sectional setting: the nonparametric kernel SFA estimator of Fan, Li and Weersink (1996) to the nonparametric bias corrected DEA estimator of Kneip, Simar and Wilson (2008). We assess the finite sample...

The computing time for Markov Chain Monte Carlo (MCMC) algorithms can be prohibitively large for datasets with many observations, especially when the data density for each observation is costly to evaluate. We propose a framework where the likelihood function is estimated from a random subset of...

We analyse overall cost efficiency in Spanish local governments during the crisis period (2008-2015). To this end, we first consider some of the most popular nonparametric methods to evaluate local government efficiency, data envelopment analysis and free disposal hull, as well as recent...