Measurement of production inefficiency in a technology and inefficiency heterogeneity setting

Abstract

This study shows how the estimates of production inefficiency and of the marginal effects of its determinants can be distorted if not accounting for technology and inefficiency heterogeneity. This is achieved by employing a hierarchical stochastic frontier model with random parameters both in the production frontier and in the inefficiency distribution and comparing its results with a conventional frontier model. German dairy farming is used as a case study and estimation is performed in a Bayesian framework. The results reveal significant differences in the inefficiencies and the calculated marginal effects of its determinants across the two models. Specifically, it is shown that inefficiency is overestimated when heterogeneity is not accounted for. An inflation of the means and the variances of the marginal effects is also observed, with the latter result suggesting that technology heterogeneity dominates inefficiency heterogeneity. According to Bayes factors, the employed hierarchical frontier model is favoured by the data when compared to the conventional frontier model.