Statistical Inference in a Spatial-Temporal Stochastic Frontier Model

Abstract

The stochastic frontier model with heterogeneous technical efficiency explained by exoge-nous variables is augmented with a spatial-temporal component, a generalization relaxing the panel independence assumption in a panel data. The estimation procedure takes advantage of additivity in the model, computational advantages over maximum likelihood estimation of parameters is exhibited. The spatial-temporal component can improve estimates of technical efficiency in a production frontier that is usually biased downwards. We present a test to veri-fy model assumptions that facilitates estimation of parameters.