The Spatial Efficiency Multiplier and Random Effects in Spatial Stochastic Frontier Models

We extend the emerging literature on spatial frontier models in three respects. Firstly, we account for latent heterogeneity by developing a maximum likelihood random effects spatial autoregressive (SAR) stochastic frontier model. Secondly, to analyze the finite sample properties of a spatial stochastic frontier model we develop a Monte Carlo experimental methodology which we then apply. Thirdly, we introduce the concept of the spatial efficiency multiplier and show that the efficiency benchmark for a productive unit from the structural form of a spatial stochastic frontier model differs from the efficiency benchmark from the reduced form of the model.

Keywords: Stochastic frontier analysis (SFA); Spatial autoregression (SAR); Panel data; Random effects; Efficiency spillovers; Agriculture.

JEL Classification: C23, C51, D24, Q10.

Suggested Citation: Suggested Citation

Glass, Anthony and Glass Kenjegalieva, Karligash and Sickles, Robin C. and Weyman-Jones, Tom G., The Spatial Efficiency Multiplier and Random Effects in Spatial Stochastic Frontier Models (November 2016). Available at SSRN: https://ssrn.com/abstract=2873520 or http://dx.doi.org/10.2139/ssrn.2873520