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On the estimation of spatial stochastic frontier models: an alternative skew-normal approach

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  • Thomas Graaff

    (Vrije Universiteit Amsterdam)

Abstract

This paper deals with an alternative approach to combine spatial dependence and stochastic frontier models using a large statistical literature on skew-normal distribution functions. I show how to combine a spatial dependence structure with a stochastic frontier model, that is, (1) straightforward to estimate, (2) able to combine spatial dependence and a technical efficiency term in a single error term, and (3) produce consistent estimates. With smaller sample sizes estimation of the parameter, governing technical efficiencies becomes imprecise. The consistency of parameter estimation is shown using simulations, and I provide an empirical application to estimate spatially correlated technical efficiencies within an European regional production function context.

Suggested Citation

  • Thomas Graaff, 2020. "On the estimation of spatial stochastic frontier models: an alternative skew-normal approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 64(2), pages 267-285, April.
    • Handle: RePEc:spr:anresc:v:64:y:2020:i:2:d:10.1007_s00168-019-00928-9
    DOI: 10.1007/s00168-019-00928-9
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    JEL classification:

    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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