4.6 Article

Modelling regional patterns of inefficiency: A Bayesian approach to geoadditive panel stochastic frontier analysis with an application to cereal production in England and Wales

Journal

JOURNAL OF ECONOMETRICS
Volume 214, Issue 2-3, Pages 513-539

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jeconom.2019.07.003

Keywords

Bayesian regularization; Distributional regression; Farm efficiency; Markov chain Monte Carlo; Regional and spatial modelling; Unobserved heterogeneity

Funding

  1. German Research Foundation (DFG) [KN 922/4-2]
  2. German Research Foundation (DFG) via the research training group 1644 Scaling Problems in Statistics

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We propose a flexible Bayesian approach to inefficiency modelling that accounts for regional patterns of local performance. The model allows for a separated treatment of individual heterogeneity and determinants of inefficiency. Regional dependence structures and location-specific unobserved spatial heterogeneity are modelled via geoadditive predictors in the inefficiency term of the stochastic frontier model. Inference becomes feasible through Markov chain Monte Carlo simulation techniques. In an empirical illustration we find that regional patterns of inefficiency characterize cereal production in England and Wales. Neglecting common performance patterns of farms located in the same region induces systematic biases to inefficiency estimates. (C) 2019 Elsevier B.V. All rights reserved.

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