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The Spatial Efficiency Multiplier and Common Correlated Effects in a Spatial Autoregressive Stochastic Frontier Model

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  • Glass, Anthony J.

    (Loughborough U)

  • Kenjegalieva, Karligash

    (Loughborough U)

  • Sickles, Robin C.

    (Rice U and Loughborough U)

  • Weyman-Jones, Thomas

    (Loughborough U)

Abstract

We extend the emerging literature on spatial frontier methods in a number of respects. One contribution includes accounting for unobserved heterogeneity. This involves developing a random effects spatial autoregressive stochastic frontier model which we generalize to a common correlated effects specification to account for correlation between the regressors and the unit specific effects. Another contribution is the introduction of the concept of a spatial efficiency multiplier to show that the efficiency frontiers from the structural and reduced forms of a spatial frontier model differ. To demonstrate various features of the estimators we develop we carry out a Monte Carlo simulation analysis and provide an empirical application. The application is to a state level cost frontier for U.S. agriculture which is a popular case in the efficiency literature and is thus well-suited to highlighting the features of the estimators we propose.

Suggested Citation

  • Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C. & Weyman-Jones, Thomas, 2018. "The Spatial Efficiency Multiplier and Common Correlated Effects in a Spatial Autoregressive Stochastic Frontier Model," Working Papers 18-003, Rice University, Department of Economics.
  • Handle: RePEc:ecl:riceco:18-003
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    References listed on IDEAS

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    Cited by:

    1. Roberto Mosheim & Robin C. Sickles, 2021. "Spatial effects of nutrient pollution on drinking water production," Empirical Economics, Springer, vol. 60(6), pages 2741-2764, June.
    2. Glass, Anthony J. & Kenjegalieva, Karligash & Douch, Mustapha, 2020. "Uncovering spatial productivity centers using asymmetric bidirectional spillovers," European Journal of Operational Research, Elsevier, vol. 285(2), pages 767-788.

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    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • Q10 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - General

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