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Integrating spatial dependence into stochastic frontier analysis

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  • Areal, Francisco J
  • Balcombe, Kelvin
  • Tiffin, R

Abstract

An approach to incorporate spatial dependence into Stochastic Frontier analysis is developed and applied to a sample of 215 dairy farms in England and Wales. A number of alternative specifications for the spatial weight matrix are used to analyse the effect of these on the estimation of spatial dependence. Estimation is conducted using a Bayesian approach and results indicate that spatial dependence is present when explaining technical inefficiency.

Suggested Citation

  • Areal, Francisco J & Balcombe, Kelvin & Tiffin, R, 2010. "Integrating spatial dependence into stochastic frontier analysis," MPRA Paper 24961, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:24961
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    References listed on IDEAS

    as
    1. Alexandra Schmidt & Ajax Moreira & Steven Helfand & Thais Fonseca, 2009. "Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency," Journal of Productivity Analysis, Springer, vol. 31(2), pages 101-112, April.
    2. Fernandez, Carmen & Koop, Gary & Steel, Mark, 2000. "A Bayesian analysis of multiple-output production frontiers," Journal of Econometrics, Elsevier, vol. 98(1), pages 47-79, September.
    3. Brummer, B. & Glauben, T. & Lu, W., 2006. "Policy reform and productivity change in Chinese agriculture: A distance function approach," Journal of Development Economics, Elsevier, vol. 81(1), pages 61-79, October.
    4. O'Donnell, Christopher J. & Coelli, Timothy J., 2005. "A Bayesian approach to imposing curvature on distance functions," Journal of Econometrics, Elsevier, vol. 126(2), pages 493-523, June.
    5. Won Kim, Chong & Phipps, Tim T. & Anselin, Luc, 2003. "Measuring the benefits of air quality improvement: a spatial hedonic approach," Journal of Environmental Economics and Management, Elsevier, vol. 45(1), pages 24-39, January.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Spatial dependence; technical efficiency; Bayesian; spatial weight matrix;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General

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