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Spatial Stochastic Frontier Models

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  • Erniel B. Barrios

    (Philippine Institute for Development Studies)

  • Rouselle F. Lavado

Abstract

The stochastic frontier model with heterogeneous technical efficiency explained by exogenous variables is augmented with a sparse spatial autoregressive component for a cross-section data, and a spatial-temporal component for a panel data. An estimation procedure that takes advantage of the additivity of the model is proposed, computational advantages over simultaneous maximum likelihood estimation of all parameters is exhibited. The technical efficiency estimates are comparable to existing models and estimation procedures based on maximum likelihood methods. A spatial or spatial-temporal component can improve estimates of technical efficiency in a production frontier that is usually biased downwards.

Suggested Citation

  • Erniel B. Barrios & Rouselle F. Lavado, 2010. "Spatial Stochastic Frontier Models," Microeconomics Working Papers 23091, East Asian Bureau of Economic Research.
    • Handle: RePEc:eab:microe:23091
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    References listed on IDEAS

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    1. GIJBELS, Irène & MAMMEN, Enno & PARK, Byeong U. & SIMAR, Léopold, 1997. "On estimation of monotone and concave frontier functions," LIDAM Discussion Papers CORE 1997031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    5. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    6. Landagan, Ohmar Z. & Barrios, Erniel B., 2007. "An estimation procedure for a spatial-temporal model," Statistics & Probability Letters, Elsevier, vol. 77(4), pages 401-406, February.
    7. Kumbhakar, Subal C & Ghosh, Soumendra & McGuckin, J Thomas, 1991. "A Generalized Production Frontier Approach for Estimating Determinants of Inefficiency in U.S. Dairy Farms," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(3), pages 279-286, July.
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    Cited by:

    1. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2021. "The spatial dimension of competition among airports at the worldwide level: a spatial stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 295(1), pages 118-130.
    2. 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.
    3. Bergantino, Angela Stefania & Intini, Mario & Volta, Nicola, 2020. "Spatial competition and efficiency: an investigation in the airport sector," The Warwick Economics Research Paper Series (TWERPS) 1287, University of Warwick, Department of Economics.
    4. Samuel Faria & Sofia Gouveia & Alexandre Guedes & João Rebelo, 2021. "Transient and Persistent Efficiency and Spatial Spillovers: Evidence from the Portuguese Wine Industry," Economies, MDPI, vol. 9(3), pages 1-20, August.
    5. Adjin, K. Christophe & Henning, Christian H. C. A., 2020. "Climate variability and farm inefficiency: A spatial stochastic frontier analysis of Senegalese agriculture," Working Papers of Agricultural Policy WP2020-09, University of Kiel, Department of Agricultural Economics, Chair of Agricultural Policy.
    6. Jacopo Canello & Francesco Vidoli, 2020. "Investigating space‐time patterns of regional industrial resilience through a micro‐level approach: An application to the Italian wine industry," Journal of Regional Science, Wiley Blackwell, vol. 60(4), pages 653-676, September.
    7. Vidoli, Francesco & Canello, Jacopo, 2016. "Controlling for spatial heterogeneity in nonparametric efficiency models: An empirical proposal," European Journal of Operational Research, Elsevier, vol. 249(2), pages 771-783.
    8. Pavlyuk, Dmitry, 2011. "Efficiency of broadband internet adoption in European Union member states," MPRA Paper 34183, University Library of Munich, Germany.
    9. Pavlyuk, Dmitry, 2010. "Regional Tourism Competition in the Baltic States: a Spatial Stochastic Frontier Approach," MPRA Paper 25052, University Library of Munich, Germany.
    10. Pavlyuk, Dmitry, 2010. "Spatial Competition and Cooperation Effects on European Airports' Efficiency," MPRA Paper 25050, University Library of Munich, Germany.
    11. Yiorgos Gadanakis & Francisco José Areal, 2020. "Accounting for rainfall and the length of growing season in technical efficiency analysis," Operational Research, Springer, vol. 20(4), pages 2583-2608, December.
    12. Vidoli, Francesco & Cardillo, Concetta & Fusco, Elisa & Canello, Jacopo, 2016. "Spatial nonstationarity in the stochastic frontier model: An application to the Italian wine industry," Regional Science and Urban Economics, Elsevier, vol. 61(C), pages 153-164.

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    More about this item

    Keywords

    stochastic frontier models; technical efficiency; spatial externalities; spatial-temporal model; backfitting;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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