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The Use of Parametric and Non Parametric Frontier Methods to Measure the Productive Efficiency in the Industrial Sector. A Comparative Study

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  • Luis R. Murillo-Zamorano
  • Juan Vega-Cervera
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    Abstract

    Parametric frontier models and non-parametric methods have monopolised the recent literature on productive efficiency measurement. Empirical applications have usually dealt with either one or the other group of techniques. This paper applies a range of both types of approaches to an industrial organisation setup. The joint use can improve the accuracy of both, although some methodological difficulties can arise. The robustness of different methods in ranking productive units allows us to make an comparative analysis of them. Empirical results concern productive and market demand structure, returns-to-scale, and productive inefficiency sources. The techniques are illustrated using data from the US electric power industry.

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    Bibliographic Info

    Paper provided by Department of Economics, University of York in its series Discussion Papers with number 00/17.

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    Handle: RePEc:yor:yorken:00/17

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    Postal: Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom
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    Keywords: Productive efficiency; parametric frontiers; DEA; industrial sector;

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    1. Greene, William H., 1980. "On the estimation of a flexible frontier production model," Journal of Econometrics, Elsevier, vol. 13(1), pages 101-115, May.
    2. Schmidt, Peter & Lovell, C. A. Knox, 1980. "Estimating stochastic production and cost frontiers when technical and allocative inefficiency are correlated," Journal of Econometrics, Elsevier, vol. 13(1), pages 83-100, May.
    3. Rajiv D. Banker & Richard C. Morey, 1986. "The Use of Categorical Variables in Data Envelopment Analysis," Management Science, INFORMS, vol. 32(12), pages 1613-1627, December.
    4. Richmond, J, 1974. "Estimating the Efficiency of Production," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 15(2), pages 515-21, June.
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    7. Kumbhakar, Subal C. & Heshmati, Almas & Hjalmarsson, Lennart, 1997. "Temporal patterns of technical efficiency: Results from competing models," International Journal of Industrial Organization, Elsevier, vol. 15(5), pages 597-616, August.
    8. Jati Sengupta, 1995. "Estimating efficiency by cost frontiers: a comparison of parametric and nonparametric methods," Applied Economics Letters, Taylor & Francis Journals, vol. 2(4), pages 86-90.
    9. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
    10. Fare, R. & Grosskopf, S. & Logan, J., 1985. "The relative performance of publicly-owned and privately-owned electric utilities," Journal of Public Economics, Elsevier, vol. 26(1), pages 89-106, February.
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    12. Kumbhakar, Subal C, 1991. "The Measurement and Decomposition of Cost-Inefficiency: The Translog Cost System," Oxford Economic Papers, Oxford University Press, vol. 43(4), pages 667-83, October.
    13. Lee, Byung-Joo, 1995. "Separability Test for the Electricity Supply Industry," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(1), pages 49-60, Jan.-Marc.
    14. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    15. Sengupta, Jati K., 1999. "A dynamic efficiency model using data envelopment analysis," International Journal of Production Economics, Elsevier, vol. 62(3), pages 209-218, September.
    16. Schmidt, Peter & Knox Lovell, C. A., 1979. "Estimating technical and allocative inefficiency relative to stochastic production and cost frontiers," Journal of Econometrics, Elsevier, vol. 9(3), pages 343-366, February.
    17. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    18. Seiford, Lawrence M. & Thrall, Robert M., 1990. "Recent developments in DEA : The mathematical programming approach to frontier analysis," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 7-38.
    19. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(03), December.
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