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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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Author Info
Luis R. Murillo-Zamorano
Juan Vega-Cervera
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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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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Keywords: Productive efficiency; parametric frontiers; DEA; industrial sector;

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  1. 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. [Downloadable!] (restricted)
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  4. 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. [Downloadable!]
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  6. 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. [Downloadable!] (restricted)
  7. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November. [Downloadable!] (restricted)
  8. 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. [Downloadable!] (restricted)
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  10. Sengupta, Jati K, 1995. "Estimating Efficiency by Cost Frontiers: A Comparison of Parametric and Nonparametric Methods," Applied Economics Letters, Taylor and Francis Journals, vol. 2(4), pages 86-90, April. [Downloadable!] (restricted)
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  13. 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. [Downloadable!] (restricted)
  14. 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. [Downloadable!] (restricted)
  15. Ferrier, Gary D. & Lovell, C. A. Knox, 1990. "Measuring cost efficiency in banking : Econometric and linear programming evidence," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 229-245. [Downloadable!] (restricted)
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