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When, where and how to perform efficiency estimation

Author

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  • Badunenko, Oleg
  • Henderson, Daniel J.
  • Kumbhakar, Subal C.

Abstract

In this paper we compare two flexible estimators of technical efficiency in a cross-sectional setting: the nonparametric kernel SFA estimator of Fan, Li and Weersink (1996) to the nonparametric bias corrected DEA estimator of Kneip, Simar andWilson (2008). We assess the finite sample performance of each estimator via Monte Carlo simulations and empirical examples. We find that the reliability of efficiency scores critically hinges upon the ratio of the variation in efficiency to the variation in noise. These results should be a valuable resource to both academic researchers and practitioners.

Suggested Citation

  • Badunenko, Oleg & Henderson, Daniel J. & Kumbhakar, Subal C., 2011. "When, where and how to perform efficiency estimation," MPRA Paper 33467, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:33467
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    References listed on IDEAS

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    1. Leopold Simar & Paul Wilson, 2000. "A general methodology for bootstrapping in non-parametric frontier models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(6), pages 779-802.
    2. repec:bla:jorssa:v:165:y:2002:i:3:p:405-434 is not listed on IDEAS
    3. Catherine J. Morrison Paul & Warren E. Johnston & Gerald A. G. Frengley, 2000. "Efficiency in New Zealand Sheep and Beef Farming: The Impacts of Regulatory Reform," The Review of Economics and Statistics, MIT Press, vol. 82(2), pages 325-337, May.
    4. Schmidt, Peter & Lin, Tsai-Fen, 1984. "Simple tests of alternative specifications in stochastic frontier models," Journal of Econometrics, Elsevier, vol. 24(3), pages 349-361, March.
    5. Berndt, Ernst R. & Morrison, Catherine J., 1995. "High-tech capital formation and economic performance in U.S. manufacturing industries An exploratory analysis," Journal of Econometrics, Elsevier, vol. 65(1), pages 9-43, January.
    6. Kneip, Alois & Simar, Léopold & Wilson, Paul W., 2008. "Asymptotics And Consistent Bootstraps For Dea Estimators In Nonparametric Frontier Models," Econometric Theory, Cambridge University Press, vol. 24(6), pages 1663-1697, December.
    7. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, University Library of Munich, Germany.
    8. 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.
    9. Louis Amato & Christie Amato, 2000. "The Impact of High Tech Production Techniques on Productivity and Profitability in Selected U.S. Manufacturing Industries," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 16(4), pages 327-342, June.
    10. 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 435-444, June.
    11. M. Stone, 2002. "How not to measure the efficiency of public services (and how one might)," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(3), pages 405-434, October.
    12. KNEIP, Alois & SIMAR, Léopold, 1995. "A General Framework for Frontier Estimation with Panel Data," LIDAM Discussion Papers CORE 1995060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    14. Daniel J. Henderson & R. Robert Russell, 2005. "Human Capital And Convergence: A Production-Frontier Approach ," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 46(4), pages 1167-1205, November.
    15. Fan, Yanqin & Li, Qi & Weersink, Alfons, 1996. "Semiparametric Estimation of Stochastic Production Frontier Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(4), pages 460-468, October.
    16. Cubbin, John & Tzanidakis, George, 1998. "Regression versus data envelopment analysis for efficiency measurement: an application to the England and Wales regulated water industry," Utilities Policy, Elsevier, vol. 7(2), pages 75-85, June.
    17. Cubbin, John, 2005. "Efficiency in the water industry," Utilities Policy, Elsevier, vol. 13(4), pages 289-293, December.
    18. Gong, Byeong-Ho & Sickles, Robin C., 1992. "Finite sample evidence on the performance of stochastic frontiers and data envelopment analysis using panel data," Journal of Econometrics, Elsevier, vol. 51(1-2), pages 259-284.
    19. Peter C. Smith & Andrew Street, 2005. "Measuring the efficiency of public services: the limits of analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 401-417, March.
    20. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    21. Bojani, Antonio N. & Caudill, Steven B. & Ford, Jon M., 1998. "Small-sample properties of ML, COLS, and DEA estimators of frontier models in the presence of heteroscedasticity," European Journal of Operational Research, Elsevier, vol. 108(1), pages 140-148, July.
    22. Park, Soo-Uk & Lesourd, Jean-Baptiste, 2000. "The efficiency of conventional fuel power plants in South Korea: A comparison of parametric and non-parametric approaches," International Journal of Production Economics, Elsevier, vol. 63(1), pages 59-67, January.
    23. Subal C. Kumbhakar & Efthymios G. Tsionas, 2011. "Stochastic error specification in primal and dual production systems," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(2), pages 270-297, March.
    24. Hayfield, Tristen & Racine, Jeffrey S., 2008. "Nonparametric Econometrics: The np Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i05).
    25. Dassler, Thoralf & Parker, David & Saal, David S., 2006. "Methods and trends of performance benchmarking in UK utility regulation," Utilities Policy, Elsevier, vol. 14(3), pages 166-174, September.
    26. Wilson, Paul W., 2008. "FEAR: A software package for frontier efficiency analysis with R," Socio-Economic Planning Sciences, Elsevier, vol. 42(4), pages 247-254, December.
    27. Banker, Rajiv D. & Gadh, Vandana M. & Gorr, Wilpen L., 1993. "A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 67(3), pages 332-343, June.
    28. Guilkey, David K & Lovell, C A Knox & Sickles, Robin C, 1983. "A Comparison of the Performance of Three Flexible Functional Forms," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(3), pages 591-616, October.
    29. 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.
    30. Clifford M. Hurvich & Jeffrey S. Simonoff & Chih‐Ling Tsai, 1998. "Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(2), pages 271-293.
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    More about this item

    Keywords

    Bootstrap; Nonparametric kernel; Technical efficiency;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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