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When, Where and How to Perform Efficiency Estimation

  • Badunenko, Oleg

    ()

    (University of Cologne)

  • Henderson, Daniel J.

    ()

    (University of Alabama)

  • Kumbhakar, Subal C.

    ()

    (Binghamton University, New York)

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 and Wilson (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.

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File URL: http://ftp.iza.org/dp5997.pdf
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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 5997.

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Length: 42 pages
Date of creation: Sep 2011
Date of revision:
Publication status: published in: Journal of the Royal Statistical Society, Series A (Statistics in Society), 2012, 175 (4), 863-892
Handle: RePEc:iza:izadps:dp5997
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  1. 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.
  2. 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.
  3. Alois Kneip & Léopold Simar & Paul W. Wilson, 2006. "Asymptotics and Consistent Bootstraps for DEA Estimators in Non-parametric Frontier Models," Bonn Econ Discussion Papers bgse12_2006, University of Bonn, Germany.
  4. 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.
  5. William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, EconWPA.
  6. 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.
  7. Berndt, Ernst R. & Morrison, Catherine J., 1992. "High-tech capital formation and economic performance in U.S. manufacturing industries : an exploratory analysis," Working papers 3419-92., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  8. KNEIP, Alois & SIMAR, Léopold, 1995. "A General Framework for Frontier Estimation with Panel Data," CORE Discussion Papers 1995060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  9. Tristen Hayfield & Jeffrey S. Racine, . "Nonparametric Econometrics: The np Package," Journal of Statistical Software, American Statistical Association, vol. 27(i05).
  10. 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.
  11. Gong, Byeong-Ho & Sickles, Robin C., 1991. "Finite Sample Evidence on the Performance of Stochastic Frontiers and Data Envelopment Analysis Using Panel Data," Working Papers 91-12, C.V. Starr Center for Applied Economics, New York University.
  12. 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.
  13. 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 460-68, October.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. Cubbin, John, 2005. "Efficiency in the water industry," Utilities Policy, Elsevier, vol. 13(4), pages 289-293, December.
  21. repec:cup:cbooks:9780521666633 is not listed on IDEAS
  22. 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.
  23. 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.
  24. 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.
  25. 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.
  26. 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.
  27. 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, vol. 16(4), pages 327-342, June.
  28. 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.
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