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When, where and how to perform efficiency estimation

  • Oleg Badunenko

    (CGS, University of Cologne)

  • Daniel J. Henderson

    (State University of New York-Binghamton)

  • Subal C. Kumbhakar

    (State University of New York-Binghamton)

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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Paper provided by Cologne Graduate School in Management, Economics and Social Sciences in its series Cologne Graduate School Working Paper Series with number 02-06.

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Date of creation: 15 Sep 2011
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Handle: RePEc:cgr:cgsser:02-06
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  24. 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.
  25. 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.
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