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When, where and how to perform efficiency estimation

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

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://hdl.handle.net/10.1111/j.1467-985X.2011.01023.x
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Article provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series A (Statistics in Society).

Volume (Year): 175 (2012)
Issue (Month): 4 (October)
Pages: 863-892

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Handle: RePEc:bla:jorssa:v:175:y:2012:i:4:p:863-892
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  1. Cubbin, John, 2005. "Efficiency in the water industry," Utilities Policy, Elsevier, vol. 13(4), pages 289-293, December.
  2. 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.
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  5. 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(06), pages 1663-1697, December.
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