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When, where and how to perform efficiency estimation

Author

Listed:
  • Oleg Badunenko

    (CGS, University of Cologne)

  • Daniel J. Henderson

    (State University of New York-Binghamton)

  • Subal C. Kumbhakar

    (State University of New York-Binghamton)

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 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.

Suggested Citation

  • Oleg Badunenko & Daniel J. Henderson & Subal C. Kumbhakar, 2011. "When, where and how to perform efficiency estimation," Cologne Graduate School Working Paper Series 02-06, Cologne Graduate School in Management, Economics and Social Sciences.
    • Handle: RePEc:cgr:cgsser:02-06
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    References listed on IDEAS

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    More about this item

    Keywords

    Bootstrap; Nonparametric Kernel; Technical Efficiency;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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