When, where and how to perform efficiency estimation
Oleg Badunenko (),
Daniel Henderson () and
Subal Kumbhakar ()
No 02-06, Cologne Graduate School Working Paper Series from Cologne Graduate School in Management, Economics and Social Sciences
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.
Keywords: Bootstrap; Nonparametric Kernel; Technical Efficiency (search for similar items in EconPapers)
JEL-codes: C1 C14 C33 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cis and nep-eff
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Journal Article: When, where and how to perform efficiency estimation (2012)
Working Paper: When, Where and How to Perform Efficiency Estimation (2011)
Working Paper: When, where and how to perform efficiency estimation (2011)
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