Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/55093
Authors: 
Badunenko, Oleg
Henderson, Daniel J.
Kumbhakar, Subal C.
Year of Publication: 
2011
Series/Report no.: 
Discussion paper series // Forschungsinstitut zur Zukunft der Arbeit 5997
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.
Subjects: 
bootstrap
nonparametric kernel
technical efficiency
JEL: 
C14
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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