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. -- bootstrap ; nonparametric kernel ; technical efficiency

MoreLess

Year of publication:	2011
Authors:	Badunenko, Oleg ; Henderson, Daniel J. ; Kumbhakar, Subal
Publisher:	Bonn : IZA
Subject:	Technische Effizienz \| Technical efficiency \| Schätztheorie \| Estimation theory \| Data-Envelopment-Analyse \| Data envelopment analysis \| Bootstrap-Verfahren \| Bootstrap approach \| Monte-Carlo-Simulation \| Monte Carlo simulation \| Schätzung \| Estimation \| USA \| United States