Nonparametric efficiency estimation in stochastic environments

Nonparametric efficiency estimation in stochastic environments

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Article ID: iaor20031798
Country: United States
Volume: 50
Issue: 4
Start Page Number: 645
End Page Number: 655
Publication Date: Jul 2002
Journal: Operations Research
Authors: , ,
Keywords: statistics: data envelopment analysis
Abstract:

This paper develops a new nonparametric model for efficiency estimation. In contrast to Data Envelopment Analysis (DEA), it does not impose debatable production assumptions like free disposability and convexity, and it does not assume that the data are measured without error. The estimators are asymptotically unbiased and have an asymptotic variance that is comparable to that of stochastic frontier estimators (provided the latter use a correct specification of the functional form for the production relationships). In addition, the estimators can be computed using a simple enumeration algorithm.

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