A new approach to stochastic frontier estimation: DEA+

Publication: Working/Discussion PaperWU Working Paper

Abstract

The outcome of a production process might not only deviate from a theoretical maximum due to inefficiency, but also because of non-controllable influences. This raises the issue of reliability of Data Envelopment Analysis in noisy environments. I propose to assume an i.i.d. data generating process with bounded noise component, so that the following approach is feasible: Use DEA to estimate a pseudo frontier first (nonparametric shape estimation). Next apply a ML-technique to the DEA-estimated efficiencies, to estimate the scalar value by which this pseudo-frontier must be shifted downward to get the true production frontier (location estimation). I prove, that this approach yields consistent estimates of the true frontier. (author's abstract)
Original languageEnglish
Place of PublicationVienna
PublisherInst. für Volkswirtschaftstheorie und -politik, WU Vienna University of Economics and Business
Publication statusPublished - 1996

Publication series

NameDepartment of Economics Working Paper Series
No.39

WU Working Paper Series

  • Department of Economics Working Paper Series

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