Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+

Dieter Gstach ()

Journal of Productivity Analysis, 1998, vol. 9, issue 2, 176 pages

Abstract: In this paper a DEA+ labeled approach for efficiency measurement in the stochastic case is presented along with a consistency proof and some preliminary evidence illustrating the small sample performance. DEA+ can basically handle multi-output technologies like standard DEA but allows to filter noise, that might have disturbed production and unlike a related approach does not require panel data. Consistency of DEA+ relies on the assumption of i.i.d. distributed and bounded noise and requires radial efficiency measurement. First Monte Carlo experiments show that a DEA+ based average inefficiency estimator performs well for samples of size n=100 in one-output, two-input settings compared to the corresponding Stochastic Frontier Estimator. Sensitivity of DEA+ performance with respect to parametrization of noise is weak, but higher noise contribution requires much larger sample size for satisfactory results. Copyright Kluwer Academic Publishers 1998

Keywords: Stochastic DEA; Consistency; Semi-Parametric Frontier Estimation; Maximum Likelihood Estimation (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (29)

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DOI: 10.1023/A:1018312801700

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