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

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  • Dieter Gstach

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

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  • Dieter Gstach, 1998. "Another Approach to Data Envelopment Analysis in Noisy Environments: DEA+," Journal of Productivity Analysis, Springer, vol. 9(2), pages 161-176, March.
    • Handle: RePEc:kap:jproda:v:9:y:1998:i:2:p:161-176
    DOI: 10.1023/A:1018312801700
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