Performance estimation when the distribution of inefficiency is unknown

Tsionas, Mike G. (2022) Performance estimation when the distribution of inefficiency is unknown. European Journal of Operational Research. ISSN 0377-2217 (In Press)

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Abstract

We show how to compute inefficiency or performance scores when the distribution of the one-sided error component in Stochastic Frontier Models (SFMs) is unknown; and we do the same with Data Envelopment Analysis (DEA). Our procedure, which is based on the Fast Fourier Transform (FFT), utilizes the empirical characteristic function of the residuals in SFMs or efficiency scores in DEA. The new techniques perform well in Monte Carlo experiments and deliver reasonable results in an empirical application to large U.S. banks. In both cases, deconvolution of DEA scores with the FFT brings the results much closer to the inefficiency estimates from SFM.

Item Type:
Journal Article
Journal or Publication Title:
European Journal of Operational Research
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1800/1802
Subjects:
ID Code:
170328
Deposited By:
Deposited On:
13 May 2022 08:25
Refereed?:
Yes
Published?:
In Press
Last Modified:
27 May 2022 23:43