Performance estimation when the distribution of inefficiency is unknown

Tsionas, Mike G. (2023) Performance estimation when the distribution of inefficiency is unknown. European Journal of Operational Research, 304 (3). pp. 1212-1222. ISSN 0377-2217

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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/2600/2611

Subjects:

?? productivity and competitivenessstochastic frontier modelsdata envelopment analysis (dea)fast fourier transformempirical characteristic functionmodelling and simulationmanagement science and operations researchinformation systems and management ??

Departments:

Lancaster University Management School > Economics

ID Code:

170328

Deposited By:

ep_importer_pure

Deposited On:

13 May 2022 08:25

Refereed?:

Yes

Published?:

Published

Last Modified:

23 Sep 2024 00:43

URI:

https://eprints.lancs.ac.uk/id/eprint/170328