How to properly decompose economic efficiency using technical and allocative criteria with non-homothetic DEA technologies

Juan Aparicio*, Jesus T. Pastor, Jose L. Zofio

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

29 Citations (Scopus)

Abstract

We discuss how to properly decompose economic efficiency when the underlying technology is non-homothetic using alternative allocative and technical efficiency criteria. We first show that only under the production of one output and assuming the particular case of constant returns to scale homotheticity, we may claim that the standard radial models correctly measure pure technical efficiency. Otherwise, when non-homotheticity is assumed, we then show that these traditional estimations would measure an undetermined mix of technical and allocative efficiency. To restore a consistent measure of technical efficiency in the non-homothetic case we introduce a new methodology that takes as reference for the economic efficiency decomposition the preservation of the allocative efficiency of firms producing in the interior of the technology. This builds upon the so-called reversed approach recently introduced by Bogetoft et al. (2006) that allows estimating allocative efficiency without presuming that technical efficiency has been already accomplished. We illustrate our methodology within the Data Envelopment Analysis framework adopting the most simple non-homothetic BCC model and a numerical application. In this application we show that there are significant differences in the allocative and technical efficiency scores depending on the approach.

Original languageEnglish
Pages (from-to)882-891
Number of pages10
JournalEuropean Journal of Operational Research
Volume240
Issue number3
DOIs
Publication statusPublished - 1 Feb 2014

Bibliographical note

Funding Information:
We thank three anonymous referees for providing comments and help in improving the contents and presentation of this paper. Additionally, J. Aparicio is grateful to the Generalitat Valenciana for supporting this research with Grant GV/2013/112.

Publisher Copyright:
© 2014 Elsevier B.V. All rights reserved.

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