Malmquist indexes using a geometric distance function (GDF)

Maria C.A.S. Portela, Emmanuel Thanassoulis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Traditional approaches to calculate total factor productivity change through Malmquist indexes rely on distance functions. In this paper we show that the use of distance functions as a means to calculate total factor productivity change may introduce some bias in the analysis, and therefore we propose a procedure that calculates total factor productivity change through observed values only. Our total factor productivity change is then decomposed into efficiency change, technological change, and a residual effect. This decomposition makes use of a non-oriented measure in order to avoid problems associated with the traditional use of radial oriented measures, especially when variable returns to scale technologies are to be compared.
Original languageEnglish
Title of host publicationData envelopment analysis and performance management
EditorsAli Emrouznejad, Victor Podinovski
PublisherWarwick University
Pages231-238
Number of pages8
ISBN (Print)0-90268-373-X
Publication statusPublished - Sep 2004
Event4th International Symposium of DEA : Data Envelopment Analysis and Performance Management - Birmingham, United Kingdom
Duration: 5 Sep 20046 Sep 2004

Other

Other4th International Symposium of DEA : Data Envelopment Analysis and Performance Management
CountryUnited Kingdom
CityBirmingham
Period5/09/046/09/04

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  • Research Output

    Data envelopment analysis and performance management

    Emrouznejad, A. (ed.) & Podinovski, V. (ed.), Sep 2004, Warwick University. 421 p.

    Research output: Book/ReportAnthology

  • Cite this

    Portela, M. C. A. S., & Thanassoulis, E. (2004). Malmquist indexes using a geometric distance function (GDF). In A. Emrouznejad, & V. Podinovski (Eds.), Data envelopment analysis and performance management (pp. 231-238). Warwick University.