Malmquist indexes using a geometric distance function (GDF)

Portela, Maria C.A.S. and Thanassoulis, Emmanuel (2004). Malmquist indexes using a geometric distance function (GDF). IN: Data envelopment analysis and performance management. Emrouznejad, Ali and Podinovski, Victor (eds) Warwick University.

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.

Divisions: Aston Business School > Operations & information management
Aston Business School
Aston Business School > Operations & information management research group
Event Title: 4th International Symposium of DEA : Data Envelopment Analysis and Performance Management
Event Type: Other
Event Dates: 2004-09-05 - 2004-09-06
Full Text Link: http://deazone. ... ook-deabook2004
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Published Date: 2004-09
Authors: Portela, Maria C.A.S.
Thanassoulis, Emmanuel ( 0000-0002-3769-5374)

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