Research Output per year
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.
|Title of host publication||Data envelopment analysis and performance management|
|Editors||Ali Emrouznejad, Victor Podinovski|
|Number of pages||8|
|Publication status||Published - Sep 2004|
|Event||4th International Symposium of DEA : Data Envelopment Analysis and Performance Management - Birmingham, United Kingdom|
Duration: 5 Sep 2004 → 6 Sep 2004
|Other||4th International Symposium of DEA : Data Envelopment Analysis and Performance Management|
|Period||5/09/04 → 6/09/04|
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.