Publication
Malmquist indexes using a geometric distance function (GDF)
dc.contributor.author | Portela, Maria | |
dc.contributor.author | Thanassoulls, Emmanuel | |
dc.date.accessioned | 2011-09-08T11:01:38Z | |
dc.date.available | 2011-09-08T11:01:38Z | |
dc.date.issued | 2004 | |
dc.description.abstract | Traditional approaches to calculate anal factor pmthwtivity change through Malmquist indexes rely on distance fin chaos. In this paper we show that the use of distance Junctions as a means to calculate total factor productivity change 'nth, introduce some bias in the analysis. and tnerefire tee 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 effimt. This decomposition makes use of a non-oriented measure in (E yler to avoid problems associated with the traditional use of radial oriented measures. especially when variable returns to seale technologies are to be compared. | por |
dc.identifier.citation | PORTELA, Maria; THANASSOULIS, Emmanuel - Malmquist indexes using a geometric distance function (GDF). In 4th International Symposium On DEA: Data Envelopment Analysis And Performance Management, Birmingham, United Kingdom, 5-6 September, 2004. – In [Proceedings of the] Data Envelopment Analysis and Performance Management. Aston Business School, 2004. p. 231-238 | por |
dc.identifier.uri | http://hdl.handle.net/10400.14/5284 | |
dc.language.iso | eng | por |
dc.peerreviewed | yes | por |
dc.publisher | Aston Business School | por |
dc.title | Malmquist indexes using a geometric distance function (GDF) | por |
dc.type | conference object | |
dspace.entity.type | Publication | |
rcaap.rights | openAccess | por |
rcaap.type | conferenceObject | por |
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