Selecting DEA specifications and ranking units via PCA
Selecting DEA specifications and ranking units via PCA
DEA model selection is problematic. The estimated efficiency for any DMU depends on the inputs and outputs included in the model. It also depends on the number of outputs plus inputs. It is clearly important to select parsimonious specifications and to avoid as far as possible models that assign full high efficiency ratings to DMUs that operate in unusual ways (mavericks). A new method for model selection is proposed in this paper. Efficiencies are calculated for all possible DEA model specifications. The results are analysed using Principal Components Analysis. It is shown that model equivalence or dissimilarity can be easily assessed using this approach. The reasons why particular DMUs achieve a certain level of efficiency with a given model specification become clear. The methodology has the additional advantage of producing DMU rankings.
DEA model selection, data envelopment analysis, efficiency, principal component analysis, cluster analysis
University of Southampton
Serrano Cinca, C.
90e6b01c-17ba-44b6-b723-b18e19ad28bc
Mar Molinero, C.
915e1795-1028-433b-8ec3-b530fb25cbbf
2001
Serrano Cinca, C.
90e6b01c-17ba-44b6-b723-b18e19ad28bc
Mar Molinero, C.
915e1795-1028-433b-8ec3-b530fb25cbbf
Serrano Cinca, C. and Mar Molinero, C.
(2001)
Selecting DEA specifications and ranking units via PCA
(Discussion Papers in Management, M01-3)
Southampton, UK.
University of Southampton
23pp.
Record type:
Monograph
(Discussion Paper)
Abstract
DEA model selection is problematic. The estimated efficiency for any DMU depends on the inputs and outputs included in the model. It also depends on the number of outputs plus inputs. It is clearly important to select parsimonious specifications and to avoid as far as possible models that assign full high efficiency ratings to DMUs that operate in unusual ways (mavericks). A new method for model selection is proposed in this paper. Efficiencies are calculated for all possible DEA model specifications. The results are analysed using Principal Components Analysis. It is shown that model equivalence or dissimilarity can be easily assessed using this approach. The reasons why particular DMUs achieve a certain level of efficiency with a given model specification become clear. The methodology has the additional advantage of producing DMU rankings.
More information
Published date: 2001
Additional Information:
ISSN 1356-3548
Keywords:
DEA model selection, data envelopment analysis, efficiency, principal component analysis, cluster analysis
Identifiers
Local EPrints ID: 35727
URI: http://eprints.soton.ac.uk/id/eprint/35727
ISSN: 1356-3548
PURE UUID: a0511c58-1d31-42f9-b0a4-c4739bf6510c
Catalogue record
Date deposited: 24 May 2006
Last modified: 15 Mar 2024 07:54
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Contributors
Author:
C. Serrano Cinca
Author:
C. Mar Molinero
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