The Simar and Wilson’s Bootstrap DEA approach: a critique
AbstractIn this paper we provide a critique on certain aspects of Simar and Wilson’s methodologies on bootstrap DEA. In particular, we argue that the bootstrap bias has a completely different nature compared to the DEA bias. This imposes a question about the validity of the twice “bias-corrected” efficiency scores of Simar and Wilson (1998) as well as about the consistency of Simar and Wilson’s (2000) confidence intervals which both use this assumption. Moreover, we examine the extent to which the complicated procedure of smoothing the empirical distribution is necessary. We provide evidence by performing an extensive Monte Carlo experiment over three different populations and three different model dimensions. We follow an approach of moment comparison which has not been used in previous studies as the less reliable “coverage probabilities” have been used instead. Our results offer a deep insight on the workings of bootstrap DEA, while they confirm our arguments and suggest that the practice of smoothing the empirical distribution should be avoided.
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Bibliographic InfoPaper provided by Cardiff University, Cardiff Business School, Economics Section in its series Cardiff Economics Working Papers with number E2012/19.
Length: 29 pages
Date of creation: Aug 2012
Date of revision: Nov 2012
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Web page: http://business.cardiff.ac.uk/research/academic-sections/economics/working-papers
More information through EDIRC
Data Envelopment Analysis; Efficiency; Bootstrap; Bootstrap DEA; Monte Carlo;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
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