Data Envelopment Analysis in a Stochastic Setting: The right answer from the wrong model?
Data envelopment analysis (DEA) is compared to stochastic production function estimation (SPFE) in a noisy setting. The statistic of interest is the average efficiency estimator. Monte-Carlo simulations show that the mean squared error of the DEA-estimator even for considerable noise remains below t...
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| Format: | Others |
| Language: | en |
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Inst. für Volkswirtschaftstheorie und -politik, WU Vienna University of Economics and Business
1994
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| Online Access: | http://epub.wu.ac.at/6304/1/WP_29.pdf |
| Summary: | Data envelopment analysis (DEA) is compared to stochastic production function estimation (SPFE) in a noisy setting. The statistic of interest is the average efficiency estimator. Monte-Carlo simulations show that the mean squared error of the DEA-estimator even for considerable noise remains below the MSE of the SPFE analogue. A bootstrapping approach is designed to get some first-step statistical underpinning of this DEA average efficiency estimator. The coverage of the bootstrapping approximation to the distribution of this estimator is shown to be fairly good. === Series: Department of Economics Working Paper Series |
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