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Data Envelopment Analysis in a Stochastic Setting: The right answer from the wrong model?

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  • Gstach, Dieter

Abstract

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.

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  • Gstach, Dieter, 1994. "Data Envelopment Analysis in a Stochastic Setting: The right answer from the wrong model?," Department of Economics Working Paper Series 29, WU Vienna University of Economics and Business.
    • Handle: RePEc:wiw:wus005:6304
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    3. Haefke, Christian & Helmenstein, Christian, 1996. "Neural Networks in the Capital Markets: An Application to Index Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 9(1), pages 37-50, February.
    4. Bellak, Christian & Cantwell, John, 1995. "Measuring the Importance of International Production: The Re-estimation of Foreign Direct Investment at Current Values," Department of Economics Working Paper Series 30, WU Vienna University of Economics and Business.
    5. Martin Currie & Ingrid Kubin, 2005. "Fixed Price Dynamics versus Flexible Price Dynamics," Department of Economics Working Papers wuwp089, Vienna University of Economics and Business, Department of Economics.

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