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On the consistency of the DEA-based average efficiency bootstrap

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  • Mickael Lothgren

Abstract

It is shown that the bootstrap method should be applied with care for the Data Envelopment Analysis (DEA) estimator of average technical efficiency if the production frontier is stochastic. A stochastic production frontier leads to an inconsistency of the DEA estimator, which in turn leads to inconsistent and potentially highly misleading bootstrap confidence intervals. A Monte Carlo simulation study reveals that the empirical coverage accuracy of the bootstrap confidence intervals approaches zero as the sample size increases, even for small contributions of frontier variance to total frontier and efficiency variance.

Suggested Citation

  • Mickael Lothgren, 2000. "On the consistency of the DEA-based average efficiency bootstrap," Applied Economics Letters, Taylor & Francis Journals, vol. 7(1), pages 53-57.
    • Handle: RePEc:taf:apeclt:v:7:y:2000:i:1:p:53-57
    DOI: 10.1080/135048500352103
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    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    3. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
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    Cited by:

    1. A. Assaf & K. M. Matawie, 2010. "A bootstrapped metafrontier model," Applied Economics Letters, Taylor & Francis Journals, vol. 17(6), pages 613-617.

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