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Confidence Statements for Efficiency Estimates from Stochastic Frontier Models

Author

Listed:
  • William C. Horrace

    (University of Arizona)

  • Peter Schmidt

    (Michigan State University)

Abstract

This paper is an empirical study of the uncertainty associated with estimates from stochastic frontier models. We show how to construct confidence intervals for estimates of technical efficiency levels under different sets of assumptions ranging from the very strong to the relatively weak. We demonstrate empirically how the degree of uncertainty associated with these estimates relates to the strength of the assumptions made and to various features of the data.

Suggested Citation

  • William C. Horrace & Peter Schmidt, 2002. "Confidence Statements for Efficiency Estimates from Stochastic Frontier Models," Econometrics 0206006, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0206006
    Note: Type of Document - Acrobat PDF; prepared on IBM PC; to print on HP; pages: 42; figures: Included. None
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0206/0206006.pdf
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    References listed on IDEAS

    as
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    3. Fare,Rolf & Grosskopf,Shawna & Lovell,C. A. Knox, 2008. "Production Frontiers," Cambridge Books, Cambridge University Press, number 9780521072069, January.
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    7. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    8. repec:cor:louvrp:-1139 is not listed on IDEAS
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    12. KNEIP, Alois & SIMAR, Léopold, 1995. "A General Framework for Frontier Estimation with Panel Data," LIDAM Discussion Papers CORE 1995060, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Confidence intervals; stochastic frontier models; efficiency measurement;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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