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A Bias-Corrected Nonparametric Envelopment Estimator Of Frontiers


  • Bădin, Luiza
  • Simar, Léopold


In efficiency analysis, the production frontier is defined as the set of the most efficient alternatives among all possible combinations in the input-output space. The nonparametric envelopment estimators rely on the assumption that all the observations fall on the same side of the frontier. The free disposal hull (FDH) estimator of the attainable set is the smallest free disposal set covering all the observations. By construction, the FDH estimator is an inward-biased estimator of the frontier.

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  • Bădin, Luiza & Simar, Léopold, 2009. "A Bias-Corrected Nonparametric Envelopment Estimator Of Frontiers," Econometric Theory, Cambridge University Press, vol. 25(05), pages 1289-1318, October.
  • Handle: RePEc:cup:etheor:v:25:y:2009:i:05:p:1289-1318_09

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    References listed on IDEAS

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    Cited by:

    1. Graziella Bonanno & Domenico De Giovanni & Filippo Domma, 2017. "The ‘wrong skewness’ problem: a re-specification of stochastic frontiers," Journal of Productivity Analysis, Springer, vol. 47(1), pages 49-64, February.
    2. Aldea, Anamaria & Ciobanu, Anamaria & Stancu, Ion, 2012. "The Renewable Energy Development: A Nonparametric Efficiency Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 5-19, March.
    3. Halkos, George E. & Tzeremes, Nickolaos G., 2011. "A conditional nonparametric analysis for measuring the efficiency of regional public healthcare delivery: An application to Greek prefectures," Health Policy, Elsevier, vol. 103(1), pages 73-82.
    4. Astrid Cullmann & Christian Hirschhausen, 2008. "Efficiency analysis of East European electricity distribution in transition: legacy of the past?," Journal of Productivity Analysis, Springer, vol. 29(2), pages 155-167, April.
    5. Halkos, George & Tzeremes, Nickolaos, 2009. "Exploring the effect of countries’ economic prosperity on their biodiversity performance," MPRA Paper 32102, University Library of Munich, Germany.
    6. Xia, X.H. & Chen, Y.B. & Li, J.S. & Tasawar, H. & Alsaedi, A. & Chen, G.Q., 2014. "Energy regulation in China: Objective selection, potential assessment and responsibility sharing by partial frontier analysis," Energy Policy, Elsevier, vol. 66(C), pages 292-302.
    7. Byeong Park & Léopold Simar & Valentin Zelenyuk, 2015. "Categorical data in local maximum likelihood: theory and applications to productivity analysis," Journal of Productivity Analysis, Springer, vol. 43(2), pages 199-214, April.
    8. George Halkos & Nickolaos Tzeremes, 2010. "The effect of foreign ownership on SMEs performance: An efficiency analysis perspective," Journal of Productivity Analysis, Springer, vol. 34(2), pages 167-180, October.
    9. Calogero Guccio & Marco Ferdinando Martorana & Isidoro Mazza, 2016. "Efficiency assessment and convergence in teaching and research in Italian public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1063-1094, June.

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