Regularization of nonparametric frontier estimators
AbstractIn production theory and efficiency analysis, we estimate the production frontier, the locus of the maximal attainable level of an output (the production), given a set of inputs (the production factors). In other setups, we estimate rather an input (or cost) frontier, the minimal level of the input (cost) attainable for a given set of outputs (goods or services produced). In both cases the problem can be viewed as estimating a surface under shape constraints (monotonicity, …). In this paper we derive the theory of an estimator of the frontier having an asymptotic normal distribution. It is based on the order-m partial frontier where we let the order m to converge to infinity when n→∞ but at a slow rate. The final estimator is then corrected for its inherent bias. We thus can view our estimator as a regularized frontier. In addition, the estimator is more robust to extreme values and outliers than the usual nonparametric frontier estimators, like FDH and than the unregularized order-mn estimator of Cazals et al. (2002) converging to the frontier with a Weibull distribution if mn→∞ fast enough when n→∞. The performances of our estimators are evaluated in finite samples and compared to other estimators through some Monte-Carlo experiments, showing a better behavior (in terms of robustness, bias, MSE and achieved coverage of the resulting confidence intervals). The practical implementation and the robustness properties are illustrated through simulated data sets but also with a real data set.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 168 (2012)
Issue (Month): 2 ()
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Web page: http://www.elsevier.com/locate/jeconom
Production function; Free Disposal Hull; Nonparametric frontier; Robust estimation; Extreme value index;
Other versions of this item:
- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2009. "Regularization of Nonparametric Frontier Estimators," IDEI Working Papers 614, Institut d'Économie Industrielle (IDEI), Toulouse.
- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2009. "Regularization of Nonparametric Frontier Estimators," TSE Working Papers 10-168, Toulouse School of Economics (TSE).
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Daouia, Abdelaati & Simar, Leopold, 2007. "Nonparametric efficiency analysis: A multivariate conditional quantile approach," Journal of Econometrics, Elsevier, vol. 140(2), pages 375-400, October.
- Alois Kneip & Léopold Simar & Paul W. Wilson, 2006.
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Bonn Econ Discussion Papers
bgse12_2006, University of Bonn, Germany.
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- Daouia, Abdelaati & Simar, Léopold, 2005. "Robust nonparametric estimators of monotone boundaries," Journal of Multivariate Analysis, Elsevier, vol. 96(2), pages 311-331, October.
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- Simar, Léopold & Vanhems, Anne, 2010. "Probabilistic Characterization of Directional Distances and their Robust Versions," TSE Working Papers 10-195, Toulouse School of Economics (TSE).
- Anna Simoni & Jean-Pierre Florens, 2013. "Regularizing Priors for Linear Inverse Problems," THEMA Working Papers 2013-32, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
- Girard, Stéphane & Guillou, Armelle & Stupfler, Gilles, 2013. "Frontier estimation with kernel regression on high order moments," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 172-189.
- 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.
- Jean-Pierre Florens & Anna Simoni, 2013. "Regularizing Priors for Linear Inverse Problems," Working Papers hal-00873180, HAL.
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