Nonparametric Frontier Estimation: A Conditional Quantile-based Approach
AbstractIn frontier analysis, most of the nonparametric approaches (free disposal hull FDH , data envelopment analysis DEA ) are based on envelopment ideas, and their statistical theory is now mostly available. However, by construction, they are very sensitive to outliers. Recently, a robust nonparametric estimator has been suggested by Cazals, Florens, and Simar (2002, Journal of Econometrics 1, 1 25). In place of estimating the full frontier, they propose rather to estimate an expected frontier of order m. Similarly, we construct a new nonparametric estimator of the efficient frontier. It is based on conditional quantiles of an appropriate distribution associated with the production process. We show how these quantiles are interesting in efficiency analysis. We provide the statistical theory of the obtained estimators. We illustrate with some simulated examples and a frontier analysis of French post offices, showing the advantage of our estimators compared with the estimators of the expected maximal output frontiers of order m.We thank J.P. Florens for helpful discussions and C. Cazals for providing the post office data set. We also are very grateful to the referees for useful suggestions.
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Bibliographic InfoPaper provided by University of Toulouse 1 Capitole in its series Open Access publications from University of Toulouse 1 Capitole with number http://neeo.univ-tlse1.fr/1388/.
Date of creation: 2005
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Publication status: Published in Econometric Theory (2005) v., p.358-389
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Web page: http://www.univ-tlse1.fr/
Other versions of this item:
- Aragon, Y. & Daouia, A. & Thomas-Agnan, C., 2005. "Nonparametric Frontier Estimation: A Conditional Quantile-Based Approach," Econometric Theory, Cambridge University Press, vol. 21(02), pages 358-389, April.
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