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Nonparametric Frontier Estimation from Noisy Data

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  • Florens, Jean-Pierre
  • Schwarz, Maik
  • Van Bellegem, Sébastien

Abstract

A new nonparametric estimator of production a frontier is defined and studied when the data set of production units is contaminated by measurement error. The measurement error is assumed to be an additive normal random variable on the input variable, but its variance is unknown. The estimator is a modification of the m-frontier, which necessitates the computation of a consistent estimator of the conditional survival function of the input variable given the output variable. In this paper, the identification and the consistency of a new estimator of the survival function is proved in the presence of additive noise with unknown variance. The performance of the estimator is also studied through simulated data.

Suggested Citation

  • Florens, Jean-Pierre & Schwarz, Maik & Van Bellegem, Sébastien, 2010. "Nonparametric Frontier Estimation from Noisy Data," IDEI Working Papers 625, Institut d'Économie Industrielle (IDEI), Toulouse.
    • Handle: RePEc:ide:wpaper:22801
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    References listed on IDEAS

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    Cited by:

    1. DEVOLDER, Olivier & GLINEUR, François & NESTEROV, Yurii, 2011. "First-order methods of smooth convex optimization with inexact oracle," LIDAM Discussion Papers CORE 2011002, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. NESTEROV, Yurii, 2011. "Random gradient-free minimization of convex functions," LIDAM Discussion Papers CORE 2011001, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Dai, Xiaofeng, 2016. "Non-parametric efficiency estimation using Richardson–Lucy blind deconvolution," European Journal of Operational Research, Elsevier, vol. 248(2), pages 731-739.
    4. Leonardo Andrade Rocha & Ahmad Saeed Khan & Patrícia Verônica Pinheiro Sales Lima & Maria Ester Dal Poz & Fernando Porfirio Soares De Oliveira, 2016. "Corrupção, Burocracia E Outras Falhas Institucionais: O “Câncer” Da Inovação E Do Desenvolvimento," Anais do XLIII Encontro Nacional de Economia [Proceedings of the 43rd Brazilian Economics Meeting] 090, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    5. AGRELL, Per & KASPERZEC, Roman, 2010. "Dynamic joint investments in supply chains under information asymmetry," LIDAM Discussion Papers CORE 2010085, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • P42 - Political Economy and Comparative Economic Systems - - Other Economic Systems - - - Productive Enterprises; Factor and Product Markets; Prices

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