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Uniform Bias Study and Bahadur Representation for Local Polynomial Estimators of the Conditional Quantile Function

Author

Listed:
  • Emmanuel Guerre

    (Queen Mary, University of London)

  • Camille Sabbah

    (Université Pierre et Marie Curie, Paris)

Abstract

This paper investigates the bias and the Bahadur representation of a local polynomial estimator of the conditional quantile function and its derivatives. The bias and Bahadur remainder term are studied uniformly with respect to the quantile level, the covariates and the smoothing parameter. The order of the local polynomial estimator can be higher that the differentiability order of the conditional quantile function. Applications of the results deal with global optimal consistency rates of the local polynomial quantile estimator, performance of random bandwidths and estimation of the conditional quantile density function. The latter allows to obtain a simple estimator of the conditional quantile function of the private values in a first price sealed bids auctions under the independent private values paradigm and risk neutrality.

Suggested Citation

  • Emmanuel Guerre & Camille Sabbah, 2009. "Uniform Bias Study and Bahadur Representation for Local Polynomial Estimators of the Conditional Quantile Function," Working Papers 648, Queen Mary University of London, School of Economics and Finance.
  • Handle: RePEc:qmw:qmwecw:648
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    File URL: https://www.qmul.ac.uk/sef/media/econ/research/workingpapers/2009/items/wp648.pdf
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    References listed on IDEAS

    as
    1. Emmanuel Guerre & Isabelle Perrigne & Quang Vuong, 2000. "Optimal Nonparametric Estimation of First-Price Auctions," Econometrica, Econometric Society, vol. 68(3), pages 525-574, May.
    2. Kong, Efang & Linton, Oliver & Xia, Yingcun, 2010. "Uniform Bahadur Representation For Local Polynomial Estimates Of M-Regression And Its Application To The Additive Model," Econometric Theory, Cambridge University Press, vol. 26(5), pages 1529-1564, October.
    3. Li, Qi & Racine, Jeffrey S, 2008. "Nonparametric Estimation of Conditional CDF and Quantile Functions With Mixed Categorical and Continuous Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 423-434.
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    Cited by:

    1. Kong, Efang & Linton, Oliver & Xia, Yingcun, 2013. "Global Bahadur Representation For Nonparametric Censored Regression Quantiles And Its Applications," Econometric Theory, Cambridge University Press, vol. 29(5), pages 941-968, October.

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    More about this item

    Keywords

    Bahadur representation; Conditional quantile function; Local polynomial estimation; Econometrics of auctions;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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