Uniform Bias Study And Bahadur Representation For Local Polynomial Estimators Of The Conditional Quantile Function
AbstractThis 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.
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Bibliographic InfoArticle provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 28 (2012)
Issue (Month): 01 (February)
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Other versions of this item:
- 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.
- 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
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.:
- Marmer, Vadim & Shneyerov, Artyom, 2012.
"Quantile-based nonparametric inference for first-price auctions,"
Journal of Econometrics,
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- Marmer, Vadim & Shneyerov, Artyom, 2006. "Quantile-Based Nonparametric Inference for First-Price Auctions," MPRA Paper 5899, University Library of Munich, Germany, revised 02 Mar 2006.
- repec:cup:cbooks:9780521496032 is not listed on IDEAS
- Emmanuel Guerre & Isabelle Perrigne & Quang Vuong, 2009. "Nonparametric Identification of Risk Aversion in First-Price Auctions Under Exclusion Restrictions," Econometrica, Econometric Society, vol. 77(4), pages 1193-1227, 07.
- 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.
- Emmanuel Guerre & Isabelle Perrigne & Quang Vuong, 2000. "Optimal Nonparametric Estimation of First-Price Auctions," Econometrica, Econometric Society, vol. 68(3), pages 525-574, May.
- Sokbae 'Simon' Lee & Kyungchul Song & Yoon-Jae Whang, 2014.
"Testing for a general class of functional inequalities,"
CeMMAP working papers
CWP09/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Sokbae Lee & Kyungchul Song & Yoon-Jae Whang, 2014. "Testing For A General Class Of Functional Inequalities," KIER Working Papers 889, Kyoto University, Institute of Economic Research.
- Shih-Kang Chao & Katharina Proksch & Holger Dette & Wolfgang Härdle, 2014. "Confidence Corridors for Multivariate Generalized Quantile Regression," SFB 649 Discussion Papers SFB649DP2014-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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