Global Bahadur representation for nonparametric censored regression quantiles and its applications

Efang Kong, Oliver Linton and Yingcun Xia
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Efang Kong: Institute for Fiscal Studies
Yingcun Xia: Institute for Fiscal Studies

No CWP33/11, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

Abstract:

This paper is concerned with the nonparametric estimation of regression quantiles where the response variable is randomly censored. Using results on the strong uniform convergence of U-processes, we derive a global Bahadur representation for the weighted local polynomial estimators, which is sufficiently accurate for many further theoretical analyses including inference. We consider two applications in detail: estimation of the average derivative, and estimation of the component functions in additive quantile regression models.

Date: 2011-11-03
New Economics Papers: this item is included in nep-ecm
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http://cemmap.ifs.org.uk/wps/cwp3311.pdf (application/pdf)

Related works:
Journal Article: GLOBAL BAHADUR REPRESENTATION FOR NONPARAMETRIC CENSORED REGRESSION QUANTILES AND ITS APPLICATIONS (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:ifs:cemmap:33/11

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