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The Stochastic Fluctuation of the Quantile Regression Curve

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Author Info
Wolfgang Härdle
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Abstract

Let (X1, Y1), . . ., (Xn, Yn) be i.i.d. rvs and let l(x) be the unknown p-quantile regression curve of Y on X. A quantile-smoother ln(x) is a localised, nonlinear estimator of l(x). The strong uniform consistency rate is established under general conditions. In many applications it is necessary to know the stochastic fluctuation of the process {ln(x) - l(x)}. Using strong approximations of the empirical process and extreme value theory allows us to consider the asymptotic maximal deviation sup06x61 |ln(x)-l(x)|. The derived result helps in the construction of a uniform confidence band for the quantile curve l(x). This confidence band can be applied as a model check, e.g. in econometrics. An application considers a labour market discrimination effect.

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Publisher Info
Paper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2008-027.

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Length: 28 pages
Date of creation: Mar 2008
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Handle: RePEc:hum:wpaper:sfb649dp2008-027

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Related research
Keywords: Quantile Regression Consistency Rate Confidence Band Check Function Kernel Smoothing Nonparametric Fitting

Find related papers by JEL classification:
C00 - Mathematical and Quantitative Methods - - General - - - General
C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods
J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials

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  1. Cai, Zongwu, 2002. "Regression Quantiles For Time Series," Econometric Theory, Cambridge University Press, vol. 18(01), pages 169-192, March. [Downloadable!]
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This page was last updated on 2008-10-1.


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