Tie the straps: uniform bootstrap confidence bands for bounded influence curve estimators
AbstractWe consider theoretical bootstrap \coupling" techniques for nonparametric robust smoothers and quantile regression, and verify the bootstrap improvement. To cope with curse of dimensionality, a variant of \coupling" bootstrap techniques are developed for additive models with both symmetric error distributions and further extension to the quantile regression framework. Our bootstrap method can be used in many situations like constructing con dence intervals and bands. We demonstrate the bootstrap improvement over the asymptotic band theoretically, and also in simulations and in applications to rm expenditures and the interaction of economic sectors and the stock market.
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Bibliographic InfoPaper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2013-047.
Length: 33 pages
Date of creation: Oct 2013
Date of revision:
Nonparametric Regression; Bootstrap; Quantile Regression; Con- dence Bands; Additive Model; Robust Statistics;
Find related papers by JEL classification:
- C00 - Mathematical and Quantitative Methods - - General - - - General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
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- Johnston, Gordon J., 1982. "Probabilities of maximal deviations for nonparametric regression function estimates," Journal of Multivariate Analysis, Elsevier, vol. 12(3), pages 402-414, September.
- Efang Kong & Oliver Linton & Yingcun Xia, 2009.
"Uniform Bahadur Representation for LocalPolynomial Estimates of M-Regressionand Its Application to The Additive Model,"
STICERD - Econometrics Paper Series
/2009/535, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- 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(05), pages 1529-1564, October.
- Sokbae Lee & Joel L. Horowitz, 2004.
"Nonparametric Estimation of an Additive Quantile Regression Model,"
Econometric Society 2004 Far Eastern Meetings
721, Econometric Society.
- Horowitz, Joel L. & Lee, Sokbae, 2005. "Nonparametric Estimation of an Additive Quantile Regression Model," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1238-1249, December.
- Joel Horowitz & Sokbae 'Simon' Lee, 2004. "Nonparametric estimation of an additive quantile regression model," CeMMAP working papers CWP07/04, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Härdle, Wolfgang, 1989. "Asymptotic maximal deviation of M-smoothers," Journal of Multivariate Analysis, Elsevier, vol. 29(2), pages 163-179, May.
- Yishay Yafeh & Oved Yosha, 2003. "Large Shareholders and Banks: Who Monitors and How?," Economic Journal, Royal Economic Society, vol. 113(484), pages 128-146, January.
- Horowitz, Joel L, 2001. "Nonparametric Estimation of a Generalized Additive Model with an Unknown Link Function," Econometrica, Econometric Society, vol. 69(2), pages 499-513, March.
- Newey, Whitney K. & McFadden, Daniel, 1986. "Large sample estimation and hypothesis testing," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 36, pages 2111-2245 Elsevier.
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