Asymptotic behavior of regression quantiles in non-stationary, dependent cases
AbstractRegression quantiles provide a natural and powerful approach for robust analysis of the general linear model. However, departures from independence and stationarity of the errors can have an extremely potent effect on statistical analysis. Here, a Bahadur representation for regression quantiles is provided for error processes which are highly non-stationary (i.e., for which there is a nonvanishing bias term) and which are close to being m-dependent. The conditions for dependence are based on a decomposition of Chanda, Puri, and Ruymgaart which covers linear processes; and, hence, includes ARMA processes.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 38 (1991)
Issue (Month): 1 (July)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Gourieroux, C. & Jasiak, J., 2008.
"Dynamic quantile models,"
Journal of Econometrics,
Elsevier, vol. 147(1), pages 198-205, November.
- Tae-Hwan Kim, & Christophe Muller, 2012.
"Bias Transmission and Variance Reduction in Two-Stage Quantile Regression,"
AMSE Working Papers
1221, Aix-Marseille School of Economics, Marseille, France.
- Tae-Hwan Kim & Christophe Muller, 2012. "Bias Transmission and Variance Reduction in Two-Stage Quantile Regression," Working Papers halshs-00793372, HAL.
- Komunjer, Ivana, 2002.
"Quasi-Maximum Likelihood Estimation for Conditional Quantiles,"
1139, California Institute of Technology, Division of the Humanities and Social Sciences.
- Komunjer, Ivana, 2005. "Quasi-maximum likelihood estimation for conditional quantiles," Journal of Econometrics, Elsevier, vol. 128(1), pages 137-164, September.
- Gounder, Rukmani & Xing, Zhongwei, 2012. "Impact of education and health on poverty reduction: Monetary and non-monetary evidence from Fiji," Economic Modelling, Elsevier, vol. 29(3), pages 787-794.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007.
"Quantile and probability curves without crossing,"
CeMMAP working papers
CWP10/07, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2010. "Quantile and Probability Curves without Crossing," Sciences Po publications info:hdl:2441/5rkqqmvrn4t, Sciences Po.
- Victor Chernozhukov & Ivan Fernandez-Val & Alfred Galichon, 2007. "Quantile And Probability Curves Without Crossing," Boston University - Department of Economics - Working Papers Series WP2007-011, Boston University - Department of Economics.
- Fitzenberger, Bernd, 1998. "The moving blocks bootstrap and robust inference for linear least squares and quantile regressions," Journal of Econometrics, Elsevier, vol. 82(2), pages 235-287, February.
- Zernov, Serguei & Zinde-Walsh, Victoria & Galbraith, John W., 2009. "Asymptotics for estimation of quantile regressions with truncated infinite-dimensional processes," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 497-508, March.
- Neocleous, Tereza & Portnoy, Stephen, 2008. "On monotonicity of regression quantile functions," Statistics & Probability Letters, Elsevier, vol. 78(10), pages 1226-1229, August.
- Fitzenberger, Bernd, 1994. "A note on estimating censored quantile regressions," Discussion Papers 14, University of Konstanz, Center for International Labor Economics (CILE).
- Komunjer, Ivana & Vuong, Quang, 2010. "Efficient estimation in dynamic conditional quantile models," Journal of Econometrics, Elsevier, vol. 157(2), pages 272-285, August.
- Mukherjee, Kanchan, 2000. "Linearization Of Randomly Weighted Empiricals Under Long Range Dependence With Applications To Nonlinear Regression Quantiles," Econometric Theory, Cambridge University Press, vol. 16(03), pages 301-323, June.
- repec:spo:wpecon:info:hdl:2441/5rkqqmvrn4tl22s9mc4b6ga2g is not listed on IDEAS
- George Kouretas & Leonidas Zarangas, 2005. "Conditional autoregressive valu at risk by regression quantile: Estimatingmarket risk for major stock markets," Working Papers 0521, University of Crete, Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.