Bayesian Bootstrap of the Quantile Regression Estimator: A Large Sample Study
AbstractThe large sample property of the Bayesian bootstrap distribution of the quantile regression estimator is investigated. When the pair of dependent and independent variables are resampled, the Bayesian bootstrap is shown to converge weakly in probability to the limiting distribution of the quantile regression estimator. The Bayesian bootstrap thus has the same asymptotic distribution as the Frequentist bootstrap. In addition, the median of the Bayesian bootstrap distribution has the same asymptotic distribution as the quantile regression estimator. Copyright 1997 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoArticle provided by Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association in its journal International Economic Review.
Volume (Year): 38 (1997)
Issue (Month): 4 (November)
Contact details of provider:
Postal: 160 McNeil Building, 3718 Locust Walk, Philadelphia, PA 19104-6297
Phone: (215) 898-8487
Fax: (215) 573-2057
Web page: http://www.econ.upenn.edu/ier
More information through EDIRC
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Alexandre Belloni & Victor Chernozhukov & Iván Fernández-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP77/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Joshua Angrist & Victor Chernozhukov & Ivan Fernandez-Val, 2004.
"Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure,"
NBER Working Papers
10428, National Bureau of Economic Research, Inc.
- Joshua Angrist & Victor Chernozhukov & Iván Fernández-Val, 2006. "Quantile Regression under Misspecification, with an Application to the U.S. Wage Structure," Econometrica, Econometric Society, vol. 74(2), pages 539-563, 03.
- Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.
- Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
- Giuseppe Ragusa, 2007. "Bayesian Likelihoods for Moment Condition Models," Working Papers 060714, University of California-Irvine, Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or ().
If references are entirely missing, you can add them using this form.