Advanced Search
MyIDEAS: Login

Bayesian Bootstrap of the Quantile Regression Estimator: A Large Sample Study

Contents:

Author Info

  • Hahn, Jinyong
Registered author(s):

    Abstract

    The 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 Info

    To 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 Info

    Article 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)
    Pages: 795-808

    as in new window
    Handle: RePEc:ier:iecrev:v:38:y:1997:i:4:p:795-808

    Contact details of provider:
    Postal: 160 McNeil Building, 3718 Locust Walk, Philadelphia, PA 19104-6297
    Phone: (215) 898-8487
    Fax: (215) 573-2057
    Email:
    Web page: http://www.econ.upenn.edu/ier
    More information through EDIRC

    Order Information:
    Email:
    Web: http://www.blackwellpublishing.com/subs.asp?ref=0020-6598

    Related research

    Keywords:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. 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.
    2. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    3. Alexandre Belloni & Victor Chernozhukov & Iván Fernández-Val & Christian Hansen, 2013. "Program evaluation with high-dimensional data," CeMMAP working papers CWP57/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Giuseppe Ragusa, 2007. "Bayesian Likelihoods for Moment Condition Models," Working Papers 060714, University of California-Irvine, Department of Economics.
    5. Chernozhukov, Victor & Hong, Han, 2003. "An MCMC approach to classical estimation," Journal of Econometrics, Elsevier, vol. 115(2), pages 293-346, August.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:ier:iecrev:v:38:y:1997:i:4:p:795-808. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or ().

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.