IDEAS home Printed from https://ideas.repec.org/p/ags/quedwp/273459.html

Applications of the Fast Double Bootstrap

Author

Listed:
  • MacKinnon, James

Abstract

The fast double bootstrap, or FDB, is a procedure for calculating bootstrapP values that is much more computationally efficient than the double bootstrap itself. In many cases, it can provide more accurate results than ordinary bootstrap tests. For the fast double bootstrap to be valid, thetest statistic must be asymptotically independent of the random parts of thebootstrap data generating process. This paper presents simulation evidenceon the performance of FDB tests in three cases of interest toeconometricians. One of the cases involves both symmetric and equal-tailbootstrap tests, which, interestingly, can have quite different power properties. Another highlights the importance of imposing the nullhypothesis on the bootstrap DGP.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • MacKinnon, James, 2006. "Applications of the Fast Double Bootstrap," Queen's Economics Department Working Papers 273459, Queen's University - Department of Economics.
    • Handle: RePEc:ags:quedwp:273459
    DOI: 10.22004/ag.econ.273459
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/273459/files/qed_wp_1023.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.273459?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. is not listed on IDEAS
    2. Richard, Patrick, 2009. "Modified fast double sieve bootstraps for ADF tests," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4490-4499, October.
    3. Davidson, Russell & MacKinnon, James G., 2007. "Improving the reliability of bootstrap tests with the fast double bootstrap," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3259-3281, April.

    More about this item

    Keywords

    ;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:quedwp:273459. See general information about how to correct material in RePEc.

    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.

    We have no bibliographic references for this item. You can help adding them by using 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/qedquca.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.