IDEAS home Printed from https://ideas.repec.org/p/kud/kuiedp/0726.html

Selecting a Regression Saturated by Indicators

Author

Listed:
  • David F. Hendry

    (Oxford University)

  • Søren Johansen

    (Department of Economics, University of Copenhagen)

  • Carlos Santos

    (Portuguese Catholic University)

Abstract

We consider selecting a regression model, using a variant of Gets, when there are more variables than observations, in the special case that the variables are impulse dummies (indicators) for every observation. We show that the setting is unproblematic if tackled appropriately, and obtain the finite-sample distribution of estimators of the mean and variance in a simple location-scale model under the null that no impulses matter. A Monte Carlo simulation confirms the null distribution, and shows power against an alternative of interest.

Suggested Citation

  • David F. Hendry & Søren Johansen & Carlos Santos, 2007. "Selecting a Regression Saturated by Indicators," Discussion Papers 07-26, University of Copenhagen. Department of Economics.
    • Handle: RePEc:kud:kuiedp:0726
    as

    Download full text from publisher

    File URL: http://www.econ.ku.dk/english/research/publications/wp/2007/0726.pdf/
    Download Restriction: no
    ---><---

    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. Collier, Paul & Hoeffler, Anke, 2009. "Testing the neocon agenda: Democracy in resource-rich societies," European Economic Review, Elsevier, vol. 53(3), pages 293-308, April.
    3. Bhattacharyya, Sambit & Hodler, Roland, 2010. "Natural resources, democracy and corruption," European Economic Review, Elsevier, vol. 54(4), pages 608-621, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:kud:kuiedp:0726. 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: Thomas Hoffmann (email available below). General contact details of provider: https://edirc.repec.org/data/okokudk.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.