IDEAS home Printed from https://ideas.repec.org/a/tpr/restat/v72y1990i2p321-27.html
   My bibliography  Save this article

Robust and Partially Adaptive Estimation of Regression Models

Author

Listed:
  • Butler, Richard J, et al

Abstract

It is well known that least squares estimates can be very sensitive to departures from normality. Various robust estimators, such as least absolute deviations, L(superscript "p") estimators or M-estimators provide possible alternatives to least squares when such departures occur. This paper applies a partially adaptive technique to estimate the parameters of William F. Sharpe's market model. This methodology is based on a generalized t-distribution and includes as special cases least squares, least absolute deviation, and L(superscript "p"), as well as some estimation procedures that have bounded and redescending influence functions. Coauthors are James B.McDonald, Ray D. Nelson, and Steven B. White. Copyright 1990 by MIT Press.

Suggested Citation

  • Butler, Richard J, et al, 1990. "Robust and Partially Adaptive Estimation of Regression Models," The Review of Economics and Statistics, MIT Press, vol. 72(2), pages 321-327, May.
  • Handle: RePEc:tpr:restat:v:72:y:1990:i:2:p:321-27
    as

    Download full text from publisher

    File URL: http://links.jstor.org/sici?sici=0034-6535%28199005%2972%3A2%3C321%3ARAPAEO%3E2.0.CO%3B2-P&origin=repec
    File Function: full text
    Download Restriction: Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    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:tpr:restat:v:72:y:1990:i:2:p:321-27. 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: Kelly McDougall (email available below). General contact details of provider: https://direct.mit.edu/journals .

    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.