IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v74y1997i0p239-25710.1023-a1018974405520.html
   My bibliography  Save this article

Estimation and testing in least absolute value regression with serially correlated disturbances

Author

Listed:
  • Terry Dielman
  • Elizabeth Rose

Abstract

Least absolute value (LAV) regression provides a robust alternative to least squares, particularly when the disturbances follow distributions that are nonnormal and subject to outliers. While inference in least squares estimation is well-understood, inferential procedures in the context of LAV estimation have not been studied as extensively, particularly in the presence of non-independent disturbances. In this work, we study three alternative significance test procedures in LAV regression, along with two approaches used to correct for serial correlation. The study is based on large-scale Monte Carlo simulations, and comparisons are made based on both observed significance levels and power. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Terry Dielman & Elizabeth Rose, 1997. "Estimation and testing in least absolute value regression with serially correlated disturbances," Annals of Operations Research, Springer, vol. 74(0), pages 239-257, November.
    • Handle: RePEc:spr:annopr:v:74:y:1997:i:0:p:239-257:10.1023/a:1018974405520
    DOI: 10.1023/A:1018974405520
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1023/A:1018974405520
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1023/A:1018974405520?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
    ---><---

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

    Citations

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


    Cited by:

    1. Khaled Elsayed, 2007. "Does CEO Duality Really Affect Corporate Performance?," Corporate Governance: An International Review, Wiley Blackwell, vol. 15(6), pages 1203-1214, November.
    2. Mike G. Tsionas, 2021. "Multi-criteria optimization in regression," Annals of Operations Research, Springer, vol. 306(1), pages 7-25, November.

    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:spr:annopr:v:74:y:1997:i:0:p:239-257:10.1023/a:1018974405520. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.