IDEAS home Printed from https://ideas.repec.org/p/exe/wpaper/9406.html
   My bibliography  Save this paper

The Asymptotic Influence of VAR Dimension on Estimator Biases

Author

Listed:
  • Abadir, Karim
  • Hadri, K.
  • Tzavalis, E.

Abstract

We show that in a purely nonstationary Vector Autoregression (VAR), the biases of Maximum Likelihood and Least Squares Estimators are asymptotically proportional to the dimension of the system, even when the equations and regressors are generated independantly of each other. When some stable linear combinations exist, as when the variables are cointegrated, these biases are in general asymptotically proportional to the sum of the characteristic roots of the VAR. Adding irrelevant variables to a VAR is thus shown to have more serious negative consequences in integrated time series than in classical ergodic or cross section analyses.

Suggested Citation

  • Abadir, Karim & Hadri, K. & Tzavalis, E., 1994. "The Asymptotic Influence of VAR Dimension on Estimator Biases," Discussion Papers 9406, University of Exeter, Department of Economics.
    • Handle: RePEc:exe:wpaper:9406
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below 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.

    More about this item

    Keywords

    time series ; econometrics;

    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:exe:wpaper:9406. 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: Sebastian Kripfganz (email available below). General contact details of provider: https://edirc.repec.org/data/deexeuk.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.