IDEAS home Printed from https://ideas.repec.org/p/hhs/hastef/0022.html
   My bibliography  Save this paper

A Comparison between bias Approximations Applied to Bivariate VAR Models

Author

Listed:
  • Brännström, Tomas

    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

Bivariate VAR models are Monte Carlo simulated and OLS estimated, The resulting biases are used to compare two alternative approximations to the bias. They are found to be equivalent for first-order models, whereas for second-order models Nicholls and Pope's approximation outperforms Tjostheim and Paulsen's approximation, although the difference is negligible. This being the case when approximations are based on true parameters as well as when they are based on estimates, any of the two approximation can be used to construct bias-reduced estimates as outlined in an earlier paper, leading to better estimates both in terms of bias and mean square error than the original OLS estimate. Finally, using a more correct version of Nicholls and Pope's approximation turns out to improve results only marginally for second-order models, and for first-order models they appear to deteriorate.

Suggested Citation

  • Brännström, Tomas, 1994. "A Comparison between bias Approximations Applied to Bivariate VAR Models," SSE/EFI Working Paper Series in Economics and Finance 22, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0022
    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

    VAR models; Monte Carlo simulation; bias approximation and reduction;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

    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:hhs:hastef:0022. 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: Helena Lundin (email available below). General contact details of provider: https://edirc.repec.org/data/erhhsse.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.