IDEAS home Printed from https://ideas.repec.org/p/sce/scecf1/191.html
   My bibliography  Save this paper

Small sample properties of panel time-series estimators with I(1) errors

Author

Listed:
  • Jerry Coakley, Ana-Maria Fuertes, Ron Smith

Abstract

Monte Carlo simulations are used to explore the small-sample properties of a mean group and two pooled panel estimators of a regression coefficient when the regressor is I(1). We compare and contrast the effect of I(0) and I(1) errors and homogeneous and heterogeneous coefficients in a design based on two typical PPP panels. The results confirm that the asymptotic theory is relevant to practical applications. With I(0) errors and homogeneous coefficients, the estimators are unbiased, dispersion depends on the signal-noise ratio and falls at rate T(rootN) as expected. With I(1) errors and no cointegration, dispersion falls at rate rootN. When heterogeneity is introduced with I(0) errors, the dispersion of the pooled estimators falls at rate root N, but that of the mean group continues to fall at rate T(rootN). Finally, the pooled estimators are likely to lead to distorted inference both in the case of I(1) errors and the case of I(0) errors with heterogeneous coefficients case. The mean group estimators are, however, are generally correctly sized.

Suggested Citation

  • Jerry Coakley, Ana-Maria Fuertes, Ron Smith, 2001. "Small sample properties of panel time-series estimators with I(1) errors," Computing in Economics and Finance 2001 191, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:191
    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

    Monte Carlo; response surface; spurious regression; PPP;
    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
    • F31 - International Economics - - International Finance - - - Foreign Exchange

    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:sce:scecf1:191. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.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.