IDEAS home Printed from
   My bibliography  Save this paper

Using GMM when testing for a unit root in panels where the time-series dimension is fixed


  • Edith Madsen

    (Institute of Economics, University of Copenhagen)


In this paper we investigate GMM-based unit root inference in an autoregressive panel data model with individual-specific levels. We consider tests based on GMM estimators of the AR parameter and moment condition tests. The limiting distributions of the corresponding test statistics are derived when the AR parameter is unity and local-to-unity. This provides information about which statistics lead to valid test procedures. The performance of the valid tests in terms of their local power can then be compared. The results show that the GMM estimator of the AR parameter based on the Arellano-Bover type moment conditions, expressing that lagged differences are used as instruments for the equations in levels, can be used to detect a unit root. On the other hand, the widely used GMM estimator of the AR parameter based on the Arellano-Bond type moment conditions, expressing that lagged levels are used as instruments for the equations in first-differences, can not be used for this purpose. Instead a moment condition test of the hypothesis that the Arellano-Bond type moment conditions do not identify the AR parameter is valid as a unit root test. Finally, a simulation study demonstrates that the local power of the tests provides good approximations of their actual power in finite samples.

Suggested Citation

  • Edith Madsen, 2003. "Using GMM when testing for a unit root in panels where the time-series dimension is fixed," CAM Working Papers 2003-11, University of Copenhagen. Department of Economics. Centre for Applied Microeconometrics.
  • Handle: RePEc:kud:kuieca:2003_11

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    dynamic panel data model; unit roots; GMM estimation; local alternatives; weak instruments;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models


    Access and download statistics


    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:kud:kuieca:2003_11. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Thomas Hoffmann). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.