IDEAS home Printed from
   My bibliography  Save this paper

Bootstrap Methods for Inference in a SUR model with Autocorrelated Disturbances


  • Clarisse Messemer
  • Richard Parks


Although the Parks (1967) estimator for a SUR model with AR disturbances is efficient both asymptotically and in small samples, Kmenta and Gilbert (1970) and more recently Beck and Katz (1995) note that estimated standard errors tend to be biased downward as compared with the true variability of the estimates. This bias leads to tests that show over-rejection and to confidence intervals that are too small. We suggest bootstrapping the tests to correct this inference problem. After illustrating the over rejection associated with the estimated asymptotic standard errors, we develop a bootstrap approach to inference for this model, illustrate its use, and show using Monte Carlo methods that the bootstrap gives rejection probabilities close to the nominal level chosen by the researcher.

Suggested Citation

  • Clarisse Messemer & Richard Parks, 2004. "Bootstrap Methods for Inference in a SUR model with Autocorrelated Disturbances," Working Papers UWEC-2004-24, University of Washington, Department of Economics.
  • Handle: RePEc:udb:wpaper:uwec-2004-24

    Download full text from publisher

    File URL:
    Download Restriction: no


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

    Cited by:

    1. Ana Rodríguez-Álvarez & Ignacio Rosal & José Baños-Pino, 2007. "The cost of strikes in the Spanish mining sector: modelling an undesirable input with a distance function," Journal of Productivity Analysis, Springer, vol. 27(1), pages 73-83, February.

    More about this item


    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:udb:wpaper:uwec-2004-24. 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: (Michael Goldblatt). 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.