IDEAS home Printed from https://ideas.repec.org/a/bes/jnlbes/v14y1996i3p367-73.html
   My bibliography  Save this article

Small-Sample Properties of Estimators of Nonlinear Models of Covariance Structure

Author

Listed:
  • Clark, Todd E

Abstract

This study examines the small sample properties of generalized method of moments (GMM) and maximood likelihood estimators of nonlinear models of covariance structure. It considers the properties of estimates for a simple factor model, the Hall and Mishkin (1982) model of consumption and income, and a simple structural vector-autoregression-type error model. This analysis establishes three basic results. First, optimally weighted GMM estimation yields some biased parameter estimates. Second, GMM estimation yields a model specification test with size substantially greater than the asymptotic size. Third, these problems are mitigated when the number of overidentifying restrictions in a model is reduced.

Suggested Citation

  • Clark, Todd E, 1996. "Small-Sample Properties of Estimators of Nonlinear Models of Covariance Structure," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 367-373, July.
  • Handle: RePEc:bes:jnlbes:v:14:y:1996:i:3:p:367-73
    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.

    Other versions of this item:

    More about this item

    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:bes:jnlbes:v:14:y:1996:i:3:p:367-73. 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: (Christopher F. Baum). General contact details of provider: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main .

    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.