Advanced Search
MyIDEAS: Login

The Generalized Method of Moments in the Bayesian Framework and a Model of Moment Selection Criterion

Contents:

Author Info

  • Jae-Young Kim

    (SUNY at Albany)

Registered author(s):

    Abstract

    While the classical framework has a rich set of limited information procedures such as GMM and other related methods, the situation is not so in the Bayesian framework. We develop a limited information procedure in the Bayesian framework that does not require the knowledge of the likelihood function. The developed procedure is a Bayesian counterpart of the classical GMM but has advantages over the classical GMM in practical applications. The necessary limited information for our approach is a set of moment conditions, instead of the likelihood function, which has a counterpart in the classical GMM. Such moment conditions in the Bayesian framework are obtained from the equivalence condition of the Bayes' estimator and the GMM estimator. From such moment conditions, a posterior probability measure is derived that forms the basis of our limited information Bayesian procedure. This limited information posterior has some desirable properties for small and large sample analyses. An alternative approach is also provided in this paper for deriving a limited information posterior based on a variant of the empirical likelihood method where an empirical likelihood is obtained from the moment conditions of GMM. This alternative approach yields asymptotically the same result as the approach explained above. Based on our limited information method, we develop a procedure for selecting the moment for GMM. This moment selection procedure is an extension of the Bayesian model selection procedure to the Bayesian semi-parametric, limited information framework. It is shown that under some conditions the proposed moment selection procedure is a consistent decision rule.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://fmwww.bc.edu/RePEc/es2000/1779.pdf
    File Function: main text
    Download Restriction: no

    Bibliographic Info

    Paper provided by Econometric Society in its series Econometric Society World Congress 2000 Contributed Papers with number 1779.

    as in new window
    Length:
    Date of creation: 01 Aug 2000
    Date of revision:
    Handle: RePEc:ecm:wc2000:1779

    Contact details of provider:
    Phone: 1 212 998 3820
    Fax: 1 212 995 4487
    Email:
    Web page: http://www.econometricsociety.org/pastmeetings.asp
    More information through EDIRC

    Related research

    Keywords:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. Song Chen, 1993. "On the accuracy of empirical likelihood confidence regions for linear regression model," Annals of the Institute of Statistical Mathematics, Springer, vol. 45(4), pages 621-637, December.
    2. Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-08, May.
    3. Yuichi Kitamura & Peter C.B. Phillips, 1994. "Fully Modified IV, GIVE and GMM Estimation with Possibly Non-Stationary Regressions and Instruments," Cowles Foundation Discussion Papers 1082, Cowles Foundation for Research in Economics, Yale University.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:ecm:wc2000:1779. 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).

    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.

    If references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link to it, you can help with 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 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.