We describe an intuitive, simple, and systematic approach to generating moment conditions for generalized method of moments (GMM) estimation of the parameters of a structural model. The idea is to use the score of a density that has an analytic expression to define the GMM criterion. The auxiliary model that generates the score should closely approximate the distribution' of the observed data but is not required to nest it. If the auxiliary model nests the structural model then the estimator is as efficient as maximum likelihood. The estimator is advantageous when expectations under a structural model can be computed by simulation, by quadrature, or by analytic expressions but the likelihood cannot be computed easily.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. 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.
Publisher Info
Article provided by Cambridge University Press in its journal Econometric Theory.
Volume (Year): 12 (1996) Issue (Month): 04 (October) Pages: 657-681 Download reference. The following formats are available: HTML
(with abstract),
plain text
(with abstract),
BibTeX,
RIS (EndNote, RefMan, ProCite),
ReDIF
Contact details of provider: Postal: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK Fax: +44 (0)1223 325150 Email: Web page: http://journals.cambridge.org/jid_ECT
For technical questions regarding this item, or to correct its listing, contact: (Mike Eden).
Related research
Keywords:
Other versions of this item:
Cited by: (explanations, 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.) This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.