Which moments to match?

dc.contributor.author

Ronald Gallant, A

dc.contributor.author

Tauchen, G

dc.date.accessioned

2010-06-28T18:49:47Z

dc.date.issued

1996-12-01

dc.description.abstract

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. © 1996 Cambridge University Press.

dc.format.mimetype

application/pdf

dc.identifier.issn

0266-4666

dc.identifier.uri

https://hdl.handle.net/10161/2542

dc.language.iso

en_US

dc.publisher

Cambridge University Press (CUP)

dc.relation.ispartof

Econometric Theory

dc.title

Which moments to match?

dc.type

Journal article

pubs.begin-page

657

pubs.end-page

681

pubs.issue

4

pubs.organisational-group

Duke

pubs.organisational-group

Economics

pubs.organisational-group

Faculty

pubs.organisational-group

Trinity College of Arts & Sciences

pubs.publication-status

Published

pubs.volume

12

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