DukeSpace

Which Moments to Match?

DukeSpace

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dc.contributor.author Gallant, A. Ronald en_US
dc.contributor.author Tauchen, George en_US
dc.date.accessioned 2010-06-28T18:49:47Z
dc.date.available 2010-06-28T18:49:47Z
dc.date.issued 1996-10 en_US
dc.identifier.uri http://hdl.handle.net/10161/2542
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. en_US
dc.format.extent 270530 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher Econometric Theory en_US
dc.subject generating moment conditions en_US
dc.subject quadrature en_US
dc.subject simulation en_US
dc.title Which Moments to Match? en_US
dc.type Journal Article en_US
dc.department Economics

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