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dc.contributor.author Gallant, AR
dc.contributor.author Tauchen, G
dc.date.accessioned 2010-03-09T15:29:20Z
dc.date.issued 1999-09-01
dc.identifier.citation Journal of Econometrics, 1999, 92 (1), pp. 149 - 172
dc.identifier.issn 0304-4076
dc.identifier.uri http://hdl.handle.net/10161/1900
dc.description.abstract The asymptotic relative efficiency of efficient method of moments when implemented with a seminonparametric auxiliary model is compared to that of conventional method of moments when implemented with polynomial moment functions. Because the expectations required by these estimators can be computed by simulation, these two methods are commonly used to estimate the parameters of nonlinear latent variables models. The comparison is for the models in the Marron-Wand test suite, a scale mixture of normals, and the second largest order statistic of the lognormal distribution. The latter models are representative of financial market data and auction data, respectively, which are the two most common applications of simulation estimators. Efficient method of moments dominates conventional method of moments over these models. © 1999 Elsevier Science S.A. All rights reserved.
dc.format.extent 149 - 172
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.relation.ispartof Journal of Econometrics
dc.title The relative efficiency of method of moments estimators
dc.type Journal Article
dc.department Economics
pubs.issue 1
pubs.organisational-group /Duke
pubs.organisational-group /Duke/Faculty
pubs.organisational-group /Duke/Trinity College of Arts & Sciences
pubs.organisational-group /Duke/Trinity College of Arts & Sciences/Economics
pubs.publication-status Published
pubs.volume 92

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