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Nonlinear models and small sample performance of the generalized method of moments

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dc.contributor.author Ventura, Eva
dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
dc.date.accessioned 2017-07-26T10:50:32Z
dc.date.available 2017-07-26T10:50:32Z
dc.date.issued 1996-09-01
dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=186
dc.identifier.uri http://hdl.handle.net/10230/839
dc.description.abstract In this paper I explore the issue of nonlinearity (both in the data generation process and in the functional form that establishes the relationship between the parameters and the data) regarding the poor performance of the Generalized Method of Moments (GMM) in small samples. To this purpose I build a sequence of models starting with a simple linear model and enlarging it progressively until I approximate a standard (nonlinear) neoclassical growth model. I then use simulation techniques to find the small sample distribution of the GMM estimators in each of the models.
dc.language.iso eng
dc.relation.ispartofseries Economics and Business Working Papers Series; 186
dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.title Nonlinear models and small sample performance of the generalized method of moments
dc.type info:eu-repo/semantics/workingPaper
dc.date.modified 2017-07-23T02:02:43Z
dc.subject.keyword gmm
dc.subject.keyword small sample
dc.subject.keyword simulation
dc.subject.keyword Macroeconomics and International Economics
dc.rights.accessRights info:eu-repo/semantics/openAccess


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