Nonlinear models and small sample performance of the generalized method of moments
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- dc.contributor.author Ventura, Evaca
- 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.date.modified 2017-07-23T02:02:43Z
- 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.format.mimetype application/pdfca
- dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=186
- dc.identifier.uri http://hdl.handle.net/10230/839
- 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.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
- dc.subject.keyword gmm
- dc.subject.keyword small sample
- dc.subject.keyword simulation
- dc.subject.keyword Macroeconomics and International Economics
- dc.title Nonlinear models and small sample performance of the generalized method of momentsca
- dc.type info:eu-repo/semantics/workingPaper