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dc.contributor.authorBEYER, Andreas
dc.contributor.authorFARMER, Roger E. A.
dc.contributor.authorHENRY, Jérôme
dc.contributor.authorMARCELLINO, Massimiliano
dc.date.accessioned2016-07-07T08:35:15Z
dc.date.available2016-07-07T08:35:15Z
dc.date.issued2007
dc.identifier.urihttps://hdl.handle.net/1814/42360
dc.description.abstractDSGE models are characterized by the presence of expectations as explanatory variables. To use these models for policy evaluation, the econometrician must estimate the parameters of expectation terms. Standard estimation methods have several drawbacks, including possible lack or weakness of identification of the parameters, misspecification of the model due to omitted variables or parameter instability, and the common use of inefficient estimation methods. Several authors have raised concerns over the implications of using inappropriate instruments to achieve identification. In this paper we analyze the practical relevance of these problems and we propose to combine factor analysis for information extraction from large data sets and GMM to estimate the parameters of systems of forward looking equations. Using these techniques, we evaluate the robustness of recent findings on the importance of forward looking components in the equations of a standard New-Keynesian model.
dc.language.isoen
dc.relation.ispartofseriesNBER Working Paper Seriesen
dc.relation.ispartofseries2007/13404en
dc.titleFactor analysis in a model with rational expectations
dc.typeWorking Paper
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