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dc.contributor.authorKRIWOLUZKY, Alexander
dc.contributor.authorSTOLTENBERG, Christian A.
dc.date.accessioned2009-10-20T13:48:09Z
dc.date.available2009-10-20T13:48:09Z
dc.date.issued2009
dc.identifier.issn1725-6704
dc.identifier.urihttp://hdl.handle.net/1814/12694
dc.description.abstractUncertainty about the appropriate choice among nested models is a central concern for optimal policy when policy prescriptions from those models differ. The standard procedure is to specify a prior over the parameter space ignoring the special status of some sub-models, e.g. those resulting from zero restrictions. This is especially problematic if a model's generalization could be either true progress or the latest fad found to fit the data. We propose a procedure that ensures that the specified set of sub-models is not discarded too easily and thus receives no weight in determining optimal policy. We find that optimal policy based on our procedure leads to substantial welfare gains compared to the standard practice.en
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.relation.ispartofseriesEUI ECOen
dc.relation.ispartofseries2009/37en
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectE32en
dc.subjectC51en
dc.subjectE52en
dc.subjectOptimal monetary policyen
dc.subjectmodel uncertaintyen
dc.subjectBayesian model estimationen
dc.titleNested Models and Model Uncertaintyen
dc.typeWorking Paperen
dc.neeo.contributorSTOLTENBERGZ|Christian A.|aut|
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