Nested Models and Model Uncertainty

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Show simple item record KRIWOLUZKY, Alexander STOLTENBERG, Christian A. 2009-10-20T13:48:09Z 2009-10-20T13:48:09Z 2009
dc.identifier.issn 1725-6704
dc.description.abstract Uncertainty 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.mimetype application/pdf
dc.language.iso en en
dc.relation.ispartofseries EUI ECO en
dc.relation.ispartofseries 2009/37 en
dc.rights info:eu-repo/semantics/openAccess
dc.subject E32 en
dc.subject C51 en
dc.subject E52 en
dc.subject Optimal monetary policy en
dc.subject model uncertainty en
dc.subject Bayesian model estimation en
dc.title Nested Models and Model Uncertainty en
dc.type Working Paper en
dc.neeo.contributor STOLTENBERGZ|Christian A.|aut|
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