Nested Models and Model Uncertainty
Copyright policy )Nested Models and Model Uncertainty
AbstractUncertainty about the appropriate choice among nested models is a 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 submodels (e.g., those resulting from zero restrictions). Following Sims (, Journal of Economic Dynamics and Control 32, 2460–2475), we treat nested submodels as probability models, and we formalize a procedure that ensures that submodels are not discarded too easily and do matter for optimal policy. For the United States, we find that optimal policy based on our procedure leads to substantial welfare gains compared to the standard procedure.
- University of Amsterdam Netherlands
- European University Institute Italy
- Martin Luther University Halle-Wittenberg Germany
C51, 330, Bayesian model estimation, Optimal monetary policy, model uncertainty, E52, E32
C51, 330, Bayesian model estimation, Optimal monetary policy, model uncertainty, E52, E32
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