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Nested Models and Model Uncertainty
Author(s) -
Kriwoluzky Alexander,
Stoltenberg Christian A.
Publication year - 2016
Publication title -
the scandinavian journal of economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.725
H-Index - 64
eISSN - 1467-9442
pISSN - 0347-0520
DOI - 10.1111/sjoe.12134
Subject(s) - economics , econometrics , welfare , mathematical economics , space (punctuation) , economic model , computer science , microeconomics , market economy , operating system
Abstract Uncertainty 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 ([Sims, C. A., 2008], 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.