Are forecasting models usable for policy analysis?
AbstractIn this article, Christopher A. Sims argues the answer to his title is yes. Sims explains that any decisionmaking model must incorporate some identifying assumptions to enable it to forecast the effects of alternative decisions. He argues that although all identifying assumptions in econometric policymaking models are of uncertain validity, those incorporated in vector autoregression (VAR) forecasting models have the advantage of allowing their uncertainty to be measured. Sims concludes by demonstrating a method for identifying a small macroeconomic VAR model so that it can be used to analyze monetary policy
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Bibliographic InfoArticle provided by Federal Reserve Bank of Minneapolis in its journal Quarterly Review.
Volume (Year): (1986)
Issue (Month): Win ()
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