Monetary Policy with Model Uncertainty: Distribution Forecast Targeting

Lars E.O. Svensson () and Noah Williams ()

No 11733, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: We examine optimal and other monetary policies in a linear-quadratic setup with a relatively general form of model uncertainty, so-called Markov jump-linear-quadratic systems extended to include forward-looking variables. The form of model uncertainty our framework encompasses includes: simple i.i.d. model deviations; serially correlated model deviations; estimable regime-switching models; more complex structural uncertainty about very different models, for instance, backward- and forward-looking models; time-varying central-bank judgment about the state of model uncertainty; and so forth. We provide an algorithm for finding the optimal policy as well as solutions for arbitrary policy functions. This allows us to compute and plot consistent distribution forecasts---fan charts---of target variables and instruments. Our methods hence extend certainty equivalence and "mean forecast targeting" to more general certainty non-equivalence and "distribution forecast targeting."

JEL-codes: E42 E52 E58 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-cba, nep-for, nep-mac and nep-mon
Date: 2005-11
Note: EFG IFM ME
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Related works:
Working Paper: Monetary Policy with Model Uncertainty: Distribution Forecast Targeting (2007)
Working Paper: Monetary policy with model uncertainty: distribution forecast targeting (2005)
Working Paper: Monetary Policy with Model Uncertainty: Distribution Forecast Targeting (2005)
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