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Monetary Policy with a Wider Information Set: a Bayesian Model Averaging Approach

Fabio Milani ()

Macroeconomics from University Library of Munich, Germany

Abstract: Monetary policy has been usually analyzed in the context of small macroeconomic models where central banks are allowed to exploit a limited amount of information. Under these frameworks, researchers typically derive the optimality of aggressive monetary rules, contrasting with the observed policy conservatism and interest rate smoothing. This paper allows the central bank to exploit a wider information set, while taking into account the associated model uncertainty, by employing Bayesian Model Averaging with Markov Chain Model Composition (MC³). In this enriched environment, we derive the optimality of smoother and more cautious policy rates, together with clear gains in macroeconomic efficiency.

Keywords: Bayesian model averaging; leading indicators; model uncertainty; optimal monetary policy; interest rate smoothing. (search for similar items in EconPapers)
JEL-codes: C11 C15 C52 E52 E58 (search for similar items in EconPapers)
Pages: 43 pages
Date: 2004-01-18
New Economics Papers: this item is included in nep-mac and nep-mon
Note: Type of Document - pdf; prepared on Win2000; pages: 43; figures: included
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Citations: View citations in EconPapers (8) Track citations by RSS feed

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https://econwpa.ub.uni-muenchen.de/econ-wp/mac/papers/0401/0401004.pdf (application/pdf)

Related works:
Journal Article: MONETARY POLICY WITH A WIDER INFORMATION SET: A BAYESIAN MODEL AVERAGING APPROACH (2008) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpma:0401004

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