Learning, robust monetray policy and the merit of precaution

Marine André and Meixing Dai ()

Working Papers of BETA from Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg

Abstract: We study in a New Keynesian framework the consequences of adaptative learning for the design of robust monetary policy. Compared to rational expectations, the fact that private follows adaptative learning gives the central bank an additional intertemporal trade-off between optimal behavior thanks to ability to manipulate future inflation expectations. We show that adaptative learning imposes a more restrictive constraint on monetary policy robustness to ensure the dynamic stability of the equilibrium than under rational expectations and weakens the argument in favor of a more aggressive monetary policy when the central bank takes account of model misspecifications.

Keywords: robust control; model uncertainty; adaptative learning; optimal monetary policy. (search for similar items in EconPapers)
JEL-codes: C62 D83 D84 E52 E58 (search for similar items in EconPapers)
Date: 2016
New Economics Papers: this item is included in nep-cba, nep-dge, nep-mac and nep-mon
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Related works:
Journal Article: Learning, robust monetary policy and the merit of precaution (2018)
Working Paper: Learning, robust monetary policy and the merit of precaution (2018)
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Persistent link: https://EconPapers.repec.org/RePEc:ulp:sbbeta:2016-54

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