Learning, robust monetary policy and the merit of precaution

Marine André and Meixing Dai ()

Post-Print from HAL

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

Keywords: Robust control; Optimal monetary policy; Model uncertainty; Adaptive learning (search for similar items in EconPapers)
Date: 2018
Note: View the original document on HAL open archive server: https://hal.science/hal-03030047v1
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Published in B.E. Journal of Macroeconomics, 2018, 18 (2), 21 p. ⟨10.1515/bejm-2016-0236⟩

Downloads: (external link)
https://hal.science/hal-03030047v1/document (application/pdf)

Related works:
Journal Article: Learning, robust monetary policy and the merit of precaution (2018)
Working Paper: Learning, robust monetray policy and the merit of precaution (2016)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03030047

DOI: 10.1515/bejm-2016-0236

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().