Central bank accountability under adaptive learning

Marine André and Meixing Dai ()

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

Abstract: Using a New Keynesian model, we examine the accountability issue in a delegation framework where private agents form expectations through adaptive learning while the central bank is rational and optimally sets monetary policy under discretion. Learning gives rise to an incentive for the central bank to accommodate less the effect of inflation expectations and cost-push shocks on inflation and induces thus a deviation of endogenous variables from rational expectations equilibrium. To help the central bank to better manage the intratemporal tradeoff, the government should nominate a liberal central banker, i.e., set a negative optimal inflation penalty according to the value of learning coefficient. By reducing the deviation of the feedback effects of inflation expectations and cost-push shocks on inflation and the output gap from the corresponding ones under rational expectations, the optimal inflation penalty allows the economy to be more efficient and improves the social welfare. The main conclusions are valid under both constant- and decreasing-gain learning.

Keywords: Adaptive learning; optimal monetary policy; accountability; inflation penalty; rational expectations. (search for similar items in EconPapers)
JEL-codes: E42 E52 E58 (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-cba, nep-dge, nep-mac and nep-mon
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Persistent link: https://EconPapers.repec.org/RePEc:ulp:sbbeta:2015-32

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