Rule-Based Monetary Policy Under Central Banking Learning

Working Paper: CEPR ID: DP5056

Authors: Kosuke Aoki; Kalin Nikolov

Abstract: The paper evaluates the performance of three popular monetary policy rules when the central bank is learning about the parameter values of a simple New Keynesian model. The three policies are: (1) the optimal non-inertial rule; (2) the optimal history-dependent rule; (3) the optimal price-level targeting rule. Under rational expectations rules (2) and (3) both implement the fully optimal equilibrium by improving the output-inflation trade off. When imperfect information about the model parameters is introduced, it is found that the central bank makes monetary policy mistakes, which affect welfare to a different degree under the three rules. The optimal history-dependent rule is worst affected and delivers the lowest welfare. Price level targeting performs best under learning and maintains the advantages of conducting policy under commitment. These findings are related to the literatures on feedback control and robustness. The paper argues that adopting integral representations of rules designed under full information is desirable because they deliver the beneficial output-inflation trade-off of commitment policy while being robust to implementation errors.

Keywords: learning; monetary policy rules

JEL Codes: E31; E50


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
central bank's learning process (E58)performance of monetary policy rules (E61)
optimal price level targeting rule (E31)performance compared to optimal history-dependent rule under learning conditions (D91)
optimal history-dependent rule (C61)performance deterioration due to policy mistakes (E65)
systematic monetary policy mistakes (E60)propagation through time under optimal history-dependent rule (C41)
optimal price level targeting rule (E31)mitigate adverse effects of mistakes (D91)

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