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Federal Reserve Bank of Richmond
Working Paper
Optimized Taylor Rules for Disinflation When Agents are Learning
Timothy Cogley
Christian Matthes
Argia M. Sbordone
Abstract

Highly volatile transition dynamics can emerge when a central bank disinflates while operating without full transparency. In our model, a central bank commits to a Taylor rule whose form is known but whose coefficient are not. Private agents learn about policy parameters via Bayesian updating. Under McCallum's (1999) timing protocol, temporarily explosive dynamics can arise, making the transition highly volatile. Locally-unstable dynamics emerge when there is substantial disagreement between actual and perceived feedback parameters. The central bank can achieve low average inflation, but its ability to adjust reaction coefficients is more limited.


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Timothy Cogley & Christian Matthes & Argia M. Sbordone, Optimized Taylor Rules for Disinflation When Agents are Learning, Federal Reserve Bank of Richmond, Working Paper 14-7, 15 Mar 2014.
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Subject headings:
Keywords: Inflation; Monetary policy; Learning; Policy reforms; Transitions
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