Federal Reserve Bank of Richmond
Optimized Taylor Rules for Disinflation When Agents are Learning
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.
Cite this item
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.
- E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
Keywords: Inflation; Monetary policy; Learning; Policy reforms; Transitions
This item with handle RePEc:fip:fedrwp:14-07
is also listed on EconPapers
For corrections, contact Christian Pascasio ()