Optimized Taylor rules for disinflation when agents are learning

被引:11
|
作者
Cogley, Timothy [1 ]
Matthes, Christian [2 ]
Sbordone, Argia M. [3 ]
机构
[1] NYU, Dept Econ, New York, NY 10012 USA
[2] Fed Reserve Bank Richmond, Res Dept, Richmond, VA USA
[3] Fed Reserve Bank New York, Res Dept, New York, NY USA
关键词
Inflation; Monetary policy; Learning; Policy reforms; Transitions; ROBUST MONETARY-POLICY; TREND INFLATION; STAGGERED PRICES; MEDIUM-SCALE; EXPECTATIONS; PERSISTENCE; CONVERGENCE; UTILITY; MODEL;
D O I
10.1016/j.jmoneco.2015.02.003
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
When private agents learn a new policy rule, an optimal simple Taylor rule for disinflation differs substantially from that under full information. The central bank can reduce target inflation without much difficulty, but adjusting reaction coefficients on lagged inflation and output is more costly. Temporarily explosive dynamics emerge when there is substantial disagreement between perceived and actual feedback parameters, making the transition highly volatile. The bank copes by choosing reaction coefficients close to the private sector's prior mode, thereby sacrificing long-term performance in exchange for achieving lower transitional volatility. (C) 2015 Elsevier B.V. All rights reserved.
引用
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页码:131 / 147
页数:17
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