Learning with uncertain inflation target

被引:0
|
作者
Marzioni, Stefano [1 ,3 ]
Traficante, Guido [2 ,4 ]
机构
[1] LUISS Guido Carli, CASMEF, Rome, Italy
[2] European Univ Rome, CASMEF, Rome, Italy
[3] LUISS Guido Carli, Viale Romania 32, I-00197 Rome, Italy
[4] European Univ Rome, Univ Europea Roma, Via Aldobrandeschi 190, I-00163 Rome, Italy
关键词
Kalman filter; Adaptive learning; Policy targets; MONETARY-POLICY;
D O I
10.1016/j.iref.2022.11.031
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper studies the effects of a temporary increase in the inflation target in a model with adaptive learning and imperfect credibility of the central bank. In such a setup the private sector has to learn the model governing the economy and assess if the change in the interest rate is due to a standard interest rate shock or to a persistent shock to the inflation target. We find that the analytical condition that guarantees asymptotical E-stability under full credibility is the same that we obtain for the calibrated version of our model under imperfect credibility. Under full credibility the transition to the long-run equilibrium is faster and the variance of inflation is lower. Our results are consistent with the view that increasing the inflation target can be used as a policy instrument without unanchoring expectations.
引用
收藏
页码:624 / 634
页数:11
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