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Learning and Signals under Discretionary Monetary Policy
Author(s) -
Marzioni Stefano
Publication year - 2014
Publication title -
economic notes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.274
H-Index - 19
eISSN - 1468-0300
pISSN - 0391-5026
DOI - 10.1111/ecno.12020
Subject(s) - monetary policy , inflation (cosmology) , new keynesian economics , central bank , private sector , economics , inflation targeting , relevance (law) , stability (learning theory) , monetary economics , order (exchange) , adaptive learning , signal (programming language) , forward guidance , econometrics , macroeconomics , computer science , finance , credit channel , physics , machine learning , artificial intelligence , theoretical physics , political science , law , programming language , economic growth
This paper aims at assessing the relevance of communicating central bank's forecasts to the private sector under discretionary monetary policy. In a New Keynesian environment, the central bank and the private sector have different information sets. The private sector uses the central bank's expectations as a signal in order to update its priors, which are constituted by standard adaptive learning expectations. E‐stability is positively affected by a high correlation between actual inflation and the signal about inflation. Numerical simulations show that the presence of signals is beneficial both in the long and in the short run.

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