Inflation targeting as a signaling mechanism

Bedri Kamil Onur Taş*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper theoretically investigates inflation targeting when there is asymmetric information between the Central Bank and the public. The main argument of this study is that the inflation target can be used as a signaling mechanism through which the private sector learns about the private information of the Central Bank about future inflation and output. Thus, inflation targeting increases transparency and this causes the monetary policy actions (changes in the interest rate) to be more effective. I construct a Kalman filter algorithm to analyze the information and learning dynamics between the Central Bank and a representative private-sector agent. An increase (decrease) in the interest rate and the inflation target signals that the Central Bank has private information that inflation and output will be higher (lower) in the future thus the public expect inflation to be higher (lower) in the future. The main results of the paper are as follows. First, the private-sector agents (public) revise their expectations about future inflation and output after observing the actions of the Central Bank: changes in the interest rate and the inflation target. Second, in the case of inflation targeting, the response of inflation to a monetary policy shock (change in the interest rate) is higher than it is in the case of no inflation targeting. So, when there is inflation targeting the interest rate tool of the CB is more effective in decreasing inflation.

Original languageEnglish
Pages (from-to)1-16
Number of pages16
JournalDigital Signal Processing: A Review Journal
Volume22
Issue number1
DOIs
Publication statusPublished - Jan 2012
Externally publishedYes

Keywords

  • Asymmetric information
  • Inflation target
  • Kalman filter
  • Learning
  • Monetary policy

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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