volume 100 pages 157-174

Disinflations in a model of imperfectly anchored expectations

Publication typeJournal Article
Publication date2017-11-01
scimago Q1
wos Q2
SJR2.395
CiteScore4.8
Impact factor2.4
ISSN00142921, 1873572X
Economics and Econometrics
Finance
Abstract
We study disinflations under imperfect credibility of the central bank. We propose a framework to model imperfectly credible announcements and use it to study the distribution of the output cost for a given disinflation. Imperfect credibility is modeled as the extent to which agents rely on adaptive learning to form expectations. Lower credibility increases the mean, variance, and skewness of the distribution of the sacrifice ratio. When credibility is low, disinflations become very costly for adverse realizations of the shocks. But, an opportunistic disinflation, a disinflation implemented after a period of below trend inflation, can significantly lower the sacrifice ratio. With simulated data, we reinterpret the reduced form evidence in sacrifice ratio regressions. Coefficient estimates from these regressions can be misleading for policymakers considering the cost of disinflation.
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GOST Copy
Gibbs C., Kulish M. Disinflations in a model of imperfectly anchored expectations // European Economic Review. 2017. Vol. 100. pp. 157-174.
GOST all authors (up to 50) Copy
Gibbs C., Kulish M. Disinflations in a model of imperfectly anchored expectations // European Economic Review. 2017. Vol. 100. pp. 157-174.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1016/j.euroecorev.2017.08.003
UR - https://doi.org/10.1016/j.euroecorev.2017.08.003
TI - Disinflations in a model of imperfectly anchored expectations
T2 - European Economic Review
AU - Gibbs, Christopher
AU - Kulish, Mariano
PY - 2017
DA - 2017/11/01
PB - Elsevier
SP - 157-174
VL - 100
SN - 0014-2921
SN - 1873-572X
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2017_Gibbs,
author = {Christopher Gibbs and Mariano Kulish},
title = {Disinflations in a model of imperfectly anchored expectations},
journal = {European Economic Review},
year = {2017},
volume = {100},
publisher = {Elsevier},
month = {nov},
url = {https://doi.org/10.1016/j.euroecorev.2017.08.003},
pages = {157--174},
doi = {10.1016/j.euroecorev.2017.08.003}
}