Survey expectations, learning and inflation dynamics
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985998%3A_____%2F25%3A00639779" target="_blank" >RIV/67985998:_____/25:00639779 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11640/25:00646392
Result on the web
<a href="https://doi.org/10.1016/j.euroecorev.2025.105118" target="_blank" >https://doi.org/10.1016/j.euroecorev.2025.105118</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.euroecorev.2025.105118" target="_blank" >10.1016/j.euroecorev.2025.105118</a>
Alternative languages
Result language
angličtina
Original language name
Survey expectations, learning and inflation dynamics
Original language description
We propose a framework that exploits survey data on inflation expectations to refine the identification of processes that drive inflation in DSGE models. By decomposing fundamental markup shocks into persistent and transitory components, our approach effectively integrates timely survey information about the nature of inflation shocks, enhancing forecasts of inflation and other macroeconomic variables. Models with expectations based on a learning setup can more effectively utilize signals from the combined datasets of realized inflation and survey forecasts compared to their Rational Expectations counterparts. The learning model’s ability to generate time variation in the perceived inflation target, inflation persistence, and sensitivity to various shocks enables it to detect changes in the fundamental processes driving inflation. These features help overcome limitations of survey data and enhance forecast accuracy, particularly during periods when survey forecasts exhibit systematic prediction errors. Specifically, the model with learning successfully identifies the more persistent nature of the recent inflation surge.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50202 - Applied Economics, Econometrics
Result continuities
Project
<a href="/en/project/LX22NPO5101" target="_blank" >LX22NPO5101: The National Institute for Research on the Socioeconomic Impact of Diseases and Systemic Risks</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
European Economic Review
ISSN
0014-2921
e-ISSN
1873-572X
Volume of the periodical
180
Issue of the periodical within the volume
November
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
35
Pages from-to
105118
UT code for WoS article
001590412900001
EID of the result in the Scopus database
2-s2.0-105017613148