Learning in an estimated medium-scale DSGE model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11640%2F12%3A00373840" target="_blank" >RIV/00216208:11640/12:00373840 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.jedc.2011.01.016" target="_blank" >http://dx.doi.org/10.1016/j.jedc.2011.01.016</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.jedc.2011.01.016" target="_blank" >10.1016/j.jedc.2011.01.016</a>
Alternative languages
Result language
angličtina
Original language name
Learning in an estimated medium-scale DSGE model
Original language description
We evaluate the empirical relevance of learning by private agents in an estimated medium-scale DSGE model.We replace the standard rational expectations assumption in the Smets and Wouters (2007) model by a constant gain learning mechanism. If agents knowthe correct structure of the model and only learn about the parameters, both expectation mechanisms produce very similar results, and only the transition dynamics that are generated by specific initial beliefs seem to improve the fit. If, instead, agents use only a reduced information set in forming the perceived law of motion, the implied model dynamics change and, depending on the specification of the initial beliefs, the marginal likelihood of the model can improve significantly.These best-fitting models add additional persistence to the dynamics and this reduces the gap between the IRFs of the DSGE model and the more data-driven DSGE-VAR model. However, the learning dynamics do not systematically alter the estimated structural para
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
AH - Economics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GCP402%2F11%2FJ018" target="_blank" >GCP402/11/J018: Comparative Approach to Macroeconomic Modeling and Policy Analysis: Introducing Adaptive Learning</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Journal of Economic Dynamics & Control
ISSN
0165-1889
e-ISSN
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Volume of the periodical
36
Issue of the periodical within the volume
1
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
21
Pages from-to
26-46
UT code for WoS article
000298571200002
EID of the result in the Scopus database
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