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Learning can generate long memory

Abstract:

We study learning dynamics in a prototypical representative-agent forward-looking model in which agents’ beliefs are updated using linear learning algorithms. We show that learning in this model can generate long memory endogenously, without any persistence in the exogenous shocks, depending on the weights agents place on past observations when they update their beliefs, and on the magnitude of the feedback from expectations to the endogenous variable. This is distinctly different from the ca...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.jeconom.2017.01.001

Authors


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Institution:
University of Oxford
Oxford college:
University College
Role:
Author
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Funding agency for:
Mavroeidis, S
Grant:
FP7 Marie Curie Fellowship CIG 293675
Publisher:
Elsevier Publisher's website
Journal:
Journal of Econometrics Journal website
Volume:
198
Issue:
1
Pages:
1–9
Publication date:
2017-01-18
Acceptance date:
2017-01-07
DOI:
EISSN:
1872-6895
ISSN:
0304-4076
Source identifiers:
668636
Keywords:
Pubs id:
pubs:668636
UUID:
uuid:21b3fbd1-aef4-4ef8-8b3e-9e4411490b99
Local pid:
pubs:668636
Deposit date:
2017-01-09

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