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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
Version:
Accepted Manuscript

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Publisher copy:
10.1016/j.jeconom.2017.01.001

Authors


Chevillon, G More by this author
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Department:
University College
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Funding agency for:
Mavroeidis, S
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
Pubs id:
pubs:668636
URN:
uri:21b3fbd1-aef4-4ef8-8b3e-9e4411490b99
UUID:
uuid:21b3fbd1-aef4-4ef8-8b3e-9e4411490b99
Local pid:
pubs:668636

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