Journal article
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 case of rational expectations, where the memory of the endogenous variable is determined exogenously.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Accepted manuscript, pdf, 356.6KB, Terms of use)
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(Preview, Accepted manuscript, pdf, 241.1KB, Terms of use)
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- Publisher copy:
- 10.1016/j.jeconom.2017.01.001
Authors
+ European Commission
More from this funder
- Funding agency for:
- Mavroeidis, S
- Grant:
- FP7 Marie Curie Fellowship CIG 293675
- Publisher:
- Elsevier
- Journal:
- Journal of Econometrics More from this journal
- Volume:
- 198
- Issue:
- 1
- Pages:
- 1–9
- Publication date:
- 2017-01-18
- Acceptance date:
- 2017-01-07
- DOI:
- EISSN:
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1872-6895
- ISSN:
-
0304-4076
- Keywords:
- Pubs id:
-
pubs:668636
- UUID:
-
uuid:21b3fbd1-aef4-4ef8-8b3e-9e4411490b99
- Local pid:
-
pubs:668636
- Source identifiers:
-
668636
- Deposit date:
-
2017-01-09
Terms of use
- Copyright holder:
- Elsevier BV
- Copyright date:
- 2017
- Notes:
- Copyright © 2017 Elsevier B.V. This is the accepted manuscript version of the article. The final version is available online from Elsevier at: https://doi.org/10.1016/j.jeconom.2017.01.001
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