Models, Inattention and Expectation Updates

Raffaella Giacomini (), Vasiliki Skreta and Javier Turen

No 1602, Discussion Papers from Centre for Macroeconomics (CFM)

Abstract: We formulate a theory of expectation updating that fits the dynamics of accuracy and disagreement in a new survey dataset where agents can update at any time while observing each other's expectations. Agents use heterogeneous models and can be inattentive but, when updating, they follow Bayes' rule and assign homogeneous weights to public information. Our empirical findings suggest that agents do not herd and, despite disagreement, they place high faith in their models, whereas during a crisis they lose this faith and undergo a paradigm shift. This simple, "micro-founded" theory could enhance the explanatory power of macroeconomic and finance models.

Keywords: Bayesian Learning; Information Rigidities; Heterogeneous Agents; Expectation Formation; Disagreement; Forecast Accuracy; Herding (search for similar items in EconPapers)
JEL-codes: D80 D83 E27 E37 (search for similar items in EconPapers)
Pages: 45 pages
Date: 2015-12
New Economics Papers: this item is included in nep-mac and nep-ore
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Citations: View citations in EconPapers (5)

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Related works:
Working Paper: Models, inattention and expectation updates (2016)
Working Paper: Models, Inattention and Expectation Updates (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:cfm:wpaper:1602

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