Year: 2016
Type: preprint
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.
Language: English
Subfield: General Decision Sciences
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2237214788