Belief Updating: Inference versus Forecast Revision
Abstract/Contents
- Abstract
- Individual forecasts of economic variables show widespread overreaction to news, but laboratory experiments on belief updating typically find underinference from signals. We provide new experimental evidence to connect these two seemingly inconsistent phenomena. Building on a classic experimental paradigm, we study how people make inferences and revise forecasts in the same information environment. Subjects underreact to signals when inferring about underlying states, but overreact to signals when revising forecasts about future outcomes. This gap in belief updating is largely driven by the use of different simplifying heuristics for the two tasks. Additional treatments link our results to the difficulty of recognizing the conceptual connection between making inferences and revising forecasts.
Description
| Type of resource | text |
|---|---|
| Date created | August 9, 2021 |
Creators/Contributors
| Author | Fan, Tony Q. |
|---|---|
| Author | Liang, Yucheng |
| Author | Peng, Cameron |
| Organizer of meeting | Bernheim, B. Douglas |
| Organizer of meeting | Beshears, John |
| Organizer of meeting | Crawford, Vincent |
| Organizer of meeting | Laibson, David |
| Organizer of meeting | Malmendier, Ulrike |
Subjects
| Subject | economics |
|---|---|
| Genre | Text |
| Genre | Working paper |
| Genre | Grey literature |
Bibliographic information
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- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution 4.0 International license (CC BY).
Preferred citation
- Preferred citation
- Fan, T., Liang, Y., and Peng, C. (2022). Belief Updating: Inference versus Forecast Revision. Stanford Digital Repository. Available at https://purl.stanford.edu/ng088wz4065
Collection
SITE Conference 2021
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