Arbeitspapier
Non-Bayesian updating in a social learning experiment
In our laboratory experiment, subjects, in sequence, have to predict the value of a good. We elicit the second subject's belief twice: first ("first belief"), after he observes his predecessor's action; second ("posterior" belief.), after he observes his private signal. Our main result is that the second subjects weigh the private signal as a Bayesian agent would do when the signal confirms their first belief; they overweight the signal when it contradicts their first belief. This way of updating, incompatible with Bayesianism, can be explained by multiple priors on the predecessor's rationality and a generalization of the Maximum Likelihood Updating rule. In another experiment, we directly test this theory and find support for it.
- Language
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Englisch
- Bibliographic citation
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Series: cemmap working paper ; No. CWP39/18
- Classification
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Wirtschaft
- Event
-
Geistige Schöpfung
- (who)
-
De Filippis, Roberta
Guarinno, Antonio
Jehiel, Philippe
Kitagawa, Toru
- Event
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Veröffentlichung
- (who)
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Centre for Microdata Methods and Practice (cemmap)
- (where)
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London
- (when)
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2018
- DOI
-
doi:10.1920/wp.cem.2018.3918
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- De Filippis, Roberta
- Guarinno, Antonio
- Jehiel, Philippe
- Kitagawa, Toru
- Centre for Microdata Methods and Practice (cemmap)
Time of origin
- 2018
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