Artikel
Fragility of asymptotic agreement under Bayesian learning
Under the assumption that individuals know the conditional distributions of signals given the payoff-relevant parameters, existing results conclude that as individuals observe infinitely many signals, their beliefs about the parameters will eventually merge. We first show that these results are fragile when individuals are uncertain about the signal distributions: given any such model, vanishingly small individual uncertainty about the signal distributions can lead to substantial (non-vanishing) differences in asymptotic beliefs. Under a uniform convergence assumption, we then characterize the conditions under which a small amount of uncertainty leads to significant asymptotic disagreement.
- Sprache
-
Englisch
- Erschienen in
-
Journal: Theoretical Economics ; ISSN: 1555-7561 ; Volume: 11 ; Year: 2016 ; Issue: 1 ; Pages: 187-225 ; New Haven, CT: The Econometric Society
- Klassifikation
-
Wirtschaft
Bayesian Analysis: General
Noncooperative Games
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- Thema
-
Asymptotic disagreement
Bayesian learning
merging of opinions
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Yildiz, Muhamet
Acemoglu, Daron
Chernozhukov, Victor
- Ereignis
-
Veröffentlichung
- (wer)
-
The Econometric Society
- (wo)
-
New Haven, CT
- (wann)
-
2016
- DOI
-
doi:10.3982/TE436
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:44 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Yildiz, Muhamet
- Acemoglu, Daron
- Chernozhukov, Victor
- The Econometric Society
Entstanden
- 2016
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