Arbeitspapier

Operationalizing reverse Bayesianism

Karni and Viero (2013) propose a model of belief revision under growing awareness reverse Bayesianism which posits that as a person becomes aware of new acts, consequences, or act-consequence links, she revises her beliefs over an expanded state space in a way that preserves the relative likelihoods of events in the original state space. A key limitation of the model is that reverse Bayesianism alone does not fully determine the revised probability distribution. We provide an assumption act independence that imposes additional restrictions on reverse Bayesian belief revision. We show that under act independence, knowledge of the probabilities of new events in the expanded state space is sufficient to fully determine the revised probability distribution in each case of growing awareness. We thereby operationalize the reverse Bayesian model for applications. To illustrate how act independence operationalizes reverse Bayesianism, we consider the law and economics problem of optimal safety regulation.

Language
Englisch

Bibliographic citation
Series: CeDEx Discussion Paper Series ; No. 2020-18

Classification
Wirtschaft
Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
Regulated Industries and Administrative Law
Subject
act independence
reverse Bayesianism
safety regulation
unawareness

Event
Geistige Schöpfung
(who)
Chakravarty, Surajeet
Kelsey, David
Teitelbaum, Joshua C.
Event
Veröffentlichung
(who)
The University of Nottingham, Centre for Decision Research and Experimental Economics (CeDEx)
(where)
Nottingham
(when)
2020

Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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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

  • Chakravarty, Surajeet
  • Kelsey, David
  • Teitelbaum, Joshua C.
  • The University of Nottingham, Centre for Decision Research and Experimental Economics (CeDEx)

Time of origin

  • 2020

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