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Theoretical Economics
Article . 2022 . Peer-reviewed
License: CC BY NC
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Article . 2022
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EconStor
Article . 2022
License: CC BY NC
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Monologues, dialogues, and common priors

Authors: Di Tillio, Alfredo; Lehrer, Ehud; Samet, Dov;

Monologues, dialogues, and common priors

Abstract

The main purpose of this paper is to provide a simple criterion enabling to conclude that two agents do not share a common prior. The criterion is simple, as it does not require information about the agents' knowledge and beliefs, but rather only the record of a dialogue between the agents. In each stage of the dialogue, the agents tell each other the probability they ascribe to a fixed event and update their beliefs about the event. To characterize dialogues consistent with a common prior, we first study monologues, which are sequences of probabilities assigned by a single agent to a given event in an exogenous learning process. A dialogue is consistent with a common prior if and only if each selection sequence from the two monologues comprising the dialogue is itself a monologue.

Country
Italy
Keywords

joint fluctuation, Bayesian dialogue, ddc:330, Joint fluctuation, Ratio variation, LEARNING PROCESSES, BAYESIAN DIALOGUE, BAYESIAN MONOLOGUE, ratio variation, Individual preferences, Agreement, learning processes, D83, Bayesian monologue, Learning processes, agreement

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    popularity
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    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
gold