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Theoretical Economics
Article . 2023 . Peer-reviewed
License: CC BY NC
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Article . 2023
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Article . 2020 . Peer-reviewed
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Article . 2023
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Subjective information choice processes

Authors: Dillenberger, David; Krishna, R. Vijay; Sadowski, Philipp;

Subjective information choice processes

Abstract

We propose a class of dynamic models that capture subjective (and, hence, unobservable) constraints on the amount of information a decision maker can acquire, pay attention to, or absorb via an information choice process (ICP). An ICP specifies the information that can be acquired about the payoff‐relevant state in the current period and how this choice affects what can be learned in the future. In spite of their generality, wherein ICPs can accommodate any dependence of the information constraint on the history of information choices and state realizations, we show that the constraints imposed by them are identified up to a dynamic extension of Blackwell dominance. All the other parameters of the model are also uniquely identified.

Keywords

rational inattention, Markov and semi-Markov decision processes, ddc:330, dynamic Blackwell dominance, subjective Markov decision process, Decision theory, dynamic preferences, information choice process, D81, D90, D80, Dynamic preferences

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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!
0
Average
Average
Average
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