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Informational separability and entropy

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  • Tian, Jianrong

Abstract

Informational separability occurs when information decreases as the result of suppressing information that differentiates a subset of states in experiments. With multiple states, informational separability leads to entropy measures. Its implications in multiple different contexts are discussed, including segregation measurement, inference with partial information, and rational inattention.

Suggested Citation

  • Tian, Jianrong, 2024. "Informational separability and entropy," Journal of Economic Theory, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:jetheo:v:216:y:2024:i:c:s0022053124000024
    DOI: 10.1016/j.jet.2024.105796
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    References listed on IDEAS

    as
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Information suppression; Informational separability; Shannon entropy; Invariance; Segregation measurement; Inference with partial information;
    All these keywords.

    JEL classification:

    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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