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Assortative Information Disclosure

Author

Listed:
  • Anton Kolotilin

    (School of Economics, UNSW Business School)

  • Alexander Wolitzky

    (Department of Economics, MIT)

Abstract

We consider a standard persuasion problem in which the receiver’s action and the state of the world are both one-dimensional. Fully characterizing optimal signals when utilities are non-linear is a daunting task. Instead, we develop a general approach to understanding a key qualitative property of optimal signals: their assortative structure, which describes the overall pattern of what states are pooled together. We derive simple conditions—driven by intuitive economic properties, such as supermodularity and submodularity of preferences—for the optimality of positive and negative assortative patterns of information disclosure. Our approach unifies a wide range of previous findings and generates new applications.

Suggested Citation

  • Anton Kolotilin & Alexander Wolitzky, 2020. "Assortative Information Disclosure," Discussion Papers 2020-08, School of Economics, The University of New South Wales.
    • Handle: RePEc:swe:wpaper:2020-08
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    File URL: http://research.economics.unsw.edu.au/RePEc/papers/2020-08.pdf
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    References listed on IDEAS

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    7. Kolotilin, Anton, 2018. "Optimal information disclosure: a linear programming approach," Theoretical Economics, Econometric Society, vol. 13(2), May.
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    Citations

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    Cited by:

    1. Anton Kolotilin & Alexander Wolitzky, 2020. "The Economics of Partisan Gerrymandering," Discussion Papers 2020-12, School of Economics, The University of New South Wales.
    2. Emiliano Catonini & Sergey Stepanov, 2022. "On the optimality of full disclosure," Papers 2202.07944, arXiv.org, revised Feb 2023.
    3. SunAh An & Michael Anderson & Cary Deck, 2023. "Gerrymandering in the laboratory," Southern Economic Journal, John Wiley & Sons, vol. 90(1), pages 182-213, July.
    4. Masaki Aoyagi & Maxime Menuet, 2024. "Career Concerns and Incentive Compatible Task Design," ISER Discussion Paper 1232, Institute of Social and Economic Research, Osaka University.
    5. Arieli, Itai & Babichenko, Yakov & Smorodinsky, Rann & Yamashita, Takuro, 2023. "Optimal persuasion via bi-pooling," Theoretical Economics, Econometric Society, vol. 18(1), January.
    6. Rastislav Rehak & Maxim Senkov, 2021. "Form of Preference Misalignment Linked to State-Pooling Structure in Bayesian Persuasion," CERGE-EI Working Papers wp708, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    7. Emir Kamenica & Kyungmin Kim & Andriy Zapechelnyuk, 2021. "Bayesian persuasion and information design: perspectives and open issues," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(3), pages 701-704, October.

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    More about this item

    Keywords

    persuasion; information design; assortative matching;
    All these keywords.

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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