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Optimal Information Censorship

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  • Ginzburg, Boris

Abstract

This paper analyses Bayesian persuasion of a privately informed receiver in a linear framework. The sender is restricted to censorship, that is, to strategies in which each state is either perfectly revealed or hidden. I develop a new approach to finding optimal censorship strategies based on direct optimisation. I also show how this approach can be used to restrict the set of optimal censorship schemes, and to analyse optimal censorship under certain classes of distributions of the receiver's type.

Suggested Citation

  • Ginzburg, Boris, 2019. "Optimal Information Censorship," MPRA Paper 94603, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:94603
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    References listed on IDEAS

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    1. Geoffrey Brennan & Alan Hamlin, 1998. "Expressive voting and electoral equilibrium," Public Choice, Springer, vol. 95(1), pages 149-175, April.
    2. Kolotilin, Anton & Li, Hongyi, 2021. "Relational communication," Theoretical Economics, Econometric Society, vol. 16(4), November.
    3. Anton Kolotilin & Andriy Zapechelnyuk, 2018. "Persuasion Meets Delegation," Discussion Papers 2018-06, School of Economics, The University of New South Wales.
    4. Anton Kolotilin & Andriy Zapechelnyuk, 2018. "Persuasion Meets Delegation," Discussion Papers 2018-06, School of Economics, The University of New South Wales.
    5. Piotr Dworczak & Giorgio Martini, 2019. "The Simple Economics of Optimal Persuasion," Journal of Political Economy, University of Chicago Press, vol. 127(5), pages 1993-2048.
    6. Anton Kolotilin & Tymofiy Mylovanov & Andriy Zapechelnyuk & Ming Li, 2017. "Persuasion of a Privately Informed Receiver," Econometrica, Econometric Society, vol. 85(6), pages 1949-1964, November.
    7. Alonso, Ricardo & Câmara, Odilon, 2016. "Political disagreement and information in elections," Games and Economic Behavior, Elsevier, vol. 100(C), pages 390-412.
    8. Kolotilin, Anton, 2018. "Optimal information disclosure: a linear programming approach," Theoretical Economics, Econometric Society, vol. 13(2), May.
    9. Ricardo Alonso & Odilon Câmara, 2016. "Persuading Voters," American Economic Review, American Economic Association, vol. 106(11), pages 3590-3605, November.
    10. Bardhi, Arjada & Guo, Yingni, 2018. "Modes of persuasion toward unanimous consent," Theoretical Economics, Econometric Society, vol. 13(3), September.
    11. Matthew Gentzkow & Emir Kamenica, 2016. "A Rothschild-Stiglitz Approach to Bayesian Persuasion," American Economic Review, American Economic Association, vol. 106(5), pages 597-601, May.
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    Cited by:

    1. Hu, Ju & Zhou, Zhen, 2022. "Disclosure in epidemics," Journal of Economic Theory, Elsevier, vol. 202(C).
    2. Philipp Denter & Martin Dumav & Boris Ginzburg, 2021. "Social Connectivity, Media Bias, and Correlation Neglect," The Economic Journal, Royal Economic Society, vol. 131(637), pages 2033-2057.
    3. Junze Sun & Arthur Schram & Randolph Sloof, 2019. "A Theory on Media Bias and Elections," Tinbergen Institute Discussion Papers 19-048/I, Tinbergen Institute.
    4. Farzaneh Farhadi & Demosthenis Teneketzis, 2022. "Dynamic Information Design: A Simple Problem on Optimal Sequential Information Disclosure," Dynamic Games and Applications, Springer, vol. 12(2), pages 443-484, June.

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    More about this item

    Keywords

    Bayesian persuasion; censorship;

    JEL classification:

    • 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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