Censorship as optimal persuasion

Anton Kolotilin; Timofiy Mylovanov; Andriy Zapechelnyuk

doi:10.3982/te4071

Censorship as optimal persuasion

Anton Kolotilin, Timofiy Mylovanov, Andriy Zapechelnyuk

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Abstract

We consider a Bayesian persuasion problem where a sender's utility depends only on the expected state. We show that upper censorship that pools the states above a cutoff and reveals the states below the cutoff is optimal for all prior distributions of the state if and only if the sender's marginal utility is quasi‐concave. Moreover, we show that it is optimal to reveal less information if the sender becomes more risk averse or the sender's utility shifts to the left. Finally, we apply our results to the problem of media censorship by a government.

Original language	English
Pages (from-to)	561-585
Number of pages	25
Journal	Theoretical Economics
Volume	17
Issue number	2
DOIs	https://doi.org/10.3982/te4071
Publication status	Published - 5 May 2022

Keywords

Bayesian persuasion
Information design
Censorship
Media

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10.3982/te4071Licence: CC BY-NC

Kolotilin_2022_TE_Censorship-as-optimal-persuasion_CC
Copyright © 2022 The Authors. Open Access. Licensed under the Creative Commons Attribution-NonCommercial License 4.0. Available at https://doi.org/10.3982/TE4071
Final published version, 311 KBLicence: CC BY-NC

Theoretical Foundations: Theoretical foundations and design of persuasion mechanism
Zapechelnyuk, A. (PI)
Economic & Social Research Council
19/06/17 → 18/12/20
Project: Standard

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title = "Censorship as optimal persuasion",

abstract = "We consider a Bayesian persuasion problem where a sender's utility depends only on the expected state. We show that upper censorship that pools the states above a cutoff and reveals the states below the cutoff is optimal for all prior distributions of the state if and only if the sender's marginal utility is quasi‐concave. Moreover, we show that it is optimal to reveal less information if the sender becomes more risk averse or the sender's utility shifts to the left. Finally, we apply our results to the problem of media censorship by a government.",

keywords = "Bayesian persuasion, Information design, Censorship, Media",

author = "Anton Kolotilin and Timofiy Mylovanov and Andriy Zapechelnyuk",

note = "Kolotilin acknowledges financial support from the Australian Research Council Discovery Early Career Research Award DE160100964 and from MIT Sloan{\textquoteright}s Program on Innovation in Markets and Organizations. Mylovanov acknowledges financial support from the Office of Naval Research Multidisciplinary University Research Initiative Award N0001417-1-2675 and from Kyiv School of Economics. Zapechelnyuk acknowledges financial support from the Economic and Social Research Council Grant ES/N01829X/1.",

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N1 - Kolotilin acknowledges financial support from the Australian Research Council Discovery Early Career Research Award DE160100964 and from MIT Sloan’s Program on Innovation in Markets and Organizations. Mylovanov acknowledges financial support from the Office of Naval Research Multidisciplinary University Research Initiative Award N0001417-1-2675 and from Kyiv School of Economics. Zapechelnyuk acknowledges financial support from the Economic and Social Research Council Grant ES/N01829X/1.

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N2 - We consider a Bayesian persuasion problem where a sender's utility depends only on the expected state. We show that upper censorship that pools the states above a cutoff and reveals the states below the cutoff is optimal for all prior distributions of the state if and only if the sender's marginal utility is quasi‐concave. Moreover, we show that it is optimal to reveal less information if the sender becomes more risk averse or the sender's utility shifts to the left. Finally, we apply our results to the problem of media censorship by a government.

AB - We consider a Bayesian persuasion problem where a sender's utility depends only on the expected state. We show that upper censorship that pools the states above a cutoff and reveals the states below the cutoff is optimal for all prior distributions of the state if and only if the sender's marginal utility is quasi‐concave. Moreover, we show that it is optimal to reveal less information if the sender becomes more risk averse or the sender's utility shifts to the left. Finally, we apply our results to the problem of media censorship by a government.

KW - Bayesian persuasion

KW - Information design

KW - Censorship

KW - Media

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Censorship as optimal persuasion

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Theoretical Foundations: Theoretical foundations and design of persuasion mechanism

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