On Monotone Persuasion

Anton Kolotilin, Hongyi Li and Andriy Zapechelnyuk

Papers from arXiv.org

Abstract: We study monotone persuasion in the linear case, where posterior distributions over states are summarized by their mean. We solve the two leading cases where optimal unrestricted signals can be nonmonotone. First, if the objective is s-shaped and the state is discrete, then optimal monotone signals are upper censorship, whereas optimal unrestricted signals may require randomization. Second, if the objective is m-shaped and the state is continuous, then optimal monotone signals are interval disclosure, whereas optimal unrestricted signals may require nonmonotone pooling. We illustrate our results with an application to media censorship.

Date: 2024-12, Revised 2024-12
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http://arxiv.org/pdf/2412.14400 Latest version (application/pdf)

Related works:
Working Paper: ON MONOTONE PERSUASION (2024)
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