Elias Tsakas

Department of Economics
Maastricht University

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Noisy persuasion
(with Nikolas Tsakas)

Abstract.
We study the effect of noise due to exogenous information distortions in the context of Bayesian persuasion. In particular, we ask whether more noise is always harmful for the information designer (viz., the sender). We show that in general this is not the case. This is due to the fact that combining different sources of distortions affects, not only the "amount of noise", but also the underlying "structure of noise". Whenever we compare noisy channels (in Blackwell's sense) with similar basic structures, monotonicity is restored, i.e., more noise cannot be beneficial for the sender. We apply our theory to applications from the literatures on voting and cognitive biases.