Noisy Persuasion

22 Pages Posted: 27 Mar 2017 Last revised: 22 May 2020

See all articles by Elias Tsakas

Elias Tsakas

Maastricht University - Department of Economics

Nikolas Tsakas

University of Cyprus - Department of Economics

Date Written: May 3, 2020

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 (a la Blackwell) is always harmful for
the information designer, i.e., the sender. We show that in general this is not the case. We
provide a necessary and sufficient condition for the sender to always be worse off when noise
increases in a binary noisy channel. There are two ways to read our result: (a) the sender always
dislikes additional noise if and only if we start with little noise in the first place, (b) the sender
always dislikes additional noise if and only if this additional noise is modelled by a sufficiently
symmetric channel. Finally, we provide sufficient conditions that extend this result to channels
of arbitrary cardinality.

Keywords: Bayesian Persuasion; Data Distortions; Optimal Signal; Garbling

JEL Classification: C72, D72, D82, D83, K40, M31

Suggested Citation

Tsakas, Elias and Tsakas, Nikolas, Noisy Persuasion (May 3, 2020). Available at SSRN: https://ssrn.com/abstract=2940681 or http://dx.doi.org/10.2139/ssrn.2940681

Elias Tsakas

Maastricht University - Department of Economics ( email )

P.O. Box 616
Maastricht, 6200 MD
Netherlands

Nikolas Tsakas (Contact Author)

University of Cyprus - Department of Economics ( email )

75 Kallipoleos Street
P.O. Box 20537
1678 Nicosia
Cyprus

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