Persuasion by Dimension Reduction

Semyon Malamud and Andreas Schrimpf
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Semyon Malamud: Ecole Polytechnique Federale de Lausanne; Centre for Economic Policy Research (CEPR); Swiss Finance Institute

No 21-69, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: How should an agent (the sender) observing multi-dimensional data (the state vector) persuade another agent to take the desired action? We show that it is always optimal for the sender to perform a (non-linear) dimension reduction by projecting the state vector onto a lower-dimensional object that we call the "optimal information manifold." We characterize geometric properties of this manifold and link them to the sender's preferences. Optimal policy splits information into "good" and "bad" components. When the sender's marginal utility is linear, it is always optimal to reveal the full magnitude of good information. In contrast, with concave marginal utility, optimal information design conceals the extreme realizations of good information and only reveals its direction (sign). We illustrate these effects by explicitly solving several multi-dimensional Bayesian persuasion problems.

Keywords: Bayesian Persuasion; Information Design; Signalling (search for similar items in EconPapers)
JEL-codes: D82 D83 E52 E58 E61 (search for similar items in EconPapers)
Pages: 105 pages
Date: 2021-10
New Economics Papers: this item is included in nep-mac, nep-mic, nep-ore and nep-upt
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Citations: View citations in EconPapers (3)

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Working Paper: Persuasion by Dimension Reduction (2022)
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2169

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