Bayesian Persuasion with Quadratic Preferences

51 Pages Posted: 19 Jan 2012 Last revised: 24 Mar 2018

See all articles by Wataru Tamura

Wataru Tamura

Nagoya University - Graduate School of Economics

Date Written: March 21, 2018

Abstract

This paper examines the optimal information design within a Bayesian persuasion setup with multidimensional information. Assuming a linear-quadratic specification, I provide a new approach to the optimal information design by addressing the statistical properties of the receiver's posterior expectation about the state. I derive an upper bound of the gain from information design by formulating a semidefinite programming problem, and then show that the optimal policy can be the disclosure of multiple statistics constructed by linear combinations of the state when it has a multivariate normal distribution. Applications of the theory include price leadership strategy and central bank communication.

Keywords: Bayesian persuasion, multidimensional information design, information disclosure, quadratic preferences, semidefinite programming

JEL Classification: D82, D83

Suggested Citation

Tamura, Wataru, Bayesian Persuasion with Quadratic Preferences (March 21, 2018). Available at SSRN: https://ssrn.com/abstract=1987877 or http://dx.doi.org/10.2139/ssrn.1987877

Wataru Tamura (Contact Author)

Nagoya University - Graduate School of Economics ( email )

1 Furo-cho
Chikusa-ku
Nagoya, 464-8601
Japan

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
575
Abstract Views
2,532
rank
50,247
PlumX Metrics