Bayesian Persuasion by an Informed Mechanism Designer

64 Pages Posted: 4 Apr 2022

See all articles by Jun Zhang

Jun Zhang

University of Technology Sydney

Yanlin Chen

Nanjing Audit University

Date Written: March 08, 2022

Abstract

We investigate how an informed designer maximizes her objective when facing
a player whose payoff depends on both the designer's private information and
on an unknown state within the classical quasilinear environment. The
designer can disclose arbitrary information about the state via Bayesian
persuasion and adopt arbitrary mechanisms. We characterize the
Rothschild-Stiglitz-Wilson (RSW) mechanism and identify three channels for
achieving separation. While disclosing inefficient information is essential,
providing a bonus for participation and randomization are supplementary. The
equilibrium is unique and robust under weak assumptions. Our results can
provide rationales for many phenomenons in practice.

Keywords: Bayesian persuasion, information design, mechanism design, informed principal

JEL Classification: D11, D82, D83, L12

Suggested Citation

Zhang, Jun and Chen, Yanlin, Bayesian Persuasion by an Informed Mechanism Designer (March 08, 2022). Available at SSRN: https://ssrn.com/abstract=4054109 or http://dx.doi.org/10.2139/ssrn.4054109

Jun Zhang (Contact Author)

University of Technology Sydney ( email )

EDG, School of Business
University of Technology Sydney
Sydney, NSW
Australia

HOME PAGE: http://www.zhangjun.weebly.com

Yanlin Chen

Nanjing Audit University ( email )

86 Yushan West Road
Nanjing, Jiangsu 210017
China

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