Abstract
We study information design in games where players choose from a continuum of ac-tions and have continuously differentiable payoffs. We show that an information structure is optimal when the equilibrium it induces can also be implemented in a principal-agent contracting problem. Building on this result, we characterize optimal information struc-tures in symmetric linear-quadratic games. With common values, targeted disclosure is robustly optimal across all priors. With interdependent and normally distributed values, linear disclosure is uniquely optimal. We illustrate our findings with applications in venture capital, Bayesian polarization, and price competition.
Keywords
Bayesian persuasion; information design; dual certification; first-order approach; linear-quadratic games; targeted disclosure; Gaussian coupling, linea; disclosure.;
Reference
Alex Smolin, and Takuro Yamashita, “Information Design in Smooth Games”, TSE Working Paper, n. 25-1671, October 2025.
See also
Published in
TSE Working Paper, n. 25-1671, October 2025