LQG Information Design

Masaki Miyashita and Takashi Ui

Papers from arXiv.org

Abstract: This paper addresses information design in a workhorse model of network games, where agents have linear best responses, the information designer optimizes a quadratic objective, and the payoff state follows a multivariate Gaussian distribution. We formulate the problem as semidefinite programming (SDP) and utilize the duality principle to characterize an optimal information structure. A Gaussian information structure is shown to be optimal among all information structures. A necessary and sufficient condition for optimality is that the induced equilibrium strategy profile and the state jointly satisfy a linear constraint derived from complementary slackness conditions. Consequently, the true state is typically revealed to the entire population of agents, even though individual agents remain only partially informed. In symmetric network games, an optimal information structure inherits the same degree of symmetry, which facilitates its computation.

Date: 2023-12, Revised 2025-02
New Economics Papers: this item is included in nep-des, nep-gth and nep-mic
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://arxiv.org/pdf/2312.09479 Latest version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2312.09479

Access Statistics for this paper

More papers in Papers from arXiv.org
Bibliographic data for series maintained by arXiv administrators ().