Selling Information in Games with Externalities

2025-05-01

AI Summary

This paper studies how a seller designs information-selling mechanisms in incomplete-information games where buyers are competitors whose payoffs depend on their beliefs, and acquiring information shifts the game’s equilibrium—imposing negative externalities. The seller must balance revenue from information sales against the cost of intensified competition arising from belief refinement. Methodologically, the paper formulates information selling as a Bayesian mechanism design problem with belief-dependent externalities, characterizing the optimal information menu in binary-state/binary-action games. Key contributions include: (i) proving that zero information provision can be optimal under sufficiently intense competition; (ii) demonstrating that information trading can yield Pareto improvements for both seller and buyers without harming social welfare; and (iii) rigorously establishing an inverse relationship between competitive intensity and the volume of information supplied. The analysis integrates tools from game theory, Bayesian mechanism design, and information structure optimization.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Search and Optimization: Learning to Search

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• User Modeling, Personalization and Recommendation: Psychology-informed user models and recommender systems
• Web Mining and Content Analysis: Content-based information diffusion

Abstract

A competitive market is modeled as a game of incomplete information. One player observes some payoff-relevant state and can sell (possibly noisy) messages thereof to the other, whose willingness to pay is contingent on their own beliefs. We frame the decision of what information to sell, and at what price, as a product versioning problem. The optimal menu screens buyer types to maximize profit, which is the payment minus the externality induced by selling information to a competitor, that is, the cost of refining a competitor's beliefs. For a class of games with binary actions and states, we derive the following insights: (i) payments are necessary to provide incentives for information sharing amongst competing firms; (ii) the optimal menu benefits both the buyer and the seller; (iii) the seller cannot steer the buyer's actions at the expense of social welfare; (iv) as such, as competition grows fiercer it can be optimal to sell no information at all.

Problem

• Modeling competitive markets as incomplete information games
• Optimizing information sale pricing to maximize profit
• Analyzing binary-action games for information sharing incentives

Innovation

• Model market as incomplete information game
• Optimize menu for profit and externality
• Derive insights for binary action games