Information Games and Robust Trading Mechanisms Gabriel Carroll, Stanford University
[email protected] October 3, 2017 Abstract Agents about to engage in economic transactions may take costly actions to influence their own or others’ information: costly signaling, information acquisition, hard evidence disclosure, and so forth. We study the problem of optimally designing a mechanism to be robust to all such activities, here termed information games. The designer cares about welfare, and explicitly takes the costs incurred in information games into account. We adopt a simple bilateral trade model as a case study. Any trading mechanism is evaluated by the expected welfare, net of information game costs, that it guarantees in the worst case across all possible games. Dominant- strategy mechanisms are natural candidates for the optimum, since there is never any incentive to manipulate information. We find that for some parameter values, a dominant-strategy mechanism is indeed optimal; for others, the optimum is a non- dominant-strategy mechanism, in which one party chooses which of two trading prices to offer. Thanks to (in random order) Parag Pathak, Daron Acemoglu, Rohit Lamba, Laura Doval, Mohammad Akbarpour, Alex Wolitzky, Fuhito Kojima, Philipp Strack, Iv´an Werning, Takuro Yamashita, Juuso Toikka, and Glenn Ellison, as well as seminar participants at Michigan, Yale, Northwestern, CUHK, and NUS, for helpful comments and discussions. Dan Walton provided valuable research assistance. 1 Introduction A large portion of theoretical work in mechanism design, especially in the world of market design applications, has focused on dominant-strategy (or strategyproof ) mechanisms — 1 those in which each agent is asked for her preferences, and it is always in her best interest to report them truthfully, no matter what other agents are doing.