Saturday, Jan. 7, 2017 10:15 AM – 12:15 PM
Hyatt Regency Chicago, Field
- Chair: Tymofiy Mylovanov, University of Pittsburgh
Information Design: The Epistemic Approach
AbstractInformation design studies how to disclose information to a group of interacting agents in order to influence their behavior. In this paper, we introduce a belief-based approach to the problem, viewing it as belief manipulation rather than as information disclosure. We characterize and then exploit
the equivalence between information structures and distributions over belief hierarchies. Our main result is a representation theorem that poses the design problem as a choice of an optimal distribution over a special family of belief-hierarchy distributions—the minimal consistent ones—subject to Bayes plausibility. A two-step decomposition of the theorem follows, leading to a concave-envelope representation of optimality that subsumes Kamenica and Gentzkow (2011)’s single-agent result. We apply our representation theorem to a managerial problem, where we study Bayes Nash information design, and to a classic investment game, where we study information design under bounded depths of reasoning.
Buyer-Optimal Demand and Monopoly Pricing
AbstractThis paper analyzes a bilateral trade model where the buyer can choose any cumulative
distribution function (CDF) supported on [0; 1], which then determines her valuation. The seller, after observing the buyer's choice of the CDF but not its realization, gives a takeit-or-leave-it offer to the buyer. We characterize the unique equilibrium outcome of this game and show that in this outcome, the price and the payoffs of both the buyer and the seller are equal to 1/e. The equilibrium CDF of the buyer generates a unit-elastic demand on [1/e; 1].
- D0 - General