Mechanism Design in Large Games: Incentives and Privacy
- (pp. 431-35)
Abstract
We study the design of mechanisms satisfying a novel desideratum: privacy. This requires the mechanism not reveal "much" about any agent's type to other agents. We propose the notion of joint differential privacy: a variant of differential privacy used in the privacy literature. We show by construction that mechanisms satisfying our desiderata exist when there are a large number of players, and any player's action affects any other's payoff by at most a small amount. Our results imply that in large economies, privacy concerns of agents can be accommodated at no additional "cost" to standard incentive concerns.Citation
Kearns, Michael, Mallesh M. Pai, Aaron Roth, and Jonathan Ullman. 2014. "Mechanism Design in Large Games: Incentives and Privacy." American Economic Review, 104 (5): 431-35. DOI: 10.1257/aer.104.5.431Additional Materials
JEL Classification
- C70 Game Theory and Bargaining Theory: General
- D82 Asymmetric and Private Information; Mechanism Design