Game Theory & Math Economics: Alex Gershkov - "The Dimensions of Consensus" (joint with B. Moldovanu and X. Shi)

Sun, 27/11/201616:00-17:00
Elath Hall, 2nd floor, Feldman Building, Edmond J. Safra Campus
We study a multi-dimensional collective decision under incomplete information. With votes taken by simple majority in each dimension, the outcome is the coordinate-wise median. But, judicious rotations of the orthogonal axes - the dimensions, or issues that are voted upon - lead to welfare improvements. Such rotations cover the entire set of anonymous, Pareto efficient and dominant strategy incentive compatible mechanisms in our environment (Kim and Rousch (1984) and Peters et. al (1992)). If the agents' types are drawn from a distribution with independent marginals, then voting on the original issues is not optimal. We also provide various lower bounds on incentive efficiency: in particular, if agents' types are drawn from a logconcave density with symmetric marginals, a second-best voting mechanism attains around 88% of the first-best efficiency.