Social choice under gradual learning

Department d'Economie et Sciences de la Décision 
Intervenant : Caroline Thomas (UT Austin)
Salle T-008

Abstract :

This paper combines dynamic mechanism design with collective experimentation. Agents are heterogeneous in that some stand to benefit from a proposed policy reform, while others are better off under the status quo policy. Each agent's private information regarding her preference type accrues only gradually, over time. A principal seeks a mechanism that maximizes the agents' joint welfare, while providing incentives for the agents to truthfully report their gradually acquired, private information. The first-best policy may not be incentive compatible, as uninformed agents may have an incentive to prematurely vote for a policy instead of waiting for their private signal. Under the second-best policy, the principal can incentivize truth-telling by setting a deadline for experimentation, delaying the implementation of the policy reform, and keeping agents in the dark regarding others' reports.

Joint work with Yiman Sun and Takuro Yamashita