Social Choice Under Gradual Learning

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 maximises 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 incentivise 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 with Yiman Sun and Takuro Yamashita

More on Caroline Thomas

signup sheet