Delegated Costly Screening

Delegated Costly Screening (via Zoom)

Abstract: A policymaker relies on regulators or bureaucrats to screen agents along a costly dimension. How can she maintain some control over the design of the screening process? She solves a two-layer mechanism design problem: she restricts the set of allowable allocations, after which a screener picks a menu that maps an agent’s costly evidence to this restricted set. In general, the policymaker can set a floor in a way that dominates full delegation no matter how the screener’s objectives are misaligned. When this misalignment is only over the relative importance of reducing allocation errors or agent’s screening costs, the effectiveness of this restriction hinges sharply on the direction of the screener’s bias. In the min-max optimal mechanism, if the screener is more concerned with reducing errors, setting this floor is robustly optimal for the policymaker. But if the screener is more concerned with keeping costs down, not only does this particular floor have no effect: any restriction that strictly improves over full delegation is complex and sensitive to the details of the screener’s preferences. I consider the implications for regulatory governance.

Bio: Suraj graduated with a PhD in Economics from the Stanford Graduate School of Business in the summer of 2021 and subsequently joined the economics department at Cornell. Currently he studes microeconomic theory and networks. In particular, he is interested in (1) studying questions about optimal policy design when policymakers have limited information, and (2) exploring the value of acquiring costly information in these settings. Suraj has explored these themes in topics such as delegated mechanism design, diffusion in networks, curbing misinformation in networks and fair auction design.