Three Essays In Information And Mechanism Design

This thesis comprises three independent essays, exploring various theoretical issues related to the design of information structures and incentive mechanisms. The first chapter investigates how to optimally design selection mechanisms, taking into account that candidates can strategically invest in the attributes upon which they are evaluated. We demonstrate that when the goal is to maximize the expected quality of admitted candidates, deterministic "pass or fail" selection rules prove to be optimal. The second chapter examines a non-Bayesian persuasion model where the receiver's belief formation process is motivated. We show that persuasion is more effective compared to the Bayesian case when it encourages the receiver to adopt a risky behavior that can lead to significant gains, but it is less effective when promoting more cautious behavior. We illustrate this finding with applications. The third and final chapter studies the distributive impacts of market segmentation. We examine how to segment a monopolistic market with a redistributive objective, i.e., favoring the poorest consumers. We show that optimal redistributive segmentations always generate Pareto-efficient allocations, but may require granting a strictly positive share of the surplus to the seller.