[Paper]

We study how to screen agents without monetary transfers, when the agents can make costly investments affecting their type. A principal commits to a screening mechanism that prescribes a probability of approval based on the agents' one-dimensional type and values admitting higher-type agents above a certain eligibility threshold. Agents are initially endowed with a privately known natural type and can perform costly actions to modify their type before the principal can observe it. We show that deterministic cutoff mechanisms are optimal for the principal. This result provides a firmer foundation and a potential explanation for using simple "pass-or-fail" rules in environments where agents may invest in response to how they are screened.

[Paper]

We study how to segment monopolistic markets with a redistributive objective. We show that redistributive segmentations (i) exhibit a monotone structure and (ii) might give extra profit to the seller compared to consumer-surplus-maximizing segmentations if the redistributive concerns are sufficiently strong. We characterize the aggregate markets for which strongly redistributive segmentations allocate some surplus to the seller. For the remaining aggregate markets, we show that the optimal segmentation generates only two segments: one where the lowest possible price is charged and one where the uniform price is charged. We also show that redistributive segmentations are implementable through price-based regulation.

[Paper]

We study a persuasion problem in which a sender designs an information structure to induce a non-Bayesian receiver to take a particular action. The receiver, who is privately informed about his preferences, is a wishful thinker: he is systematically overoptimistic about the most favorable outcomes. We show that wishful thinking can lead to a qualitative shift in the structure of optimal persuasion compared to the Bayesian case, whenever the sender is uncertain about what the receiver perceives as the best-case outcome in his decision problem.