With Doug Bernheim
American Economic Review, 107(2), 2017
Although economists have made substantial progress toward formulating theories of collusion in industrial cartels that account for a variety of fact patterns, important puzzles remain. Standard models of repeated interaction formalize the observation that cartels keep participants in line through the threat of punishment, but they fail to explain two important factual observations: first, apparently deliberate cheating actually occurs; second, it frequently goes unpunished even when it is detected. We propose a theory of equilibrium price cutting and business stealing in cartels to bridge this gap between theory and observation.
With Annie Liang
Many firms, such as banks and insurers, condition their level of service on a consumer's perceived "quality," for instance their creditworthiness. Increasingly, firms have access to consumer segmentations derived from auxiliary data on behavior, and can link outcomes across individuals in a segment for prediction. How does this practice affect consumer incentives to exert (socially-valuable) effort, e.g. to repay loans? We show that the impact of a linkage on behavior depends crucially on whether the linkage reflects quality (via correlations in types) or a shared circumstance (via common shocks to observed outcomes).
With Aaron Kolb
We study how an organization dynamically screens an agent of uncertain loyalty whom it suspects of committing damaging acts of undermining. The organization controls the stakes of the relationship, while the agent strategically times undermining, which can occur repeatedly and is detected only stochastically. The optimal commitment stakes policy exhibits both discreteness and gradualism, with distinct "untrusted" and "trusted" phases featuring gradually rising stakes during the untrusted phase and a discrete gap in stakes between phases. This policy is also the unique equilibrium outcome when the organization cannot commit, and the agent's unique equilibrium undermining policy exhibits variable, non-monotonic intensity.
With Rishabh Kirpalani
Motivated by stylized facts in the market for entrepreneurial fundraising, we study a setting in which two firms strategically time when to learn about the profitability of a project and when (if ever) to invest in it. Firms learn about the project privately, while investment decisions are public and provide a channel for social learning. Multiple equilibria exist, differing with respect to how much information firms acquire as well as how quickly firms learn and invest. The equilibrium structure maximizing firm welfare varies with model parameters, implying testable predictions about the relationship between investor behavior and market conditions.
I study how an organization should optimally manage a project of uncertain scope when advised by an expert with private information about the project's state who prefers to prolong his employment. The optimal long-term contract involves a combination of a deadline for project completion and incentive payments to the expert which decline as the deadline approaches. When the firm can additionally learn about the project's state from output, the optimal deadline exhibits variable sensitivity to output, with a hard deadline at the outset of the project and increasingly soft deadlines as the project's performance declines.