Date of Award
Doctor of Philosophy (PhD)
George J. Mailath
Steven A. Matthews
In the first chapter of the dissertation, "When and How to Reward Bad News"(joint with Aditya Kuvalekar), we explore when and how to reward the bearer of bad news in a dynamic principal-agent relationship with experimentation. The agent receives flow rents from experimentation, and divides his time between searching for conclusive good news and conclusive bad news about project quality. The principal commits in advance to rewards conditional on the type of news. At each instant, the principal makes a firing decision. We explore two environments: when the principal observes the agent's allocation and when she does not. We show that, in both the environments, the principal's optimal equilibrium features a stark reward structure---either the principal does not reward the bearer of bad news at all or rewards the bearer of either news equally.
In the second chapter of the dissertation "Supervising to Motivate", I study a dynamic principal-agent relationship in which the principal invests costly resources in a project of uncertain quality to induce costly effort from an agent. The principal observes the output from the project privately and can be either informed (has learned that project quality is high) or uninformed. The agent learns about project quality through the investments made by the principal. The principal wants to invest less when pessimistic about project quality; however, the agent demands higher investment when pessimistic to exert effort. The principal faces the trade-off between investing optimally and transmitting information about project quality to the agent. The principal's optimal equilibrium features full information transmission when the uninformed principal has high beliefs (probability that project quality is high) and no information transmission at low beliefs. The informed principal may invest at sub-optimally high levels early in the relationship, but eventually, optimality is restored. That is, the principal's optimal equilibrium may exhibit distortions in the short run but not in the long run.
Ravi, Nishant, "Essays On Dynamic Games And Contracts With Learning" (2019). Publicly Accessible Penn Dissertations. 3367.