Essays in Microeconomic Theory

Xu, Boli

doi:https://doi.org/10.21985/n2-hvjf-gq46

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Essays in Microeconomic Theory

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This dissertation consists of three essays in microeconomic theory. In the first two chapters, I study a class of partnerships where partners can exit and continue to free-ride on the remaining partners' efforts. The crucial force to deter players from strategic exiting is the ripple effect that it may trigger --- an initial exit may trigger a second exit, which further triggers a third, and so on. I build a framework to study how to promote cooperation in these partnerships. In Chapter 1, I ask the following question: What makes a partnership stable in the sense that all the partners are deterred from strategic exiting? I characterize the conditions for a partnership to be stable. I show that a partnership switches between being stable and unstable as the number of partners grows, and increasing partners' abilities may harm a partnership. Moreover, when partners can choose efforts over time in addition to their exit decisions, noisy monitoring of other partners' efforts can facilitate cooperation --- in particular, I design a random auditing rule that achieves the first-best outcome. In Chapter 2, I extend the above framework to a stochastic setting where the partnership's output is affected by some exogenous factors that evolve over time. In this setting, the most interesting finding is that, under some conditions, a partnership is subject to the curse of profitability: An increase in the partnership's profitability strictly harms all the partners. Intuitively, while a higher level of profitability means that the partnership generates more outputs, it also stimulates strategic exiting in the first place as the remaining partners are now more willing to run the project by themselves. In Chapter 3, I switch the gear to study a different economic context --- matching platforms. I ask the following question: How can a matching platform persuade two customers to form a match by disclosing their information (i.e., quality types)? The platform has the incentive to hide some information from the customers, knowing that adverse selection may occur and undermine matchmaking if the customers are uncertain about each other's type. I find that the optimal disclosure policy features upper censorship: It pools the customer types above a threshold and fully reveals the rest. This policy is optimal because it not only maximizes the chance that each customer is accepted by his partner but also eliminates the adverse selection problem. It is consistent with some observed practices in real-world matching platforms.

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