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Essays in Experimentation, Voting with Sabotage, and Dynamic Inconsistency

Abstract

This dissertation examines the optimal design of incentives or mechanisms in various strategic and non-strategic settings.

Chapter 1 studies how to provide incentives for creativity by analyzing a stylized model of delegated creative experimentation. A principal desires an agent to frequently switch to new uncertain projects to maximize the chance of success, while the agent faces a fixed cost of switching. We show that the principal's optimal reward scheme is maximally uncertain—the agent receives transfers for success, but their distribution has extreme variance. Despite being stationary, the optimal reward scheme achieves the principal's first-best outcome provided that the agent's outside option is sufficiently valuable. These results shed light on the value of randomized incentives for motivating creativity and provide guidance on how to design optimal bonus schemes in online platforms and other applications.

Chapter 2 studies the design of robust voting mechanisms in the presence of sabotage. We consider a preference aggregation problem in which the designer faces both genuine agents and outside saboteurs. We show that plurality voting and other standard mechanisms are typically not robust to sabotage. The optimal voting mechanism must make saboteurs indifferent between each alternative they can vote for. Based on the property, we suggest simple ways of improving standard voting mechanisms to make them more robust to outside sabotage.

Chapter 3 studies perceptions of dynamic inconsistency in labor provision over time. We present a novel laboratory experimental design intended to measure both actual and perceived dynamic inconsistency by using a convex commitment device. In a pilot experiment, we find that participants demand significant amounts of commitment despite showing little dynamic inconsistency in their labor choices. This implies that they believe themselves to be more dynamically inconsistent than they are. The results suggest caution when employing commitment devices, as their usage may be unrelated to the inconsistency they attempt to solve.

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