This dissertation examines strategic settings in which agents have imperfect information. In the first chapter, an informed agent decides how to influence an uninformed decision-maker. In the second chapter, a group of agents decides how to learn. Both chapters discuss how these models can be applied in a political economy setting to study how politicians persuade voters and how policymakers identify the best available policies.
Chapter 1 studies persuasion with verifiable information. An informed sender with state-independent preferences sends private verifiable messages to multiple receivers attempting to convince them to approve a proposal. I find that every equilibrium outcome is characterized by each receiver's set of approved states that satisfies this receiver's obedience and the sender's incentive-compatibility constraints. That allows me to characterize the full equilibrium set. The sender-worst equilibrium outcome is one in which information unravels, and receivers act as if under complete information. The sender-preferred equilibrium outcome is the commitment outcome of the Bayesian persuasion game. In the leading application, I study targeted advertising in elections and show that by communicating with voters privately, a challenger may win elections that are unwinnable with public disclosure. As the electorate becomes more polarized, the challenger can swing unwinnable elections by targeted advertising with a higher probability.
Chapter 2 studies a model of costly sequential search among risky alternatives performed by a group of agents. The learning process stops, and the best uncovered option is implemented when the agents unanimously agree to stop or when all the projects have been researched. Both the implemented project and all the information gathered during the search process are public goods. I show that the equilibrium path implements the same project based on the same information gathered in the same order as the social planner. At the same time, due to free riding, search in teams leads to a delay at each stage of the learning process, which grows with search costs.
