This course in Game Theory will provide you with more advanced tools that will allow you to formally analyze strategic interaction among economic agents in the presence of incomplete information — i.e., in environments where players are not aware of all relevant characteristics of the other players with whom they interact.
First, you will learn how to formally represent static games in strategic form and how to analyze them using the concept of Bayesian Nash equilibrium. Second, you will learn how to apply these tools to the analysis of auctions. Specifically, you will learn: (i) the characteristics of different auction mechanisms and how to analyze bidders’ strategies in these different mechanisms; (ii) the celebrated Revenue Equivalence Theorem; (iii) the main elements that must be taken into account when designing an auction; (iv) the concepts of common values and the winner’s curse. Third, you will learn how to formally represent dynamic Bayesian games and how to analyze them using the notions of consistent beliefs and sequential rationality and the concept of Perfect Bayesian Nash equilibrium. You will also learn how to formalize signaling models, where an informed player sends a message that may affect the behavior of another uninformed player. Finally, will learn how to solve signaling models using the concepts of pooling and separating equilibria and how to use them to analyze the job market.
This course is part of the "Market Analysis" Program. If you wish to follow this course, you need to enrol via the Program at this link.
