Course: ECO418
Instructor: Abreu
F 2015

Description of Course Goals and Curriculum

The course is about game theory and its applications in Economics. First the basic concepts of game theory and the derivation of Nash Equilibria are covered in the context of static games of perfect information. Static games of perfect information include the Cournot and the Bertrand models of duopoly. Then the concept of backwards induction and the derivation of Subgame Perfect Equilibria are introduced in the context of dynamic games of perfect information. Dynamic games of perfect information include the Stackelberg model of duopoly, sequential bargaining and repeated games. Then the concept and derivation of Bayesian Nash Equilibria are presented in the context of static games of incomplete information. These games include various types of auctions. Lastly the concept and derivation of Perfect Bayesian Nash Equilibria are introduced in the context of dynamic games of incomplete information. Dynamic games of incomplete information include signaling games, cheap talk games and reputation formation. The course includes these four parts and numerous subtopics. The parts are very much connected and build upon each other. Furthermore the kinds of thinking and problem solving techniques required are very similar across all subtopics. The overall goal of the class is to teach these fundamental techniques and to equip the students to be able to analyze and solve a range of game theoretical problems in a rigorous way. Since the different parts require a similar type of logical thinking and problem solving and specific methods, it is very crucial to understand the logic behind these techniques from the beginning. These skill and ways of thinking the classes teaches include the following: the logic behind a Nash equilibrium and how to find it, the idea of backward induction and the technique of using probability and Bayes rule with other game theoretic tools to find equilibria in static and dynamic games with incomplete information. Prerequisites for the class include a familiarity with probability and experience with probabilistic thinking and in general analytic and logical problem solving skill are essential.

Learning From Classroom Instruction

Lectures are the place where the new information is presented; theories and techniques for solving different types of games, how they are derived and how to use them. The lectures provide great opportunities for acquiring an understanding of where game theoretic thinking comes from and how to apply it for solving problems. Every time a new topic is introduced the process follows the same, structured and logical process: introduction of new terms and definitions, description of the problem, the approach for solving the problem and proving that the approach indeed works. Furthermore example problems are presented and solved and the students have an opportunity to ask questions and ensure that they understand the technique and the reason behind it and that they can also apply this knowledge for problem solving. Precepts and office hour provide additional opportunities to clarify questions, ensure understanding and provide access to additional application and further implications of the topics taught. The course book and other recommended text can be use as a supplement or as a substitution to the lectures.

Learning For and From Assignments

The overall goal of the class is to enable students to acquire the necessary understandings and problem solving skills to be able to solve a range of game theoretic problems. Therefore the assignments are a crucial part of the class and of learning. The assignments provide the opportunity to put the newly acquired knowledge to use and to check whether the understanding is sufficient for application. Additionally the problem sets are a great preparation for the exams as both types of assessments require the same skill sets and underlying understandings. Following along the lectures and understanding the theories and methods and why they work are essential preparation for the assignments. At the same time the assignments provide feedback about whether the learning has taken place. Therefore the assignments and the lectures complement each other well to achieve the goal of the class: teaching usable and enduring understanding and skills for approaching game theoretic problems.

External Resources

For further questions and topics, more advanced game theory books and articles mentioned in class can be a good resource. For additional practice, additional questions in the textbook and recommended books can be helpful. In general office hours and talking to the professor and the preceptor can be a good way to access external resources.

What Students Should Know About This Course For Purposes Of Course Selection

This is one of those type of economics classes that involves more math and is problem set heavy. However, what is great about this class is that it requires more math than simply being able to take derivatives. It brings together probability, economics and real life in an exciting and challenging way. The class is rigorous but at the same time manageable if one has a background in math and/or logical thinking and problem solving skills. If that is the case, what is great about this class is that the problem sets require not only knowing the basic tools and methods learnt in class but also actual thinking beyond manipulating equations or dealing with boring and annoying calculations. This is one of those kinds of classes, where preparing for exams is either a straightforward process - if one understands the methods, how to use them and how to approach the problems - or otherwise a long and troublesome one. The class gives a solid introduction to game theory and in general to more theoretical economics at the level close to that of a graduate level class. It can be a great experience for economics majors considering a theoretical thesis and/or applying to graduate school. At the same time this class can also be interesting for math majors looking for something more applicable than pure math classes. ECO 310 and ECO 321 (Industrial Organizations) are good preparations for this class, there are some minor overlaps and generally a similar feel to the class, but on a more advanced level. Without having taken any of those too, it is still very much manageable. Nevertheless, a background in probability is highly recommended. Without a reasonable math and probability background, consider taking the game theory class offered by the politics department instead. With a stronger background in math and interest in the theory of it mostly, consider taking the game theory class offered by the math department.
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