Game Theory
A.Y. 2019/2020
Learning objectives
The aim of this course is to equip students with a solid understanding of game theory and its most used solution concepts. The first part of the course focuses on static games and on how these strategic environments can be analyzed using Nash equilibrium and rationalizability. The second part of the course extends the analysis to dynamic games and describes how to modify known solution concepts to incorporate credibility of dynamic behavior. In the third and last part of the course, incomplete and asymmetric information is introduced.
Expected learning outcomes
By the end of the course the student should be able to (i) model strategic interactions as games, (ii) discuss and predict the behavior of players according to different solution concepts, (iii) understand the benefits and limitations of different solution concepts, (iv) understand the implications of repeated interactions, (v) model incomplete and asymmetric information in games and understand how they can affect individuals' behavior.
Lesson period: First trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
First trimester
Course syllabus
This is a course in game theory at an intermediate level.
The course focuses on strategic reasoning and emphasizes how and to what extent game theory can be used to predict the behavior of individuals in a broad range of environments.
We will introduce several solutions concepts and we will stress the assumptions that each of them entails.
The course is mostly methodological, but we will overview some important applications to economics and political science. If time permits, additional application will be presented at the end of the course.
Topics include static games with complete and incomplete information as well as extensive-form games.
[Programma]:
I. Introduction to Game Theory [1 Class]
· Game Theory: what is it and why is it useful?
· Taxonomy of games and some jargon.
II. Static Games with Complete Information [6 Classes]
· Pure actions and mixed actions.
· Beliefs, best replies and undominated actions.
· Rationalizability and iterated dominance.
· Nash equilibrium: definition, existence and interpretation.
III. Extensive-form Games with Perfect Information [6 Classes]
· Strategies and outcomes.
· Normal form game and Subgame Perfect Equilibrium.
· Backward Induction and forward induction.
· Repeated Games with perfect information.
· Bargaining.
IV. Static Games with Incomplete Information [4 Classes]
· Private information and beliefs.
· Belief restrictions: independence and correlation.
· Bayes-Nash equilibrium.
V. Extensive-form Games with Incomplete Information [3 Classes]
· Perfect Bayesian Equilibrium.
· Sequential Equilibrium.
· Signaling Games.
The course focuses on strategic reasoning and emphasizes how and to what extent game theory can be used to predict the behavior of individuals in a broad range of environments.
We will introduce several solutions concepts and we will stress the assumptions that each of them entails.
The course is mostly methodological, but we will overview some important applications to economics and political science. If time permits, additional application will be presented at the end of the course.
Topics include static games with complete and incomplete information as well as extensive-form games.
[Programma]:
I. Introduction to Game Theory [1 Class]
· Game Theory: what is it and why is it useful?
· Taxonomy of games and some jargon.
II. Static Games with Complete Information [6 Classes]
· Pure actions and mixed actions.
· Beliefs, best replies and undominated actions.
· Rationalizability and iterated dominance.
· Nash equilibrium: definition, existence and interpretation.
III. Extensive-form Games with Perfect Information [6 Classes]
· Strategies and outcomes.
· Normal form game and Subgame Perfect Equilibrium.
· Backward Induction and forward induction.
· Repeated Games with perfect information.
· Bargaining.
IV. Static Games with Incomplete Information [4 Classes]
· Private information and beliefs.
· Belief restrictions: independence and correlation.
· Bayes-Nash equilibrium.
V. Extensive-form Games with Incomplete Information [3 Classes]
· Perfect Bayesian Equilibrium.
· Sequential Equilibrium.
· Signaling Games.
Prerequisites for admission
There is no formal requirement. A generic attitude toward logic and abstract reasoning is useful.
Teaching methods
Regular taught classes.
Teaching Resources
The reference book for the course is
· Osborne M. J., An introduction to Game Theory (International Edition), Oxford University Press.
It may also be useful to read the lecture notes written by Prof. Pierpaolo Battigalli
· http://didattica.unibocconi.it/mypage/upload/48808_20180609_055040_22.05.2018DISPENSAGT-PART_I.PDF
· Osborne M. J., An introduction to Game Theory (International Edition), Oxford University Press.
It may also be useful to read the lecture notes written by Prof. Pierpaolo Battigalli
· http://didattica.unibocconi.it/mypage/upload/48808_20180609_055040_22.05.2018DISPENSAGT-PART_I.PDF
Assessment methods and Criteria
Written exam at the end of the course with theoretical questions and exercises.
SECS-P/01 - ECONOMICS - University credits: 6
Lessons: 40 hours
Professor:
Grillo Edoardo
Shifts:
-
Professor:
Grillo Edoardo