Bachelor
2023/2024
Game Theory and Industrial Organization
Type:
Compulsory course (Data Science and Business Analytics)
Area of studies:
Applied Mathematics and Information Science
Delivered by:
Big Data and Information Retrieval School
Where:
Faculty of Computer Science
When:
4 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Evgeny Zalyubovsky
Language:
English
ECTS credits:
5
Contact hours:
56
Course Syllabus
Abstract
The course introduces students to strategic thinking and demonstrates the powerful toolbox of modern game theory. The main application is the field of industrial organization, i.e. we will study competition and collusion between firms, market entry, integration, etc.
Learning Objectives
- To introduce students to the modern game-theoretic analysis of industrial organization.
Expected Learning Outcomes
- Know basic game theory concepts.
- Solve games theoretic models and obtain basic properties of game equilibrium.
- Create simple game-theoretic models and apply them to provide policy implications in various economic environments.
- Know basic industrial organization models, understand the economic problems they help to tackle.
- Apply IO models to analyze key problems of market regulation and antitrust policy.
Course Contents
- Thinking about strategic games. Game-theoretic modelling.
- Games with sequential moves.
- Simultaneous-moves games.
- Combining sequential and simultaneous moves. Extended-form games.
- Mixed strategies. Equilibrium existence.
- Microeconomics review.
- Oligopoly competition.
- Collusion: Cartels and antitrust.
- Horizontal product differentiation.
- Entry and entry deterrence
