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Game Theory for Social Scientists

Course Dates and Times

Monday 5 to Friday 9 March 2018
15 hours over 5 days

Dominik Klein

University of Bamberg

This course will serve as an introduction to game theory and formal models, aimed at students who have little or no experience in the two subjects. Through the formalization of logic, the course will also enhance participants' commands of theory building and deriving causal mechanisms of political science phenomena. We will develop the theory of choice, the theory of choice under uncertainty, and non-cooperative game theory.  Specific concepts that will be covered include: preferences and utility, expected utility, games in normal form, games in extensive form (including models of bargaining and repeated games) and games with imperfect information. Applications will be drawn from comparative politics and international relations. By the end of the course, not only will the participants have gained a sufficient foundation to understand research articles with game, but they will also have improved their theory-building skills.

Tasks for ECTS Credits

  • Participants attending the course: 2 credits (pass/fail grade) The workload for the calculation of ECTS credits is based on the assumption that students attend classes and carry out the necessary reading and/or other work prior to, and after, classes.
  • Participants attending the course and completing one task (see below): 3 credits (to be graded)
  • Participants attending the course, and completing two tasks (see below): 4 credits (to be graded)

There will be a total of five daily assignments, a take-home exam, and a take-home paper with an original game theoretical model. To receive 2 ECTS credits, participants will be required to attend all classes and carry out the necessary readings and assignments. Participants who elect to receive 3 ECTS credits are required to complete a take-home exam, while students who elect to receive 4 ECTS credits will be required to submit a paper containing an original game theoretic model (max 10 pages), due on March 16, 2018.

Instructor Bio

Dominik Klein is a postdoctoral researcher at the Political Science Department at the University of Bamberg as well as at the Philosophy Department at the University of Bayreuth. He received his PhD from the University of Tilburg in 2015.

Dominik’s research interest include game and decision theory, agent-based modeling and the  philosophy of the social sciences. In his research he has worked, among others,  the emergence of trust, informational dynamics preceding revolutionary uprisings and  the relationship between rationality and the emergence of inequality. 

Formal modeling and game theory have become two common pieces of analytical apparatus in a wide range of political science research, including legislative behavior, coalition formation and termination, political violence, authoritarian regime breakdown, and international security. Both approaches are utilized in addressing political phenomena that seem counterintuitive, such as but not limited to the following. Why does war occurs even though it is clearly costly? Why does foreign aid sometimes fail to help the targeted countries? Why is it that some opposition parties failed to “get its act together” and win elections, even when opinion polls goes against the government? Why do parties sometimes failed to reach a coalition agreement, even if it in their interests to do so? The use of formal models helps ensure that the logic of a theoretical mechanism is sound, while game theory is an attractive methodological tool for explaining suboptimal political outcomes. It gives actors the benefit of the doubt: even smart people can make logical but harmful decisions. With game theory, we no longer need to rely on using event-specific factors to explain phenomena that could otherwise be interpreted in a systematic manner. That is, game theory helps us derive the systematic logic behind political phenomena. This increases our ability to accurately predict event occurrence. Game theory--and formal models in general--also offer us the tools for explaining phenomena with more parsimonious conditions, thereby reducing our propensity to rely on ad hoc explanations for events that occur across countries and over time. Finally, both approaches allow us to spell out the logic of our arguments, and can potentially help us make sense of political events that are counter-intuitive, or of phenomena that seems to be the result of irrational actors.

While one can often understand the game theoretic models’ basic logic, particular with research articles that contain formal/game theoretic models, without some training in game theory or formal modeling, the finer ideas of these models' mechanisms may become lost in midst of mathematical formulations. This not only limits scholars’ ability to offer insightful critiques of the theories embedded in formal models, but may deter them from using game theory as a means for checking the logical consistencies of their own theoretical arguments. Understanding the intricacies of formal models/games is therefore essential for maximizing a scholar's ability to fully grasp the theoretical mechanisms of a wide range of political phenomena.

Even if one does not intend to build formal models in his/her own research, learning game theory can have wide-reaching benefits for his/her scholarly development. By learning how to build game theoretic models, scholars will also become familiar with the structure of a formal model (i.e., setup, assumptions, predictions) and in the process internalize the skills for theory building, particularly developing a causal logic and extracting the causal logic of existing theoretical arguments. Through this learning process, scholars will be equipped with the tools to spell out their theories' causal mechanism, particularly by being explicit about the assumptions that are often hidden in theoretical arguments. In other words, when scholars master game theoretic concepts, they also become skillful in crafting theoretical mechanisms that are logically sound.

Therefore, this course will offer the tools for dissecting game theoretic models--and formal models in general--in political science articles, and also the skills to construct this kind of models in their own research. These involve determining the importance of ad hoc, case-specific elements when explaining political events, building theoretical arguments with explicitly stated assumptions, formulating concise and coherent mechanisms, and producing a set of testable predictions.

In doing so, this course will cover five basic types of games in detail. They are extensive form (sequential) games, normal form (simultaneous) games, repeated games, Bayesian games, and games with imperfect information. It will utilize empirical examples to introduce the games and supply plenty of exercises to ensure a full grasp of the games’ mechanisms. These exercises are the key to developing the skillset necessary for building your own games: the only way to gauge whether you have truly understood the concepts is to apply what you have learned to different contexts. The more time you put in to these exercises, the more you will be able to grasp both the technical aspects and the intuitions behind the solution concepts, and to apply them for building your own game theoretic models in the future.

Although this course has mathematical pre-requisites, there is no need to be intimated by them! The math is often the least challenging aspect of game theory. The most demanding part is unpacking the logic behind the games, and for this you will receive plenty of support from your fellow students and (of course) your instructor.

Participants should be adept at solving simple algebraic equations. If you are rusty, now is a good time to revisit these topics. For algebra practice, any decent high school text will be sufficient.

Each course includes pre-course assignments, including readings and pre-recorded videos, as well as daily live lectures totalling at least three hours. The instructor will conduct live Q&A sessions and offer designated office hours for one-to-one consultations.

Please check your course format before registering.

Online courses

Live classes will be held daily for three hours on a video meeting platform, allowing you to interact with both the instructor and other participants in real-time. To avoid online fatigue, the course employs a pedagogy that includes small-group work, short and focused tasks, as well as troubleshooting exercises that utilise a variety of online applications to facilitate collaboration and engagement with the course content.

In-person courses

In-person courses will consist of daily three-hour classroom sessions, featuring a range of interactive in-class activities including short lectures, peer feedback, group exercises, and presentations.


This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.). Registered participants will be informed at the time of change.

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.

Day Topic Details
1 Games in Extensive Form 2 x 90 minute lectures. Exercises.
2 Games in Normal Form 2 x 90 minute lectures. Exercises.
3 Bayesian Games Part 1

2 x 90 minute lectures. Exercises.

4 Bayesian Games Part 2

2 x 90 minute lectures. Exercises.

5 Repeated Games

2 x 90 minute lectures. Exercises.

Day Readings
1 McCarty and Meirowitz Chapters 2.1, 2.3, 3 (but not 3.5), 7.1, 7.3

Lecture Notes, Games in Extensive Form


Lecture Notes, Games in Normal Form


Lecture Notes, Bayesian Games Part 1


Lecture Notes, Bayesian Games Part 2

Software Requirements


Hardware Requirements



Nolan McCarty and Adam Meirowitz, Political Game Theory.