Course coordinator
Professor Lionel Page
Course overview
- Study period
- Semester 1, 2025 (24/02/2025 - 21/06/2025)
- Study level
- Postgraduate Coursework
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Economics School
Game theory is the method economists employ to analyse strategic situations. One aim of the course is to teach you some strategic considerations to take into account when making your own choices. A second aim is to predict how other people or organizations behave when they are in strategic settings. We will see that these aims are closely related. We will learn new concepts, methods and terminology. A third aim is to apply these tools to settings from economics, business and finance. The course will emphasize examples.
Non-cooperative game theory is the principal method that economists use to think about and analyseﾠstrategic situations.ﾠThis course willﾠintroduce you to many of the main concepts, methods and terminology of game theory and show how these tools may be applied to settings from economics and other disciplines. The course will use examples and applications to motivate concepts.
Course requirements
Assumed background
Knowledge of microeconomics up to the level of ECON7000 or 7002, as well as simple univariate calculus is assumed.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
ECON1010 or ECON7000 or ECON7010
Incompatible
You can't enrol in this course if you've already completed the following:
ECON2070
Course contact
School enquiries
School Enquiries, School of Economics
All enquiries regarding student and academic administration (i.e. non-course content information, e.g., class allocation, timetables, extension to assessment due date, etc.) should be directed toﾠenquiries@economics.uq.edu.au.ﾠ
Enquiries relating specifically to course content should be directed to the Course Coordinator/Lecturer.
Course staff
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Lectures commence in Week 1.
Tutorials commence in Week 2.
Please see the Learning Activities section of this Course Profile for the timetabling implications of public holidays.
Important Dates:
· Public Holidays: Fri 18 April (Good Friday), Mon 5ﾠMay (Labour Day).
· Mid-Semester Break: 21ﾠApril - 25ﾠApril. Semester 1 classes recommence on Mon 28ﾠApril.
Students should refer to the timetable prior to the commencement of classes to ensure that they have the most up to date information, as from time to time late room changes may occur.
Aims and outcomes
The way that economists think about strategic situations is through the application of game theory.
The aims of the course are:
1. To teach you some strategic considerations to take into account when making your own choices.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Analyse and evaluate complex strategic interactions between decision makers in a variety of settings.
LO2.
Acquire a deep understanding of advanced game theoretic tools and models, and their applications in real-world scenarios.
LO3.
Develop the ability to make informed predictions about the behaviour of individuals and organisations in strategic environments, and understand the impact of their decisions.
LO4.
Apply advanced game theoretic concepts to real-world problems in economics, political science, and other relevant fields, and make recommendations based on your findings.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Tutorial/ Problem Set |
In-tutorial exercise
|
10% 4 out of best 6 in-tutorial exercises count |
Tutorial week 2 |
| Tutorial/ Problem Set |
In-tutorial exercise
|
10% 4 out of best 6 in-tutorial exercises count |
Tutorial week 5 |
| Tutorial/ Problem Set |
In-tutorial exercise
|
10% 4 out of best 6 in-tutorial exercises count |
Tutorial week 6 |
| Tutorial/ Problem Set |
In-tutorial exercise
|
10% 4 out of best 6 in-tutorial exercises count |
Tutorial week 7 |
| Tutorial/ Problem Set |
In-tutorial exercise
|
10% 4 out of best 6 in-tutorial exercises count |
Tutorial week 9 |
| Tutorial/ Problem Set |
In-tutorial exercise
|
10% 4 out of best 6 in-tutorial exercises count |
Tutorial week 11 |
| Examination |
Final exam
|
60% |
End of Semester Exam Period 7/06/2025 - 21/06/2025 |
Assessment details
In-tutorial exercise
- In-person
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 10% 4 out of best 6 in-tutorial exercises count
- Due date
Tutorial week 2
- Learning outcomes
- L01, L02
Task description
In-tutorial exercises will take place in the first 30min of the tutorial. The best 4 scores out of 6 tutorials will count for your grade. You need to do the exercise in your tutorial group for it to count towards your grade.
In-tutorial exercises can cover any topic from the previous lectures. For instance, if the tutorial exercise is taking place on week 5, the exercises can be about lecture 3 and 4.
Students must attend their allocated tutorial.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If you miss an in-tutorial exercise, the best 4 grades out of all the in-tutorial exercises you attempt will count.
In-tutorial exercise
- In-person
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 10% 4 out of best 6 in-tutorial exercises count
- Due date
Tutorial week 5
- Learning outcomes
- L01, L02
Task description
In-tutorial exercises will take place in the first 30min of the tutorial. The best 4 scores out of 6 tutorials will count for your grade. You need to do the exercise in your tutorial group for it to count towards your grade.
In-tutorial exercises can cover any topic from the previous lectures. For instance, if the tutorial exercise is taking place on week 5, the exercises can be about lecture 3 and 4.
Students must attend their allocated tutorial.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If you miss an in-tutorial exercise, the best 4 grades out of all the in-tutorial exercises you attempt will count.
In-tutorial exercise
- In-person
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 10% 4 out of best 6 in-tutorial exercises count
- Due date
Tutorial week 6
- Learning outcomes
- L01, L02
Task description
In-tutorial exercises will take place in the first 30min of the tutorial. The best 4 scores out of 6 tutorials will count for your grade. You need to do the exercise in your tutorial group for it to count towards your grade.
In-tutorial exercises can cover any topic from the previous lectures. For instance, if the tutorial exercise is taking place on week 5, the exercises can be about lecture 3 and 4.
Students must attend their allocated tutorial.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If you miss an in-tutorial exercise, the best 4 grades out of all the in-tutorial exercises you attempt will count.
In-tutorial exercise
- In-person
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 10% 4 out of best 6 in-tutorial exercises count
- Due date
Tutorial week 7
- Learning outcomes
- L01, L02
Task description
In-tutorial exercises will take place in the first 30min of the tutorial. The best 4 scores out of 6 tutorials will count for your grade. You need to do the exercise in your tutorial group for it to count towards your grade.
In-tutorial exercises can cover any topic from the previous lectures. For instance, if the tutorial exercise is taking place on week 5, the exercises can be about lecture 3 and 4.
Students must attend their allocated tutorial.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If you miss an in-tutorial exercise, the best 4 grades out of all the in-tutorial exercises you attempt will count.
In-tutorial exercise
- In-person
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 10% 4 out of best 6 in-tutorial exercises count
- Due date
Tutorial week 9
- Learning outcomes
- L01, L02
Task description
In-tutorial exercises will take place in the first 30min of the tutorial. The best 4 scores out of 6 tutorials will count for your grade. You need to do the exercise in your tutorial group for it to count towards your grade.
In-tutorial exercises can cover any topic from the previous lectures. For instance, if the tutorial exercise is taking place on week5, the exercises can be about lecture 3 and 4.
Students must attend their allocated tutorial.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If you miss an in-tutorial exercise, the best 4 grades out of all the in-tutorial exercises you attempt will count.
In-tutorial exercise
- In-person
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 10% 4 out of best 6 in-tutorial exercises count
- Due date
Tutorial week 11
- Learning outcomes
- L01, L02
Task description
In-tutorial exercises will take place in the first 30min of the tutorial. The best 4 scores out of 6 tutorials will count for your grade. You need to do the exercise in your tutorial group for it to count towards your grade.
In-tutorial exercises can cover any topic from the previous lectures. For instance, if the tutorial exercise is taking place on week 5, the exercises can be about lecture 3 and 4.
Students must attend their allocated tutorial.
This assessment task is to be completed in-person. The use of generative Artificial Intelligence (AI) or Machine Translation (MT) tools will not be permitted. Any attempted use of AI or MT may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Deferral or extension
You cannot defer or apply for an extension for this assessment.
If you miss an in-tutorial exercise, the best 4 grades out of all the in-tutorial exercises you attempt will count.
Final exam
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 60%
- Due date
End of Semester Exam Period
7/06/2025 - 21/06/2025
- Learning outcomes
- L01, L02, L03, L04
Task description
Final exam in person. Composed of exercises on all the course content.
Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 60 minutes |
| Calculator options | (In person) Casio FX82 series only or UQ approved and labelled calculator |
| Open/closed book | Closed Book examination - no written materials permitted |
| Exam platform | Paper based |
| Invigilation | Invigilated in person |
Submission guidelines
Deferral or extension
You may be able to defer this exam.
Course grading
Full criteria for each grade is available in the Assessment Procedure.
| Grade | Cut off Percent | Description |
|---|---|---|
| 1 (Low Fail) | 0% - 29% |
Absence of evidence of achievement of course learning outcomes. |
| 2 (Fail) | 30% - 46% |
Minimal evidence of achievement of course learning outcomes. |
| 3 (Marginal Fail) | 47% - 49% |
Demonstrated evidence of developing achievement of course learning outcomes |
| 4 (Pass) | 50% - 64% |
Demonstrated evidence of functional achievement of course learning outcomes. |
| 5 (Credit) | 65% - 74% |
Demonstrated evidence of proficient achievement of course learning outcomes. |
| 6 (Distinction) | 75% - 84% |
Demonstrated evidence of advanced achievement of course learning outcomes. |
| 7 (High Distinction) | 85% - 100% |
Demonstrated evidence of exceptional achievement of course learning outcomes. |
Additional course grading information
A student's final overall end of semester percentage mark will be rounded to determine their final grade. For example, 64.5% rounds to 65%, while 64.4% rounds to 64%.
Supplementary assessment
Supplementary assessment is available for this course.
Additional assessment information
Plagiarism
The School of Economics is committed to reducing the incidence of plagiarism. Further information on plagiarism and how to avoid an allegation of plagiarism is available in this course profile under Policies & Procedures. Please refer to the Academic Integrity Module (AIM). It is strongly recommended that you complete the AIMﾠif you have not already done so.
Learning resources
You'll need the following resources to successfully complete the course. We've indicated below if you need a personal copy of the reading materials or your own item.
Library resources
Find the required and recommended resources for this course on the UQ Library website.
Additional learning resources information
Course Material including the course outline and tutorial answers will be posted on Blackboard.
Learning activities
The learning activities for this course are outlined below. Learn more about the learning outcomes that apply to this course.
Filter activity type by
Please select
| Learning period | Activity type | Topic |
|---|---|---|
Week 1 (24 Feb - 02 Mar) |
Lecture |
Lecture 1: Decisions Under Uncertainty Expected Utility Theorem Learning outcomes: L01, L02 |
Week 2 (03 Mar - 09 Mar) |
Tutorial |
Tutorial 1: Decisions Under Uncertainty Expected Utility Theorem Learning outcomes: L01, L02, L03 |
Lecture |
Lecture 2: Normal Form Games and Dominance Presentation of normal form games, dominance Learning outcomes: L01, L02, L03 |
|
Week 3 (10 Mar - 16 Mar) |
Tutorial |
Tutorial 2: Normal Form Games and Dominance Presentation of normal form games, dominance Learning outcomes: L02, L03 |
Lecture |
Lecture 3: Nash Equilibrium I Pure Strategy Nash Equilibrium, Mixed Strategies Learning outcomes: L02, L03 |
|
Week 4 (17 Mar - 23 Mar) |
Tutorial |
Tutorial 3: Nash Equilibrium I Pure Strategy Nash Equilibrium, Mixed Strategies Learning outcomes: L02, L03 |
Lecture |
Lecture 4: Nash Equilibrium II Mixed Strategy Nash Equilibrium Learning outcomes: L02, L03 |
|
Week 5 (24 Mar - 30 Mar) |
Tutorial |
Tutorial 4: Nash Equilibrium II Mixed Strategy Nash Equilibrium Learning outcomes: L02, L03 |
Lecture |
Lecture 5: Application of Nash Equilibrium Applying Nash Equilibrium to a range of economic situations. Learning outcomes: L01, L03, L04 |
|
Week 6 (31 Mar - 06 Apr) |
Tutorial |
Tutorial 5: Application of Nash Equilibrium Applying Nash Equilibrium to a range of economic situations. Learning outcomes: L01, L03, L04 |
Lecture |
Lecture 6: Extensive Form Games Extensive form game with perfect information, Game trees and backward induction Learning outcomes: L01, L02, L03 |
|
Week 7 (07 Apr - 13 Apr) |
Tutorial |
Tutorial 6: Extensive Form Games Extensive form game with perfect information, Game trees and backward induction. Learning outcomes: L01, L02, L03 |
Lecture |
Lecture 7: Subgame Perfect Equilibrium Applications and Limitations of Subgame Perfect Equilibrium Learning outcomes: L01, L03, L04 |
|
Week 8 (14 Apr - 20 Apr) |
Tutorial |
Tutorial 7: Subgame Perfect Equilibrium Applications and limitations of Subgame Perfect Equilibrium Friday, April 18th is the Good Friday Public Holiday. If your tutorial is scheduled for this day, please attend any of the other tutorials scheduled for the week. Learning outcomes: L01, L03, L04 |
Mid-sem break (21 Apr - 27 Apr) |
No student involvement (Breaks, information) |
Mid-Semester Break No lecture or tutorial will be held during Mid-Semester Break |
Week 9 (28 Apr - 04 May) |
Lecture |
Lecture 8: Long-term Relationship Introduction to Repeated Games Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 8: Review Tutorial Learning outcomes: L01, L02, L03 |
|
Week 10 (05 May - 11 May) |
Lecture |
Lecture 9: Bayesian Games Introduction to Bayesian Games Sub-activity: Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 9: Long-term Relationship Introduction to Repeated Games Monday, May 5th is the Labour Day public holiday. Students with Monday tutorials are advised to attend any other tutorials scheduled for the week. Learning outcomes: L01, L02, L03, L04 |
|
Week 11 (12 May - 18 May) |
Lecture |
Lecture 10: Applications of Bayesian Games Auctions and other applications of Bayesian games Learning outcomes: L01, L02, L03 |
Tutorial |
Tutorial 10: Bayesian Games Introduction to Bayesian Games Learning outcomes: L01, L02, L03, L04 |
|
Week 12 (19 May - 25 May) |
Lecture |
Lecture 11: Extensive Games Imperfect Information Learning outcomes: L01, L02, L03, L04 |
Tutorial |
Tutorial 11: Applications of Bayesian Games Learning outcomes: L01, L02, L03 |
|
Week 13 (26 May - 01 Jun) |
Tutorial |
Tutorial 12: Extensive Games Imperfect Information A Review Learning outcomes: L01, L02, L03, L04 |
Policies and procedures
University policies and procedures apply to all aspects of student life. As a UQ student, you must comply with University-wide and program-specific requirements, including the:
- Student Code of Conduct Policy
- Student Integrity and Misconduct Policy and Procedure
- Assessment Procedure
- Examinations Procedure
- Reasonable Adjustments - Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.