Course overview
- Study period
- Semester 2, 2024 (22/07/2024 - 18/11/2024)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Economics School
This course explores in detail the economics of information and uncertainty introducing mechanism design and agency theory at an advanced level. This course will be particularly useful for students who wish to specialise in the area of Microeconomics.
As a continuation of ECON6010 Microeconomics A, this course surveys areas of microeconomic theory in which the classical competitive market assumption is relaxed. The first half of the course introduces game theory as a tool for the analysis of strategic interactions. The second half applies the game theoretic tools developed to the area of information economics, which studies economic situations under asymmetric information. This course will be particularly useful for students who wish to specialise in the area of Microeconomics.
Course requirements
Assumed background
It is assumed that students have mastered the materials covered in ECON6010 Microeconomics A. Students should also be comfortable with mathematical analysis. Students enrolling in this course should familiarise themselves with the materials in the Mathematical Appendices of the principal text (see Section 3.1 - Required Learning Resources) if they have not yet done so.
Before attempting this course, you are advised that it is important to complete the appropriate prerequisite course(s) listed on the front of this course profile.ﾠ No responsibility will be accepted by UQ School of Economics, the Faculty of Business, Economics, and Law or the University of Queensland for poor student performance occurring in courses where the appropriate prerequisite(s) has/have not been completed, for any reason whatsoever.
Prerequisites
You'll need to complete the following courses before enrolling in this one:
ECON6010
Incompatible
You can't enrol in this course if you've already completed the following:
ECON8030
Restrictions
BEcon(Hons); BA(Hons)(Economics) and BAdvFin&Econ(Hons)(Economics field of Study)
Course contact
School enquiries
Student 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 to enquiries@economics.uq.edu.au.
Enquiries relating specifically to course content should be directed to the Course Coordinator/Lecturer.
Course staff
Lecturer
Dr Antonio Rosato
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
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.ﾠ
Public Holidays: Wed 14 August (Royal Queensland Show), Mon 7 October (King's Birthday).
In-Semester Break: 23 - 29 September. Semester 2 classes recommence Mon 30 September. ﾠ
Aims and outcomes
This course aimsﾠto equip students with a basic but solid understanding of microeconomic theory required for conducting quality research at an international standard. It provides an overview of key elements in game theory and information economics, as well as techniques for modelling and solving problems in these areas.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Apply game theory to solve microeconomic problems in a logical, rigorous, and precise manner.
LO2.
Critically analyse key issues and concepts in information economics and mechanism design.
LO3.
Model real-world economic situations in which the competitive market model may not be appropriate.
LO4.
Develop communications skills to devise supervised research in microeconomic theory.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Tutorial/ Problem Set | Midsemester Assignment | 35% |
27/08/2024 4:00 pm |
| Tutorial/ Problem Set | Tutorial Exercise | 20% (Best 10 out of 11) |
Due 30 minutes prior to the beginning of each tutorial session. |
| Tutorial/ Problem Set | Final Assignment | 45% |
7/11/2024 4:00 pm |
Assessment details
Midsemester Assignment
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 35%
- Due date
27/08/2024 4:00 pm
- Learning outcomes
- L01, L03, L04
Task description
An open book assignment involving problem solving and/or short answer questions. Questions can be given on any topic covered prior to the midsemester assignment (that is, any topic covered in teaching weeks 1 to 6, inclusive).
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
To be submitted via the course blackboard website.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
Tutorial Exercise
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 20% (Best 10 out of 11)
- Due date
Due 30 minutes prior to the beginning of each tutorial session.
- Learning outcomes
- L01, L02, L03, L04
Task description
A total of eleven (11) sets of tutorial questions will be uploaded on blackboard throughout the course -- one set each week prior to a tutorial session. (There is no problem set due on the week of the Midsemester Assignment.)
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
To be submitted via the course blackboard website.
Deferral or extension
You cannot defer or apply for an extension for this assessment.
Late submission
You will receive a mark of 0 if this assessment is submitted late.
Final Assignment
- Mode
- Written
- Category
- Tutorial/ Problem Set
- Weight
- 45%
- Due date
7/11/2024 4:00 pm
- Learning outcomes
- L01, L02, L03, L04
Task description
An open book assignment involving problem solving and/or short answer questions. Questions can be given on any topic covered in the course.
This assessment task evaluates students' abilities, skills and knowledge without the aid of generative Artificial Intelligence (AI). Students are advised that the use of AI technologies to develop responses is strictly prohibited and may constitute student misconduct under the Student Code of Conduct.
Submission guidelines
Submission will be via the course blackboard website.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 7 days. Extensions are given in multiples of 24 hours.
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 & Guidelines. Please refer to the link to the Academic Integrity Module (AIM). It is strongly recommended that you complete the AIMﾠif you have not already done so.
SUBMISSION OF ASSIGNMENTS
Assignments will not be accepted via E-mail. All assignments must be submitted by the due date and time stated in the course profile.
Assignments may be typed or handwritten, but they must be neat and legible. You are responsible for all points lost due to illegible handwriting.
You are encouraged to discuss the problem sets with each other and to consult reference materials. However, you must hand in individually written problem sets and list the names of all those you have worked with. Identical (or essentially similar) assignments will all receive a grade of zero. All reference materials (including but not limited to solution manuals and any materials found on the Internet) must be properly cited. Failure to do so will result in a grade of zero.
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
References to relevant journal articles will be given in class notes.
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 (22 Jul - 28 Jul) |
Lecture |
Decision Under Uncertainty vNM Expected Utility, Risk preferences, Anscombe-Aumann Subjective Expected Utility, Ambiguity, Allais Paradox and Rabin Paradox Learning outcomes: L01, L04 |
Week 2 (29 Jul - 04 Aug) |
Lecture |
Normal Form Games I Dominance, Rationalizability Learning outcomes: L01, L04 |
Week 3 (05 Aug - 11 Aug) |
Lecture |
Normal Form Games II Nash Equilibrium Learning outcomes: L01, L04 |
Week 4 (12 Aug - 18 Aug) |
Lecture |
Bayesian Games Definition of games with incomplete information, type space, common prior Learning outcomes: L01, L04 |
Week 5 (19 Aug - 25 Aug) |
Lecture |
Bayesian Games II Bayes Nash Equilibrium Learning outcomes: L01, L04 |
Week 6 (26 Aug - 01 Sep) |
Problem-based learning |
Midsemester Assignment Assignment on topics covered up to and including the lecture in Week 5 Learning outcomes: L01, L04 |
Week 7 (02 Sep - 08 Sep) |
Lecture |
Extensive Form Games I Game trees, Kuhn equivalence of mixed and behavioural strategies under perfect recall, perfect information extensive form games, backward induction Learning outcomes: L01, L04 |
Week 8 (09 Sep - 15 Sep) |
Lecture |
Extensive Form Games II Subgame and subgame perfection, belief consistency, sequential equilibrium Learning outcomes: L01, L04 |
Week 9 (16 Sep - 22 Sep) |
Lecture |
Screening Screening model, separating equilibrium, non-existence of equilibrium Learning outcomes: L03, L04 |
Mid Sem break (23 Sep - 29 Sep) |
No student involvement (Breaks, information) |
Mid-Semester Break |
Week 10 (30 Sep - 06 Oct) |
Lecture |
Signaling and Adverse Selection Signalling model, single-crossing property, separating and pooling equilibria, Cho-Kreps Intuitive Criterion, The Market for Lemons. Learning outcomes: L02, L03, L04 |
Week 11 (07 Oct - 13 Oct) |
Lecture |
Moral Hazard Principal-agent problem, first-best and second-best contracts Learning outcomes: L02, L03, L04 |
Week 12 (14 Oct - 20 Oct) |
Lecture |
Mechanism Design I Revelation Principle, Incentive compatible direct mechanism, Ex-post efficient allocation, First-price auction Learning outcomes: L02, L03, L04 |
Week 13 (21 Oct - 27 Oct) |
Lecture |
Mechanism Design II Revenue Equivalence, Optimal auction, Myerson-Satterthwaite Theorem Learning outcomes: 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.