Course coordinator
Professor Lana Friesen
Please refer to the Blackboard course for consultation details.
Course overview
- Study period
- Semester 2, 2025 (28/07/2025 - 22/11/2025)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Economics School
Experimental economics is concerned with how people make real world decisions. It is also concerned with how businesses, organisations, teams, markets and other institutions work as a result of decisions made by real people. It employs laboratory or field experiments to find out whether or not real people actually behave in the way economic theory predicts, and if not why not and why this matters for policy makers and managers. This course will examine a number of topics in economics using experimental methods.
This course introduces students to the use of experiments in economics as a means of studying decision making both in markets and individual choices. Along with being introduced to the main subject areas where experiments have been used, students will also gain an understanding of the basic methods of experimental economics.
Course requirements
Assumed background
In accordance with the prerequisite subjects, basic knowledge of microeconomics is assumed (e.g., demand and supply).
Prerequisites
You'll need to complete the following courses before enrolling in this one:
ECON1010 or ECON1011 or ECON2011
Incompatible
You can't enrol in this course if you've already completed the following:
ECON3060
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
Professor Lana Friesen
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Each week we will have a three hour lecture. At the beginning of most lectures, students will take part in economics experiments, which form an essential component of learning about experiments. We will discuss the results from these experiments during the remainder of the lecture. Refer to the Learning Activities section of this Course Profile for the schedule of experiments.
Please see the Learning Activities section of this Course Profile for the timetabling implications of public holidays.
Important Dates:
- Public Holidays: Wed 13 August (Royal Queensland Show Holiday), Mon 6 October (King’s Birthday public holiday).
- Mid-Semester Break: 29 September – 3 October. Semester 2 classes recommence on Tue 7 October.
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
Experimental economics is concerned with using experiments (both laboratory and field) to address theoretical and policy issues in economics. This course will introduce students to the experimental method in economics. The aim is to expose students to the major subject areas where the method has been applied. In the process of doing so, students will also learn about the advantages and disadvantages of the method and some key issues in experimental design.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Describe the main areas where the experimental method has been used in economics.
LO2.
Explain the key insights for decision making generated from applying the experimental method in economics.
LO3.
Discuss the methodology of experimental economics, including the advantages and disadvantages of the method.
LO4.
Apply the key insights from experimental economics to provide recommendations for policy makers and managers.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Participation/ Student contribution |
Participation in Economic Experiments
|
8% (1%, best 8 of 9) |
Experiments will be run during the timetabled lecture time. |
| Paper/ Report/ Annotation | Proposal for the Policy Recommendation Report | 10% |
1/09/2025 1:00 pm |
| Paper/ Report/ Annotation | Policy Recommendation Report | 40% |
13/10/2025 1:00 pm |
| Examination |
End-of-semester Exam
|
42% |
End of Semester Exam Period 8/11/2025 - 22/11/2025 |
Assessment details
Participation in Economic Experiments
- In-person
- Mode
- Activity/ Performance
- Category
- Participation/ Student contribution
- Weight
- 8% (1%, best 8 of 9)
- Due date
Experiments will be run during the timetabled lecture time.
- Learning outcomes
- L01, L02
Task description
There will be NINE (9) experiments conducted in lectures throughout the semester as shown in the schedule of Learning Activities.
Students will receive 1% (per experiment) for actively participating in up to 8 of these experiments and in the discussion that follows (for a maximum of 8% of your final course grade).
To participate, students will need to bring their own device to the lecture - ideally a laptop or tablet - in order to access the experimental interface. (Phone screens are too small to properly view the experiment.)
Note that due to the software used for the experiments, once the experiment begins it is impossible to add extra participants. Therefore, if you arrive late to the lecture you will not be able to participate.
Also, note that, at a minimum, active participation requires paying attention to the ongoing experiment and not unduly holding up progress by inattention.
Students are required to actively participate in the online experiments and discussion conducted during our weekly lectures.
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.
Late submission
Non-participation in experiments will result in no marks for the experiments missed. There are 9 experiments conducted in lectures throughout the semester, the best 8 will be taken into account.
Proposal for the Policy Recommendation Report
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 10%
- Due date
1/09/2025 1:00 pm
- Learning outcomes
- L02, L03, L04
Task description
The purpose of the Proposal is to identify an appropriate problem to analyse in your final Policy Recommendation Report. Students will get feedback from the marker on their proposed problem and selection of articles, which they can incorporate when developing their final Policy Recommendation Report.
Detailed instructions and the marking criteria will be provided on the course Blackboard site.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools.
Submission guidelines
Submit proposal electronically via Turnitin on Blackboard by the deadline date and time.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Extensions are limited to 14 calendar days to ensure timely feedback to other students.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
Policy Recommendation Report
- Mode
- Written
- Category
- Paper/ Report/ Annotation
- Weight
- 40%
- Due date
13/10/2025 1:00 pm
- Learning outcomes
- L02, L03, L04
Task description
You are working as a consultant for the government, a business, or an NGO. Your task is to write a research report on a problem of your choice with a recommendation on how best to address the problem based on evidence from experimental economics. The report should evaluate several different solutions to your problem and then make a recommendation based on the credibility of the experimental evidence presented.
Your report should be based on your earlier Proposal.
Detailed instructions and marking criteria will be provided on the course Blackboard site.
This task has been designed to be challenging, authentic and complex. Whilst students may use AI and/or MT technologies, successful completion of assessment in this course will require students to critically engage in specific contexts and tasks for which artificial intelligence will provide only limited support and guidance.
A failure to reference generative AI or MT use may constitute student misconduct under the Student Code of Conduct.
To pass this assessment, students will be required to demonstrate detailed comprehension of their written submission independent of AI and MT tools
Submission guidelines
Submit report electronically via Turnitin on Blackboard by the deadline date and time.
Deferral or extension
You may be able to apply for an extension.
The maximum extension allowed is 14 days. Extensions are given in multiples of 24 hours.
Extensions are limited to 14 calendar days to ensure timely feedback to other students.
Late submission
A penalty of 10% of the maximum possible mark will be deducted per 24 hours from time submission is due for up to 7 days. After 7 days, you will receive a mark of 0.
End-of-semester Exam
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 42%
- Due date
End of Semester Exam Period
8/11/2025 - 22/11/2025
- Other conditions
- Secure.
- Learning outcomes
- L01, L02, L03
Task description
The final exam will cover all course content and be comprised of a combination of multiple choice, short answer, and longer answer questions. Further details will be made available on the course Blackboard site.
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.
Exam details
| Planning time | 10 minutes |
|---|---|
| Duration | 120 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
Using AI at UQ
Visit the AI Student Hub for essential information on understanding and using Artificial Intelligence in your studies responsibly.
Plagiarism
The School of Economics is committed to reducing the incidence of plagiarism. You are encouraged to read the UQ Student Integrity and Misconduct Policy available in the Policies and Procedures section of this course profile.
The Academic Integrity Module (AIM) outlines your obligations and responsibilities as a UQ student. It is compulsory for all new to UQ students to complete the AIM.
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
Library resources are available on the UQ Library website.
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 |
Lecture |
Lecture 1: Course Introduction Learning outcomes: L01, L03 |
Week 2 |
Lecture |
Lecture 2: Markets (including Experiment 1) Learning outcomes: L01, L02, L03 |
Week 3 |
Lecture |
Lecture 3: Asset Markets (including Experiment 2) Learning outcomes: L01, L02, L03 |
Week 4 |
Lecture |
Lecture 4: Policy Recommendation Report Preparation (including Library Training Session) Learning outcomes: L04 |
Week 5 |
Lecture |
Lecture 5: Experimental Methods Learning outcomes: L01, L03 |
Week 6 |
Lecture |
Lecture 6: Gut Feelings & Effortful Thinking (including Experiment 3) Learning outcomes: L01, L02, L03 |
Week 7 |
Lecture |
Lecture 7: Thinking Strategically I (including Experiment 4) Learning outcomes: L01, L02, L03 |
Week 8 |
Lecture |
Lecture 8: Thinking Strategically II (including Experiment 5) Learning outcomes: L01, L02, L03 |
Week 9 |
Lecture |
Lecture 9: The Ultimatum Game (including Experiment 6) Learning outcomes: L01, L02, L03 |
Mid Sem break |
No student involvement (Breaks, information) |
Mid-Semester Break No Lecture this week |
Week 10 |
Lecture |
Lecture 10: Trust & Trustworthiness (including Experiment 7) Learning outcomes: L01, L02, L03 |
Week 11 |
Lecture |
Lecture 11: Trust and its Market Implications (including Experiment 8) Learning outcomes: L01, L02, L03 |
Week 12 |
Lecture |
Lecture 12: Cooperation in Social Dilemmas (including Experiment 9) Learning outcomes: L01, L02, L03 |
Week 13 |
Lecture |
Lecture: Spillovers (if required) & Review Learning outcomes: L01, L02, L03 |
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 for Students Policy and Procedure
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.