Course coordinator
Dr Antonio Andres Bellofatto
Course overview
- Study period
- Semester 1, 2026 (23/02/2026 - 20/06/2026)
- Study level
- Undergraduate
- Location
- St Lucia
- Attendance mode
- In Person
- Units
- 2
- Administrative campus
- St Lucia
- Coordinating unit
- Economics School
This is an advanced course in macroeconomics intended for Honours students. The course covers core analytical and quantitative tools which are at the backbone of a wide range of applications in macroeconomics. Topics include: dynamic optimisation, dynamic general equilibrium modelling, growth/business cycles, heterogeneous agents, and foundations of computational methods to solve macroeconomic models.
This is an advanced course in macroeconomics intended for Honours students. The course aims at building a deep understanding of modern macroeconomics and its applications.
This course is divided into two parts. The first part covers fundamental features of dynamic general equilibrium models, which are at the backbone of many areas in macroeconomics and beyond. We develop analytical and numerical tools for solving such models within deterministic frameworks, and concentrate on applications to economic growth.
The second part focuses on extensions that incorporate uncertainty, which comprise applications ranging from business cycle fluctuations to heterogeneous agents models.
Course requirements
Incompatible
You can't enrol in this course if you've already completed the following:
ECON6020
Restrictions
Enrolment restricted to students in the BEcon(Hons), BAdvFinEcon(Hons), BA(Hons - Economics)
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 Andres Bellofatto
Timetable
The timetable for this course is available on the UQ Public Timetable.
Additional timetable information
Lectures commence in Teaching Week 1.
Please see the Learning Activities section of this Course Profile for the timetabling implications of public holidays.
Important Dates:
- Public Holidays: Fri 3 April (Good Friday), Mon 4 May (Labour Day).
- Mid-Semester Break: 6 April - 10 April. Semester 1 classes recommence on Mon 13 April.
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 aim of the course is to equip students with graduate-level techniques to interpret, build, and estimate macroeconomic models. Such frameworks provide key foundations to do research in macroeconomics, and to inform and critically evaluate macroeconomic policymaking.
Learning outcomes
After successfully completing this course you should be able to:
LO1.
Interpret theoretical building blocks of modern macroeconomic models.
LO2.
Apply macroeconomic frameworks to analyse real world problems.
LO3.
Evaluate the effects and desirability of macroeconomic policies.
LO4.
Apply computational methods to solve dynamic optimisation problems in macroeconomics.
Assessment
Assessment summary
| Category | Assessment task | Weight | Due date |
|---|---|---|---|
| Computer Code, Essay/ Critique, Tutorial/ Problem Set |
Problem Set 1
|
15% |
Week 7, 5:00 pm |
| Computer Code, Essay/ Critique, Project, Tutorial/ Problem Set |
Problem Set 2
|
15% |
Week 13, 5:00 pm |
| Examination |
In-Semester Exam
|
30% |
Week 7
Exam will take place during lecture on Friday 17 April. |
| Examination |
End of Semester Exam
|
40% |
End of Semester Exam Period 6/06/2026 - 20/06/2026 |
Assessment details
Problem Set 1
- Identity Verified
- Team or group-based
- Mode
- Oral, Written
- Category
- Computer Code, Essay/ Critique, Tutorial/ Problem Set
- Weight
- 15%
- Due date
Week 7, 5:00 pm
- Other conditions
- Longitudinal.
- Learning outcomes
- L01, L02, L03, L04
Task description
This task has been designed to be challenging, authentic and complex. The assignment consists of various methodological questions that assess the understanding and the ability of the student to apply the concepts and models studied in class. The assignment may also include questions which require applying numerical solution methods using a programming language.
The assignment has two components: (1) Written submission (worth 75% of the total assignment weight), and (2) Oral follow-up (worth 25% of the total assignment weight).
(1) Written submission: Students should should prepare a pdf document including typed solutions, derivations, plots, and interpretations. Students should also include an appendix including computer codes (if applicable). Students may use Artificial Intelligence (AI) technologies for this component of the assessment. However, the use of AI tools should be disclosed---a failure to reference generative AI may constitute student misconduct under the Student Code of Conduct.
(2) Oral follow-up: To pass this assessment, students should also demonstrate detailed comprehension of their written submission in a short oral examination. The use Artificial Intelligence (AI) technologies is not permitted during the oral component.
Submission guidelines
Submission via Blackboard by the specified due date and time. In addition, students should email their codes for the computational part (if applicable) to the lecturer. Details on scheduling the oral follow-up will be provided on Blackboard.
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.
Requests for the granting of extensions must be submitted through my.UQ: Applying for an extension - my.UQ - University of Queensland with supporting documentation before the submission due date/time. If an extension is approved, the new agreed date for submission will be noted on the application and the student notified through their student email. Extensions cannot exceed the number of days you suffered from a medical condition, as stated on the medical certificate.
For full details, students should refer to the Guidelines for Applying for an Extension.
Late submission
A penalty of 10% of the maximum possible mark allocated for the assessment item will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24 hour block is recorded from the time the submission is due.
Students who fail to attend their scheduled oral follow-up without prior approval will receive a score of 0 (zero) for the entire assessment (i.e., written submission and oral presentation).
Penalties will be applied unless there is sufficient evidence that the late submission is beyond the control of the student. Course coordinators decide on the evidence presented whether they will accept a late submission.
Problem Set 2
- Identity Verified
- Team or group-based
- Mode
- Oral, Written
- Category
- Computer Code, Essay/ Critique, Project, Tutorial/ Problem Set
- Weight
- 15%
- Due date
Week 13, 5:00 pm
- Other conditions
- Longitudinal.
- Learning outcomes
- L01, L02, L03, L04
Task description
This task has been designed to be challenging, authentic and complex. The assignment consists of various methodological questions that assess the understanding and the ability of the student to apply the concepts and models studied in class. The assignment may also include questions which require applying numerical solution methods using a programming language.
The assignment has two components: (1) Written submission (worth 75% of the total assignment weight), and (2) Oral follow-up (worth 25% of the total assignment weight).
(1) Written submission: Students should should prepare a pdf document including typed solutions, derivations, plots, and interpretations. Students should also include an appendix including computer codes (if applicable). Students may use Artificial Intelligence (AI) technologies for this component of the assessment. However, the use of AI tools should be disclosed---a failure to reference generative AI may constitute student misconduct under the Student Code of Conduct.
(2) Oral follow-up: To pass this assessment, students should also demonstrate detailed comprehension of their written submission in a short oral examination. The use Artificial Intelligence (AI) technologies is not permitted during the oral component.
Submission guidelines
Submission via Blackboard by the specified due date and time. In addition, students should email their codes for the computational part (if applicable) to the lecturer. Details on scheduling the oral follow-up will be provided on Blackboard.
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.
Requests for the granting of extensions must be submitted through my.UQ: Applying for an extension - my.UQ - University of Queensland with supporting documentation before the submission due date/time. If an extension is approved, the new agreed date for submission will be noted on the application and the student notified through their student email. Extensions cannot exceed the number of days you suffered from a medical condition, as stated on the medical certificate.
For full details, students should refer to the Guidelines for Applying for an Extension.
Late submission
A penalty of 10% of the maximum possible mark allocated for the assessment item will be deducted per day for up to 7 calendar days, at which point any submission will not receive any marks unless an extension has been approved. Each 24 hour block is recorded from the time the submission is due.
Students who fail to attend their scheduled oral follow-up without prior approval will receive a score of 0 (zero) for the entire assessment (i.e., written submission and oral presentation).
Penalties will be applied unless there is sufficient evidence that the late submission is beyond the control of the student. Course coordinators decide on the evidence presented whether they will accept a late submission.
In-Semester Exam
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 30%
- Due date
Week 7
Exam will take place during lecture on Friday 17 April.
- Other conditions
- Time limited, Secure.
- Learning outcomes
- L01, L02, L03, L04
Task description
This will be a closed-book, invigilated, paper based exam, to be held during class. The material covered for this exam will be announced in class and on Blackboard. The exam will consist of short answer and problem solving questions.
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 | 90 minutes |
| Calculator options | No calculators permitted |
| 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.
End of Semester Exam
- Identity Verified
- In-person
- Mode
- Written
- Category
- Examination
- Weight
- 40%
- Due date
End of Semester Exam Period
6/06/2026 - 20/06/2026
- Other conditions
- Time limited, Secure.
- Learning outcomes
- L01, L02, L03, L04
Task description
This will be a closed-book invigilated, paper-based on campus exam, to be held during the examination period. It will cover material from all lectures, and will consist of short answer and problem solving questions.
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 | No calculators permitted |
| 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%. Grade X = "No assessable work received."
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 Section 6.1 - Assessment Related Policies & Guidelines. Please refer to Section 6.1 and the link to the Academic Integrity Module (AIM). It is strongly recommended that you complete the AIM if 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
Library resources are available on the UQ Library website.
Other course materials
If we've listed something under further requirement, you'll need to provide your own.
Required
| Item | Description | Further Requirement |
|---|---|---|
| Lecture notes/ Slides | ||
| Articles provided by the lecturer |
Additional learning resources information
The course reading list includes various recommended resources and can be accessed through the Library's reading list system Talis Aspire.
References to some articles will be provided in lecture notes and/or via 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 |
|---|---|---|
Multiple weeks From Week 1 To Week 3 |
Lecture |
Tools I Dynamic optimisation in continuous time, numerical methods, Matlab introduction Learning outcomes: L01, L04 |
Multiple weeks From Week 4 To Week 6 |
Lecture |
Dynamic General Equilibrium Ramsey-Cass-Koopmans model and applications Learning outcomes: L01, L02, L03, L04 |
Mid-sem break (06 Apr - 12 Apr) |
No student involvement (Breaks, information) |
Mid-semester Break |
Multiple weeks From Week 7 To Week 9 |
Lecture |
Tools II Dynamic optimmisation in discrete time, numerical methods Note: In-semester exam is held during lecture in teaching week 7 Learning outcomes: L01, L04 |
Multiple weeks From Week 10 To Week 12 |
Lecture |
Heterogeneous agents Models of heterogeneous households and heterogeneous firms, and applications. Learning outcomes: L01, L02, L03, L04 |
Week 13 (25 May - 31 May) |
Lecture |
Spinoffs 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 for Students Policy and Procedure
- AI for Assessment Guide
Learn more about UQ policies on my.UQ and the Policy and Procedure Library.