This course is available for on-campus & remote (online) learning. All students participate in interactive, real-time classes.
This is a Master- and PhD-level course covering a range of topics in applied microeconomics. The course introduces a series of microeconomics research tools and applies them to undertake quantitative analysis. Applications include preference and welfare analysis, productivity and efficiency measures, partial and general equilibrium, the management of open-access resources, and non-market valuation. In addition to paper-and-pen exercises, students will perform analysis such as evaluating policy impacts with computable general equilibrium models, evaluating optimal timing for infrastructure investments, comparing firm productivity levels, and estimating the willingness-to-pay for ecological services.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- Demonstrate mastery of a wide range of mathematical concepts and formalisations in applied microeconomics.
- Display competency in the techniques required for modelling microeconomic problems.
- Apply microeconomic analysis to real-world problems.
- Identify policy implications emerging from advanced microeconomic analysis.
- Communicate microeconomic methods and results in written form to technical and non-technical audiences.
Indicative Assessment
- Assignment 1 (8) [LO 1,2,3,4]
- Assignment 2 (8) [LO 1,2,3,4]
- Assignment 3 (8) [LO 1,2,3,4]
- Case study (20) [LO 1,2,3,4,5]
- Final exam (56) [LO 1,2,3,4,5]
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
A standard course workload is 130 hours including in class time and independent study. This course covers a lot of material in a short space of time. It is essential that students work consistently throughout the semester.
Inherent Requirements
None.
Requisite and Incompatibility
Prescribed Texts
None.
Assumed Knowledge
- Mathematics: Algebra, derivative/integration calculus, and optimisation.
- Statistics and econometrics: Descriptive statistics and regressions.
- Computer skills: Excel skills are assumed. Students will be introduced to R (http://www.r-project.org) for statistical analysis. However, work in any of the following platforms will also be accepted: Matlab, C, Mathematica, Maple, Python, Julia, Visual Basic, Stata, EViews.
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 34
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
First Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 2204 | 17 Feb 2025 | 24 Feb 2025 | 31 Mar 2025 | 23 May 2025 | In Person | N/A |
