This is a Master degree and PhD level course covering a range of topics in applied microeconomics. The course emphasises a series of research tools and applications with a focus on techniques for quantitative policy analysis. Applications include preference and welfare analysis, productivity and efficiency measures, partial and general equilibrium, management of open-access resources and non-market valuation. In addition to paper-and-pen exercises, students will use computers to perform analysis such as evaluating policy impacts with CGE models, optimal timing for infrastructure investments, comparing productivity of firms and estimating willingness-to-pay for ecological services
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
On successfully completing this course, students are expected to:
· Be familiar with a wide range of the mathematical concepts, formalisms and techniques that are commonly used in applied microeconomics.
· Have confidence in the mathematical techniques required for modelling microeconomic problems for policy analysis and evaluation.
· Be able to perform common policy analysis and evaluation using computers.
Indicative Assessment
The assessment include: three online quizzes (non-redemptive 10% each), a midterm exam (redemptive, 10%) and a final exam (60%). This course covers a lot of material in a short space of time. It is essential that you work consistently throughout the semester. Cramming just before the exam will bring disaster.
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.
Requisite and Incompatibility
Preliminary Reading
A package containing all required readings can be purchased during the first week of lectures. There is no single textbook. Readings are drawn from a number of texts and professional papers.
Assumed Knowledge
· Mathematics: High school algebra, derivative/integration calculus and optimization.
· Statistics and Econometrics: Descriptive statistics and regressions.
· Computer: MsExcel skill is assumed. Students will be introduced to R (http://www.r-project.org) for statistical analysis. However, works in any of the following platforms will 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.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- 3
- Unit value:
- 6 units
If you are an undergraduate student and 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). You can find your student contribution amount for each course 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 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2017 | $3852 |
- International fee paying students
| Year | Fee |
|---|---|
| 2017 | $5130 |
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 |
|---|---|---|---|---|---|---|
| 2921 | 20 Feb 2017 | 27 Feb 2017 | 31 Mar 2017 | 26 May 2017 | In Person | N/A |