This course involves on campus teaching. For students unable to come to campus there will be a remote option. See the Class Summary for more details.
This course provides an introduction to econometric methods and their applications. The main workhorse of applied econometrics is the linear regression model and the course will develop its theory and look at a wide range of applications. The course emphasizes intuitive and conceptual understanding as well as hands on econometric analysis using modern computer software on data sets from economics and business. Students learn how to conduct empirical studies, as well as how to analyze and interpret results from other empirical works. We cover a broad range of topics, including: brief review of basic statistics; ordinary least squares estimation and its properties; choice of functional form; departures from standard OLS assumptions; time series analysis.
This is a hand-on course with a focus on applications in economics as well as business. A standard statistical software will be used during computer sessions, no special programming skills are required.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
- define the ordinary least squares (OLS) estimator in the linear regression model;
- derive and examine statistical properties of the OLS estimator;
- employ the central limit theorem to approximate the statistical distribution of the OLS estimator;
- demonstrate an understanding of strengths and limitations of the OLS estimator;
- summarise and analyse actual economic data with use of a specialised econometric software;
- contextualise and critically evaluate the results of empirical analysis.
Other Information
Indicative Assessment
- Assignment 1 (10) [LO 1,2,3,4,5,6]
- Assignment 2 (10) [LO 1,2,3,4,5,6]
- Mid-semester examination (30) [LO 1,2,3,4,5,6]
- Final examination (50) [LO 1,2,3,4,5,6]
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
Students taking this course are expected to commit at least 10 hours per week consisting of 2 hours of lectures, a 1 hour of computer tutorial and a 1 hour of problem solving tutorial as well as 6 hours of private study
Inherent Requirements
Not applicable
Requisite and Incompatibility
Prescribed Texts
see Class Summary and Wattle site
Majors
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 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2022 | $4440 |
- International fee paying students
| Year | Fee |
|---|---|
| 2022 | $5700 |
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 |
|---|---|---|---|---|---|---|
| 4319 | 21 Feb 2022 | 28 Feb 2022 | 31 Mar 2022 | 27 May 2022 | In Person | View |
