- Code EMET2007
- Unit Value 6 units
- Offered by Research School of Economics
- ANU College ANU College of Business and Economics
- Course subject Econometrics
- Areas of interest Econometrics
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.
Upon successful completion, students will have the knowledge and skills to:
Upon successful completion of the requirements for this course, students will
- understand and appreciate the challenges of empirical modelling in economics and business;
- have a deep knowledge of regression analysis (including statistical foundations, underlying assumptions, properties, extensions, limitations);
- understand econometric methods relevant for analyzing data used in economics and business;
- be able to use econometric software to conduct regression analysis on actual data sets;
- be able to interpret and critically evaluate the results of empirical analysis;
- be able to read and understand academic journal articles that make use of the concepts and methods that are introduced in the course;
- be able to independently conduct small scale empirical research and write up results;
- be able to think clearly about the relationship between data, model and estimation in econometrics.
See the course outline on the College courses page. Outlines are uploaded as they become available.
Assignment 1 - 10%
Assignment 2 - 10%
Mid-semester examination - 30%
Final examination - 50%
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.
Five contact hours per week plus private study time.
Requisite and Incompatibility
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:
- 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.
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.
|Class number||Class start date||Last day to enrol||Census date||Class end date||Mode Of Delivery||Class Summary|
|2711||15 Feb 2016||26 Feb 2016||31 Mar 2016||27 May 2016||In Person||N/A|