- Code IDEC8017
- Unit Value 6 units
- Offered by Crawford School of Public Policy
- ANU College ANU College of Asia and the Pacific
- Course subject International and Developmental Economics
- Areas of interest Economics
- Academic career PGRD
- Dr Hoa Nguyen
- Mode of delivery In Person
Second Semester 2022
See Future Offerings
This course is available for in-person and remote (online) learning.
This course is an introduction for economics graduate students to the techniques of econometrics. The emphasis is on the essential ideas and the applications of econometric methods rather than on technical and theoretical details. However the results are not just presented but instead are derived using a mixture of rigour and intuition so as to leave as few loose ends as possible. We recognise that available economic data are either cross sectional (observations on several economic units - usually countries, firms or households - at a single point in time) or time series (observations one economic unit over time), or panel (observations on several economic units followed through time), and each type of data may need its special set of tools. We start with the linear regression model, which is the simplest model for explaining one variable using several explanatory variables, and then move to an introduction to ‘micro-econometrics', i.e., methods most useful for the analysis of cross sectional data, and an introduction to ‘macro-econometrics', i.e., methods most useful for the analysis of aggregate data over time.
Upon successful completion, students will have the knowledge and skills to:
- interpret regression coefficients in linear and nonlinear regression models
- assess the fit and statistical significance of econometric relationships
- construct interval estimates and hypothesis tests of interesting economic hypotheses, including those involving several parameters
- distinguish different forms of data and the models appropriate for them: cross section and time series
- critically assess choices of functional form
- understand the assumptions in the statistical model, the consequences of failure and methods of detection
- use the statistical package.
Delivery Mode: On-Campus. 2 hours of lectures and 1 hour tutorial a week for a 13 week semester.
- Assignments 15% (15) [LO null]
- Mid-semester examination 20% (20) [LO null]
- Final examination 65% Both examinations will be in the standard closed-book format. Your final grade from the course will generally not be the exact result of the calculation, as scaling of scores is often necessary after the raw score is calculated. The scaling, if needed, will preserve the order and the scaling may be up or down. (65) [LO null]
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Contact of 3 hours and a total 10 hours a week.
Jeffrey M. Wooldridge, Introductory Econometrics: A Modern Approach, South-Western, 3rd edition 2006, ISBN 0-324-28978-2
Marno Verbeek, A Guide to Modern Econometrics, Wiley, 2nd edition 2004, ISBN 0-470-85773-1.
Students should have a background with at least undergraduate study of economics, including courses in basic mathematics and statistics for economics.
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:
- 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.
Offerings, Dates and Class Summary Links
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|
|5347||25 Jul 2022||01 Aug 2022||31 Aug 2022||28 Oct 2022||In Person||N/A|
|7162||25 Jul 2022||01 Aug 2022||31 Aug 2022||28 Oct 2022||Online||N/A|