- Code EMET8014
- 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
- Academic career PGRD
- Dr Juergen Meinecke
- Mode of delivery In Person
First Semester 2019
See Future Offerings
The course covers advanced estimation methods in econometrics. Specific topics include: projections and ordinary least squares estimation; endogeneity; instrumental variables and two stage least squares estimation; maximum likelihood estimation of models with limited dependent variables. The course is primarily theoretical and looks at various estimators and their finite sample and asymptotic properties.
Upon successful completion, students will have the knowledge and skills to:
- define OLS, IV and maximum likelihood estimators mathematically;
- derive and examine finite sample and asymptotic properties of these estimators analytically;
- demonstrate an understanding of the strengths and limitations of the different estimators;
- employ linear algebra in key econometric derivations;
- apply econometric theory to concrete examples in economics.
- The assessment consists of two parts: assignments and a final exam. (100) [LO 1,2,3,4,5]
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Workload10 hours per week including class time
Requisite and Incompatibility
See Class Summary and Wattle site
Tuition fees are for the academic year indicated at the top of the page.
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- 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.
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Offerings, Dates and Class Summary Links
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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|
|2640||25 Feb 2019||04 Mar 2019||31 Mar 2019||31 May 2019||In Person||View|