6 points, SCA Band 3, 0.125 EFTSL
Postgraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
- Second semester 2017 (Day)
This unit provides a rigorous treatment of core methods of econometric estimation and inference in a single and also multiple equation settings. While students are encouraged to look at every problem from several views (informal, algebraic, geometric, etc.), a large emphasis is placed on constructing formal arguments, and the importance of clear notation, definitions, assumptions and deductive arguments is emphasised. Formal lectures and references to graduate level textbooks are provided, and students are also assigned and encouraged to read some classic journal articles. This unit is designed for PhD students who intend to write a thesis in econometrics or business statistics. It is not intended for PhD students in other disciplines who need to learn some quantitative techniques for the empirical section of their dissertations, although students from other departments who are interested in more advanced methods may wish to take this unit.
The learning goals associated with this unit are to:
- ensure PhD candidates master the core elements of econometrics to be able to generalise and apply these principles to research questions
- encourage and train PhD students to grind through complex scholarly journal articles and harvest the elements needed to conduct research
- train PhD students in developing a habit of using clear notation and clear arguments in research work.
Within semester assessment: 40% + Examination: 60%
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled learning activities and independent study. Independent study may include associated readings, assessment and preparation for scheduled activities. The unit requires on average three/four hours of scheduled activities per week. Scheduled activities may include a combination of teacher directed learning, peer directed learning and online engagement.
See also Unit timetable information