6 points, SCA Band 3, 0.125 EFTSL
Undergraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Department of Econometrics and Business Statistics
- Second semester 2017 (Day)
This unit provides a formal treatment of the core principles underlying econometric and statistical analysis, with particular focus given to likelihood-based inference. Topics covered include the likelihood principle and maximum likelihood estimation; minimum variance unbiased estimation; maximum likelihood asymptotic distribution theory; likelihood-based hypothesis testing; and quasi-maximum likelihood inference. The theoretical developments are supplemented by numerical results produced using computer simulation. Consideration is also given to the numerical optimisation techniques used to implement likelihood-based procedures in practice.
The learning goals associated with this unit are to:
- consolidate the core principles underlying econometric and statistical analysis
- understand and implement the technique of maximum likelihood estimation and develop an appreciation of the associated asymptotic distribution theory
- understand and implement likelihood-based hypothesis testing and quasi-maximum likelihood inference
- develop the skills needed to demonstrate and explore theoretical sampling properties using computer simulation.
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
Students must have passed ETC2410, ETC3440 or MTH2232 or must be enrolled in course 3822 or 4412 before undertaking this unit.