ETF5400 - Econometric theory - 2017

The topics covered in this unit would be (i) invaluable for any student intending to work in applied econometrics, and (ii) essential to understand journal articles in econometrics. This unit introduces some of the essentials to develop a working knowledge of econometrics for large samples. The topics covered include, weak law of large numbers, multivariate central limit theorem, large sample properties of the least squares estimator in the linear model, large sample properties of maximum likelihood estimators, and applications of these to some econometric models used in applied econometric research.

The learning goals associated with this unit are to:

1. define different models used in econometrics and statistics
2. compare different methods of estimating and testing econometric models
3. recommend suitable methods of inference
4. evaluate different methods of inference for econometric models
5. summarise the advantages and disadvantages of various methods of inference.

Within semester assessment: 100%

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

Professor Mervyn Silvapulle

Students must be enrolled in course code 3816 or 3822 or 3194 or 4412 or be granted permission. It is recommended that students should have a high level of familiarity with the topics covered in ETF2100 and ETF2700.