ETC5440 Econometric theory
Faculty of Business and Economics
ETC5440 Econometric theory is a level 5, 6-credit-point, postgraduate unit from the Faculty of Business and Economics, offered in 2020 in Semester 2 at Clayton. It needs ETC5340 or ETC3400.
- Credit points
- 6
- Offered in 2020
- Semester 2
- Clayton
- Workload
- 144 hours
- per semester
This is the 2020 handbook entry. See the 2027 entry.
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Requisites
Before ETC5440
Prohibitions
You can't enrol if you have passed any of these.
Prerequisites
Pass these before you enrol.
After ETC5440
No unit lists ETC5440 as a prerequisite in the 2020 handbook.
Equivalent units
The same content under another code. Only one of them counts.
Overview
The objective of this unit is to outline the general principles that underlie advanced methods of statistical inference. Building on the maximum likelihood estimator (MLE), the unit provides a formal treatment of quasi-MLE, generalized method of moments (GMM), non-parametric methods and the bootstrap. The discussion is motivated by reference to econometric and statistical models and data, and simple practical examples with which students should be familiar. It is shown that these methods find application in many areas of econometrics and business statistics, and may be viewed as encompassing many familiar econometric and statistical techniques. Broad topic headings are: quasi-MLE, classical method of moments and regression (OLS and IV), GMM, identification, non-parametric methods, the bootstrap, asymptotic distribution theory and optimal inference. Simulation experiments are used to reinforce the theoretical derivations.
Offerings in 2020
| Teaching period | Campus | Mode |
|---|---|---|
| Second semester | Clayton | On campus |
Learning outcomes
When you finish this unit, you should be able to:
- 1
build upon existing concepts developed in previous courses and to outline the basic principles underlying more advanced methods of inference
- 2
highlight when and why different inferential methods are needed
- 3
discuss the problem of endogeneity, and the link between GMM and instrumental variables
- 4
discuss asymptotic distribution theory in the context of all methods and explain its use in inference
- 5
demonstrate the use of computer simulation to explore theoretical concepts.
Workload and teaching
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.
Contacts
- Chief Examiners
- Professor Gael Martin