6 points, SCA Band 3, 0.125 EFTSL
Undergraduate, Postgraduate - Unit
Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered.
Faculty
Organisational Unit
Department of Econometrics and Business Statistics
Chief examiner(s)
Coordinator(s)
Not offered in 2019
Prerequisites
Synopsis
The objective of this unit is to outline the general principles that underlie what has become known as the Generalized Method of Moments (GMM). The discussion is motivated by reference to econometric and statistical techniques, and simple practical examples with which students should be familiar. It is shown that GMM finds application in many areas of econometrics and business statistics, and that GMM may be viewed as a methodology that encompasses many econometric and statistical techniques. Broad topic headings are: Classical Method of Moments and Regression (OLS and IV), GMM, Identification, Asymptotic Distribution Theory for GMM, GMM and Optimal Inference.
Outcomes
The learning goals associated with this unit are to:
- build upon existing concepts developed in previous courses and to outline the basic principles under-lying what has become known as the Generalized Method of Moments (GMM)
- outline the classical Method of Moments and relationship of Regression to the Method of Moments
- discuss Identification and Asymptotic Distribution Theory in the context of the GMM
- examine GMM in relation to minimum variance unbiased estimation, and GMM based inference
- consider special cases of single equation and simultaneous equations GMM.
Assessment
Within semester assessment: 40% + Examination: 60%
Workload requirements
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