units

ETC4400

Faculty of Business and Economics

Monash University

Undergraduate, Postgraduate - Unit

This unit entry is for students who completed this unit in 2014 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

print version

6 points, SCA Band 3, 0.125 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered, or view unit timetables.

LevelUndergraduate, Postgraduate
FacultyFaculty of Business and Economics
Organisational UnitDepartment of Econometrics and Business Statistics
OfferedNot offered in 2014
Coordinator(s)Professor Don Poskitt

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:

  1. 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)
  2. outline the classical Method of Moments and relationship of Regression to the Method of Moments
  3. discuss Identification and Asymptotic Distribution Theory in the context of the GMM
  4. examine GMM in relation to minimum variance unbiased estimation, and GMM based inference
  5. consider special cases of single equation and simultaneous equations GMM.

Assessment

Within semester assessment: 40%
Examination: 60%

Chief examiner(s)

Workload requirements

Minimum total expected workload equals 144 hours per semester

Prerequisites