ETC2400

Econometrics

Dr Gael Martin

6 points · Two 1-hour lectures and one 2-hour tutorial per week · First and second semester · Clayton · Prerequisite: ETC1031 or equivalent · Prohibitions: ETC2410, ETC3440

Objectives On successful completion of this subject students should have a sound understanding of the application of classical linear regression analysis in estimating and testing the validity of economic relationships. They should have a rigorous understanding of the foundations of the classical regression model and be capable of deriving the properties of least squares estimators under classical assumptions and demonstrating the consequences of common violations of these assumptions; applying tests and appropriate estimation procedures about the relationships between variables and for violations of the underlying assumptions; applying this knowledge to estimate, analyse and forecast multiple regression models with typical economic and business data.

Synopsis An introduction to linear multiple regression methods; properties of least squares estimators; probability distributions and their applications to hypothesis testing; an introduction to the generalised least squares estimator; an introduction to the problems of heteroscedasticity, serial correlation, multicollinearity, structural breaks and stochastic regressors.

Assessment Test (30 mins): 10% · Two 2-hour open-book tests: 30% · Examination (2 hours): 60%

Prescribed texts

Johnston J and Dinardo J Econometric methods 4th edn, McGraw-Hill, 1997

Recommended texts

Griffiths W E, Hill R C and Judge G G Learning and practising econometrics Wiley, 1993
Gujarati D N Basic econometrics 3rd edn, McGraw-Hill, 1995
Judge, G G, Hill R C, Letepohl H and Lee T C Introduction to the theory and practice of econometrics 2nd edn, Wiley, 1988

Back to the 1999 Business and Economics Handbook