Faculty of Business and Economics

Postgraduate - Unit

This unit entry is for students who completed this unit in 2013 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

To find units available for enrolment in the current year, you must make sure you use the indexes and browse unit tool in the current edition of the Handbook.

FacultyFaculty of Business and Economics
Organisational UnitDepartment of Econometrics and Business Statistics
OfferedCaulfield First semester 2013 (Day)
Caulfield Second semester 2013 (Day)
Coordinator(s)Dr Vasilis Sarafidis (Semester one)


This unit presents econometric models and techniques that are widely used in applied econometrics. The topics covered are:

  1. linear regression models with random regressors, method of moments and instrumental variables estimations
  2. simultaneous equations models
  3. models for time-series data
  4. introduction to maximum likelihood estimation
  5. models for discrete dependent variables
  6. models for panel data.

EViews computer software is used to carry out data analysis and estimation.


The learning goals associated with this unit are to:

  1. conduct statistical inference in linear regression models with random regressors using the method of moments and the instrumental variables estimators.
  2. conduct statistical inference for simultaneous equations models.
  3. understand the statistical properties of nonstationary macroeconomic time series data and how to model the long-run relationships among co-integrated time series.
  4. conduct statistical inference in models with discrete dependent variables.
  5. conduct statistical inference in panel data models.


Within semester assessment: 35%
Examination: 65%

Chief examiner(s)

Contact hours

3 hours per week


Students must be enrolled in course codes 3816 or 3822 or 4412 or must have passed ETF2100 or ETF9100.