Subject ECOM90002 (2010)

Note: This is an archived Handbook entry from 2010.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2010:

Semester 1, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: Three hours of classes per week plus three hours of seminars during the semester
Total Time Commitment: Estimated total time commitment of 120 hours per semester
Prerequisites: Introductory Econometrics or equivalent
Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects:

316-317 Econometrics

Core Participation Requirements:

For the purposes of considering requests for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements for this entry.

The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website:


Prof Vance Martin


Graduate School of Business and Economics Student Centre
Level 4, 198 Berkeley Street
Telephone: +61 3 8344 1670
Online Enquiries:
Subject Overview: Extensions of the multiple regression model are examined. Topics include non-linear least squares, maximum likelihood estimation and related testing procedures, generalised least squares, heteroskedasticity, autocorrelation and models with stochastic regressors. Limited dependent variable models and issues involving time-series data are introduced. Theoretical concepts are illustrated by applied examples. The computer software used is EVIEWS.
Objectives: On successful completion of this subject students should be able to:
  • Explain the concept of maximum likelihood estimation;
  • Use the EViews software program to find maximum likelihood estimates for nonlinear models, heteroskedastic and auto-correlated error models, seemingly unrelated regressions, binary choice and limited dependent variable models;
  • Interpret EViews output and place that interpretation in an economic context relevant to the model being estimated;
  • Explain the difference between the Wald, likelihood ratio and Lagrange multiplier testing procedures;
  • Use EViews output to perform tests for a variety of hypotheses;
  • Explain the concepts of endogeneity, instrumental variable and method of moments estimation and simultaneous equations models;
  • Use EViews to estimate simultaneous equation models and interpret the output;
  • Explain the time series concepts of stationarity, spurious regression, unit root tests and cointegration;
  • Describe each of the models studied in the subject, the characteristics of these models and the data for which they are suited;
  • Derive basic results related to each of the models.
  • 2-hour end-of-semester examination (65%)
  • Class assignments up to 3200 words in total (32%)
  • Tutorial attendance and participation (3%)
Prescribed Texts: You will be advised of prescribed texts by your lecturer.
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

On successful completion of this subject, students should have improved the following generic skills:

  • Evaluation of ideas, views and evidence;
  • Synthesis of ideas, views and evidence;
  • Strategic thinking;
  • Critical thinking;
  • Application of theory to economic policy and business decision making;
  • Summary and interpretation of information;
  • Using computer programs;
  • Statistical reasoning;
  • Problem solving skills;
  • Collaborative learning and teamwork;
  • Written communication.
Notes: Students may not gain credit for both 316-636 Econometrics and 316-317 Econometrics.
Related Course(s): Master of Commerce - Economics

Download PDF version.