Subject ECOM30002 (2016)

Note: This is an archived Handbook entry from 2016.

Credit Points: 12.5
Level: 3 (Undergraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2016:

Semester 1, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period 29-Feb-2016 to 29-May-2016
Assessment Period End 24-Jun-2016
Last date to Self-Enrol 11-Mar-2016
Census Date 31-Mar-2016
Last date to Withdraw without fail 06-May-2016

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: Two 1-hour lectures and a 1-hour tutorial/practice class per week
Total Time Commitment:

Estimated total time commitment of at least 170 hours.


One of:

Study Period Commencement:
Credit Points:
Semester 1, Semester 2
Semester 1
Semester 2

or a grade of H2A or above in ECON20003 Quantitative Methods 2,

AND one of:

Study Period Commencement:
Credit Points:
Summer Term, Semester 1
January, Semester 1, Semester 2
Corequisites: None
Recommended Background Knowledge:

Please refer to Prerequisites and Corequisites.

Non Allowed Subjects: None
Core Participation Requirements:

For the purposes of considering request for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Student Support and Engagement Policy, academic requirements for this subject are articulated in the Subject Overview, Learning Outcomes, Assessment and Generic Skills sections of this entry.

It is University policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student's participation in the University's programs. Students who feel their disability may impact on meeting the requirements of this subject are encouraged to discuss this matter with a Faculty Student Adviser and Student Equity and Disability Support:


Prof David Harris


David Harris

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 and panel data models and issues involving time-series data are introduced. Theoretical concepts are illustrated by applied examples. The computer software used is Eviews.

Learning Outcomes:

Information not available.

  • A 2-hour end-of-semester examination (65%)
  • A group project totalling 2000 words due week 9 (20%)
  • Four homework tasks due weeks 3, 4, 5 and 6 (10%)
  • A mid-semester test week 7 (5%)
Prescribed Texts:

You will be advised of prescribed texts by your lecturer.

Breadth Options:

This subject potentially can be taken as a breadth subject component for the following courses:

You should visit learn more about breadth subjects and read the breadth requirements for your degree, and should discuss your choice with your student adviser, before deciding on your subjects.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:
  • High level of development: problem solving; statistical reasoning; application of theory to practice; interpretation and analysis; evaluation of data and other information; use of computer software.

  • Moderate level of development: written communication; collaborative learning; team work; critical thinking; synthesis of data and other information.

  • Some level of development: accessing data and other information from a range of sources.

Related Course(s): Graduate Diploma in Economics
Master of Economics
Related Majors/Minors/Specialisations: Economics

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