Basic Econometrics

Subject ECOM30001 (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/seminar per week
Total Time Commitment:

Estimated total time commitment of 170 hours per semester.


One of:

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

And one of:

Study Period Commencement:
Credit Points:
Summer Term, Semester 1
January, Semester 1, Semester 2


Recommended Background Knowledge:

Please refer to Prerequisites and Corequisites.

Non Allowed Subjects:

Students may not gain credit for both ECOM30001 Basic Econometrics and either ECOM90001 Basic Econometrics or ECOM20001 Introductory Econometrics.

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:


Dr Andrew Clarke


Andrew Clarke

Subject Overview:

This subject examines multiple regression analysis and its use in economics, management, finance, accounting and marketing. Topics will include the properties of estimators, hypothesis testing, specification error, multicollinearity, dummy variables, heteroskedasticity, serial correlation. Empirical assignments undertaken by the student form an integral part of the subject.

Learning Outcomes:

On successful completion of this subject students should be able to:

  • Apply the classical model of ordinary least squares to data sets drawn from economics, finance, accounting and management using single and multiple regression equations;
  • Test hypotheses concerning the relationship between variables;
  • Explain in detail the consequences of the violation of any one of the classical assumptions;
  • Test for violations of the classical assumptions;
  • Estimate models in the presence of non-classical errors and stochastic explanatory variables;
  • Diagnose model misspecification using the most appropriate tests, and where appropriate identify the appropriate remedial actions;
  • Use computer software to perform simple data descriptions and to graph relationships between variables, to estimate econometric models using OLS and Instrumental Variables, and to estimate simple dynamic models;
  • Apply econometric methods to real world data and perform diagnostic testing to ensure the model is adequately specified.

A 2-hour end-of-semester examination (70%), one assignment of no more than 2000 words due week 4 (10%), a one-hour mid-semester test in week 7 (10%) and problem sheets submitted fortnightly (10%).

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: written communication; application of theory to practice; interpretation and analysis; critical thinking; synthesis of data and other information; evaluation of data and other information; use of computer software.

  • Moderate level of development: problem solving; statistical reasoning; accessing data and other information from a range of sources.

  • Some level of development: oral communication; collaborative learning; receptiveness to alternative ideas.

Related Majors/Minors/Specialisations: Economics

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