Introductory Econometrics

Subject ECOM20001 (2012)

Note: This is an archived Handbook entry from 2012.

Credit Points: 12.50
Level: 2 (Undergraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2012:

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

Semester 2, 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: Two 1-hour lectures and a 1-hour tutorial per week
Total Time Commitment: Not available
Prerequisites:

One of the following:

620-131 Scientific Programming and Simulation

620-160 Experimental Design and Data Analysis

Subject
Study Period Commencement:
Credit Points:
Semester 1, Semester 2
12.50
Semester 2
12.50
Corequisites: None
Recommended Background Knowledge: Please refer to Prerequisites and Corequisites.
Non Allowed Subjects: Students may not gain credit for both ECOM20001 Introductory Econometrics and ECOM30001 Basic 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: http://www.services.unimelb.edu.au/disability/

Coordinator

Assoc Prof Jenny Lye, Assoc Prof Joe Hirschberg

Contact

Semester 1: j.hirschberg@unimelb.edu.au

Semester 2: jnlye@unimelb.edu.au

Subject Overview:

Topics include review of statistics; F and X 2 distributions; review of simple linear regression model; multiple linear regression model; hypothesis testing, forecasting, diagnostics with regression models (including heteroskedasticity, serial correlation and model specification). Examples drawn from economics, finance, accounting, marketing and management will be illustrated using EVIEWs.

Objectives:
  • Apply the least-squares method of estimation to the context of the simple linear regression model.
  • Apply the principles of the least-squares method of estimation and inference to the multiple linear regression model.
  • Apply EViews to estimate, test hypotheses and forecast in the context of the linear regression model.
  • Explain various problems that arise from applying the linear regression model to data, including multicollinearity, specification errors, heteroskedasticity, nonstationarity and autocorrelation.
Assessment: A 2-hour end-of-semester examination (65% or 75%), an optional mid-semester multiple choice test in week 5 (0% or 10%), Assignment 1 (10%) due week 8: 10 pages A4, Assignment 2 (10%) due week 12: 10 pages A4, and tutorial attendance and participation (5%). The final mark will be calculated by weighting the end-of-semester exam at 65% and the mid-semester test at 10% OR by weighting the end-of-semester exam at 75% and the mid-semester test at 0%, whichever gives the higher mark.
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; collaborative learning; problem solving; team work; statistical reasoning; application of theory to practice; interpretation and analysis; critical thinking; synthesis of data and other information; use of computer software.

  • Moderate level of development: oral communication; evaluation of data and other information; accessing data and other information from a range of sources; receptiveness to alternative ideas.
Notes:

Students may not gain credit for both 316-205 Introductory Econometrics and 316-316 Basic Econometrics.

Related Course(s): Graduate Diploma in Economics
Related Majors/Minors/Specialisations: Economics
Economics Major
Related Breadth Track(s): Statistical Literacy
Quantitative Methods in Economics
Economics && Finance

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