Basic Econometrics

Subject ECOM30001 (2014)

Note: This is an archived Handbook entry from 2014.

Credit Points: 12.50
Level: 3 (Undergraduate)
Dates & Locations:

This subject is not offered in 2014.

Time Commitment: Contact Hours: Two 1-hour lectures and a 1-hour tutorial/seminar per week
Total Time Commitment:

Estimated total time commitment of 120 hours per semester.

Prerequisites:

One of:

Subject
Study Period Commencement:
Credit Points:
Summer Term, Semester 1, Semester 2
12.50
Semester 2
12.50

And one of:

Subject
Study Period Commencement:
Credit Points:
Summer Term, Semester 1
12.50
January, Semester 1, 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 ECOM30001 Basic Econometrics and either ECOM90001 Basic Econometrics or ECOM20001 Introductory 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/

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.
Assessment:

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
Economics
Economics Major

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