Quantitative Decision Making 3

Subject ECON90050 (2012)

Note: This is an archived Handbook entry from 2012.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
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


Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: Two 1-hour lectures and one 1-hour workshop per week
Total Time Commitment: Estimated total time commitment of 120 hours per semester
Prerequisites: ECON90049 Quantitative Decision Making 2
Subject
Study Period Commencement:
Credit Points:
Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: None
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

Prof William Griffiths

Contact

Graduate School of Business and Economics
Level 4, 198 Berkeley Street
Telephone: +61 3 8344 1670
Online Enquiries
Web: www.gsbe.unimelb.edu.au

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, and an introduction to simultaneous systems.
Objectives:

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 sing single and multiple regression equations;
  • Test hypotheses concerning the relationship between variable;
  • Explain in detail the consequences of the violation of any one of the classical assumptions;
  • Test for variations 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:
  • One 2-hour end-of-semester examination (70%)
  • Assignments not exceeding 1500 words in the first half of the semester (15%)
  • Assignments not exceeding 1500 words in the second half of the semester (15%)
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:

  • 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): Master of Management (Economics)

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