Computational Economics and Business

Subject 316-352 (2009)

Note: This is an archived Handbook entry from 2009. Search for this in the current handbook

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

This subject has the following teaching availabilities in 2009:

Semester 1, - 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: Three hours of lectures, seminars and tutorials per week
Total Time Commitment: Not available
Prerequisites:

316-205 Introductory Econometrics or 316-206 Quantitative Methods 2.
Corequisites: None
Recommended Background Knowledge: None
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: http://services.unimelb.edu.au/disability

Coordinator

Assoc Prof Joe Hirschberg
Subject Overview:

This subject covers the application of computer based techniques to solve the problems encountered in economics and business. The techniques covered include the construction and use of hierarchical data sets, the use of multivariate graphics and statistics in the context of data mining applications, the elements of computer simulations, and the application of linear programming for the analysis of productivity in the context of data envelopment analysis. One aspect of this subject is the introduction of students to different software options. Possible software to be considered will be SAS, Stata, GAUSS, SPSS, TSP, EMS, Scientific Word, and Eviews.

Objectives: .
Assessment:

A 2-hour end-of-semester examination (70%) and class assignments totalling not more than 3000 words (30%)
Prescribed Texts: None
Recommended Texts:

Information Not Available
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; interpretation and analysis; use of computer software; accessing data and other information from a range of sources.

  • Moderate level of development: written communication; application of theory to practice; critical thinking; synthesis of data and other information; evaluation of data and other information; receptiveness to alternative ideas.

  • Some level of development: oral communication; collaborative learning; team work.
Related Majors/Minors/Specialisations: Economics Major

Download PDF version.