Econometrics of Markets and Competition

Subject ECOM90017 (2013)

Note: This is an archived Handbook entry from 2013.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject is not offered in 2013.

Time Commitment: Contact Hours: Seminars, or lectures and tutorials totalling 3-hours per week
Total Time Commitment:

Approximately 2.5 hours of personal study per hour of class time is required to achieve a satisfactory level of performance.

Study Period Commencement:
Credit Points:
Not offered in 2013


Study Period Commencement:
Credit Points:


Recommended Background Knowledge:

Please refer to the Prerequisites. Computer programming experience in MATLAB, C, Java or some other language is helpful, but not necessary.

Non Allowed Subjects:

Students may not gain credit for this course and Honours subject ECON40007 Econometrics of Markets and Competition.

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:


Graduate School of Business and Economics
Level 4, 198 Berkeley Street
Telephone: +61 3 8344 1670
Online Enquiries

Subject Overview:

This course teaches students how to build econometric models from economic theory to investigate how markets operate, and evaluate policy-relevant questions. Applicants of econometric tools developed in this course will be highlighted in various fields of economics including industrial organization, public economics, health and others. Examples of topics covered include: firms’ use of price discrimination as a profit-maximizing strategy; measuring the welfare effects of mergers for antitrust analysis; identifying strategic interaction amongst governments and its impact on policy decisions; and quantifying moral hazard and adverse selection in health insurance markets. Basic topics in numerical analysis will also be covered, including optimization, numerical integration, and numerical differentiation. The computer software used is MATLAB.


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

  • Estimate structural econometric models and use counterfactual analysis to assess policy questions
  • Understand basic identification challenges in estimating the parameters of economic models
  • Learn basic programming skills and numerical methods
  • Apply methods learned in the course to address policy questions for an industry.
  • 90 minute end of semester exam (30%)
  • Four class assignments in computer code totaling a minimum of 40 hours work (10 hours per assignment) [Due dates: Assignment 1 – Week 3, Assignment 2 – Week 5, Assignment 3 – Week 9, Assignment 4 – Week 12] (40%)
  • One market written study project consisting of two 1500 word reports (totaling 300 words) [Due dates: 1500 word Market study Part 1 – due Week 6; 1500 word Market study Part 2 – due Week 12] (30%)

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: written communication; problem solving; statistical reasoning; 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; accessing data and other information from a range of sources; receptiveness to alternative ideas.
  • Some level of development: collaborative learning; team work.

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