Students

ECON2032 – Intermediate Econometrics

2026 – Session 2, Online-scheduled-In person assessment, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Hanbat Jeong
hanbat.jeong@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
ECON241 or ECON2041 or STAT272 or STAT2372 or STAT171 or STAT1371 or STAT270 or STAT2170 or STAT273 or STAT2173 or STAT271 or STAT2371
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit covers econometric techniques that go beyond the classical regression model. It helps students to develop literacy in important methods commonly used to analyse data in economics, finance and business environments. The topics covered may include heteroscedasticity, stochastic regressors, limited dependent variables, time-series regression and panel data analysis.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: Identify and describe econometric concepts and theories.
  • ULO2: Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.
  • ULO3: Diagnose and resolve problems relating to the violation of standard assumptions in econometric models, and make conclusions and recommendations.
  • ULO4: Critique the appropriateness of alternative econometric techniques in practical applications to appropriate problems.

General Assessment Information

Late Submission Penalties

If you submit your assessment late, 5% of the total possible marks will be deducted for each day (including weekends), up to 7 days. Submissions more than 7 days late will receive a mark of 0.
Example 1 (out of 100):
If you score 85/100 but submit 20 hours late, you will lose 5 marks and receive 80/100.
Example 2 (out of 30):
If you score 27/30 but submit 20 hours late, you will lose 1.5 marks and receive 25.5/30.
Extensions
Automatic short extension: Some assessments are eligible for automatic short extension. You can only apply for an automatic short extension before the due date.
 
Special Consideration: If you need more time due to serious issues and for any assessments that are not eligible for Short Extension, you must apply for Special Consideration. Need help? Review the Special Consideration page for further details.

Assessment Tasks

Name Weighting Hurdle Due Groupwork/Individual Short Extension AI Approach
Formal examination 50% No University Exam Period Individual No Observed
Skills development: Building block 30% No Week 8 Tutorial session Individual No Observed
Professional practice: Applied econometrics modelling 20% No 30/10/2026 Individual Yes Open

Formal examination

Assessment Type 1: Examination
Indicative Time on Task 2: 50 hours
Due: University Exam Period
Weighting: 50%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed

The purpose of this assessment is for you to demonstrate the expertise you have gained in this unit.

You will participate in a 2-hour, on-campus, closed-book exam held during the University Examination period.

Important information about the exam will be made available on the unit iLearn page. You should also review the MQ Exams website for general tips. 

Deliverable(s): Form exam

Individual assessment 
On successful completion you will be able to:
  • Identify and describe econometric concepts and theories.
  • Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.
  • Diagnose and resolve problems relating to the violation of standard assumptions in econometric models, and make conclusions and recommendations.

Skills development: Building block

Assessment Type 1: Problem-based task
Indicative Time on Task 2: 9 hours
Due: Week 8 Tutorial session
Weighting: 30%
Groupwork/Individual: Individual
Short extension 3: No
AI Approach: Observed

The purpose of this assessment is for you to develop the ability to apply intermediate-level statistical techniques and evaluate appropriate econometric tools to model and estimate economic data. You will be given a problem set in class that covers content up to the week prior to the task.
 
Skills in focus:
  • Discipline knowledge
  • Critical thinking and problem solving
Deliverable(s): In-class problem set
 
Individual assessment
On successful completion you will be able to:
  • Identify and describe econometric concepts and theories.
  • Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.

Professional practice: Applied econometrics modelling

Assessment Type 1: Professional task
Indicative Time on Task 2: 18 hours
Due: 30/10/2026
Weighting: 20%
Groupwork/Individual: Individual
Short extension 3: Yes
AI Approach: Open

The purpose of this case study is for you to develop skills to critically analyse real data using econometric software and regression models, in order to make a reasonable data-driven decision based on the theory studied in this course. You will be given an applied econometric problem to work on and will be required to submit a written report on your investigation of the problem. You may be required to submit relevant computer files.

Skills in focus:

  • Critical thinking and problem solving
  • Discipline knowledge
  • Work readiness
  • Digital skills

Deliverable(s): Written report [max 1000 words]

Individual assessment
On successful completion you will be able to:
  • Identify and describe econometric concepts and theories.
  • Estimate econometric models and test parametric hypotheses using techniques that are appropriate for the problem at hand.
  • Diagnose and resolve problems relating to the violation of standard assumptions in econometric models, and make conclusions and recommendations.
  • Critique the appropriateness of alternative econometric techniques in practical applications to appropriate problems.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • Academic Success for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation.

3 An automatic short extension is available for some assessments. Apply through the Service Connect Portal.

Delivery and Resources

DELIVERY FORMAT

Each week, there will be two hours of face-to-face lectures. Weekly one-hour tutorials will also be held to review assigned problems. The problems covered in the tutorial sessions will reinforce the topics discussed in the main lectures. The in-class problem set will be conducted during the Week 8 tutorial.

REQUIRED AND RECOMMENDED TEXTS AND/OR MATERIALS

Wooldridge, Jeffrey M., Introductory Econometrics: A Modern Approach, 7th edition,

  The textbook is available online via the Macquarie University Library. As the unit progresses, material such as lecture slides, examples, etc., will be made available on the unit website.

TECHNOLOGIES USED AND REQUIRED

The main software packages used are Python/R/Gretl. 

Gretl: https://gretl.sourceforge.net/

Python/R: https://colab.research.google.com/

https://jupyter.org/

R: https://posit.cloud/

Also, refer to https://www.kaggle.com/

 

Unit Schedule

Week 1: Probability 1

Week 2: Probability 2

Week 3: Estimation

Week 4: Regression/Heteroskedasticity

Week 5: Model Specification

Week 6: Endogeneity

Week 7: Binary Dependent Variables

Week 8: Work-integrated learning session

Week 9: Stationary Time Series 1

Week 10: Stationary Time Series 2

Week 11: Nonstationary Time Series 1

Week 12: Nonstationary Time Series 2

Week 13: Review

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Academic Success

Academic Success provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit https://students.mq.edu.au/support/technology/service-desk. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Unit information based on version 2026.05 of the Handbook