ECON8040 – Applied Econometrics

2022 – Session 1, In person/Online-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff Unit convenor, lecturer and tutor
Chris Heaton
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TBA on iLearn
Colin Bowers
Contact via
TBA on iLearn
Credit points Credit points
Prerequisites Prerequisites
ECON634 or ECON6034
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

The objective of this unit is to enable students with basic statistical knowledge to upgrade their understanding to a practical level where they can apply their knowledge of econometrics to empirical analysis. By successfully completing this unit, students should be able to develop an econometric model suitable for the objective of their analysis, estimate the model using an appropriate estimation method, and draw valid inferences from the estimation results. The unit starts with a brief review of the standard multiple linear regression model and the OLS estimation method. It then relaxes the standard assumptions and investigates alternative estimation methods that are valid under the new circumstances. The final part introduces the interesting discrete-choice models.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at

Learning Outcomes

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

  • ULO1: Develop an econometric model suitable for the objective of analysis.
  • ULO2: Estimate the model using an appropriate estimation method.
  • ULO3: Interpret the estimation results and draw valid inferences.
  • ULO4: Critically analyse the econometric methods covered in the unit.

General Assessment Information

Late submissions of assessments Unless a Special Consideration request has been submitted and approved, no extensions will be granted. There will be a deduction of 10% of the total available assessment-task marks made from the total awarded mark for each 24-hour period or part thereof that the submission is late. Late submissions will only be accepted up to 96 hours after the due date and time.

No late submissions will be accepted for timed assessments – e.g., quizzes, online tests.

Submission time after the due date (including weekends) 

Penalty (% of available assessment task mark) 

Example: for a non-timed assessment task marked out of 30 

<24 hours 


10% x 30 marks = 3-mark deduction 

24-48 hours 


20% x 30 marks = 6-mark deduction 

48-72 hours 


30% x 30 marks = 9-mark deduction 

72 – 96 hours 


40% x 30 marks = 12-mark deduction 

>96 hours 


Assignment won’t be accepted 

Special Consideration

To request an extension on the due date/time for a timed or non-timed assessment task, you must submit a Special Consideration application. An application for Special Consideration does not guarantee approval.

The approved extension date for a student becomes the new due date for that student. The late submission penalties above then apply as of the new due date

Assessment Tasks

Name Weighting Hurdle Due
Online lecture interaction 10% No 9am Thursdays from Week 2
Tutorial Exercises 20% No 9am Thursdays from Week 2
Take home test 50% No Week 12, Tuesday 7am
Assignment 20% No Week 14, Monday 7am

Online lecture interaction

Assessment Type 1: Participatory task
Indicative Time on Task 2: 5 hours
Due: 9am Thursdays from Week 2
Weighting: 10%


Online lecture videos will include embedded exercises that engage students in the material being taught and ensure that students grasp essential concepts.


On successful completion you will be able to:
  • Interpret the estimation results and draw valid inferences.
  • Critically analyse the econometric methods covered in the unit.

Tutorial Exercises

Assessment Type 1: Problem set
Indicative Time on Task 2: 10 hours
Due: 9am Thursdays from Week 2
Weighting: 20%


A weekly assessment (from Week 2) that covers material from previous lectures, with an emphasis on the most recent work, and ensures acquisition of the concepts and skills necessary to understand and apply the unit material.


On successful completion you will be able to:
  • Interpret the estimation results and draw valid inferences.
  • Critically analyse the econometric methods covered in the unit.

Take home test

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 20 hours
Due: Week 12, Tuesday 7am
Weighting: 50%


A diagnostic test of technical skills and applied knowledge acquired in the unit up until the week of the test.


On successful completion you will be able to:
  • Develop an econometric model suitable for the objective of analysis.
  • Interpret the estimation results and draw valid inferences.
  • Critically analyse the econometric methods covered in the unit.


Assessment Type 1: Case study/analysis
Indicative Time on Task 2: 15 hours
Due: Week 14, Monday 7am
Weighting: 20%


A written report comprising the application of technical skills and theoretical concepts acquired in the unit to a given economic problem


On successful completion you will be able to:
  • Develop an econometric model suitable for the objective of analysis.
  • Estimate the model using an appropriate estimation method.
  • Interpret the estimation results and draw valid inferences.

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
  • the Writing Centre 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

Delivery and Resources


  • Online lectures will be available each week. Lectures will include links to datasets and reference material. Lectures will also include embedded questions which must be answered by students before the weekly deadline. The lectures cover all the material necessary to pass the unit, including some material that is not available in other formats. Consequently, students are expected to study the lectures closely.
  • There is a tutorial class held in each week except Week 1. Students must register in a tutorial class and generally will not be permitted to attend a tutorial class other than the one in which they are registered. Changes to tutorial enrolments may only be made using the online system subject to available capacity. The Unit Convenor cannot make enrolment changes on behalf of students. Changes to tutorial enrolments generally take up to 24 hours to be reflected on iLearn.
  • Students must complete and submit the tutorial exercises each week before the deadline, which will be prior to the first scheduled class each week. The tutorial exercises will be discussed in class. After the completion of the last scheduled class of the week, students will be permitted to re-attempt the tutorial. Details of the marking scheme will be made available on iLearn.
  • The timetable for classes can be found on the University website:
  • Students are expected to study all lectures, attempt the lecture exercises and tutorial exercises, attend the tutorial classes, discuss the unit material both in-class and online, and read the text. It is important that students identify problems that they are having with the unit material each week. If a reasonable but unsuccessful effort has been made to solve a problem, then the student should seek help from the tutor during the tutorial. Outside class time, the best way to get help with a problem is to post it on the online discussion forum.
  • It is expected that students will spend an average of approximately 10 hours per week working on this unit (including class time).

Note: the intended delivery mode may need to change after the start of the session due to the evolving covid situation and students need to ensure they keep up with iLearn Announcements made during the session accordingly.

Required and Recommended texts and/or materials

Additional useful textbooks and resources.

  • Hill, C. H., Griffiths, W. E. and Lim, G. C. (2018) Principles of Econometrics (5th ed.) Wiley.
  • Wooldridge, J. M., Wadud, M., Lye, J. and Joyeux, R. (2021) Introductory Econometrics (2nd Asia-Pacific ed.) Cengage.
  • Gujarati, D.N., and Porter, D.C. (2010) Essentials of Econometrics (4th ed.) McGraw-Hill.

  • A list of prescribed reading will be developed on the website as the unit progresses.

  • The data sets used in the textbook and in lectures will be provided on the website.

Technology Used and Required

  • Course material is available on the learning management system (iLearn).

  • Announcements will be made regularly on iLearn. Students should ensure that these announcements, and posts on the online discussion forum, are forwarded to their email account, which they should check regularly. Staff may also occasionally directly email students. Students must check their email daily.

  • Students will need access to an internet-connected computer capable of streaming video and participating in Zoom meetings.

Policies and Procedures

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Students seeking more policy resources can visit Student Policies ( It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

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Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct:


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 or if you are a Global MBA student contact

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.

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