Students

ECON3061 – Economic and Business Forecasting

2020 – Session 2, Special circumstance

Notice

As part of Phase 3 of our return to campus plan, most units will now run tutorials, seminars and other small group learning activities on campus for the second half-year, while keeping an online version available for those students unable to return or those who choose to continue their studies online.

To check the availability of face to face activities for your unit, please go to timetable viewer. To check detailed information on unit assessments visit your unit's iLearn space or consult your unit convenor.

General Information

Download as PDF
Unit convenor and teaching staff Unit convenor and teaching staff Lecturer
Roselyne Joyeux
E4A440
TBA
Amarjeet Kuar
Credit points Credit points
10
Prerequisites Prerequisites
20cp at 2000 level or above including ECON241 or ECON2041 or STAT272 or STAT2372
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit provides an introduction to quantitative economic forecasting. Topics may include: exponential smoothing; ARIMA and vector autoregression. The emphasis of the unit is on the practical aspects of forecasting. Theory is developed only to the point necessary to understand the forecasting procedures introduced in the unit. Students are given regular forecasting exercises throughout the unit. Practical work is carried out using an econometric software package. The objective of the unit is to produce graduates who understand the nature of forecasting problems and can produce sound forecasts for use in business and economic 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 theories and measures of forecast accuracy and rank forecasting models.
  • ULO2: Apply econometric methods to seasonally adjust and detrend data.
  • ULO3: Implement Smoothing, ARIMA and VAR models to produce forecasts.

Assessment Tasks

Name Weighting Hurdle Due
Test 1 20% No Week 7
Online final examination 40% No During the end of session formal examination period
Online tutorials problems 10% No Weeks 2-12 in online tutorials
Assignment 30% No Monday in week 13

Test 1

Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 4 hours
Due: Week 7
Weighting: 20%

 

The 60-minute test will cover all of the material up to week 6.

 


On successful completion you will be able to:
  • Identify and describe theories and measures of forecast accuracy and rank forecasting models.
  • Apply econometric methods to seasonally adjust and detrend data.

Online final examination

Assessment Type 1: Examination
Indicative Time on Task 2: 20 hours
Due: During the end of session formal examination period
Weighting: 40%

 

A two-hour exam to be completed in a six hour window will be held during the end of session formal examination period, and will consist of short answer questions that require both calculation and written responses

 


On successful completion you will be able to:
  • Identify and describe theories and measures of forecast accuracy and rank forecasting models.
  • Apply econometric methods to seasonally adjust and detrend data.
  • Implement Smoothing, ARIMA and VAR models to produce forecasts.

Online tutorials problems

Assessment Type 1: Problem set
Indicative Time on Task 2: 24 hours
Due: Weeks 2-12 in online tutorials
Weighting: 10%

 

The tutorial problems/questions will be available on iLearn the week before the tutorial. Solutions will be published during the week following each tutorial. Online participation will be assessed

 


On successful completion you will be able to:
  • Identify and describe theories and measures of forecast accuracy and rank forecasting models.
  • Apply econometric methods to seasonally adjust and detrend data.
  • Implement Smoothing, ARIMA and VAR models to produce forecasts.

Assignment

Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 22 hours
Due: Monday in week 13
Weighting: 30%

 

The assignment will be a written task of less than 1,000 words that will report the results of a forecasting project.

 


On successful completion you will be able to:
  • Identify and describe theories and measures of forecast accuracy and rank forecasting models.
  • Apply econometric methods to seasonally adjust and detrend data.
  • Implement Smoothing, ARIMA and VAR models to produce forecasts.

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

Classes

  • There is a single 2 hour lecture class per week online via Zoom. There is also a 1 hour tutorial class held in each of weeks 2 to 12 online via Zoom. 
  • It will be assumed that students attend all lectures and tutorials online via Zoom.
  • The timetable for classes can be found on the University web site.

Required and Recommended Texts and/or Materials

Students are not required to purchase a textbook for ECON3061. A detailed reading list will be on the unit website, and all references are available via the Library eReserve. Students are  expected to read this material.

Technology Used and Required

  • The main software used in ECON3061 is the EViews software which can be accessed through AppStream.
  • Students will need to use a spreadsheet for some parts of this unit. 

Unit Web Page

The web page for this unit can be found on the iLearn web site.

 

Unit Schedule

Week

Topic

Tutorials

Work Due

Week 1

Introduction

 

 

Week 2

Forecast evaluation

Tutorial 1

 

Week 3

Time series decomposition

Tutorial 2

 

Week 4

Exponential smoothing

Tutorial 3

 

Week 5

Exponential smoothing

Tutorial 4

 

Week 6

Machine Learning

Tutorial 5

 

Week 7

Machine Learning

Tutorial 6

Test 1

Week 8

ARIMA

Tutorial 7

 

Week 9

ARIMA

Tutorial 8

 

Week 10

ARIMA

Tutorial 9

 

Week 11

Vector autoregression

Tutorial 10

 

Week 12

Vector autoregression

Tutorial 11

Assignment

Week 13

Review

Tutorial 12

 

 

 

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:

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

If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central).

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/study/getting-started/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 ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Student Support

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

Learning Skills

Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to help you improve your marks and take control of your study.

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

Student Services and Support

Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.

Student Enquiries

For all student enquiries, visit Student Connect at ask.mq.edu.au

If you are a Global MBA student contact globalmba.support@mq.edu.au

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/

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.