Unit convenor and teaching staff |
Unit convenor and teaching staff
Hanbat Jeong
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Credit points |
Credit points
10
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Prerequisites |
Prerequisites
Admission to GradCertFin or GradDipAppFin or MAppEcon or MAppFin or MAppFin(Adv) or MBkgFin or MBusAnalytics
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Corequisites |
Corequisites
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit is designed to bring students with no econometrics background to an intermediate level in econometrics. Starting from first principles, the unit outlines standard econometric methods to the extent necessary for students to understand key concepts, apply basic methods, and interpret empirical research results in economics, finance and business. The unit material also includes elementary discussions of violations of the standard assumptions for a regression model, such as autocorrelation and heteroscedasticity. |
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Late Assessment Submission Penalty (written assessments)
Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of ‘0’ will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A 1-hour grace period is provided to students who experience a technical concern. For any late submissions of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to submit an application for Special Consideration.
Name | Weighting | Hurdle | Due |
---|---|---|---|
Group assignment | 30% | No | Week 12 Wednesday 11.55pm |
Final Examination | 35% | No | University Examination Week |
Class Test 2 | 20% | No | Week 10 |
Class Test 1 | 15% | No | Week 6 |
Assessment Type 1: Quantitative analysis task
Indicative Time on Task 2: 15 hours
Due: Week 12 Wednesday 11.55pm
Weighting: 30%
The assignment will require students to critically analyse some sets of data using the econometric software and regression models (including time-series and cross-sectional data). The group will estimate a variety of different models, compare and contrast the outcomes, and assess the suitability of the models for the analysis.
Assessment Type 1: Examination
Indicative Time on Task 2: 17.50 hours
Due: University Examination Week
Weighting: 35%
A two-hour examination will be held during the University Examination Period, and will consist of multiple-choice and short-answer questions.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 10 hours
Due: Week 10
Weighting: 20%
A 75 minute test consisting of multiple-choice and short-answer questions will be held during the lecture in week 10.
Assessment Type 1: Quiz/Test
Indicative Time on Task 2: 7.5 hours
Due: Week 6
Weighting: 15%
A 75 minute test consisting of multiple-choice and short-answer questions will be held during the lecture in week 6.
1 If you need help with your assignment, please contact:
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 format
This unit is taught as a mix of tutorials and lectures. Weekly, there will be a one-hour face-to-face and recorded lecture. Weekly one-hour tutorials will be held (beginning with week 2) to go over assigned problems. You can find the recorded lecture stream in ECHO recordings on iLearn.
The lectures are designed to introduce the underlying knowledge in probability, statistics, and econometrics and to explain the methods that will be used to analyze and interpret data. Students are expected to read the relevant material before each lecture.
Tutorials are based mainly on numerical problems, which allow students to practice and understand the methods taught in the lectures. The tutorials include empirical applications that require the use of Gretl/Excel.
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Unit information based on version 2024.05 of the Handbook