Students
ECON333 – Econometric Methods
2018 – S1 Day
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Unit Convenor
Daehoon Nahm
Contact via daehoon.nahm@mq.edu.au
E4A 417
Available on iLearn
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| Credit points |
Credit points
3
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| Prerequisites |
Prerequisites
(6cp at 200 level including ECON232 or ECON233) or ECON334
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| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| Unit description |
Unit description
The objective of this higher-level econometrics unit is to provide students with an opportunity to acquire more advanced econometric techniques that can be applied to an empirical analysis of economic, financial, or business phenomena. The unit is suitable both for students who simply want to equip themselves with a more practical knowledge of econometrics and to those planning to pursue a research degree.
To expose students to a broad and more complete range of econometric issues, this unit may include topics such as a review of the multiple regression model and OLS estimation, matrix algebra, GLS estimation, endogenous regressors and consistent estimation, maximum-likelihood estimation, discrete choice models, treatment effects, multivariate time-series models (VECM), and models for panel data.
Real-world examples, such as analysing people’s choice of mobile phone brands, patterns of crediting rating, or the effectiveness of a medical treatment, are used to illustrate particular techniques. The use of econometric software programs such as Gretl and Shazam provide a practical problem-solving experience.
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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:
- Clearly understand key concepts and results for each topic covered in the unit.
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand statistical properties of the estimator used and draw correct inferences from them (including hypothesis tests).
- Appreciate the advantages and limitations of an econometric method in various situations.
- Understand matrix algebra
Assessment Tasks
| Name | Weighting | Hurdle | Due |
|---|---|---|---|
| Homework | 20% | No | TBA |
| Class Test | 20% | No | Week 5 |
| Assignment | 20% | No | Week 11 |
| Final Examination | 40% | No | examination period |
Homework
Due: TBA
Weighting: 20%
Four sets of homework questions, of equal value, will be given throughout the semester. Students are required to submit their answers by the due date for each set via turnitin. No homework will be received after the set due date. If an application for special consideration is made and granted, that specific set will not be included in deciding the final grade.
On successful completion you will be able to:
- Clearly understand key concepts and results for each topic covered in the unit.
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand statistical properties of the estimator used and draw correct inferences from them (including hypothesis tests).
- Appreciate the advantages and limitations of an econometric method in various situations.
- Understand matrix algebra
Class Test
Due: Week 5
Weighting: 20%
Topics: the topics covered in Weeks 1−4.
Date and time: during lecture time - 9:00 pm, 26 March (Week 5)
Duration: 50 minutes
You will need a calculator. This is a closed-book test. If you cannot sit the test due to illness or unavoidable disruption, you will have to apply for special consideration with supporting documentations attached. If approved, a supplementary test will be arranged.
On successful completion you will be able to:
- Clearly understand key concepts and results for each topic covered in the unit.
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand statistical properties of the estimator used and draw correct inferences from them (including hypothesis tests).
- Appreciate the advantages and limitations of an econometric method in various situations.
- Understand matrix algebra
Assignment
Due: Week 11
Weighting: 20%
The questions will be made available roughly 3-4 weeks before the due date. The due date is 21 May (Week 11). It must be submitted to the lecturer at the beginning of the lecture (i.e. 1 pm) in Week 11. No extension will be granted. Late submissions will be accepted up to three days after the submission deadline. There will be a deduction of 10% of the total available marks made from the total awarded marks for each 24 hour period or part thereof that the submission is late (for example, 25 hours late in submission – 20% penalty). This penalty does not apply for cases in which an application for special consideration is made, and an extension of the deadline is granted.
Always keep a copy of the document you submit for assessment, including assignment, to insure yourself against loss.
On successful completion you will be able to:
- Clearly understand key concepts and results for each topic covered in the unit.
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand statistical properties of the estimator used and draw correct inferences from them (including hypothesis tests).
- Appreciate the advantages and limitations of an econometric method in various situations.
- Understand matrix algebra
Final Examination
Due: examination period
Weighting: 40%
The examination will be closed-book and of two hours’ duration. It will cover all the topics that have been discussed in class during the semester. You will need a calculator.
The University Examination period in Semester 1, 2018 starts from 12 June. You are expected to present yourself for examination at the time and place designated in the University Examination Timetable. The timetable will be available in draft form approximately eight weeks before the commencement of the examinations and in final form approximately four weeks before the commencement of the examinations: http://www.timetables.mq.edu.au/exam.
Students who do not sit for the final exam will be awarded a grade of FA (failed absent). The only exception to this rule will occur in cases where a special consideration is granted on the grounds of unavoidable disruption to studies. Students who are prevented from sitting the final exam due to illness or unavoidable disruption may wish to consider applying for special consideration; see below for the related information. If a supplementary examination is granted as a result of the special consideration process the examination will be scheduled for after the conclusion of the official examination period. If the student does not attend the supplementary examination at the scheduled time, a grade of FA will be awarded.
You are advised that it is Macquarie University policy not to set early examinations for individuals or groups of students. All students are expected to ensure that they are available until the end of the teaching semester, that is the final day of the official examination period.
On successful completion you will be able to:
- Clearly understand key concepts and results for each topic covered in the unit.
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand statistical properties of the estimator used and draw correct inferences from them (including hypothesis tests).
- Appreciate the advantages and limitations of an econometric method in various situations.
- Understand matrix algebra
Delivery and Resources
Classes
Classes: Monday 9 am - 12 pm (14 SCO [W7B], 200)
There is a single three-hour lecture/tutorial each week of semester. Attendance to lectures is strongly recommended. Selected questions from tutorials will be discussed during lectures.
It should be noted that class attendance is only one part of university study. In addition to class attendance, students will need to spend around six to nine hours per week in private study in order to perform well in the unit.
The timetable for classes can be found on the University website at: http://www.timetables.mq.edu.au/
References
The prescribed textbook is:
Verbeek, Marno, A Guide to Modern Econometrics (latest 4th edition, 2012).
If necessary, supplementary notes will be provided (on the unit homepage). Students are expected to download the notes for the next lecture topic and bring them to the lecture.
Technology Used and Required
(1) Students will require a non-programmable calculator for tutorials, tests and the final examination.
Students will also require access to a computer, on which the following programs are installed or accessible.
(2) Gretl: It is free, open-source software. Visit the Gretl website: http://gretl.sourceforge.net/, and choose the operating system of your computer from the menu on the left-hand side. Download and install the program onto the computer. Download also the manual and all the data for practice. The program has code facilities, but it is basically menu-based. Its functions cover most of the topics, but not all of them. This program may be used in combination with Shazam to verify results and to better understand the estimation methods.
(3) Shazam: A code-based econometric software program, which can be accessed through iLab: http://students.mq.edu.au/information_technology/. The user has to write his/her own codes using the commands and language of the program. It is very flexible in the sense that users can write their own codes to suit their needs instead of being limited by the available menu items of a menu-based program. A document on how to use the program will be provided on the unit homepage.
(4) An internet browser, such as Firefox and Internet Explorer, to access iLearn.
(5) Adobe Acrobat Reader: to read course material downloaded from iLearn. This program can be downloaded from http://www.adobe.com/downloads/.
Unit web page
Useful information and some course material will be made available on the learning management system (iLearn): ilearn.mq.edu.au. Visit the homepage regularly for new information, course material and announcements.
Teaching and Learning Strategy
Lecture notes will be made available before each corresponding lecture throughout the semester. The notes will include key concepts and points that are to be explained and discussed in the lecture. It is essential to get a good grasp of the contents of the lecture notes and the related parts of the textbook.
Useful examples are provided in the tutorials and the textbook. Going through those questions will help better understand the topics discussed in lectures. Solutions to the tutorial questions will be provided on the unit homepage. However, students are recommended to attempt the questions without looking at the provided solutions first and then refer to them for the expected answers.
Attendance to the lectures is not compulsory. However, students may be seriously disadvantaged by missing a lecture. If you missed a class for an unavoidable reason, it would be a good idea to borrow notes from a friend and see what was discussed in your absence.
For some topics, some references and journal articles may be prescribed for further reading.
Unit Schedule
- A Review of Mathematics and Statistics (Appendix B)
- A Review of the Multiple Regression Model and OLS Estimation (Chs. 2 & 3)
- Matrix Algebra (Appendix A, 2.1, 2.2, and 2.3)
- Nonspherical Disturbances and Generalised Least Squares (GLS) estimation (Ch. 4)
− Heteroscedasticity
− Serial correlation of random errors
- Stochastic Regressors and Consistent Estimation(Ch. 5)
- Instrumental variables (IV) estimation
- Method of moments (MM) estimation
- Generalised method of moments (GMM) estimation
- Models with Discrete Dependent Variables (Sections 7.1, 7.2, )
- Binary-choice models
- Ordered-choice models
- Multinomial-choice models
- Maximum likelihood (ML) estimation
− Sample selection bias and treatment effects
- Time Series Models (Chs. 8 and 9)
- Nonstationarity and unit root test
- Cointegration (single-equation approach)
- Cointegration (multi-equation approach)
- Models for Panel Data (Ch. 10)*
- Fixed-effects model
- Random-effects model
* To be covered if time permits.
Learning and Teaching Activities
Lectures
Tutorials
Private study
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:
- Academic Appeals Policy
- Academic Integrity Policy
- Academic Progression Policy
- Assessment Policy
- Fitness to Practice Procedure
- Grade Appeal Policy
- Complaint Management Procedure for Students and Members of the Public
- Special Consideration Policy (Note: The Special Consideration Policy is effective from 4 December 2017 and replaces the Disruption to Studies Policy.)
Undergraduate 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 shown in iLearn, 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.
Academic Honesty
The nature of scholarly endeavour, dependent as it is on the work of others, binds all members of the University community to abide by the principles of academic honesty. Its fundamental principle is that all staff and students act with integrity in the creation, development, application and use of ideas and information. This means that:
- all academic work claimed as original is the work of the author making the claim
- all academic collaborations are acknowledged
- academic work is not falsified in any way
- when the ideas of others are used, these ideas are acknowledged appropriately.
Further information on the academic honesty can be found in the Macquarie University Academic Honesty Policy at http://www.mq.edu.au/policy/docs/academic_honesty/policy.html
Grades
Macquarie University uses the following grades in coursework units of study:
- HD - High Distinction
- D - Distinction
- CR - Credit
- P - Pass
- F - Fail
Grade descriptors and other information concerning grading are contained in the Macquarie University Grading Policy which is available at:
http://www.mq.edu.au/policy/docs/grading/policy.html
Grading Appeals and Final Examination Script Viewing
If, at the conclusion of the unit, you have performed below expectations, and are considering lodging an appeal of grade and/or viewing your final exam script please refer to the following website which provides information about these processes and the cut off dates in the first instance. Please read the instructions provided concerning what constitutes a valid grounds for appeal before appealing your grade.
SPECIAL CONSIDERATION
The University is committed to equity and fairness in all aspects of its learning and teaching. In stating this commitment, the University recognises that there may be circumstances where a student is prevented by unavoidable disruption from performing in accordance with their ability. A policy for special consideration exists to support students who experience serious and unavoidable disruption such that they do not reach their usual demonstrated performance level. The policy is available at:
https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policies/special-consideration.
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 improve your marks and take control of your study.
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
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.
Graduate Capabilities
Creative and Innovative
Our graduates will also be capable of creative thinking and of creating knowledge. They will be imaginative and open to experience and capable of innovation at work and in the community. We want them to be engaged in applying their critical, creative thinking.
This graduate capability is supported by:
Learning and teaching activities
- Six to nine hours' private study in each week, reviewing course material, reading texts and recommended journal articles, and practicing software programs.
Discipline Specific Knowledge and Skills
Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.
This graduate capability is supported by:
Learning outcomes
- Clearly understand key concepts and results for each topic covered in the unit.
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand statistical properties of the estimator used and draw correct inferences from them (including hypothesis tests).
- Appreciate the advantages and limitations of an econometric method in various situations.
- Understand matrix algebra
Assessment tasks
- Homework
- Class Test
- Assignment
- Final Examination
Learning and teaching activities
- Two to three hour lecture in each week, where the topics are introduced, key concepts and ideas are explained, and some application examples are discussed.
- Eight sets of practical questions. Solutions provided. Some selected questions are discussed in class.
- Six to nine hours' private study in each week, reviewing course material, reading texts and recommended journal articles, and practicing software programs.
Critical, Analytical and Integrative Thinking
We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.
This graduate capability is supported by:
Learning outcomes
- Clearly understand key concepts and results for each topic covered in the unit.
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand statistical properties of the estimator used and draw correct inferences from them (including hypothesis tests).
- Appreciate the advantages and limitations of an econometric method in various situations.
- Understand matrix algebra
Assessment tasks
- Homework
- Class Test
- Assignment
- Final Examination
Learning and teaching activities
- Two to three hour lecture in each week, where the topics are introduced, key concepts and ideas are explained, and some application examples are discussed.
- Eight sets of practical questions. Solutions provided. Some selected questions are discussed in class.
- Six to nine hours' private study in each week, reviewing course material, reading texts and recommended journal articles, and practicing software programs.
Problem Solving and Research Capability
Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.
This graduate capability is supported by:
Learning outcomes
- Clearly understand key concepts and results for each topic covered in the unit.
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand statistical properties of the estimator used and draw correct inferences from them (including hypothesis tests).
- Understand matrix algebra
Assessment tasks
- Homework
- Class Test
- Assignment
- Final Examination
Learning and teaching activities
- Two to three hour lecture in each week, where the topics are introduced, key concepts and ideas are explained, and some application examples are discussed.
- Eight sets of practical questions. Solutions provided. Some selected questions are discussed in class.
- Six to nine hours' private study in each week, reviewing course material, reading texts and recommended journal articles, and practicing software programs.
Effective Communication
We want to develop in our students the ability to communicate and convey their views in forms effective with different audiences. We want our graduates to take with them the capability to read, listen, question, gather and evaluate information resources in a variety of formats, assess, write clearly, speak effectively, and to use visual communication and communication technologies as appropriate.
This graduate capability is supported by:
Learning outcomes
- Specify an econometric model that is appropriate for the problem at hand, estimate it using a relevant method, and interpret the estimation results.
- Understand matrix algebra
Assessment task
- Assignment
Learning and teaching activity
- Two to three hour lecture in each week, where the topics are introduced, key concepts and ideas are explained, and some application examples are discussed.
- Eight sets of practical questions. Solutions provided. Some selected questions are discussed in class.
- Six to nine hours' private study in each week, reviewing course material, reading texts and recommended journal articles, and practicing software programs.