ECMT3110: Semester 1, 2020

University home

Library

Current students

Staff intranet

Find an event

Give

Current students

Units ECMT3110 Semester 1 2020 [Normal day]

Unit of study_

ECMT3110: Econometric Models and Methods

Overview

This unit extends methods of estimation and testing developed in association with regression analysis to cover econometric models involving special aspects of behaviour and of data. In particular, motivating examples are drawn from dynamic models, panel data and simultaneous equation models. In order to provide the statistical tools to be able to compare alternative methods of estimation and testing, both small sample and asymptotic properties are developed and discussed.

Details

Academic unit	Economics
Unit code	ECMT3110
Unit name	Econometric Models and Methods
Session, year ?	Semester 1, 2020
Attendance mode	Normal day
Location	Camperdown/Darlington, Sydney
Credit points	6

Enrolment rules

Prohibitions ?	ECMT3010
Prerequisites ?	ECMT2110 or ECMT2010 or ECMT2160
Corequisites ?	None
Available to study abroad and exchange students	Yes

Teaching staff and contact details

Coordinator	Brendan Beare, brendan.beare@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Applied project n/a	25%	-	9-12 pages
Outcomes assessed:
Final exam	Final exam (take home) Take home final exam	50%	Formal exam period	2 hours
Outcomes assessed:
In-semester test	Online Mid-semester exam n/a	25%	Week 07 Due date: 07 Apr 2020 at 12:00	1.5 hours
Outcomes assessed:

Detailed information for each assessment can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a High distinction indicates work of an exceptional standard, a Distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

Academic integrity

The Current Student website provides information on academic honesty, academic dishonesty, and the resources available to all students.

The University expects students and staff to act ethically and honestly and will treat all allegations of academic dishonesty or plagiarism seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic dishonesty. If such matches indicate evidence of plagiarism or other forms of dishonesty, your teacher is required to report your work for further investigation.

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction, review of basic matrix algebra and calculus	Lecture (2 hr)
Week 02	Review of probability, OLS - small sample properties	Lecture (2 hr)
Week 02	Tutorial 1	Tutorial (1 hr)
Week 03	Review of statistics, OLS - large sample properties	Lecture (2 hr)
Week 03	Tutorial 2	Tutorial (1 hr)
Week 04	Heteroskedasticity, Generalized Least Squares (GLS) and feasible GLS	Lecture (2 hr)
Week 04	Tutorial 3	Tutorial (1 hr)
Week 05	Endogeneity, instrumental variable method, 2SLS	Lecture (2 hr)
Week 05	Tutorial 4	Tutorial (1 hr)
Week 06	Methods of moments	Lecture (2 hr)
Week 06	Tutorial 5	Tutorial (1 hr)
Week 07	Midsemester exam	Lecture and tutorial (1.5 hr)
Week 08	Nonlinear Regession and Penalized Regression	Lecture (2 hr)
Week 08	Tutorial 7	Tutorial (1 hr)
Week 09	Tutorial 6	Tutorial (1 hr)
Week 09	Generalized Method of Moments (GMM)	Lecture (2 hr)
Week 10	Maximum likelihood - estimation and inference, numerical methods	Lecture (2 hr)
Week 10	Tutorial 8	Tutorial (1 hr)
Week 11	Maximum likelihood - models and applications	Lecture (2 hr)
Week 11	Tutorial 9	Tutorial (1 hr)
Week 12	Hypothesis testing (t, F, LR, LM, and Wald tests)	Lecture (2 hr)
Week 12	Tutorial 10	Tutorial (1 hr)
Week 13	Treatment effects, social and natural experiments	Lecture (2 hr)
Week 13	Tutorial 11	Tutorial (1 hr)

Attendance and class requirements

Attendance: According to Faculty Board Resolutions, students in the Faculty of Arts and Social Sciences are expected to attend 90% of their classes. If you attend less than 50% of classes, regardless of the reasons, you may be referred to the Examiner’s Board. The Examiner’s Board will decide whether you should pass or fail the unit of study if your attendance falls below this threshold.
Lecture recording: Most lectures (in recording-equipped venues) will be recorded and may be made available to students on the LMS. However, you should not rely on lecture recording to substitute your classroom learning experience.
Preparation: Students should commit to spend approximately three hours’ preparation time (reading, studying, homework, essays, etc.) for every hour of scheduled instruction.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed on the Library eReserve link available on Canvas.

Required textbook: Econometric Theory and Methods, by Davidson and MacKinnon, Oxford University Press, 2003.
Required textbook: A Primer in Econometric Theory, by John Stachurski, MIT Press, 2016.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University’s graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. understand modern econometric methods and models, including linear and nonlinear models
LO2. understand important estimation methods, including ordinary and nonlinear least squares, 2SLS, instrumental variable method, method of moments, generalized method of moments, and maximum likelihood
LO3. evaluate existing empirical studies using the econometric methods and models covered
LO4. apply the econometric methods and models to data sets in economics and other fields.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Closing the loop

Lecture notes, tutorial questions, and applied project have been updated according to the student feedback.

Key dates
Key dates through the academic year, including teaching periods, census, payment deadlines and exams.
Student administration
Enrolment, course planning, fees, graduation, support services, student IT
Expectations of student conduct
Code of Conduct for Students, Conditions of Enrollment, University Privacy Statement, Academic Integrity
Academic appeals
Academic appeals process, special consideration, rules and guidelines, advice and support
Learning and teaching policy
Policy register, policy search
Financial support
Scholarships, interest free loans, bursaries, money management
Study resources
Learning Centre, faculty and school programs, Library, online resources
Health and support
Student Centre, counselling & psychological services, University Health Service, general health and wellbeing

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Details

Enrolment rules

Teaching staff and contact details

Assessment

Assessment criteria

Late submission

Special consideration

Academic integrity

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Graduate qualities

Outcome map

Closing the loop

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect