ECON7331 - Econometric Theory

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ECON7331 - Econometric Theory

Semester: Sem 2 2023  |  Location: St Lucia  |  Mode: External

Printed: 14 August 2023, 01:55 pm

This printed course pro4le is valid at the date and time speci4ed above. The course pro4le may be subject to change during the semester - the online version is the authoritative version.

1. General Course Information

UQ Students: Please access the pro4le from Learn.UQ (https://learn.uq.edu.au/) or mySI-net (https://www.sinet.uq.edu.au/) to access all course contributor details held in this pro4le.

1.1 Course Details

Course Code: ECON7331

Course Title: Econometric Theory

Coordinating Unit: School of Economics

Semester: Semester 2, 2023

Mode: External

Level: Postgraduate Coursework

Location: External (administered at St Lucia)

Number of Units: 2

Pre-Requisites: ECON3320 or 7321

Incompatible: ECON3310 + 3330

Course Description: Theory of general linear model-topics include: least squares, generalised method of moments & maximum likelihood estimators under iid, auto-correlated & heteroskedastic error speci4cations.

Assumed Background: Introductory linear algebra and Statistical Theory.

1.2 Course Introduction

The purpose of this course is to provide the theoretical background to many econometric techniques covered in ECON7310. It deals with the theory behind the techniques rather than the implementation of the techniques. It also covers material on testing, generalised method of moments, and

maximum likelihood estimation not encountered in ECON7310. Matrix algebra is an important mathematical tool that is used throughout this

course. The course has been structured so that you can learn the necessary matrix algebra as an integral part of the material. Lectures will present theoretical concepts in detail.

Course Changes in Response to Previous Student Feedback

No feedback is available at this time. We look forward to your responses at the end of the semester.

1.3 Course Staff

Course Coordinator: Dr Antonio Peyrache

Email: [email protected] (mailto:[email protected])

Lecturer: Dr Antonio Peyrache

UQ Students: Please access the pro4le from Learn.UQ (https://learn.uq.edu.au/) or mySI-net (https://www.sinet.uq.edu.au/) to access all course contributor details held in this pro4le.

1.4 Timetable

Timetables are available on the UQ Public Timetable. (https://my.uq.edu.au/public-timetable)

Additional Timetable Information

Tutorials will commence in Week 2.

Students should refer to the timetable prior to the commencement of classes to ensure that they have the most up-to-date information, as from

time to time late room changes may occur. The timetable can be downloaded from Timetable

(https://timetable.my.uq.edu.au/odd/timetable/#subjects).

Public Holidays: Wednesday 16 August (Royal Queensland Show), Monday 2 October (King's Birthday).

Mid-Semester Break: 25 September - 2 October. Semester 2 classes recommence Tue 3 October.

2. Aims, Objectives & Graduate Attributes

2.1 Course Aims

The purpose of this course is to provide the theoretical background to many econometric techniques covered in ECON2300. It deals with the theory behind the techniques rather than the implementation of the techniques. It also covers material on testing, generalised method of moments, and

maximum likelihood estimation not encountered in ECON2300. Matrix algebra is an important mathematical tool that is used throughout this course. The course has been structured so that you can learn the necessary matrix algebra as an integral part of the material.

2.2 Learning Objectives

After successfully completing this course you should be able to:

1       Explain matrix algebra pro4ciently to derive properties of (and compute) various  econometric estimators.


2       Evaluate the theory behind the General Linear Regression Model.

3       Explain the numerical and statistical properties of the OLS, GLS and IV estimators.

4       Demonstrate the 4nite sample and asymptotic properties of the OLS, GLS and IV estimators.

5       Use statistical packages such as R-Studio to compute the various estimators on real world datasets.

6       Examine the learned theory and methods to the real world.

2.3 Graduate Attributes

Successfully completing this course will contribute to the recognition of your attainment of the following UQ (Postgrad Coursework) graduate attributes:

GRADUATE ATTRIBUTE

LEARNING

OBJECTIVES

A . IN-DEPTH KNOWLEDGE OF THE FIELD OF STUDY

A2 . A broad understanding of the 4eld of study, including how other disciplines relate to the 4eldof study.

1, 2, 5

A3 . A comprehensive and in-depth knowledge in the 4eldof study.

1, 2, 3, 4, 5

A5 . An international perspective on the 4eldof study.

2

A7 . An appreciation of the link between theory and practice.

5

B . EFFECTIVE COMMUNICATION

B1 . The ability to collect, analyse and organise information and ideas and to convey those ideas clearly and Yuently, in both written and spoken forms.

1, 2, 5

B2 . The ability to interact effectively with others in order to work towards a common outcome.

N/A

B3 . The ability to select and use the appropriate level, style and means of communication.

1, 2, 4

B4 . The ability to engage effectively and appropriately with information and communication technologies.

1, 2

B5 . The ability to practise as part of an interdisciplinary team.

N/A

C . INDEPENDENCE AND CREATIVITY

C2 . The ability to work and learn independently and effectively.

3, 5

C3 . The ability to generate ideas and adapt innovatively to changing environments.

3, 5

C5 . The ability to formulate and investigate problems, create solutions, innovate and improve current practices.

3

C6 . The abilities and skills that provide a foundation for future leadership roles.

N/A

D . CRITICAL JUDGEMENT

D2 . The ability to apply critical reasoning to issues through independent thought and informed judgement.

1, 3, 4, 5, 6

D4 . The ability to process material and to critically analyse and integrate information from a wide range of sources.

1

D5 . The ability to evaluate opinions, make decisions and to reYect critically on the justi4cations for decisions using an evidence-based approach.

1

E . ETHICAL AND SOCIAL UNDERSTANDING

E1 . An understanding of social and civic responsibility.

N/A

E3 . An appreciation of the philosophical and social contexts of a discipline.

1

E4 . A knowledge and respect of ethics and ethical standards in relation to a major area of study.

N/A

E5 . A knowledge of other cultures and times and an appreciation of cultural diversity.

1

E7 . The ability to work effectively and sensitively across all areas of society.

1

E8 . An understanding of and respect for the roles and expertise of associated disciplines.

N/A

3. Learning Resources

3.1 Required Resources

No required learning resources

3.2 Recommended Resources

James H. Stock and Mark W. Watson (2020), Introduction to Econometrics, Pearson

Davidson, R., & MacKinnon, J. G. (2004). Econometric theory and methods. Oxford University Press.

3.3 University Learning Resources

Access to required and recommended resources, plus past central exam papers, is available at the UQ Library website

(http://www.library.uq.edu.au/lr/ECON7331 (http://www.library.uq.edu.au/lr/ECON7331)).

The University offers a range of resources and services to support student learning. Details are available on the myUQ website (https://my.uq.edu.au/ (https://student.my.uq.edu.au/)).

3.4 School of Economics Learning Resources

For assessment in this course students will be permitted to use Casio FX82 series (82 with any letters) or university approved (labelled) calculators.

Calculator requirements may differ for other university courses and students should check each course pro4le for the speci4c requirements.

PLEASE NOTE: It is the student’s responsibility to ensure they have the correct calculator prior to assessment in each of their courses. Students without the correct calculator in a School of Economics exam may have their calculator con4scated.

Guidelines for correct referencing techniques can be found in https://guides.library.uq.edu.au/referencing?b=g&d=a&group_id=15017 (https://guides.library.uq.edu.au/referencing?b=g&d=a&group_id=15017).

3.5 Other Learning Resources & Information

Abadir M.A., Magnus J.R., "Matrix Algebra", Cambridge

4. Teaching & Learning Activities

4.1 Learning Activities

Recording of Lectures: Please be aware that teaching at UQ may be recorded for the bene4t of student learning. If you would prefer not to be

captured either by voice or image, please advise your course coordinator before class so accommodations can be made. For further information see PPL 3.20.06 Recording of Teaching at UQ (https://my.uq.edu.au/information-and-services/information-technology/software-and-web-apps/software-uq/zoom).

Date

Activity

Learning

Objectives

24 Jul 23 - 30 Jul 23

Linear Algebra and Regression (Lecture): Review of statistical concepts and matrix algebra. Introduction to the linear regression model.

1, 2, 3

31 Jul 23 - 06 Aug 23

Geometry of Linear Regression 1 (Lecture): Geometry of vector spaces; geometry of OLS

1, 2, 3

07 Aug 23 - 13 Aug 23

Geometry of Linear Regression 2 (Lecture): More on linear regression

3, 4

14 Aug 23 - 20 Aug 23

Statistical properties of OLS 1 (Lecture Series): Finite sample properties, consistency, erciency.

4, 5, 6

21 Aug 23 - 27 Aug 23

Statistical Properties of OLS 2 (Lecture): More on the statistical properties of OLS.

5, 6

28 Aug 23 - 03 Sep 23

Hypothesis Testing and Con^dence Intervals 1 (Lecture): Some common distribution. Exact and large sample tests.

5, 6

04 Sep 23 - 10 Sep 23

Hypothesis Testing and Con^dence Intervals 2 (Lecture): More on hypothesis testing and con4dence intervals.

5, 6

11 Sep 23 - 17 Sep 23

Generalized Least Squares (GLS) (Lecture): GLS estimator; FGLS.

18 Sep 23 - 24 Sep 23

Instrumental Variable Regression (Lecture)

25 Sep 23 - 01 Oct 23

Mid-Semester Break (Mid-Semester Break)

02 Oct 23 - 08 Oct 23

No Lectures - King's Holiday (Lecture)

09 Oct 23 - 15 Oct 23

Maximum Likelihood Estimation (Lecture)

16 Oct 23 - 22 Oct 23

Limited Dependent Variable Models (Lecture)

23 Oct 23 - 29 Oct

2023-08-22