Classes: Tuesday 6:00 pm - 9:00 pm (6EAR [E4B] 206)

There is a single three-hour lecture each week of semester. Class attendance is not compulsory and will not be recorded. However, students who miss classes put themselves at a considerable disadvantage for several reasons, including:

1)      Not all of the material in the text is covered in the unit, and not all the unit material is covered in the text. In some places the text deals with issues in greater depth than is necessary for the unit, and in other places it is not detailed enough. The lectures contain all the unit material taught at the level that is required for successful completion of the assessment tasks, and they are your guide to the content of the unit.

2)      The approaches to some problems that are recommended by the lecturers are different to those in the text.

3)      The lectures will include significant guidance about the style and content of the final exam and recommendations about study technique.

4)      It is difficult (and often impossible) for staff to provide meaningful assistance to students outside class times on topics for which they did not attend the relevant lectures.

Exercise questions and solutions will be provided for private studies. Some selected questions will be discussed in class.

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/ 

Required and Recommended Texts and/or Materials      

The prescribed text for the unit is

R. Carter Hill, William E. Griffiths, and Guay C. Lim (2011) Principles of Econometrics,  4^rd ed., John Wiley & Sons.

Lecture slides will be provided on the unit home page.

Technology Used and Required

(1)     Students will require a non-programmable calculator for exercises, test and the final examination.

Students will also require access to a computer, on which the following programs are installed.

(2)     Gretl: It is free, open-source software. Visit the Gretl website: http://gretl.courceforge.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. Students are required to be able to use this program to answer exercise, test and assignment questions. Students are also required to understand its outputs.

(3)     An internet browser, such as Firefox and Internet Explorer, to access iLearn.

(4)     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

This unit is taught as a traditional lecture course. Students should attend class and read the relevant parts of the text each week. Exercise questions will be set and made available on the unit homepage throughout the semester. The solutions to selected questions will be discussed in class. Students should attempt all the exercises before they are covered in class. The text also contains many examples and exercises which students should work through as part of their private study.

1. THE MULTIPLE REGRESSION MODEL (Chs 5 & 6)

       - Interpretation

       - The properties of the OLS estimator under the standard assumptions

       - Testing a single-equation hypothesis

       - Goodness of fit

       - Analysis of Variance (ANOVA)

       - Summary Report

       - F test (including the overall significance test, testing economic hypothesis, the use of nonsample information)

       - Model specification (omitted & irrelevant variables, RESET test, and multicollinearity)

       - Prediction

       - Functional forms

       - Dummy variables

2. HETEROSKEDASTICITY (Ch 8)

       - Nature

       - Detection

       - Consequences

       - Remedy

3. REGRESSION WITH TIME-SERIES DATA (Chs 9 & 12)

       - Autoregressive Distributed-lag (ADL) models

       - Autocorrelation functions, partial autocorrelation functions, and correlogram)

       - Serially correlated errors

       - Autoregressive Moving-Average (ARMA) models

       - Non-stationarity

       - Unit-root test

       - Spurious regression and cointegration

4. RANDOM REGRESSORS & MOMENT-BASED ESTIMATION (Ch 10)

       - Random regressors and endogeneity

       - Consequences

       - IV, MM and GMM estimation

       - The Hausman test for endogeneity

       - The Sargan’s overidentifying restrictions test

       - Weak instruments

5. BINARY-CHOICE MODELS (Ch 16)

       - Linear probability model

       - Probit model

       - Logit model

       - Maximum likelihood estimation

6. MODELS FOR PANEL DATA (Ch 15)

       - Fixed-effects model

       - Random-effects model