Course Title: Regression Models in Econometrics

Part A: Course Overview

Course Title: Regression Models in Econometrics

Credit Points: 12.00


Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)


Course Coordinator: Kaye Marion

Course Coordinator Phone: +61 3 9925 3162

Course Coordinator Email: k.marion@rmit.edu.au


Pre-requisite Courses and Assumed Knowledge and Capabilities

A knowledge of basic calculus, matrix algebra and statistics will be assumed to the level of MATH 1324 Statistical Methods.


Course Description

This course helps the student to understand how to construct models appropriate to particular applications, how to test the models statistically and how to apply them to problems in forecasting and analysis.


Objectives/Learning Outcomes/Capability Development

On completion of this course, students will
(i) obtain an understanding of econometric concepts and methodology;
(ii) be able to define and formulate generalised linear regression models and appreciate their limitations;
(iii) be able to estimate and validate generalized linear regression models and interpret the results obtained.
The emphasis is on problems that arise with the building of economic models.


On completion of this course, students will
(i) obtain an understanding of econometric concepts and methodology;
(ii) be able to define and formulate generalised linear regression models and appreciate their limitations;
(iii) be able to estimate and validate generalized linear regression models and interpret the results obtained.
The emphasis is on problems that arise with the building of economic models.


Overview of Learning Activities

The course is designed to help students choose the right package for the data analysis tasks they will carry out in other courses in the program and in their working life. They will be able to transfer data easily between applications. They will also be able to communicate information in the data to colleagues in simple but meaningful ways.


Overview of Learning Resources

Learning resources comprise the list of references listed below, a set of detailed course notes and other relevant materials such as extra notes, assignments, past tests which will be available on line. 


Overview of Assessment

Assessment will be through assignments and a final examination.