ADVANCED TIME SERIES ECONOMETRICS
ECM4ATE
2014
Credit points: 15
Subject outline
The purpose of this subject is to introduce students to the theoretical and applied aspects of multivariate time series modelling in Economics and Finance. This subject provides students with a basic understanding of the linear algebra, multivariate calculus and simultaneous-equation models needed to work in this area. Topics covered include VAR modelling, Granger causality analysis, error correction models, cointegration, impulse response functions and variance decompositions. There will be a strong focus on applications from Business, Finance and Economics and on the use of the EViews time series package.
Faculty: Faculty of Business, Economics and Law
Credit points: 15
Subject Co-ordinator: Laszlo Konya
Available to Study Abroad Students: No
Subject year level: Year Level 4 - UG/Hons/1st Yr PG
Exchange Students: No
Subject particulars
Subject rules
Prerequisites: ECM3ITE
Co-requisites: N/A
Incompatible subjects: ECO3ATE
Equivalent subjects: N/A
Special conditions: N/A
Learning resources
Readings
| Resource Type | Title | Resource Requirement | Author and Year | Publisher |
|---|---|---|---|---|
| Readings | Applied Econometric Time Series (2nd ed.) | Prescribed | Enders, W. | WILEY, HOBOKEN 2004, 2ND EDITION. |
| Readings | Introduction to modern timeseries analysis | Recommended | Kirchgassner, G., Wolters, J. | SPRINGER, 2008 |
| Readings | Time series models for business and economic forecasting | Recommended | Franses, P. H. | CAMBRIDGE UNIVERSITY PRESS, 1998 |
Melbourne, 2014, Semester 1, Day
Overview
Online enrolment: Yes
Maximum enrolment size: N/A
Enrolment information:
Subject Instance Co-ordinator: Laszlo Konya
Class requirements
LectureWeek: 10 - 22
One 2.0 hours lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
WorkShopWeek: 10 - 22
One 1.0 hours workshop per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.
Assessments
| Assessment element | Comments | % |
|---|---|---|
| three 1,500-word assignments | 100 |