ecm4ate adv. time series econometrics
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.
FacultyFaculty of Business, Economics and Law
Credit points15
Subject Co-ordinatorLaszlo Konya
Available to Study Abroad StudentsNo
Subject year levelYear Level 4 - UG/Hons/1st Yr PG
Exchange StudentsNo
Subject particulars
Subject rules
Prerequisites ECM3ITE
Co-requisitesN/A
Incompatible subjects ECO3ATE
Equivalent subjectsN/A
Special conditionsN/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 |
Subject options
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Melbourne, 2014, Semester 1, Day
Overview
Online enrolmentYes
Maximum enrolment sizeN/A
Enrolment information
Subject Instance Co-ordinatorLaszlo 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 |