Advanced time series analysis
News:
- The Advanced Time Series Analysis Retake Exam takes place on Monday, April 8th at 17:30 in room G227a
- Note: the first lecture takes place on Oct 23rd
- The lectures and tutorials are planned as on-campus sessions.
- Note: sign-up for this course on ZEUS.
- Further information and course material will be provided on ILIAS .
Instructors: Prof. Dr. Ralf Brüggemann
Time and Room:
Monday, 10:00 - 11:30, in Y311 (Lecture)
Friday, 10:00 - 11:30, in F429 (Lecture and Tutorial in alternation)
Language: Lectures and Tutorials are in English
Course Description:
Economic theory suggests that many macroeconomic time series (e.g. growth rates of gross domestic product, interest and inflation rates as well as monetary variables) are interrelated. In the lecture econometric methods for analyzing two or more time series (multiple time series) are introduced. Emphasis is given on the vector autoregressive framework, which is very popular in empirical macroeconomics and finance. It is used for forecasting and for investigating the dynamic interrelations between different variables (impulse response analysis). The course covers the analysis of stable vector autoregressive (VAR) models (including model estimation, model specification and model checking) as well as the statistical analysis of integrated and cointegrated variables. Further topics to be discussed include recent advances in structural VAR modelling, panel unit roots and cointegration, factor augmented VARs, time-varying parameter and Bayesian VARs. If time permits, multivariate GARCH models will be covered. Students gain practical experience in VAR modelling during the computer sessions.
Preliminary Course Outline:
- Introduction and overview
- Stable vector autoregressive (VAR) models
- Integrated variables and cointegrated VAR models
- Structural VARs and VECMs
- Bayesian VARs
- Multivariate GARCH models
Readings:
- Text Books
- Additional Readings
- Lütkepohl, H. & Krätzig, M. (2004), Applied Time Series Econometrics, Cambridge University Press, Chapters 3, 4. Online
- Further resources to be discussed in class
Software:
python
Course Material:
- via ILIAS