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Advanced Course in Time–Series Econometrics
Brief Description
This course addresses modelling techniques for time-series data when unit roots are present in the data. An overview of the technical characteristics of time-series data and the concept of non-stationarity is provided; and the econometric techniques of co-integration and error correction modelling are revised in single equations (residual-based co-integration), with emphasis on their empirical application. The main focus of the course is however on the theory and application of multivariate co-integration. The course concludes with a discussion on the application of volatility models.
 
The course takes place in a computer lab on the main campus of the University of Pretoria. Delegates use Eviews version 10 for practical applications.
Learning Outcomes
After successful completion of this programme, delegates will be able to:
    - Understand and apply non-stationary time series analysis    
    - Understand the concept of stationarity and unit root Testing 
    - Apply the advanced econometric techniques of cointegration and error correction modelling, specifically in the multivariate context,
    - Understand and apply basic volatility modelling.
Delegates complete an open-book evaluation on the last day of the course. A certificate will be awarded upon successful completion of the course.
Course Content
The course covers the following topics:
1. Overview of residual-based co-integration
    - Data generating processes
    - Stationary vs. non-stationary time series
    - Co-integration in single equations (Engle-Granger)
    - Error correction models (ECM)
2.  Multivariate co-integration (focus of course)
    - Vector autoregressive (VAR) models
    - Impulse response functions and variance decompositions     
    - Johansen co-integration methodology (maximum likelihood estimation)
    - Vector error correction models (VECM)
    - Block causality and exogeneity tests
    - Weak exogeneity tests and model identification
3. Introduction to volatility models
    - Properties and theoretical and empirical issues
    - ARCH and GARCH models
    - Estimation and prediction
Entry Requirements
Prospective delegates should at least have a relevant honours degree with a focus on time-series econometrics, including a knowledge of the concepts of unit root testing and residualbased (Engle-Granger) cointegration. An understanding of matrix algebra is essential as well as experience as a researcher or analyst in any of the fields of economic application.Proficiency in EViews software is recommended.
Course Number:
P000537
Catalogue and Category:
Financial Management and Taxation
Who Should attend:
Experience as a researcher or analyst in any of the following fields of economic application is required: financial markets, socio- economics and health, development economics, publicfinance and tax policy or international trade and finance. 
Delivery Mode:
Contact Sessions
Contact Days:
Total Notional Hours: