This course is part three of a five-part EViews training series running throughout 2024.
You will find links for all other courses in the series below:
Course 2: Atheoretical Models in EViews
Course 4: Volatility Models and Panel Data Models
Course 5: Models for Panel Data
This course focuses on advanced time series modeling for non-stationary variables. Participants learn key concepts such as unit roots and cointegration, applying the Dickey-Fuller test and Engle-Granger analysis. The course also covers multivariate cointegration, including Johansen’s test and the (VECM). A practical session ensures hands-on proficiency. By the end, participants can confidently model non-stationary variables using EViews in real-world scenarios.
Upon the course's completion, all attendees will receive a certificate of attendance as proof of professional development.
Level: Intermediate
Learning ratio: 50% Practical; 50% Theory
1. Introduction to Stationarity and Unit Roots:
Fundamentals of stationarity and its importance in time series analysis.
Definition and significance of unit roots.
The Dickey-Fuller test for detecting unit roots in time series data.
Session 2: Non-Stationarity II - Cointegration
2. Introduction to Cointegration:
Preliminary theory on cointegration and its relevance.
Engle-Granger analysis: Understanding and implementing in EViews.
Session 3: Multivariate Cointegration I - The VECM
3. Cointegrated VARs in EViews:
Johansen’s test for cointegration in multivariate time series.
Introduction to the (Vector) Error Correction Model (VECM).
Estimating and interpreting a VECM in EViews.
Session 4: Multivariate Cointegration II - The VECM
4. Practical Session:
Hands-on application of VECM concepts learned in the previous session.
Utilizing EViews for practical exercises and real-world scenarios.
Models for Nonstationarity Variables in EViews
The number of attendees is restricted. Please register early to guarantee your place.