Econometrics with Eviews course
The course is aimed at users who already use EViews but would benefit from an introduction to a range of more advanced methodologies and their implementation in EViews. The course will introduce more advanced techniques, particularly model building, and how to apply them using EViews.
It will also introduce EViews programming. Finally there will be a half day case study, bringing different theoretical approaches together to deal with a real issue-possibly one with data provided by the client. The objective is that following this course attendees should be comfortable in their knowledge of some more advanced methodologies and how to apply them to do using EViews.
Morning - Theory session.
- Introduction to econometric modelling.
- Review of Econometric Theory: univariate and multivariate modelling; non-stationary data: spurious regressions; cointegration and error correction models.
Afternoon - Applications.
- Model building in EViews: Data Entry and Management
- The process of setting up and estimating a model in EViews
- Automated specification search
- Dynamic and static solutions
- Forecasting with a model in EViews
- Testing the model and forecasts.
- Exercise on building a small macro model.
Morning - Unit Roots and Cointegration (combined theory and practical).
- ADF tests and alternatives
- Engle-Granger method and alternatives
- VAR vs VECM
- Johansen’s method
- Testing restrictions
- Small case study.
Afternoon - Economic Theory and Econometric Models.
- The Importance of Long Run Theoretical Restrictions
- The Blanchard-Quah decomposition.
- Practical Session on Long Run Theoretical Restrictions with Blanchard-Quah decomposition and on GMM methods to allow for expectations in consumption models and/or Taylor interest rate rules.
Morning - Structural vector autoregressive models (SVARs) in monetary policy.
- The monetary transmission mechanism and the impact of monetary shocks.
- Testing for structural breaks: e.g. interest rate data, price convergence and applications also using data provided by delegates attending the course. Sequential break-point tests.
- Review: Summary of the issues raised thus far. Questions and answers.
Afternoon - GARCH Processes and Exogeneity.
- Theory-Introduction to GARCH Processes for Time Series; Hausmans Test for Exogeneity; Weak and Strong Exogeneity; Granger Causality.
- Exercise- Estimating univariate and multivariate GARCH models. Testing for Exogeneity.
Morning - Theory-Panel Data modelling using EViews.
- Cointegration testing in Panels.
- Exercise- Building a simple Panel Data model using EViews.
Afternoon - Case study: Example - Growth Convergence.
- Statistical methods for assessing convergence: X-sectional tests – beta-convergence, sigmaconvergence; time-series tests – e.g. testing for a common trend.