VAR Model EViews - EViews Workfile + Slides + Dataset

The video tutorial provides an overview of Vector Autoregression (VAR) models in EViews, explaining how they generalize univariate autoregressive models to multivariate time series. The presenter discusses the main premise of VAR models, their applications in forecasting and policy analysis, and the assumptions involved. Using an example from Stock and Watson (2001), the tutorial walks through setting up a VAR model in EViews, including selecting lag lengths and estimating coefficients. It covers stability conditions, residual diagnostics, and Granger causality tests to assess model validity and interpret relationships between variables. Topics such as impulse response functions and variance decomposition are also covered.