Question #47961

what are the proper steps to test GRANGER CAUSALITY test, please explain it. if you any book in your mind regarding this topic then pleas mention it.

Expert's answer

The steps to test GRANGER CAUSALITY test are the following 1. Check that both series are stationary in mean, variance and covariance (if necessary transform the data via logs, differences to ensure this) 2. Estimate AR(p) models for each series, where p is large enough to ensure white noise residuals. F tests and other criteria (for instance Schwartz or Akaike) can be used to establish the maximum lag p that is needed.

3) Re-estimate both models, now including all the lags of the other variable

4) Use F tests to determine whether, after controlling for past Y, past values of X can improve forecasts Y (and vice versa)

We can also test it using Eviews. To test if one of our variables Granger-causes one of the other variables, choose View/Lag structure/Granger causality test. Where our Ho is that we do not have Granger-causaility.

3) Re-estimate both models, now including all the lags of the other variable

4) Use F tests to determine whether, after controlling for past Y, past values of X can improve forecasts Y (and vice versa)

We can also test it using Eviews. To test if one of our variables Granger-causes one of the other variables, choose View/Lag structure/Granger causality test. Where our Ho is that we do not have Granger-causaility.

## Comments

## Leave a comment