How best can I use the Granger causality test in time series data and understand it better because I have never used it. I want to analyze long run relationship and bi-directional relationship between two variables.
Here is an off the cuff answer.
Granger causality means that the shock or error from one variable has a cross correlation or impacts another.
H0 or the null hypothesis is NO CAUSALITY. It means your result falls within a range or confidence interval close to zero significance.
If the p>.05, the probability you 'struck out' and the one variable does not impact the other is high enough you 'cannot reject the null of no causality.' Stats-speak: you must accept that you failed to show causality on the variable.