I have two time series (Stocks and GDP) that I want to check for Granger causality. After reading the literature and documentations of various statistics software documentations (py statsmodels), I'm a little puzzled: What are the necessary steps for conducting a Granger causality test?
- First, I understand that the time series should be both stationary if we want to measure Granger causality. Here, the ADF test is a Unit root test that checks whether a time series is stationary or not. In my case, both time series are stationary at level.
- Second, I should check for the lag order to determine the maximum lag length for the Granger causality analysis. I do that via model.select_order(10) in Python statmodels and check which lags are indicated, for example by AIC and BIC.
- Now, how about cointegration? How do I check for cointegration in IPython and how do I interpret the results? I read in the literature about the "order of integration", written like I(0),I(1),I(2). I do not really understand what it means and how to produce the measure.
Otherwise, I'm well informed about how to check Granger itself and how to interpret its results.
Thanks for your help!