python做格兰杰因果检验

http://www.statsmodels.org/dev/generated/statsmodels.tsa.stattools.grangercausalitytests.html

 

The Null hypothesis for grangercausalitytests is that the time series in the second column, x2, does NOT Granger cause the time series in the first column, x1. Grange causality means that past values of x2 have a statistically significant effect on the current value of x1, taking past values of x1 into account as regressors. We reject the null hypothesis that x2 does not Granger cause x1 if the pvalues are below a desired size of the test.

The null hypothesis for all four test is that the coefficients corresponding to past values of the second time series are zero.

‘params_ftest’, ‘ssr_ftest’ are based on F distribution

‘ssr_chi2test’, ‘lrtest’ are based on chi-square distribution