statsmodels.tsa.vector_ar.vecm.VECMResults.test_granger_causality

VECMResults.test_granger_causality(caused, causing=None, signif=0.05) [source]

Test for Granger-causality.

The concept of Granger-causality is described in chapter 7.6.3 of [1]. Test H₀: “The variables in causing do not Granger-cause those in caused” against H₁: “causing is Granger-causal for caused”.

Parameters:	caused (int or str or sequence of int or str) – If int or str, test whether the variable specified via this index (int) or name (str) is Granger-caused by the variable(s) specified by causing. If a sequence of int or str, test whether the corresponding variables are Granger-caused by the variable(s) specified by causing. causing (int or str or sequence of int or str or None, default: None) – If int or str, test whether the variable specified via this index (int) or name (str) is Granger-causing the variable(s) specified by caused. If a sequence of int or str, test whether the corresponding variables are Granger-causing the variable(s) specified by caused. If None, causing is assumed to be the complement of caused (the remaining variables of the system). signif (float, 0 < signif < 1, default 5 %) – Significance level for computing critical values for test, defaulting to standard 0.05 level.
Returns:	results
Return type:	statsmodels.tsa.vector_ar.hypothesis_test_results.CausalityTestResults

References

[1]	Lütkepohl, H. 2005. New Introduction to Multiple Time Series Analysis. Springer.