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:
causedint 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.

causingint 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).

signiffloat, 0 < signif < 1, default 5 %

Significance level for computing critical values for test, defaulting to standard 0.05 level.

Returns:
resultsstatsmodels.tsa.vector_ar.hypothesis_test_results.CausalityTestResults

References

[1]

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


Last update: Apr 19, 2024