Granger causality is a statistical hypothesis test for determining whether one time series can predict another time series. This concept is crucial in understanding relationships between variables in multivariate time series analysis, especially when using models that capture dynamic interactions like vector autoregression. It does not imply true causation but rather indicates a predictive relationship where past values of one series help forecast future values of another.
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