Wiener and Granger have introduced an intuitive concept of causality between
two variables which is based on the idea that an effect never occurs before its
cause. Later, Geweke has generalized this concept to a multivariate Granger
causality, i.e., n variables Granger-cause another variable. Although Granger
causality is not "effective causality", this concept is useful to infer
directionality and information flow in observational data. Granger causality is
usually identified by using VAR models due to their simplicity.