The Vector Autoregression (VAR) model is a statistical model used to analyze the
dynamic relationships among multiple time series variables. It allows for the examination of
interdependencies and feedback effects between the variables. In a VAR model, each variable in
the system is regressed on its own lagged values as well as the lagged values of the other
variables. This captures the autoregressive nature of the variables and allows for the
exploration of their mutual interactions. The model assumes that each variable is influenced by
its own past values, the past values of other variables, and potentially exogenous shocks.