Vector Autoregression (VAR) Impulse Response Analysis is a powerful statistical tool used to analyze the dynamic behavior of multiple time series data. It allows researchers to understand how a shock or impulse in one variable affects other variables over time. In a VAR model, each variable is regressed on its own lagged values and the lagged values of all other variables in the system. The impulse response function (IRF) captures the effect of a one-time shock to one of the variables, illustrating its impact on the subsequent values of all variables in the model.
Mathematically, if we have a VAR model represented as:
where is a vector of endogenous variables, are the coefficient matrices, and is the error term, the impulse response can be computed to show how responds to a shock in over several future periods. This analysis is crucial for policymakers and economists as it provides insights into the time path of responses, helping to forecast the long-term effects of economic shocks.
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