Vector Autoregression (VAR) is a statistical model used to capture the linear interdependencies among multiple time series data. It allows researchers to analyze how each variable in a system influences others over time, making it useful for forecasting and understanding dynamic relationships. In a VAR model, each variable is regressed on its own past values and the past values of all other variables in the system. This approach helps in identifying patterns and predicting future values based on historical data, making it a popular tool in fields like economics and finance.