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 expressed as a linear function of its own past values and the past values of all other variables in the system. This approach helps in identifying patterns and predicting future trends, making it a popular tool in fields like economics, finance, and social sciences.