How does a Vector Autoregression (VAR) model in time series differ from a simple AR model?

VAR and AR models are interchangeable and have no significant differences.
VAR considers multiple time series variables simultaneously, while AR models focus on a single variable.
VAR is a non-parametric model, whereas AR is parametric.
VAR is only used for long-term forecasting, whereas AR is for short-term forecasting.

The key distinction is that VAR models consider multiple time series variables simultaneously, allowing for a more comprehensive understanding of interdependencies among variables. In contrast, AR models focus on forecasting a single variable over time.

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