An introduction to vector autoregressive (VAR) analysis is given with special emphasis on cointegration. The models, estimating their parameters and specifying the autoregressive order, the cointegrating rank and other restrictions are discussed. Possibilities for model validation are also considered, Causality tests, impulse responses and forecast error variance decompositions are presented as tools for analyzing VAR models.