Reviews the main competing approaches to modeling multiple time series: simultaneous equations, ARIMA, error correction models, and vector autoregression. This book focuses on vector autoregression (VAR) models as a generalization of the other approaches mentioned. It also reviews arguments for and against using multi-equation time series models.
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