Multiple Time Series Models

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.