Multiple Time Series Models

by Patrick T. Brandt, John Taylor Williams

Multiple Time Series Models introduces researchers and students to the different approaches to modeling multivariate time series data including simultaneous equations, ARIMA, error correction models, and vector autoregression. Authors Patrick T. Brandt and John T. Williams focus on vector autoregression (VAR) models as a generalization of these other approaches and discuss specification, estimation, and inference using these models.

120 pages, Paperback

First published September 19, 2006