Vector Autoregressive Models for Multivariate Time Series
This is page 383Printer: Opaque this11Vector Autoregressive Models forMultivariate Time IntroductionThevector autoregression(VAR)modelis one of the most successful,flexi-ble, and easy to use Models for the analysis of Multivariate time Series . It isa natural extension of the univariate Autoregressive model to dynamic mul-tivariate time Series . The VAR model has proven to be especially useful fordescribing the dynamic behavior of economic andfinancial time Series andfor forecasting. It often provides superior forecasts to those from univari-ate time Series Models and elaborate theory-based simultaneous equationsmodels.
388 11. Vector Autoregressive Models for Multivariate Time Series 11.2.2 Inference on Coefficients The ithelement of vec(Πˆ), ˆπi, is asymptotically normally distributed with 0 Z)−1. Hence, asymptotically valid t-tests on individual coefficients may be con-
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