Transcription of Vector Autoregressive Models for Multivariate Time Series
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Vector Autoregressive Models for Multivariate Time Series
This is page 383 Printer: Opaque this11 Vector 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.
Vector Autoregressive Models for Multivariate Time Series 11.1 Introduction The vector autoregression (VAR) model is one of the most successful, flexi-ble, and easy to use models for the analysis of multivariate time series. It is a natural extension of the univariate autoregressive model to dynamic mul-tivariate time series.
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