Part of the Use R! book series (USE R)

In the previous chapters, a brief explanation of univariate and multivariate time series models and their characteristics was presented. The focus of this chapter is on the simultaneous modeling of time series and inferences of the relationships between them if some or all of them are integrated processes of order one. As will be shown, the degree of integration and a careful examination of the data-generating processes are of utmost importance. We will begin by briefly reviewing the case of a spurious regression before we proceed by providing a definition of cointegration and its error-correction representation. In the last section, the more encompassing vector error-correction models are presented.


Granger Causality Cointegrating Vector Spurious Regression Cointegration Relation Cointegration Rank 
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© Springer Science+Business Media, LLC 2008

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