Which time series test should researchers choose to best describe the interactions among a set of time series variables? Providing guidelines for identifying the appropriate multivariate time series model to use, this book explores the nature and application of these increasingly complex tests. In addition, it covers such topics as: joint stationarity; testing for cointegration; testing for causality; and model order and forecast accuracy. Related models explained include transfer function, vector autoregression and error correction models.

Computational Methods for Performing the Tests

The purpose of this chapter is to provide some insights into the software available for constructing the models and performing the tests proposed here. To better facilitate this endeavor, we suggest software such as MicroTSP (1992), RATS, and SHAZAM, which can perform some of the identification tests and the ...

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