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Multivariate Tests for Time Series Models
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Multivariate Tests for Time Series Models



July 1994 | 104 pages | SAGE Publications, Inc
Which time series test should a researcher chose to best describe the interactions among a set of time series variables? Aimed at providing social scientists with practical guidelines for identifying the appropriate multivariate time series model to use, this book explores the nature and application of these increasingly complex tests. Other topics it covers are joint stationarity, testing for cointegration, testing for Granger causality, and testing for model order, and forecast accuracy. Related models explained include transfer function, vector autoregression, error correction models, and others. Readers with a working knowledge of time series regression will find this helpful book accessible.


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Introduction
 
Testing for Joint Stationarity, Normality and Independence
 
Testing for Cointegration
 
Testing for Causality
 
Multivariate Linear Model Specification
 
Multivariate Nonlinear Specification
 
Model Order and Forecast Accuracy
 
Computational Methods for Performing the Tests

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ISBN: 9780803954403
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