Multivariate Tests for Time Series Models

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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.

Author(s): Jeff B. Cromwell, Walter C. Labys, Michael J. Hannan, Michel Terraza
Series: Quantitative Applications in the Social Sciences
Edition: 1
Publisher: Sage Publications, Inc
Year: 1994

Language: English