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.

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.