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Multivariate Tests for Time Series Models

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Multivariate Tests for Time Series Models Synopsis

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.

About This Edition

ISBN: 9780803954403
Publication date:
Author: Jeffrey B Cromwell, Walter C Labys, Michael J Hannan, Michel Terraza
Publisher: SAGE Publications Inc
Format: Paperback
Pagination: 104 pages
Series: Quantitative Applications in the Social Sciences
Genres: Social research and statistics