Multivariate Tests for Time Series Models

by Jeff B. Cromwell, Michel Terraza, Walter C. Labys

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.

104 pages, Paperback

First published July 6, 1994

About the author

Jeff B. Cromwell has a PhD in Natural Resource Economics from West Virginia University and writes books in mathematics, computer science, music, science, science fiction, romance and fantasy. He is an accomplished author and software engineer with appointments at several universities and consulting for several financial and academic research departments and institutes. He has written for magazines as a columnist and contributed articles to books and journals. Along with fluency in several computer languages, Jeff speaks and can write in Mandarin and Japanese as well as play the clarinet and piano. This site shares his love of literature and reading that first started with a dictionary, a collection of encyclopedia volumes and a Timex-Sinclair computer in his youth. Enjoy the day.