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.
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Dr. Jeff B. Cromwell is a graduate of West Virginia University with research interests in computational statistics, econometrics and time series analysis.
Dr. Hannan joined Edinboro University′s Department of Business & Economics in 1988 after earning a Ph.D. in Mineral Resource Economics from West Virginia University and a Bachelor of Arts degree in Economics from the University of Pittsburgh. Prior to coming to Edinboro University, Dr. Hannan also served as Senior Research Assistant at the Regional Research Institute, Morgantown, West Virginia. He has published several articles in professional journals, given presentations at professional meetings, conducted applied economic research and made several invited community presentation on economic topics. His recent research has focussed on measuring asymetry in economic relationships and in analyzing perceptions of economic impact from prison sitings in rural communities. Dr. Hannan was President of the Pennsylvania Economic Association in 2004-2005 and continues to serve on the PEA Board of Directors. Dr. Hannan also received Edinboro University′s 2001 Advisor of the Year Award, and was recently honored as Reviewer of the Year by the Journal of the Northeastern Association of Business, Economics and Technology. Dr. Hannan also serves as a mentor and site reviewer for the Accredidation Council of Business Schools & Programs.
Michel Terraza is a science Professor of economics at Montpellier I University. He applied this decomposed measure when studying the wages inequalities in the Languedoc-Roussillon region (see the bibliography). He did it in collaboration with Françoise Seyte (Associate Professor) and Stéphane Mussard (Assistant Professor).
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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