Characterizing Interdependencies of Multiple Time Series

Yuzo Hosoya, Professor Emeritus, Tohoku UniversityKosuke Oya, Osaka UniversityTaro Takimoto, Kyushu UniversityRyo Kinoshita, Tokyo Keizai University

• 1: Introduction to statistical causal analysis.-  2: Measures of one-way effect, reciprocity and association.- 3: Partial measures of interdependence.- 4: Inference based on the vector autoregressive and moving average model.- 5: Inference on change in causality measures.- 6: Simulation performance of estimation methods.- 7: Empirical analysis of macroeconomic series.- 8: Empirical analysis of change in causality measures.- 9: Conclusion.- Appendix.- References.- Index.

“This book is concerned with concepts and methods for characterizing interdependencies of multiple time series in the frequency domain. … the authors have written an interesting and high valuable book, with emphasis on the practical analysis of time series. At the end of each chapter, a short list of references is provided and this will help a reader wishing to pursue this area further.” (Apostolos Batsidis, zbMATH 1387.62003, 2018)“This is very nicely written book on interdependence measures between time series. The exposition is clear and the book is enriched with various examples and applications. Basic knowledge of time-series analysis is assumed. The book should trun out to be very useful for statisticians, econometricians or time-series analysts.” (Alexander M. Lindner, Mathematical Reviews, February, 2019)