Characterizing Interdependencies of Multiple Time Series Theory and Applications /

• Main Authors: Hosoya, Yuzo (Author), Oya, Kosuke (Author), Takimoto, Taro (Author), Kinoshita, Ryo (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2017.
• Series: SpringerBriefs in Statistics,
• Subjects: Statistics.; Statistical Theory and Methods.; Statistics for Life Sciences, Medicine, Health Sciences.; Statistics for Business/Economics/Mathematical Finance/Insurance.; Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.; Statistics and Computing/Statistics Programs.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.

This book introduces academic researchers and professionals to the basic concepts and methods for characterizing interdependencies of multiple time series in the frequency domain. Detecting causal directions between a pair of time series and the extent of their effects, as well as testing the non ex...

Table of Contents:

• 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.