Yuzo Hosoya, Kosuke Oya, Taro Takimoto, Ryo Kinoshita

Characterizing Interdependencies of Multiple Time Series (eBook, PDF)

Theory and Applications

• Format: PDF

Produktbeschreibung

Presents an approach to characterizing the interdependencies of multivariate time series by means of the basic concept of the one-way effect

Shows how the third-series effect is eliminated with least causal distortion, introducing partial measures of the one-way effect, reciprocity, and association

Illustrates the proposed causal characterization by means of empirical applications to real data sets of the US macroeconomy and Japan's financial economy

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 133
• Erscheinungstermin: 26. Oktober 2017
• Englisch
• ISBN-13: 9789811064364
• Artikelnr.: 53064174

Autorenporträt

Yuzo Hosoya, Professor Emeritus, Tohoku University

Kosuke Oya, Osaka University

Taro Takimoto, Kyushu University

Ryo Kinoshita, Tokyo Keizai University

Inhaltsangabe

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.

Rezensionen

"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)