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This volume presents original and up-to-date studies in unobserved components (UC) time series models from both theoretical and methodological perspectives. It also presents empirical studies where the UC time series methodology is adopted. Drawing on the intellectual influence of Andrew Harvey, the work covers three main topics: the theory and methodology for unobserved components time series models; applications of unobserved components time series models; and time series econometrics and estimation and testing. These types of time series models have seen wide application in economics, statistics, finance, climate change, engineering, biostatistics, and sports statistics.The volume effectively provides a key review into relevant research directions for UC time series econometrics and will be of interest to econometricians, time series statisticians, and practitioners (government, central banks, business) in time series analysis and forecasting, as well to researchers and graduate students in statistics, econometrics, and engineering.
This volume investigates the theoretical foundations and practical applications of unobserved components (UC) time series models within the field of econometrics. The authors, Neil Shephard and Siem Jan Koopman, synthesize research influenced by Andrew Harvey to provide a rigorous framework for modeling non-observable variables. By bridging the gap between abstract statistical theory and empirical methodology, the text serves as a comprehensive reference for analyzing complex data structures in economics and related quantitative disciplines.
What You Will Find
Experts recognize this volume as a significant contribution to the literature on UC time series models, particularly for its integration of theoretical rigor and applied methodology. Readers frequently note the technical density of the prose, making it a primary resource for graduate students and professional econometricians seeking to advance their analytical capabilities.
Page Count:
384
Publication Date:
2016-01-19
Publisher:
Oxford University Press
ISBN-10:
0199683662
ISBN-13:
9780199683666
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