9780199683666-0199683662-Unobserved Components and Time Series Econometrics

Unobserved Components and Time Series Econometrics

ISBN-13: 9780199683666
ISBN-10: 0199683662
Edition: 1
Author: Siem Jan Koopman, Neil Shephard
Publication date: 2016
Publisher: Oxford University Press
Format: Hardcover 384 pages
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Book details

ISBN-13: 9780199683666
ISBN-10: 0199683662
Edition: 1
Author: Siem Jan Koopman, Neil Shephard
Publication date: 2016
Publisher: Oxford University Press
Format: Hardcover 384 pages

Summary

Unobserved Components and Time Series Econometrics (ISBN-13: 9780199683666 and ISBN-10: 0199683662), written by authors Siem Jan Koopman, Neil Shephard, was published by Oxford University Press in 2016. With an overall rating of 4.5 stars, it's a notable title among other books. You can easily purchase or rent Unobserved Components and Time Series Econometrics (Hardcover) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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.
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