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Unobserved components and time series econometrics

Author: S J Koopman; Neil Shephard
Publisher: Oxford : Oxford University Press, 2015.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:
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  Read more...
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: S J Koopman; Neil Shephard
ISBN: 9780199683666 0199683662
OCLC Number: 913853179
Description: xvii, 370 pages : illustrations ; 24 cm
Contents: 1. Introduction ; 2. The Development of a Time Series Methodology: from Recursive Residuals to Dynamic Conditional Score Models ; 3. A State-Dependent Model for Inflation Forecasting ; 4. Measuring the Tracking Error of Exchange Traded Funds ; 5. Measuring the Dynamics of Global Business Cycle Connectedness ; 6. Inferring and Predicting Global Temperature Trends ; 7. Forecasting the Boat Race ; 8. Tests for Serial Dependence in Static, Non-Gaussian Factor Models ; 9. Inference for Models with Asymmetric alpha-Stable Noise Processes ; 10. Martingale Unobserved Component Models ; 11. More is Not Always Better: Kalman Filtering in Dynamic Factor Models ; 12. On Detecting End-of-Sample Instabilities ; 13. Improved Frequentist Prediction Intervals for Autoregressive Models by Simulation ; 14. The Superiority of the LM Test in a Class of Econometric Models Where the Wald Test Performs Poorly ; 15. Generalised Linear Spectral Models
Other Titles: Unobserved components & time series econometrics
Responsibility: edited by Siem Jan Koopman and Neil Shephard.
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Abstract:

Presents original and up-to-date studies in unobserved components (UC) time series models from both theoretical and methodological perspectives.  Read more...

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