Arbeitspapier
Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment
This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are introduced for exact maximum likelihood estimation, component estimation and forecasting. Identification issues are considered and a novel periodic version of the stochastic cycle component is presented. In the empirical illustration, the model is applied to postwar monthly US unemployment series and we discover a significantly periodic cycle. Furthermore, a comparison is made between the performance of the periodic unobserved components time series model and a periodic seasonal autoregressive integrated moving average model. Moreover, we introduce a new method to estimate the latter model.
- Language
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Englisch
- Bibliographic citation
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Series: Tinbergen Institute Discussion Paper ; No. 06-101/4
- Classification
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Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Model Construction and Estimation
Business Fluctuations; Cycles
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Subject
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Unobserved component models
state space methods
seasonal adjustment
time–varying parameters
forecasting
- Event
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Geistige Schöpfung
- (who)
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Koopman, Siem Jan
Ooms, Marius
Hindrayanto, Irma
- Event
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Veröffentlichung
- (who)
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Tinbergen Institute
- (where)
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Amsterdam and Rotterdam
- (when)
-
2006
- Handle
- Last update
-
10.03.2025, 11:44 AM CET
Data provider
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Koopman, Siem Jan
- Ooms, Marius
- Hindrayanto, Irma
- Tinbergen Institute
Time of origin
- 2006
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