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  • Search: subject:"Unobserved components time series model"
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Year of publication
Subject
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Kalman filter 16 State space model 11 Zeitreihenanalyse 9 Zustandsraummodell 9 unobserved components time series model 9 Unobserved components time series model 8 Theorie 6 Time series analysis 6 Konjunktur 5 Schätzung 5 USA 5 Band-pass filter 4 Bandpass filter 4 Coincident indicator 4 Common stochastic variance 4 Dynamic factor model 4 Frequency-specific model 4 Leading indicator 4 Markov chain Monte Carlo 4 Phase shift 4 Revisions 4 Stochastic volatility 4 Stochastischer Prozess 4 Theory 4 Trend-cycle decomposition 4 Unobserved Components Time Series Model 4 model-based seasonal adjustment 4 Business cycle 3 EU-Staaten 3 Estimation 3 Eurozone 3 Stochastic process 3 United States 3 Volatility 3 Volatilität 3 Dekompositionsverfahren 2 EU countries 2 Euro area 2 Importance Sampling 2 Inflation 2
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Online availability
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Free 22
Type of publication
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Book / Working Paper 22
Type of publication (narrower categories)
All
Working Paper 13 Arbeitspapier 6 Graue Literatur 6 Non-commercial literature 6
Language
All
English 13 Undetermined 9
Author
All
Koopman, Siem Jan 22 Hindrayanto, Irma 6 Aston, John A.D. 4 Bos, Charles S. 4 Creal, Drew 4 Ooms, Marius 4 Zivot, Eric 4 Rua, Antonio 3 Azevedo, Joao Valle e 2 Brauning, Falk 2 Galati, Gabriele 2 Li, Mengheng 2 Vlekke, Marente 2 Azevedo, João Valle e 1 Rua, António 1 e Azevedo, Joao Valle 1
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Institution
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Tinbergen Instituut 5 Tinbergen Institute 4
Published in...
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Tinbergen Institute Discussion Papers 9 Tinbergen Institute Discussion Paper 7 Discussion paper / Tinbergen Institute 6
Source
All
RePEc 9 EconStor 7 ECONIS (ZBW) 6
Showing 1 - 10 of 22
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Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction
Li, Mengheng; Koopman, Siem Jan - 2018
We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...
Persistent link: https://www.econbiz.de/10011819542
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Unobserved components with stochastic volatility in U.S. inflation : estimation and signal extraction
Li, Mengheng; Koopman, Siem Jan - 2018
We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...
Persistent link: https://www.econbiz.de/10011809984
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Measuring Financial Cycles in a Model-Based Analysis: Empirical Evidence for the United States and the Euro Area
Galati, Gabriele; Hindrayanto, Irma; Koopman, Siem Jan; … - 2016
We adopt an unobserved components time series model to extract financial cycles for the United States and the five …
Persistent link: https://www.econbiz.de/10011526106
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Measuring financial cycles in a model-based analysis : empirical evidence for the United States and the euro area
Galati, Gabriele; Hindrayanto, Irma; Koopman, Siem Jan; … - 2016
We adopt an unobserved components time series model to extract financial cycles for the United States and the five …
Persistent link: https://www.econbiz.de/10011456728
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Forecasting Macroeconomic Variables using Collapsed Dynamic Factor Analysis
Brauning, Falk; Koopman, Siem Jan - 2012
indicators using a multivariate unobserved components time series model. When the key economic variables are observed at a low …
Persistent link: https://www.econbiz.de/10010326452
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Forecasting Macroeconomic Variables using Collapsed Dynamic Factor Analysis
Brauning, Falk; Koopman, Siem Jan - Tinbergen Instituut - 2012
macroeconomic indicators using a multivariate unobserved components time series model. When the key economic variables are observed …
Persistent link: https://www.econbiz.de/10011257430
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Modeling Trigonometric Seasonal Components for Monthly Economic Time Series
Hindrayanto, Irma; Aston, John A.D.; Koopman, Siem Jan; … - 2010
The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...
Persistent link: https://www.econbiz.de/10010325881
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Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production
Bos, Charles S.; Koopman, Siem Jan - 2010
Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...
Persistent link: https://www.econbiz.de/10010326058
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Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production
Bos, Charles S.; Koopman, Siem Jan - Tinbergen Instituut - 2010
Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...
Persistent link: https://www.econbiz.de/10011256745
Saved in:
Cover Image
Modeling Trigonometric Seasonal Components for Monthly Economic Time Series
Hindrayanto, Irma; Aston, John A.D.; Koopman, Siem Jan; … - Tinbergen Institute - 2010
The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...
Persistent link: https://www.econbiz.de/10008838551
Saved in:
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