Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/87073
Authors: 
Bos, Charles S.
Koopman, Siem Jan
Year of Publication: 
2010
Series/Report no.: 
Tinbergen Institute Discussion Paper 10-017/4
Abstract: 
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 depending on dynamic stochastic processes can be sufficiently robust against changes in their dynamic properties. We further show that the implementation of the treatment is relatively straightforward. An illustration is given for monthly U.S. Industrial Production. The empirical results including estimates of time-varying means and variances are discussed in detail.
Subjects: 
Common stochastic variance
Kalman filter
State space model
unobserved components time series model
JEL: 
C22
C51
C53
E23
Document Type: 
Working Paper

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