We examine the implications of treating seasonality as an unobserved component which changes slowly over time. This approach simplifies the specification of dynamic relationships by separating non-seasonal from seasonal factors. We illustrate this approach using the consumption model of Davidson...

Trends and cyclical components in economic time series are modeled in a Bayesian framework. This enables prior notions about the duration of cycles to be used, while the generalized class of stochastic cycles employed allows the possibility of relatively smooth cycles being extracted. The...

This paper looks at unobserved components models and examines the implied weighting pat- terns for signal extraction. There are three main themes. The first is the implications of correlated disturbances driving the components, especially those cases in which the correlation is perfect. The...

Cyclical components in economic time series are analysed in a Bayesian framework, thereby allowing prior notions about periodicity to be used. The method is based on a general class of unobserved component models that encompasses a range of dynamics in the stochastic cycle. This allows for...

A new class of model-based filters for extracting trends and cycles in economic time series is presented. These low pass and band pass filters are derived in a mutually consistent manner as the joint solution to a signal extraction problem in an unobserved components model. The resulting trends...

Cyclical components in economic time series are analysed in a Bayesian framework, thereby allowing prior notions about periodicity to be used. The method is based on a general class of unobserved component models that allow relatively smooth cycles to be extracted. Posterior densities of...