This discussion paper resulted in a publication in <I>Computational Statistics & Data Analysis</I> (2006). Vol. 51, issue 2, pages 885-903.<P> We explore a periodic analysis in the context of unobserved components time series models that decompose time series into components of interest such as trend and...</p></i>

We propose a new Markov switching model with time varying probabilities for the transitions. The novelty of our model is that the transition probabilities evolve over time by means of an observation driven model. The innovation of the time varying probability is generated by the score of the...

This discussion paper led to a publication in the <I>International Journal of Forecasting</I> (2013). Vol. 29, pages 676-694.<P> We extend the class of dynamic factor yield curve models for the inclusion of macro-economic factors. We benefit from recent developments in the dynamic factor literature for...</p></i>

We introduce a dynamic statistical model for Skellam distributed random variables. The Skellam distribution can be obtained by taking differences between two Poisson distributed random variables. We treat cases where observations are measured over time and where possible serial correlation is...

We adopt a structural time series analysis to investigate the impact of parole abolition and sentence reform in Virginia on reported crime rates. The Commonwealth of Virginia abolished parole and reformed sentencing for all felony offences committed on or after January 1, 1995. To examine the...

We propose a novel econometric model for estimating and forecasting cross-sections of time-varying conditional default probabilities. The model captures the systematic variation in corporate default counts across e.g. rating and industry groups by using dynamic factors from a large panel of...

A growing number of empirical studies provides evidence that dynamic properties of macroeconomic time series have been changing over time. Model-based procedures for the measurement of business cycles should therefore allow model parameters to adapt over time. In this paper the time dependencies...

We study the performance of two analytical methods and one simulation method for computing in-sample confidence bounds for time-varying parameters. These in-sample bounds are designed to reflect parameter uncertainty in the associated filter. They are applicable to the complete class of...

This discussion paper led to an article in the <I>Statistica Neerlandica</I> (2008). Vol. 62, issue 1, pages 104-130.<P> We model panel data of crime careers of juveniles from a Dutch Judicial Juvenile Institution. The data are decomposed into a systematic and an individual-specific component, of which...</p></i>

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...