This discussion paper resulted in an article in the <I>Oxford Bulletin of Economics and Statistics</I> (2008). Vol. 70 issue 1, pages 23-51.<P> This paper investigates business cycle relations among different economies in theEuro area. Cyclical dynamics are explicitly modelled as part of a time series...</p></i>

We consider likelihood inference and state estimation by means of importance sampling for state space models with a nonlinear non-Gaussian observation y ~ p(y|alpha) and a linear Gaussian state alpha ~ p(alpha). The importance density is chosen to be the Laplace approximation of the smoothing...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...

This discussion paper led to an article in <I>Statistica Neerlandica</I> (2003). Vol. 57, issue 4, pages 439-469.<P> The linear Gaussian state space model for which the common variance istreated as a stochastic time-varying variable is considered for themodelling of economic time series. The focus of this...</p></i>

In this paper we investigate whether the dynamic properties of the U.S. business cycle have changed in the last fifty years. For this purpose we develop a flexible business cycle indicator that is constructed from a moderate set of macroeconomic time series. The coincident economic indicator is...

This discussion paper led to an article in the <I>Journal of Time Series Analysis</I> (2010). Vol. 31, pages 407-414.<P> State space models with nonstationary processes and fixed regression effects require a state vector with diffuse initial conditions. Different likelihood functions can be adopted for...</p></i>

This discussion paper led to an article in the <I>Journal of Business and Economic Statistics</I> (2008). Vol. 26, issue 4, pages 510-525.<p> We model 1981–2002 annual US default frequencies for a panel of firms in different rating and age classes. The data is decomposed into a systematic and...</p></i>

The linear Gaussian state space model for which the common variance is treated as a stochastic time-varying variable is considered for the modelling of economic time series. The focus of this paper is on the simultaneous estimation of parameters related to the stochastic processes of the mean...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...

This discussion paper has resulted in a publication in the A rated journal 'Journal of Business and Economic Statistics'.<p>