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...

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...

This paper has been accepted for publication in the 'Review of Economics and Statistics'.We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be...

We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and Monte Carlo integration methods. Our methodology explores the idea that...

The evidence on the implications of transport for regionaleconomic and political integration is mixed. This is not surprisingsince transport is one element of a complex web of factors thatdetermine the extent to which spatial areas become integrated.There are also good reasons to expect the...

This paper addresses the issue of technogenesis and its geographical pattern. It aims to offer both a general analysis framework and a test on innovation data from several European cities. This framework is mainly built on the product life-cycle and the incubation approach. On the basis of this...