See the article in <I>Mathematics and Computers in Simulation (MATCOM)</I> (2013). Volume 93(c), pages 9-18.<P> Many macroeconomic forecasts and forecast updates like those from IMF and OECD typically involve both a model component, which is replicable, as well as intuition, which is non-replicable....</p></i>

We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...

This discussion paper led to the article with the same title in 'Social Choice and Welfare' (2014), 43, 173-194.<P> We consider the problem of sharing water among agents located along a river. Each agent has quasi-linear preferences over river water and money, where the benefit of consuming an...</p>

This discussion paper resulted in a publication in the 'SIAM Journal on Optimization', 2006, 16, 854-870. <P> It is well known that an upper semi-continuous compact- and convex-valued mapping fi from a nonempty compact and convex set X to the Euclidean space of which X is a subset has at least one...</p>

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>

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 multivariate analysis of a panel of economic and financial time series with mixed frequencies is a challenging problem. The standard solution is to analyze the mix of monthly and quarterly time series jointly by means of a multivariate dynamic model with a monthly time index: artificial...

We present a model for hourly electricity load forecasting based on stochastically time-varying processes that are designed to account for changes in customer behaviour and in utility production efficiencies. The model is periodic: it consists of different equations and different parameters for...

This version has replaced the version of January 30, 2012.<P> A successful construction of an importance density for nonlinear non-Gaussian state space models is crucial when Monte Carlo simulation methods are used for likelihood evaluation, signal extraction of dynamic latent factors and...</p>