We investigate the prediction of Italian industrial production. We first specify a model based on electricity consumption; we show that the cubic trend in such a model mostly captures the evolution over time of the electricity coefficient, which can be well approximated by a smooth transition...

This paper proposes the use of Bayesian model averaging (BMA) as a tool to select the predictors' set for bridge models. BMA is a computationally feasible method that allows us to explore the model space even in the presence of a large set of candidate predictors. We test the performance of BMA...

In this paper we develop a mixed frequency dynamic factor model featuring stochastic shifts in the volatility of both the latent common factor and the idiosyncratic components. We take a Bayesian perspective and derive a Gibbs sampler to obtain the posterior density of the model parameters. This...

The prominent role assigned to money by the ECB has been the subject of an intense debate because of the declining predictive power of the monetary aggregate M3 for inflation in recent years. This paper reassesses the information content of monetary analysis for future inflation using dynamic...

The aim of the present work is to obtain short-term predictions of the monthly volume of the industrial production of the euro area. Preliminary information on the behaviour of this variable is needed, since the index is released with a lag of about two months. A model based on the US industrial...