This paper discusses the forecasting performance of alternative factor models based on a large panel of quarterly time series for the german economy. One model extracts factors by static principals components analysis, the other is based on dynamic principal components obtained using frequency...

We produce predictions of Norwegian GDP. To this end, we estimate a Bayesian Dynamic Factor model on a panel of 14 variables (all followed closely by market operators) ranging from 1990 to 2011. By means of a pseudo real-time exercise we show that the Bayesian Dynamic Factor Model performs well...

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...

This paper discusses the forecasting performance of alternative factor models based on a large panel of quarterly time series for the German economy. One model extracts factors by static principal components analysis; the second model is based on dynamic principal components obtained using...

This paper studies the pathways for the propagation of shocks across G7 and major Asia-Pacific countries using multi-horizon forecasts of real GDP growth from 1995 to 2017. We show that if the forecasts are efficient in the long run, results obtained using the forecasts are comparable to those...

This paper describes a dynamic factor model for the Maltese economy. The model mainly serves as a tool to timely provide the Central Bank of Malta with nowcasts as well as short-term forecasts of the growth rate of the real gross domestic product, which in turn are used as an input in the...