The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

The use of large datasets for macroeconomic forecasting has received a great deal of interest recently. Boosting is one possible method of using high-dimensional data for this purpose. It is a stage-wise additive modelling procedure, which, in a linear specification, becomes a variable selection...

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...

Expectations are at the centre of modern macroeconomic theory and policymakers. In this paper, we examine the predictive ability and the consistency properties of macroeconomic expectations using data of the European Central Bank (ECB) Survey of Professional Forecasters (SPF)

This paper analyses the real-time forecasting performance of the New Keynesian DSGE model of Galí, Smets, and Wouters (2012) estimated on euro area data. It investigates to what extent forecasts of inflation, GDP growth and unemployment by professional forecasters improve the forecasting...

We assess the effectiveness of the forward guidance undertaken by European Central Bank using a standard medium-scale DSGE model à la Smets and Wouters (2007). Exploiting data on expectations from surveys, we show that incorporating expectations should be crucial in performance evaluation of...