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...

The paper investigates the sources of macroeconomic forecast errors in Germany. The predictions of the so-called "six leading" research institutes are analyzed. The forecast errors are discussed within an aggregate demand/supply scheme. Structural Vector Autoregressive Models are estimated to...

We propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several specifications of multivariate time-varying weights are introduced with a particular focus on weight dynamics driven...

This note considers the reliability of Federal Reserve Board staff estimates of the output gap after the mid-1990s, and examines the usefulness of these estimates for inflation forecasting. Over this period, we find that the Federal Reserve's output gap is more reliably estimated in real time...

In this paper we argue that future inflation in an economy depends on the way people perceive current inflation, their inflation sentiment. We construct some simple measures of inflation sentiment which capture whether price acceleration is shared by many components of the CPI basket. In a...

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In the empirical application, we forecast U.S. business cycle turning points with state-level employment data. We find that forecasts...

This paper introduces new weighting schemes for model averaging when one is interested in combining discrete forecasts from competing Markov-switching models. In particular, we extend two existing classes of combination schemes – Bayesian (static) model averaging and dynamic model averaging...

This paper analyzes the forecasting performance of financial market data in comparison to other indicator groups to forecast industrial production for Germany and the US. We focus on single-indicator models and various weighting schemes and evaluate the forecasting performance using a...

Facing several economic and financial uncertainties, assessing accurately global economic conditions is a great challenge for economists. The International Monetary Fund proposes within its periodic World Economic Outlook report a measure of the global GDP annual growth, that is often considered...

We compare real-time density forecasts for the euro area using three DSGE models. The benchmark is the Smets-Wouters model and its forecasts of real GDP growth and inflation are compared with those from two extensions. The first adds financial frictions and expands the observables to include a...