A practice that has become widespread and widely endorsed is that of evaluating forecasts of financial variability obtained from discrete time models by comparing them with high-frequency ex post estimates (e.g. realised volatility) based on continuous time theory. In explanatory financial...

A practice that has become widespread and widely endorsed is that of evaluating forecasts of financial variability obtained from discrete time models by comparing them with high-frequency ex post estimates (e.g. realised volatility) based on continuous time theory. In explanatory financial...

This study presents a model that delivers more accurate forecasts of the revised rather initial estimates of the quarterly GDP growth rate in Switzerland during the period of the recent financial crisis. The key explanation to our findings is that our model, capitalizing on the information...

Recent articles suggest that a Bayesian vector autoregression (BVAR) with shrinkage is a good forecast device even when the number of variables is large. In this paper we evaluate different variants of the BVAR with respect to their forecast accuracy for euro area real GDP growth and HICP...

This paper investigates the accuracy of point and density forecasts of four DSGE models for inflation, output growth and the federal funds rate. Model parameters are estimated and forecasts are derived successively from historical U.S. data vintages synchronized with the Fed’s Greenbook...

This paper documents GDPNow, a "nowcasting" model for gross domestic product (GDP) growth that synthesizes the "bridge equation" approach relating GDP subcomponents to monthly source data with the factor model approach used by Giannone, Reichlin, and Small (2008). The GDPNow model forecasts GDP...

We compare forecasts from different adaptive learning algorithms and calibrations applied to US real-time data on inflation and growth. We find that the Least Squares with constant gains adjusted to match (past) survey forecasts provides the best overall performance both in terms of forecasting...

Using the Consensus Economics dataset with individual expert forecasts from G7 countries we investigate determinants of disagreement (crosssectional dispersion of forecasts) about six key economic indicators. Disagreement about real variables (GDP, consumption, investment and unemployment) has a...

This paper derives new theoretical results for forecasting with Global VAR (GVAR) models. It is shown that the presence of a strong unobserved common factor can lead to an undeter-mined GVAR model. To solve this problem, we propose augmenting the GVAR with additional proxy equations for the...

In this paper we present a methodology which can help to improve the assessment of the current economic situation. We propose an approach which combines multivariate single equations to forecast the monthly growth rate of industrial production with a density forecast. This allows to estimate the...