We study the impact of diverse beliefs on conduct of monetary policy. We use a New Keynesian Model solved with a quadratic approximation. Aggregation renders the belief distribution an aggregate state variable. Diverse expectations change standard results about a smooth trade-off between...

We study the impact of diverse beliefs on conduct of monetary policy. We use a New Keynesian Model solved with a quadratic approximation. Aggregation renders the belief distribution an aggregate state variable. Diverse expectations change standard results about a smooth trade-off between...

We develop a non-linear forecast combination rule based on copulas that incorporate the dynamic interaction between individual predictors. This approach is optimal in the sense that the resulting combined forecast produces the highest discriminatory power as measured by the receiver operating...

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...

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...

In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a unique data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden-Württemberg) and Eastern Germany. We overcome the problem of a...

This paper proposes a new method of forecasting euro area quarterly real GDP that uses area-wide indicators, which are derived by optimally pooling the information contained in national indicator series. Following the ideas of predictive modeling, we construct the area-wide indicators by...

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...

We tackle the nowcasting problem at the regional level using a large set of indicators (regional, national and international) for the years 1998 to 2013. We explicitly use the ragged-edge data structure and consider the different information sets faced by a regional forecaster within each...

This paper explores a range of different forecast methods for Brent oil prices and analyses their performance relative to oil futures and the random walk over the period 1995Q1-2015Q2, including periods of stable, upwardly trending and rapidly dropping oil prices. None of the individual methods...