This paper proposes a new method of forecasting euro area quarterly real GDP that uses areawide 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...

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...

This paper applies component-wise boosting to the topic of regional economic forecasting. Component-wise boosting is a pre-selection algorithm of indicators for forecasting. By using unique quarterly real gross domestic product data for two German states (the Free State of Saxony and...

Over the last decade, the topic of regional economic forecasting has become increasingly prevalent in academic literature. The most striking problem in this context is data availability at a regional level. However, considerable methodological improvements have been made to address this problem....

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 robustness of determinants of economic growth in the presence of model uncertainty, parameter heterogeneity and outliers. The robust model averaging approach introduced in the paper uses a flexible and parsimonious mixture modeling that allows for fat-tailed errors...

Prediction markets - markets used to forecast future events - have been used to accurately forecast the outcome of political contests, sporting events, and, occasionally, economic outcomes. This chapter summarizes the latest research on prediction markets in order to further their utilization by...