In this paper we assess the information content of seven widely cited early indicators for the euro area with respect to forecasting area-wide industrial production. To this end, we use various tests that are designed to compare competing forecast models. In addition to the standard...

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...

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...

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...

This paper looks into the 'fine print' of boosting for economic forecasting. By using German industrial production for the period from 1996 to 2014 and a data set consisting of 175 monthly indicators, we evaluate which indicators get selected by the boosting algorithm over time and four...

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...