Different studies provide surprisingly a large variety of controversial conclusions about the forecasting power of an indicator, even when it is supposed to forecast the same time series. In this study we aim to provide a thorough overview of linear forecasting techniques and draw conclusions...

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...

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...

Der Bereich Dienstleistungen macht mehr als 70% der deutschen Bruttowertschöpfung aus, jedoch ist die Konjunkturanalyse und -prognose in diesem Wirtschaftsbereich noch sehr unterentwickelt. Ein Blick in die Literatur zeigt, dass die Forschung hier noch am Anfang steht und sich bisher diesem...

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...