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 analysis investigates the predictive power of the most important leading indicators for the German economy, which are provided by the ifo Institute and IHS Markit. We conduct an out-of-sample, real-time forecast experiment for growth of gross domestic product and growth of gross value added...

Comprehensive and international comparable leading indicators across countries and continents are rare. In this paper, we use a free and instantaneous available source of leading indicators, the ifo World Economic Survey (WES), to forecast growth of Gross Domestic Product (GDP) in 44 countries...

The ifo Institute is Germany’s largest business survey provider, with the ifo Business Climate Germany as one of the most important leading indicators for gross domestic product. However, the ifo Business Survey is not solely limited to the Business Climate and also delivers a multitude of...

In this paper, we study the predictive power of electricity consumption data for regional economic activity. Using unique weekly and monthly electricity consumption data for the second-largest German state, the Free State of Bavaria, we conduct a pseudo out-of-sample forecasting experiment for...

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...