Many countries consider the lifting of restrictions of social contacts (RSC). We quantify the effects of RSC for Germany. We initially employ a purely statistical approach to predicting prevalence of COVID19 if RSC were upheld after April 20. We employ these findings and feed them into our...

This paper provides an ex-post analysis of football matches’ contribution to the spread of COVID-19 during Germany’s second infection wave in summer and autumn 2020. We find slightly positive effects from occurring professional football matches on newly registered cases of the virus in the...

This paper examines the relation between crowd support and home advantage in professional football in making use of a unique “natural experiment” induced by restrictions due to the Corona pandemic: so-called ghost games in the top three German football divisions during the 2019/2020 season....

This paper examines the relation between crowd support and home advantage in professional soccer. For that purpose, we make use of a unique "natural experiment": so-called ghost games in the three top divisions of German professional soccer during the Corona pandemic. We find that there is a...

This paper examines the relation between crowd support and home advantage in professional football in making use of a unique “natural experiment” induced by restrictions due to the Corona pandemic: so-called ghost games in the top three German football divisions during the 2019/2020 season....

In this paper we develop a small open economy model explaining the joint determination of output, inflation, interest rates, unemployment and the exchange rate in a multi-country framework. Our model – the Halle Economic Projection Model (HEPM) – is closely related to studies recently...

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 study the forecasting performance of three alternative large scale approaches using a dataset for Germany that consists of 123 variables in quarterly frequency. These three approaches handle the dimensionality problem evoked by such a large dataset by aggregating information, yet on different...

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...

We study the forecasting performance of three alternative large scale approaches for German key macroeconomic variables using a dataset that consists of 123 variables in quarterly frequency. These three approaches handle the dimensionality problem evoked by such a large dataset by aggregating...