Using a novel rich dataset at the regional level, this paper provides new empirical evidence on the fiscal transmission mechanism in the Eurozone. Our baseline estimates reveal a government spending relative output multiplier of 2.9, an employment multiplier of 1.9, and a cost per job created of...

I propose a novel approach to uncover business cycle reports' priorities and relate them to economic fluctuations. To this end, I leverage quantitative business-cycle forecasts published by leading German economic research institutes since 1970 to estimate the proportions of latent topics in...

This paper evaluates whether publicly available daily news lead texts help nowcasting Swiss GDP growth. I collect titles and lead texts from three Swiss newspapers and calculate text-based indicators for various economic concepts. A composite indicator calculated from these indicators is highly...

This paper applies machine learning to forecast business cycles in the German economy using a high-dimensional dataset with 73 indicators, primarily from the OECD Main Economic Indicator Database, covering a time period from 1973 to 2023. Sequential Floating Forward Selection (SFFS) is used to...

We use Dynamic Bayesian networks to classify business cycle phases. We compare classifiers generated by learning the Dynamic Bayesian network structure on different sets of admissible network structures. Included are sets of network structures of the Tree Augmented Naive Bayes (TAN) classifiers...