Research agenda
A vital aspect of the digital transformation is the exploration and analysis of big data, which are often not amenable to standard econometric models. In a series of publications, we propose machine learning techniques that can be used for these purposes. The findings of these projects have theoretical implications for research on the use of machine learning in econometrics, but also practical applications for large companies and (smaller) family-owned firms.
Current research projects
Learning from high-dimensional, heterogeneous data: Machine learning methods in econometrics, supported by the German Research Foundation (DFG), 2021-2024.
In this project we work with methods from Machine Learning and Artificial Intelligence in microeconomic applications to estimate heterogeneous causal effects and to predict individual and firm behaviour.