I am an Assistant Professor of Econometrics at the Swiss Institute for Empirical Economic Research of the University of St. Gallen and part of the Data and Method Consulting that advices students and faculty regarding their empirical work. I am moving to a tenure track position at the University of Tübingen in August 2022.
My research interests are at the intersection of causal inference and machine learning to answer questions in empirical, mostly labor, economics. In particular I am currently working on the estimation of average and heterogeneous treatment effects as well as optimal policy estimation. See my research section or Google Scholar for more details.
February 2022: I am excited to start a tenure track position at the University of Tübingen in August 2022.
October 2021: New working paper with Phillip Heiler called “Effect or Treatment Heterogeneity? Policy Evaluation with Aggregated and Disaggregated Treatments” available on arXiv
June 2021: Teaching PhD course in Supervised and Causal Machine Learning at the University of Hamburg
March 2021: Teaching PhD course in Causal Machine Learning at the GESIS Leibniz Institute for the Social Sciences
January 2021: Paper “Machine Learning Estimation of Heterogeneous Causal Effects: Empirical Monte Carlo Evidence”, with Michael Lechner and Anthony Strittmatter published at The Econometrics Journal
January 2021: Single-authored paper “A Double Machine Learning Approach to Estimate the Effects of Musical Practice on Student’s Skills” published at the Journal of the Royal Statistical Society: Series A
October 2020: Update of “Double Machine Learning based Program Evaluation under Unconfoundedness” now with R-package causalDML and a replication notebook
September 2020: “For Better or Worse? - The Effects of Physical Education on Child Development”, with Michael Lechner and Anne K. Reimers, published at Labour Economics
March 2020: New preprint “Double Machine Learning based Program Evaluation under Unconfoundedness” available on arXiv
January 2020: Our first causal machine learning paper “Heterogeneous Employment Effects of Job Search Programmes: A Machine Learning Approach”, with Michael Lechner and Anthony Strittmatter got accepted at the Journal of Human Resources
January 2020: Causal Machine Learning Workshop in St. Gallen sponsored by the National Research Programme 75 “Big Data” (you find the program here )
CALL FOR PAPERS: Workshop on Causal Machine Learning, January 20-21, 2019 in St. Gallen, Switzerland; sponsored by the National Research Programme 75 “Big Data”; organized jointly with Michael Lechner and Anthony Strittmatter