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.
My research interests are at the intersection of causal inference and machine learning to answer questions in empirical economics. In particular I am currently working on the estimation of average and heterogeneous treatment effects. See my research section for more details.
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
June 2019: Presenting our paper that reviews and compares estimators for the estimation of heterogeneous causal effects at the BGSE Summer Forum on “Machine Learning for Economics” in Barcelona and the annual conference of the IAAE in Nikosia
23.05.2018: Pre-print of “A Double Machine Learning Approach to Estimate the Effects of Musical Practice on Student’s Skills” available on arXiv, ResearchGate, and as an IZA Discussion Paper, the accompanying R package dmlmt is available on GitHub
24.04.2018: Oldest chapter of the thesis “Work Hour Mismatch and Job Mobility: Adjustment Channels and Resolution Rates”, with Steffen Otterbach, accepted and published online at Economic Inquiry
06.03.2018: Public defense of my thesis “Essays in Empirical Economics using Microeconometric and Causal Machine Learning Methods” (slides)