Occassionally, I teach a Ph.D. course in Computational Data Analytics (CDA) for economic and business students (partly together with Helge Liebert). The course typically emphasize both theory and practical computation.

Selected topics:

• Machine Learning for Prediction (R-tutorial: Used Cars)

• Web-Scraping (R-tutorials: Wikipedia, Kiva)

• Text Analysis (R-tutorial: Kiva)

• Causal Machine Learning (R-tutorial: Job Corps)

• Optimal Policy Learning (R-tutorial: Charitable Givings)

The R-tutorials can be downloaded in HTML. Alternatively, an interactive version of the R-tutorials is provided here.

Planned and Past Courses

• DFG-Graduiertenkolleg, Regional Disparities and Economic Policies, jointly by the TU Dortmund, University of Duisburg-Essen, and Ruhr-Universität Bochum, scheduled.

• Joint Doctoral School in Economics and Innovation of the Baltic Economic Association, scheduled.

• University of Basel, 2020, course materials.

• CES Lecture, Ludwigs-Maximilians-University Munich, 2020, course materials.

• Tübingen-Hohenheim Economic Winter School, jointly by the University Tübingen, University Hohenheim, and Institute for Applied Economic Research (IAW), 2019, course materials.

• Leibnitz Centre for European Economic Research (ZEW), Mannheim, 2019, course materials.

• University of Basel, 2019, course materials.