Computational Data Analytics
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.