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
Joint Doctoral School in Economics and Innovation of the Baltic Economic Association, Bank of Estonia, Tallinn, scheduled.
Graduate College "Regional Disparities and Economic Policies" of the German Research Council, University of Duisburg-Essen, 2021, course materials.
University of Basel, 2020, 2019, course materials.
CES Lecture, Ludwigs-Maximilians-University Munich, 2020, course materials.
Tübingen-Hohenheim Economic Winter School, University Hohenheim, 2019, course materials.
Centre for European Economic Research (ZEW), Mannheim, 2019, course materials.