Machine Learning in Health Economics

From Monday, September 16 until Friday, September 20, 2024

Lecturer(s): Prof. Helmut Farbmacher
Location: Lucerne

The course covers a selection of state-of-the-art methods in econometrics and machine
learning. It aims to provide students with a sound understanding of the methods discussed, such that
they are able to do research using modern econometric techniques, as well as critically assess existing

Course Program: SGGÖ-Kursprogramm 

In particular, the course will likely cover the following topics:
• Regression Shrinkage Methods (Ridge, Lasso, Elastic Net)
• Decision Trees, Random/Causal Forests
• Advanced Identification Strategies (e.g., Double Machine Learning)
• Introduction to Neural Networks