Machine Learning in Econometrics (master)
Lecture: 16009
Exercise: 16008
LSF link
Tutor: Daniel Wilhelm (d.wilhelm@lmu.de)
Teaching content: Topics will include:
1. review of machine learning foundations (LASSO, orthogonal moments, …)
2. classification
3. text analysis
4. treatment effect estimation with high-dimensional heterogeneity and possibly:
5. network data
6. policy learning
The course will discuss theoretical properties of the methods and illustrate them with applications in economics. Students will be required to work on regular problem sets to learn practical implication of the methods.
Requisites: Master-level econometrics and basic statistics, probability concepts
Audience: PhD and Master students in statistics and economics
Evaluation: empirical project
ECTS Credits: 6 ECTS