- Trainer/in: Christophe René Raymond Gaillac
The goal of this course is to provide a theoretical and practical understanding of the problems that machine learning tools can solve in economics and econometrics. This course aims to expand participants' knowledge of machine learning to apply it in contexts traditionally reserved for economics and econometrics.
Preliminary Program
1. Review of useful statistical and causal inference tools
2. Post-selection inference and generalization
3. High dimension, Machine Learning, and endogeneity
4. Inference on heterogeneous treatment effects
5. Optimal policy learning
6. Prediction policy problems
7. The synthetic control method
8. Machine Learning for forecasting
9. Working with text data in economics