Teaching
Courses With Materials
Course: Econometrics with Unobserved Heterogeneity
Level: Graduate
Description: Unobserved heterogeneity is pervasive in economics, driven by heterogeneous parameters and treatment effects, unobserved characteristics of agents, missing variables, etc. This class introduces methods for estimating parameters of interest in settings with such unobserved heterogeneity. Topics include linear models with heterogeneous coefficients, nonparametric models with unobserved heterogeneity, and quantile and distribution regression.
Access Materials
GitHub
Other Courses
Other courses I have taught over the years include:
| Year | Course | Level | Institution |
|---|---|---|---|
| 2025 | Advanced Econometrics | Undergraduate | Bonn |
| 2024 | Topics in Econometrics and Statistics | Graduate | Bonn |
| 2023 | Data Science and Machine Learning with Python | Graduate/Professional | BSE |
| 2018-2022 | TA: Advanced Econometrics I | Graduate | BSE |
| 2018-2022 | TA: Advanced Econometrics II | Graduate | BSE |
| 2022 | TA: Forecasting Techniques | Undergraduate | UPF |
| 2021-2022 | TA: Econometrics 2 | Undergraduate | UPF |
| 2018-2021 | TA: Probability and Statistics | Undergraduate | UPF |
| 2019 | TA: Data Science BSE Summer School (Text Mining with R) | Graduate | BSE |
| 2018 | TA: Econometrics 1 | Undergraduate | UPF |
