Contemporary approaches to causal inference and its application to policy questions
| Instructor: | Dr. William E. M. Lowe |
| Office: | Room 3.14 |
| Office Hours | By arrangement. Email the instructor directly. |
| Class Times | Tuesdays 16:00-18:00 |
| Classroom | 2.30 |
| Moodle | Course page |
| Date | Title | |
|---|---|---|
| 1 | 08.09.2020 | Foundations |
| 2 | 15.09.2020 | Experiments, Quasi-experiments, and Definitely not Experiments |
| Assignment 1 out | ||
| 3 | 22.09.2020 | Stratification, Regression, and all that |
| 4 | 29.09.2020 | Machine Learning and Big Data Changes Everything |
| Assignment 2 out | ||
| 5 | 06.10.2020 | Even More Machine Learning |
| Assignment 3 out | ||
| 6 | 13.10.2020 | Half Time Review, plus some Diff-in-Diff |
| Assignment 4 out | ||
| 7 | 27.10.2020 | Collider Bias in Theory and Practice |
| 8 | 03.11.2020 | Mediation, of the Statistical Variety |
| 9 | 10.11.2020 | Fairness and Bias in Algorithms and Humans |
| 10 | 17.11.2020 | Fairness and Bias: Case Study |
| 11 | 24.11.2020 | Special topics: Sensitivity and Bounds |
| Assignment 5 out | ||
| 12 | 01.12.2020 | Special Topics: Alternative approaches to Causal Inference |
| 14.12.2020 | Final Exam Week |
Hernán Miguel A. and Robins James M. (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC.
Pearl, Judea, Glymour, Madelyn, and Jewell, Nicholas 2016. Causal Inference in Statistics: A Primer. Wiley.
Angrist, Joshua D. and Pischke, Jörn-Steffen 2009 Mostly Harmless Econometrics. Princeton University Press