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