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Announcements
- Syllabus (NB: some parts to be updated): [pdf]
- No class on the following dates (check back for updates):
- January 21
- February 9
- February 11
- Midterm (in class): March 11
- Final (in class): May 11
- Teaching Assistant: Yinxuan Wang
- Recitation information:
Lectures
Inferential foundations
- 1 Introduction to causal effects and mechanisms [pdf]
- 2 Causal identification analysis with potential outcomes and DAGs [pdf]
- 3 Design based statistical inference I [pdf]
- 4 Design based statistical inference II [pdf]
- 5 Design based causal inference [pdf]
Conditioning-Based Identification Strategies
- 6 Conditioning to identify causal effects [pdf]
- 7 Matching and weighting [pdf]
- 8 Double machine learning for treatment effects [pdf]
Instrumental Variables
- 9 Instrumental variables basics [pdf]
- 10 Instrumental variables extensions [pdf]
Partial Identification
- 11 Partial identification bounds [pdf]
Difference in differences
- 12 Difference in differences with a single event [pdf]
- 13 Difference in differences with multiple events [pdf]
Synthetic control and panel imputation
- 14 Synthetic control for one treated unit [pdf]
- 15 Generalized synthetic control and panel imputation [pdf]
Regression discontinuity
- 16 Sharp regression discontinuity design [pdf]
- 17 Regression discontinuity extensions [pdf]
Experimental design
- 18 Experimental design I [pdf]
- 19 Experimental design II [pdf]
Homework
- Homework 1 (due Feb 17): [pdf]
- Homework 2 (due March 4): [assignment pdf] [replication files]
- Homework 3 (due April 15):
- [assignment pdf]
- [datasets]. Dataset assignments:
- student_01: Sahil and auditors/non-registered
- student_02: Emir
- student_03: Sebastian
- student_04: Juan
- student_05: Amin
- student_06: Asher
- student_07: Eoin
- student_08: Guillermo
- student_09: Sijie