Announcements and Resources

• Syllabus (always under construction)
• Cyrus office hours sign-up
• No class on the following dates (check back for updates):
  • Thu, Feb 8.
• Midterm: Thu March 14
• Final: Mon May 6-Tue May 14 (Final exam period).
  • Sign-up sheet: [link]
• Dias’s recitations: [link]

Lecture Slides

Causal Identification and Statistical Inference Foundations

• 1 introduction to causal effects and mechanisms [pdf]
• 2 a primer on causal identification analysis with potential outcomes and DAGs [pdf]
• 3 a primer on design-based statistical inference for descriptive quantities I [pdf]
• 4 design-based statistical inference for descriptive quantities II [pdf]
  • bootstrap examples: [R code]
• 5 design-based statistical inference for causal quantities [pdf]

Canonical Observational Designs

• 6 conditioning to identify causal effects [pdf]
• 7 multiple regression [pdf]
• 8 matching and weighting [pdf]
• 9 instrumental variables basics [pdf]
• 10 instrumental variables extensions [pdf]
• 11 front door criterion [pdf]
• 12 difference-in-differences for a single event [pdf]
• 13 difference-in-differences with multiple events [pdf] [sim output]
• 14 synthetic control with one treated unit [pdf]
• 15 general panel imputation methods [pdf]
• 16 regression discontinuity introduction [pdf]
• 17 regression discontinuity extensions [pdf]

Designing Experiments

• 18 experimental design introduction [pdf]
• 19 complex experimental designs and design effects [pdf]

Beyond Average Treatment Effects

• 20 moderation and mediation effects [pdf]
• 21 interference and spillover effects [pdf]
• 22 multiple outcomes and multiple comparisons [pdf]
  • recent DI blog post with review of current methods: [link]
• missing data [pdf]

Homework Assignments

• Homework 1 (due February 15): [assignment pdf]
• Homework 2 (due February 29): [assignment pdf] [replication files]
• Homework 3 (due April 11): [assignment pdf] [replication files]
• Homework 4 (due April 29): [assignment pdf] [replication files]