ECON 8825 Econometric Methods for Causal Inference
This course covers a modern approach to the estimation of causal treatment effects. Topics covered include the estimation of treatment effects under unconfoundedness, instrumental variables, regression discontinuity, and a range of panel data methods (diff-in-diff, synthetic controls, fixed effects). We also discuss nonparametric estimation techniques, including kernel regression and machine learning methods, focussing on how these can be incorporated into treatment effect estimators.
Course overview
- Department
- Economics
- School
- MCAS
- Credits
- 3
- Level
- Graduate
- Offered
- Annually
Course evaluations
- Course rating
- 4.95 / 5 · Excellent
- Instructor rating
- 4.95 / 5 · Excellent
- Terms evaluated
- 3
| Term | Instructor | Course overall | Instructor overall | Well organized | Clear learning objectives | Intellectually challenging | Helpful assignments | Applicable beyond course | Attendance necessary | Weekly effort | Responses |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Fall 2025 | David Hughes | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | 4–6 hrs/week | 9 of 9 |
| Fall 2024 | David Hughes | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | 5.0 | 4.9 | 10+ hrs/week | 9 of 11 |
| Fall 2023 | David Hughes | — | — | — | — | — | — | — | — | — | 3 of 5 |