26.10 Multiple Treatments
When you have 2 treatments in a setting, you should always try to model both of them under one regression to see whether they are significantly different.
- Never use one treated groups as control for the other, and run separate regression.
- Could check this answer
\[ \begin{aligned} Y_{it} &= \alpha + \gamma_1 Treat1_{i} + \gamma_2 Treat2_{i} + \lambda Post_t \\ &+ \delta_1(Treat1_i \times Post_t) + \delta_2(Treat2_i \times Post_t) + \epsilon_{it} \end{aligned} \]
(Clement De Chaisemartin and D’haultfœuille 2023) video code
References
De Chaisemartin, Clement, and Xavier D’haultfœuille. 2023. “Two-Way Fixed Effects and Differences-in-Differences Estimators with Several Treatments.” Journal of Econometrics 236 (2): 105480.
Fricke, Hans. 2017. “Identification Based on Difference-in-Differences Approaches with Multiple Treatments.” Oxford Bulletin of Economics and Statistics 79 (3): 426–33.