When you cannot run an A/B test, synthetic control is a practical way to estimate causal impact from observational data. But it leans on assumptions that are easy to state and hard to verify and most prior theory effectively assumes those assumptions keep holding after the intervention, even though the model is only learned before it. … Read More
