I disagree with the suggestion that the MV example presented here undermines the difs-in-difs approach. Again, the crucial question is *What would have happened at the project site if the MVP had never existed?* This is ultimately unknowable, because we never observe the project site in this state of the world--that's why it's called the counterfactual. But it is impossible to meaningfully define "impact" without identifying what an estimate of the counterfactual is, so we have to come up with a some estimate. It's true that without the MVP, things at the MVP site might have gotten worse. By the same taken, without the MVP, things might have improved *more* than they did with the MVP. What we're looking for is not the full distribution of possible counterfactual states, but rather what is our best estimate of what the counterfactual is. A very good--though not perfect--estimate of the counterfactual is what happened in rural areas in the same region as the MVP site. This is the counterfactual behind the difs-in-difs estimates. The hypothetical fertilizer and seed example confuses the issue by suggesting that the question is one of analyzing simple interventions which are also taking place elsewhere. But the evaluation question is not "What is the impact of free fertilizer?" Rather, it is "What is the impact of the MVP package of interventions?" The fact that programs similar to some components of the MVP may have been implemented elsewhere does not complicate the question of evaluating the impact of the full package.