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The key idea behind how we use panel data to get a causality was the common trends assumption. If there's some unobserved confounder, it can differ in levels across the treatment and control group, but the changes over time have to affect each group the same, on average. Now, there's one very important, special case of this, and that's called a fixed effect or an individual effect. This is a variable that doesn't change over time. So the idea here is that we can let the value of this unobserved variable be different in the treatment group and in the control group. Okay, but as long as the changes aren't systematic, which they are because by assumption, this variable isn't changing over time so the changes are always zero, that's fine. That's totally fine. It doesn't violate the common trends assumption. So we can allow for these unobserved fixed effects. Variables that don't change over time, but are systematically different across the treatment and control group. So for example, let'...
