Description: Difference-in-differences (DiD) is one of the most widely used approaches for estimating causal effects in empirical economics. While the properties of the canonical two-period, two-group DiD design are well understood, recent research has shown that standard DiD estimators often lack a clear causal interpretation in more complex settings that are common in applied work. Such settings include staggered treatment adoption (where units receive treatment at different points in time) or variation in treatment intensity across units.