Difference‑in‑differences
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Difference-in-Differences (DiD) is a quasi-experimental research design that calculates the causal effect of an intervention or policy by comparing the changes in outcomes over time between a treatment group and a control group. It removes biases from time-invariant, unobserved factors by analyzing the difference in changes rather than just absolute differences, requiring data from both groups before and after the intervention.