Regression Discontinuity Design
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Regression discontinuity design (RDD) is a robust quasi‑experimental approach used to estimate causal effects when random assignment is not feasible. It relies on a predetermined cutoff in a continuous assignment variable, where individuals on one side of the threshold receive a treatment and those on the other do not. By comparing outcomes for units positioned just above and just below this cutoff—who are otherwise highly similar—RDD isolates the causal impact of the intervention by exploiting the discontinuous change in treatment status.
