Fuzzy regression discontinuity is a design used in impact evaluation that allows researchers to estimate causal effects when treatment assignment is not strictly determined by an observable cutoff. Unlike sharp regression discontinuity, where individuals clearly fall into treatment or control groups based on a threshold, fuzzy designs acknowledge that some individuals may not receive the treatment despite meeting the criteria or may receive it even if they do not. This method helps to assess the average treatment effect at the cutoff, accounting for cases where compliance with treatment is imperfect.
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