The continuity assumption is a key concept in causal inference that posits that potential outcomes for units near a threshold will be similar to one another, allowing for the identification of causal effects. This assumption is critical in methods like regression discontinuity analysis, where it supports the idea that any discontinuities observed in outcomes at the threshold are attributable to the treatment or intervention being evaluated.
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