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Multilevel DD (Difference-in-Differences) is an econometric technique used to analyze causal relationships in data with hierarchical structures, such as individuals nested within groups or regions. It extends the traditional Difference-in-Differences approach by allowing for variations at multiple levels, enabling researchers to account for both individual-level and group-level factors. This method is particularly useful in evaluating policy effects over time while controlling for unobserved heterogeneity across different levels of analysis. It helps provide more robust estimates of treatment effects in complex datasets.

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