Analyze Causal Effect Using Diff-in-Diff Model

With a real-world application

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It is not always feasible to do randomized AB experiments, but we can still recover the causal effect of a treatment if we have a near-experiment that generates observational data over time (i.e. panel data). One of the models we can use to estimate causal effect with observational data is Difference-in-Difference (Diff-in-Diff, or…