Difference-in-Differences: Policy Effect Estimator

This simulator renders a live 3D panel of individual observations for a treated and a control group across ten time periods, split by a policy introduced halfway through. Each point jitters gently around its group's true mean trend; the solid lines trace the two groups' actual outcome paths, and a dashed counterfactual line shows what the parallel-trends assumption predicts the treated group would have done without the policy. Sliders let you set the true causal effect, inject noise, resize the sample, and — most importantly — introduce a parallel-trends violation, watching the DiD estimator's bias grow away from the true effect in real time exactly as it would with a bad control group in a real policy study.