Data Science, Causal Inference, Causality, Econometrics, Impact.
(DD) The underlying assumption of Difference-in-Differences (DD) design is that the trend of the control group provides an adequate proxy for the trend that would have been observed in the treatment group in the absence of treatment. Thus, the difference in change of slope would be the actual