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Often abbreviated DID or DD, this is a technique for inferring causality from observational data. It involves comparing measurements before and after a treatment occurs (hence, the growth rate) in both a group that received the treatment, and an otherwise comparable group that did not.

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Difference-in-difference and panel data models

I understand that according to the observations you have (two independent cross-sections in two or more time periods or the same individuals observed in two different periods), then difference-in-diff …
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