Causal inference with treatment/control groups over time. Use when user mentions: treatment effects, policy evaluation, pre/post comparison, parallel trends, DID, DiD, difference in differences, natural experiment, quasi-experimental.
The exact command may vary by repository. Check the README on GitHub.
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<skill_content>
<overview>
Difference-in-Differences (DID) is a causal inference method that estimates treatment effects by comparing changes over time between treated and control groups. It leverages both cross-sectional and temporal variation to identify causal effects when randomization is infeasible.
DID is the workhorse of policy evaluation in economics and social sciences.
</overview>
