<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>
<mandatory_requirements>
<requirement priority="critical"> <name>Parallel Trends Testing</name> <d[Description truncada. Veja o README completo no GitHub.]