did-analysis

Community

End-to-end Difference-in-Differences analysis guide.

Authorsheehe
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Analyzes causal effects in panel data using Difference-in-Differences (DID) design, providing a structured workflow and interpretation to distinguish treatment effects from time trends.

Core Features & Use Cases

  • DID design validation: verify parallel trends, treatment timing, and eligibility.
  • Modeling options: 2×2 DID, TWFE with entity/time fixed effects, and robust alternatives for staggered adoption.
  • Event-study diagnostics: estimate dynamic effects and visualize pre/post trends.
  • Robustness & reporting: placebo tests, alternative controls, and interpretability guidelines for policy evaluation.
  • Guidance for heterogeneity: subgroup analyses and robust standard errors.

Quick Start

Provide a ready-to-use DID analysis workflow for your panel dataset with treatment and control groups.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: did-analysis
Download link: https://github.com/sheehe/coase/archive/main.zip#did-analysis

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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