.zenodo.json

{
  "upload_type": "software",
  "title": "diff-diff: Difference-in-Differences Causal Inference for Python",
  "description": "A Python library for Difference-in-Differences (DiD) causal inference analysis. Provides sklearn-like estimators for modern DiD methods including Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies, and parallel trends testing. Validated against R packages (did, synthdid, fixest).",
  "creators": [
    {
      "name": "Gerber, Isaac",
      "orcid": "0009-0009-3275-5591"
    }
  ],
  "license": "MIT",
  "access_right": "open",
  "keywords": [
    "difference-in-differences",
    "causal-inference",
    "econometrics",
    "python",
    "treatment-effects",
    "event-study",
    "staggered-adoption",
    "parallel-trends",
    "synthetic-control",
    "panel-data"
  ],
  "related_identifiers": [
    {
      "relation": "isSupplementTo",
      "identifier": "https://github.com/igerber/diff-diff",
      "resource_type": "software"
    },
    {
      "relation": "isDocumentedBy",
      "identifier": "https://diff-diff.readthedocs.io/en/stable/"
    }
  ]
}