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cff-version: 1.2.0

title: "diff-diff: Difference-in-Differences Causal Inference for Python"

message: "If you use this software, please cite it as below."

type: software

authors:

- given-names: Isaac

family-names: Gerber

orcid: "https://orcid.org/0009-0009-3275-5591"

license: MIT

version: "3.6.1"

date-released: "2026-07-01"

doi: "10.5281/zenodo.19646175"

url: "https://github.com/igerber/diff-diff"

repository-code: "https://github.com/igerber/diff-diff"

keywords:

- difference-in-differences

- causal-inference

- econometrics

- python

- treatment-effects

- event-study

- staggered-adoption

- parallel-trends

- synthetic-control

- panel-data

abstract: >-

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).