Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.
-
Updated
Jul 6, 2026 - Python
Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.
Stata implementation of Double Difference-in-Differences (Egami & Yamauchi, 2023). Optimally combines standard DID and sequential DID via GMM for improved efficiency and robustness. Supports staggered adoption designs.
this repository contains EViews-codes for parallel trend assumption
this repository contains Stata-codes for parallel trend assumption
Python implementation of the conditional extrapolation pre-test for difference-in-differences (Mikhaeil & Harshaw, 2026). Returns pass/fail decision, conditional confidence interval, and diagnostic scalars as a typed result object.
Add a description, image, and links to the parallel-trends topic page so that developers can more easily learn about it.
To associate your repository with the parallel-trends topic, visit your repo's landing page and select "manage topics."