Difference In Differences Python Packages

diff-diff

Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.

statspai

StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.

differences

difference-in-differences in Python

diddesign

Double Difference-in-Differences for Python — GMM-optimal combination of multiple pre-treatment periods with bootstrap inference, diagnostic tools, and publication-ready plotting (Egami & Yamauchi, 2023).

pretest-did

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.

insurance-causal-policy

Causal evaluation of insurance pricing interventions using Synthetic Difference-in-Differences

equitrends

Equivalence tests for pre-trends in Difference-in-Differences estimation. Implements max, mean, and RMS tests from Dette & Schumann (2024, JBES).

moderndid

Scalable, GPU-accelerated Python library for modern difference-in-differences.

did-imputation

Borusyak-Jaravel-Spiess (2024) difference-in-differences imputation estimator with event-study plots for Python.

contdid

Continuous treatment difference-in-differences estimation for Python — dose-response curves, event-study dynamics, and uniform confidence bands.

factor-factory

Domain-agnostic factor-model + analysis-pipeline framework with Protocol-based pluggable engines (DiD, SDID, SCM, RDD, survival, event study, mediation, het-TE, …) and first-class jellycell tearsheet integration.

doublediff

Scalable, GPU-accelerated Python library for modern difference-in-differences.

causaldid

Modern difference-in-differences estimators.