Synthetic Control 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.

syntheticcontrolmethods

A Python package for causal inference using Synthetic Controls

insurance-causal-policy

SDID for causal rate change evaluation in insurance pricing — event study, HonestDiD sensitivity, FCA evidence pack (170 tests)

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.