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

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.

Robust inference in difference-in-differences and event study designs

R & Python code and datasets for Everyday Causal Inference — a free book on experiments, DiD, IV, RDD, and causal time series for business

difference-in-differences in Python

Robust inference in difference-in-differences and event study designs (Stata version of the R package of the same name)

Synthetic difference in differences for Python

Implementing Local Projections Difference-in-Differences (LP-DiD) estimators

Step-by-step causal inference — method selection, assumptions, and robustness checks

A suite of Julia packages for difference-in-differences

Agent skills that help you publish in the AER faster — identification-first empirics, AEA-compliant replication, Keith-Head intros, R&R rebuttals for AER / AER:Insights / AEJ. | 助你更快发表 AER 论文的 agent skill 栈：识别优先实证、AEA 合规复现、Keith Head 式引言、R&R 审稿回复，覆盖选题到投稿全流程。

fast and flexible Difference-in-Differences

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

Causalis - State-of-the-art robust causal inference for experiments and observational data in python

Causal Inference Using Quasi-Experimental Methods

Estimation of Difference-in-Differences Treatment Effects with Staggered Treatment Onset Using Heterogeneity-Robust Two-Way Fixed Effects Regressions

Regression-based multi-period difference-in-differences with heterogenous treatment effects

End-to-end AI workflow for economic & finance research: 43 MCP data sources, 47 econometric methods (DID/IV/RD/PSM/GMM), 30 journal templates (JF/JFE/RFS/经济研究/金融研究/管理世界), HITL gates, 3-LLM adversarial review. MIT. Zenodo: 10.5281/zenodo.21262689

Lecture slides, video recordings, and coding exercises from the 2024 Northwestern University Causal Inference Workshop. This repository is not affiliated with Northwestern University or the workshop.

Difference-in-Differences analysis of survey data to estimate causal effects