Difference-in-Differences causal inference in Python. Callaway-Sant'Anna, Synthetic DiD, Honest DiD, event studies. sklearn-like API, validated against R.
difference-in-differences 开源项目推荐(377 个)
difference-in-differences 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 377 个仓库StatsPRI是第一个用于因果推理和应用计量经济学的代理原生Python库-统一API、广泛的跨方法覆盖范围、结构化结果对象、机器可读模式、技能、HCP服务器和R/Stata平价验证。
Robust inference in difference-in-differences and event study designs
与 Stata 对齐的 Python 计量经济学,并在文档化支持面上进行字段级验证。
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)
Evidence-first AI workflow for economic and financial research: literature → identification → data → econometrics → verifiable LaTeX. 43 data sources, 58 method modules, 18 AI skills, 30 journal templates.
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
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。
A suite of Julia packages for difference-in-differences
fast and flexible Difference-in-Differences
Modern difference-in-differences in Python.
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
Claude Code skills for rigorous social science research: DID, RCTs, regression diagnostics, visualization, literature reviews, and more. Encode methodological best practices directly into your AI coding workflow.
Automatic data-aware staggered-adoption DID analysis in Stata - 8 estimators + full diagnostics via one command or one sentence
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/difference-in-differences。
- 该话题在 GitHub 上共有 377 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 2214 Star,覆盖 5 种主要语言,数据更新于 2026-11-06。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。