AI_EFR_v1.0.0
AI for Economics and Finance Research — v1.0.0
The first public release of a practical, GitHub-native handbook and resource library for using AI and large language models responsibly and effectively in economics and finance research.
This release brings the repository to a complete, stable, and citable v1.0.0: a full bilingual handbook, a library of copy-ready research skills, agent and automation workflows, worked examples, source notes, and teaching materials — all built around one simple loop: read, copy a skill, use it on a real task, verify the output, and record what changed.
What's included
- 01 · Start Here — The Handbook. One consolidated reading guide covering the mental model, the maturity ladder, what AI is and isn't good at, the econ/finance research workflow, and data, GitHub, and project safety.
- 02 · Copy and Use — Skills and Templates. 13 ready-to-use skill files: research ideas, paper drafting and citations, economics and finance empirical methods, coding and debugging, literature review, causal inference and time series, theory and math, referee reports, and more.
- 03 · Set Up Agents and Workflows. 6 multi-step, Git-safe workflows for cleaning projects, the one-paper-one-repo setup, replication packages, update digests, parallel agents and worktrees, and GitHub review/publish.
- 04 · Examples, Diagrams, and Failure Cases. Worked asset-pricing and corporate-finance examples, a research-workflow diagram, and failure cases.
- 05 · Check Sources and Official Docs. A source-to-repo map, a source-use policy, and privacy-safe ways to stay updated.
- 06 · Teach, Practice, and Share Slides. Workshop outlines, a slide-ready talk structure, RA onboarding checklists, and presentation-practice activities.
Who it's for
Students, research assistants, PhD students, and faculty in economics and finance who want the genuine productivity gains of AI without surrendering the judgment, rigor, and integrity that good scholarship depends on.
Core principle
AI can automate labor, but not scholarly responsibility. Treat every AI output as a draft, checklist, critique, or coding aid — and verify claims, citations, coefficients, code, and equations against original sources before using them. Always follow your institution, funder, journal, and data-provider rules; where they are stricter, follow the stricter rule.
Languages
Fully bilingual — English and 中文 (Simplified Chinese).
License and citation
Released under the MIT License. If this repository supports your research or teaching, please cite it using the included CITATION.cff.
Connect
- LinkedIn: Chaojie (Jay) Liu
- 小红书 (RED): SuperJay
Feedback and contributions
Questions, corrections, or new-skill suggestions are welcome: jay.liu@bristol.ac.uk — subject line [AI Econ Finance Handbook] Question or correction.
#高效地将AI应用于经济与金融研究 — v1.0.0
本仓库的首个公开发布版本：一本实用的、以 GitHub 为载体的手册与资源库，帮助经济学与金融学研究者负责任且高效地使用 AI 与大语言模型。
此版本将仓库带到一个完整、稳定、可引用的 v1.0.0：包含完整的双语手册、可直接复制使用的研究 skills 库、agent 与自动化工作流、实例、来源说明，以及教学材料——全部围绕一个简单的循环展开：阅读、复制一个 skill、在真实研究任务上使用、核查输出、并记录改动。
包含内容
- 01 · 从这里开始 — 手册。 一份整合的阅读指南，涵盖思维模型、成熟度阶梯、AI 擅长与不擅长的事、经济/金融研究工作流，以及数据、GitHub 和项目安全。
- 02 · 复制与使用 — Skills 与模板。 13 个可直接使用的 skill 文件：研究想法、论文写作与引用、经济与金融实证方法、编程与调试、文献综述、因果推断与时间序列、理论模型与数学、审稿报告等。
- 03 · 搭建 Agents 与工作流。 6 个多步骤、Git 安全的工作流：清理项目、one-paper-one-repo 设置、复现包、更新摘要、并行 agents 与 worktrees，以及 GitHub review/publish。
- 04 · 实例、图示与失败案例。 资产定价与公司金融的实例、研究工作流图示，以及失败案例。
- 05 · 核查来源与官方文档。 来源到仓库的映射、来源使用政策，以及保护隐私的更新方式。
- 06 · 教学、练习与分享幻灯片。 工作坊大纲、可直接使用的演讲结构、RA 入门清单，以及演讲练习活动。
适合谁
经济学与金融学领域的学生、研究助理、博士生与教师——希望获得 AI 带来的真实效率提升，同时不放弃优秀学术研究所依赖的判断力、严谨性与诚信。
核心原则
AI 可以自动化劳动，但不能替代学术责任。请把每一份 AI 输出都当作草稿、清单、批评意见或编程辅助——在用于研究之前，对照原始来源核查论断、引用、系数、代码与公式。始终遵守所在机构、资助方、期刊与数据提供方的规则；当这些规则更严格时，遵守更严格的规则。
语言
完全双语——English 与 中文（简体）。
许可与引用
基于 MIT License 发布。如果本仓库对你的研究或教学有帮助，请使用附带的 CITATION.cff 进行引用。
联系方式
- 领英 LinkedIn: Chaojie (Jay) Liu
- 小红书: SuperJay
反馈与贡献
欢迎提出问题、修正或新的 skill 建议：jay.liu@bristol.ac.uk——邮件主题 [AI Econ Finance Handbook] Question or correction。
Released by Chaojie (Jay) Liu · v1.0.0