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依据实证论文的规范结构与写作风格生成学术论文；适用于生成金融、经济、会计等领域的研究论文框架与正文内容
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| name | empirical-paper-writer |
| description | 依据实证论文的规范结构与写作风格生成学术论文；适用于生成金融、经济、会计等领域的研究论文框架与正文内容 |
| dependency | {"python":["requests==2.28.0"]} |
依据实证论文的规范结构与写作风格，生成符合学术期刊要求的完整论文框架与正文内容。
要求:
生成指南:
规范:
模板句式:
We study/conduct/investigate [RESEARCH QUESTION]. Using [METHODOLOGY]
on [DATA SAMPLE], we find that [KEY FINDING]. [ECONOMIC IMPLICATION].
标准结构:
3.1 研究背景与问题 (Research Motivation)
- 阐述领域核心问题
- 引用2-3篇经典文献说明研究缺口
3.2 研究贡献 (Main Contributions)
- 理论贡献
- 方法贡献
- 实证贡献
- 实践贡献
3.3 论文结构 (Paper Organization)
- "Section 2 describes... Section 3 presents... Section 4 concludes..."
写作要点:
组织方式:
4.1 [领域主题A]
- 研究现状
- 研究空白
4.2 [领域主题B]
- 研究现状
- 研究空白
注意事项:
必要组成部分:
5.1 数据与样本 (Data and Sample)
- 数据来源
- 样本选择标准
- 变量定义
- 描述性统计
5.2 研究设计 (Research Design)
- 理论框架
- 模型设定
- 识别策略
5.3 估计方法 (Empirical Methodology)
- 基准模型
- 稳健性检验
- 内生性处理
数学公式规范:
结构模板:
6.1 基准回归 (Baseline Results)
6.2 经济显著性 (Economic Significance)
6.3 稳健性检验 (Robustness Checks)
- 替代变量
- 子样本分析
- 方法稳健性
6.4 内生性分析 (Endogeneity)
结果呈现:
结构:
7.1 研究总结
7.2 理论贡献
7.3 实践启示
7.4 研究局限与未来方向
推荐表达:
避免表达:
标准段落(5-7句):
文中引用:
表格规范:
图形规范:
见 references/asset_pricing_template.md
输入: 研究主题:机器学习在资产定价中的应用 研究假设:神经网络预测股票收益优于线性模型 数据类型:CRSP股票收益数据，1957-2020
生成步骤:
输入: 已有Introduction草稿，需要润色
操作:
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