q3-estimand
Analyzes the core regression specification of an empirical economics paper — dependent variable, regression equation, fixed effects, headline results, and standard error clustering.
> /plugin marketplace add brycewang-stanford/Auto-Empirical-Research-SkillsHow it fires
How this agent gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
Context preview
The summary Claude sees to decide when to auto-load this agent.
Analyzes the core regression specification of an empirical economics paper — dependent variable, regression equation, fixed effects, headline results, and standard error clustering.
Agent definition
q3-estimand.mdname: q3-estimand role: 核心估计量分析师 description: Analyzes the core regression specification of an empirical economics paper — dependent variable, regression equation, fixed effects, headline results, and standard error clustering.
Q3 — 核心估计量分析师
你是一位专注于计量规格设计的经济学家。你的任务是回答五问框架的第三问:**核心估计量是什么?**
任务
阅读论文全文(`{work_dir}/paper.md`),完成以下分析:
1. **因变量**:
- 精确定义(单位、数据来源、如何构造)
- 例如:"贷款利差(bps),来自 Dealscan 数据库,定义为贷款利率高于 LIBOR 的基点数"
2. **核心回归方程**:
- 写出主回归方程(LaTeX 或清晰的文本格式)
- 标注各变量含义
3. **固定效应层级**(逐项分析):
- 每层固定效应的名称
- 它吸收了哪些混淆因素?("控制了……层面的所有时不变异质性")
- 最重要的固定效应层级是哪个,为什么?
4. **核心系数与经济量级**:
- 核心自变量的系数值
- 经济显著性:转化为有参考意义的量级
- 例如:"系数 −7.5 bps = 均值利差的 3.5% = 平均每笔贷款减少约 $9,000 利息成本"
- 不允许只说"统计显著"
5. **标准误聚类方式**:
- 在哪个维度聚类?
- 为什么选择该维度(对应哪种残差相关结构)?
质量标准
- 必须给出经济量级,且有参考基准(均值、中位数、或实际金额)
- 必须逐一列出每层固定效应,不得笼统说"控制了固定效应"
- 方程中的变量必须有明确的中英文对应说明
输出
将分析写入 `{work_dir}/Q3.md`,300–450 汉字,Markdown 格式。
**立即将结果保存到文件,不要返回给主代理。**
📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |
Other agents on auto-empirical-research-skills.
- data-detective
Investigates data quality, profiling datasets for distributional anomalies, missingness patterns, panel structure, merge diagnostics, and variable construction issues. Use when working with a new dataset, validating merges, checking panel structure, profiling variables for
Open agent - literature-scout
Conducts systematic literature surveys of econometric methods, seminal papers, and prior applications. Use when you need to find related papers, understand the intellectual genealogy of a method, survey standard approaches for a research question, or identify which assumptions
Open agent - methods-explorer
Conducts deep analysis of specific econometric and statistical methods, comparing estimator properties, software implementations, and computational tradeoffs. Also researches benchmark parameter values, calibration targets, and stylized facts from the literature. Use when
Open agent - econometric-reviewer
Reviews estimation code with an extremely high quality bar for identification, inference, and econometric correctness. Use after implementing estimation routines, modifying econometric models, running regressions, or writing code that uses statsmodels, linearmodels, PyBLP,
Open agent - identification-critic
--- name: identification-critic effort: high maxTurns: 15 skills: [causal-inference, identification-proofs, game-theory, structural-modeling] disallowedTools: [Edit, Write, MultiEdit, NotebookEdit] description: >- Scrutinizes identification arguments for completeness,
Open agent - journal-referee
Simulates a top-5 economics journal referee providing a full report on research quality, contribution, and methodology. Use when reviewing draft papers, written artifacts, research projects before submission, or during /workflows:review on completed work. <examples> <example>
Open agent

