Agent Skills
› brycewang-stanford/Awesome-Journal-Skills
› jar-tables-figures
jar-tables-figures
GitHub用于构建JAR论文的标准实证展示材料，包括样本构建表、描述性统计、相关矩阵、主回归及识别图。遵循期刊排版规范，确保自包含且推断清晰，通过工具从结果直接生成，避免手动录入错误。
触发场景
表格混乱或不一致
审稿人无法识别样本或聚类信息
需要组装符合JAR风格的展示集
需要绘制趋势或RD图以支持因果推断
安装
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jar-tables-figures -g -y
SKILL.md
Frontmatter
{
"name": "jar-tables-figures",
"description": "Use when finalizing the descriptive, results, and identification exhibits for a Journal of Accounting Research (JAR) manuscript — the summary-statistics table, correlation matrix, main regression tables, and identification plots that an empirical-archival accounting paper lives or dies on. Builds the exhibits; it does not run the estimation (jar-data-analysis) or polish prose (jar-writing-style)."
}
Tables & Figures (jar-tables-figures)
When to trigger
- Tables are cluttered, inconsistent, or not self-explanatory
- A referee cannot tell the sample, units, or SE clustering from the table notes
- You need the standard JAR exhibit set assembled in house style
- Identification needs a figure (pre-trends, RD plot) to be believed
The standard JAR exhibit set
An empirical-archival JAR paper is read through its tables. Build, in order:
- Sample construction table — from the raw population to the final N, line by line, with each screen and the observations lost. Referees expect to trace the sample.
- Descriptive statistics — N, mean, SD, and key percentiles for every variable; state winsorization (e.g., 1/99%).
- Correlation matrix — Pearson (and often Spearman) among the main variables; flag significance.
- Main results — the central regression(s): coefficients with t-/z-stats or standard errors beneath, the SE clustering stated in the note, fixed effects indicated, and N and R² (or pseudo-R²) reported.
- Identification & robustness — first-stage (IV), DiD dynamics, RD estimates, falsification/placebo, alternative measures, and cross-sectional (channel) partitions.
House-style discipline
JAR uses a custom author-date house style; match the typographic conventions of recent JAR articles rather than importing a reference manager's defaults. For exhibits specifically:
- Self-contained: a title, the sample/period, the units, and the dependent variable are clear from the table and its note alone.
- Inference visible: report what is beneath the coefficients (t-stats / SEs) and state the clustering in the note; mark significance consistently.
- Variable definitions: every variable defined (often an appendix variable-definitions table) with its data source (Compustat/CRSP/I/B/E/S/Audit Analytics/EDGAR).
- Numbers consistent: Ns, coefficients, and signs match the text; decimal places consistent.
Figures that earn their place
Use figures where they do identification work a table cannot: DiD event-study plots (coefficients by period with confidence bands, showing flat pre-trends), RD plots (binned means around the cutoff), and time series of the treatment/setting. Avoid decorative charts; every figure should support the causal claim.
Execution bridge (StatsPAI / Stata MCP)
Generate exhibits from the fitted result, not by retyping numbers (the usual source of
body-vs-appendix drift). Full map: execution-with-mcp. JAR is archival/empirical accounting; foreground identification around disclosure and regulation shocks, with modern DiD where adoption is staggered.
- Tables:
etable(multi-model columns) ordid_summary_to_latexstraight from theresult_id. - Figures:
plot_from_result/enhanced_event_study_plot/event_study_table— axis units and the SE/clustering note baked in. - Every note names the estimator + clustering and states the effect size in interpretable units.
See a full fitted-result → exhibit chain in the JF execution walkthrough.
Checklist
- Sample-construction table traces raw population → final N
- Descriptives with winsorization stated; correlation matrix included
- Main table reports coefficients, inference statistics, FE, N, R²
- SE clustering stated in every regression-table note
- Variable-definitions table with data sources included
- Identification figure (pre-trends / RD) present where the claim is causal
- All numbers reconcile with the text; formatting matches recent JAR articles
Anti-patterns
- Mystery samples: a final N with no construction table.
- Naked coefficients: no SEs/t-stats and no clustering note.
- Reference-manager defaults instead of JAR house style.
- Decorative figures that do no identification work.
- Undefined variables or sources scattered through the text.
Output format
【Exhibit set】sample / descriptives / correlations / main / robustness present?
【Inference shown】t-stats or SEs + clustering stated in notes?
【Variable definitions】table with sources included?
【Identification figure】pre-trends / RD plot present where causal?
【Consistency】Ns and coefficients reconcile with text?
【House style】matches recent JAR articles?
【Next step】jar-writing-style
Resources
../../resources/official-source-map.md— official JAR/Chicago Booth/Wiley URLs (accessed 2026-06-01)../../resources/external_tools.md— exhibit-export tooling (estout / outreg2 / modelsummary) and data sources
版本历史
- 1839142 当前 2026-07-05 13:25
