跳到主要内容
知仓学习社ZHICANG

ecta-tables-figures

Use when finalizing the simulation tables and any empirical / illustrative exhibits in an Econometrica manuscript so each is self-contained, precise…

不碰外部(只输出文字)无严重或高危命中brycewang-stanford/Awesome-Journal-Skills

它会碰到什么

扫了多少1 个文本文件,6 KB
它会碰到什么不碰外部(只输出文字)
命中总数0 处
命中统计严重 0 · 高 0 · 中 0 · 低 0

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

Tables and Figures (ecta-tables-figures)

When to trigger

  • A Monte Carlo or empirical table is overloaded, ambiguous, or not self-contained
  • Notes do not say what is being reported (size? coverage? bias?) at what sample size and nominal level
  • Figures (power curves, coverage plots, value-function illustrations) lack axis labels or a legend
  • Numbers in the table cannot be traced to a specific script / seed

Econometrica exhibits are read closely by referees who will recompute or sanity-check

entries — and at conditional acceptance the ES Data Editor re-runs the code behind every

table, figure, and number that comes from data or simulation. Every table and figure must

stand alone and trace to a seeded script in the replication package. Two Econometrica

specifics that differ from applied siblings: (1) the 45-page main-text limit (incl.

references and appendices) forces ruthless triage — keep the headline size/power/coverage

tables in the body and push secondary designs to the Supplemental Material; (2)

reproducibility is enforced by the Econometric Society Data Editor with a Zenodo

deposit, not the AEA/openICPSR pipeline the AER/AEJ packs assume.

Simulation-table standards

  1. Self-contained. The caption + notes must let a reader interpret every number without

the body text: estimator(s), DGP / design, sample size(s), number of replications, nominal

level, and what each column reports (bias, RMSE, empirical size, coverage, length).

  1. One concept per table where possible — do not mix size, power, and point-estimation

quality in one undifferentiated block.

  1. Consistent precision. Choose decimal places deliberately (e.g., sizes to 3 decimals so

0.052 vs. 0.048 is visible) and keep them consistent down a column.

  1. Highlight the comparison. The reader should see at a glance that the proposed method

controls size / has lower RMSE than the competitor — order columns/rows so the contrast reads.

  1. Monte Carlo error. Where a size or coverage near the nominal level carries the argument,

make the simulation precision clear (replication count in notes, or a reported MC standard error).

  1. Three-line / booktabs style. Clean rules (top, mid, bottom), no vertical lines, no

shading — the standard for formal economics journals.

Figures

  • Label everything: axes with units, every series, the nominal-level reference line on a

size/coverage plot, the null on a power curve.

  • Power curves: plot rejection probability against the departure parameter; mark the null

and the nominal level; use size-adjusted curves for fair comparison.

  • Coverage plots: show coverage across designs / sample sizes against the nominal target.
  • Theory illustrations: equilibrium / value function / comparative statics across the

parameter range, with the relevant region annotated.

  • Vector format (PDF/EPS) so curves stay crisp; legible at print size; colorblind-safe and

readable in grayscale.

Traceability

  • Each table/figure should be regenerated by a named script with a fixed seed (tie this to

ecta-replication-package). Keep a map: Table N ↔ script ↔ seed ↔ output file.

  • Numbers in the text must match the tables exactly (no rounding drift between prose and table).

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers. Full map:

[execution-with-mcp](../../../shared-resources/empirical-methods/execution-with-mcp.md). Econometrica publishes econometric theory and applied micro; the chain below serves its applied/empirical papers (weak-IV-robust and modern-DiD reporting expected) — pure theory uses its own apparatus.

  • Tables: etable (multi-model) or did_summary_to_latex straight from the result_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 magnitude in interpretable units.

See a full fitted-result → exhibit chain in the [JF execution walkthrough](../../../Journal-of-Finance-Skills/resources/worked-examples/02-execution-walkthrough.md).

Checklist

  • [ ] Caption + notes make each exhibit fully self-contained
  • [ ] DGP/design, n, replications, nominal level, and per-column meaning all stated
  • [ ] Decimal precision deliberate and consistent
  • [ ] Competitor methods included; the key comparison reads at a glance
  • [ ] Monte Carlo precision conveyed where size/coverage carries the argument
  • [ ] Three-line / booktabs style; no vertical rules or shading
  • [ ] Figures fully labeled; vector format; readable in grayscale
  • [ ] Every exhibit traces to a named script + seed; text numbers match tables

Anti-patterns

  • A size table with no nominal level stated, so 0.07 is uninterpretable
  • Mixing size, power, and bias in one block with no clear separator
  • Reporting power without indicating size, making the method look artificially good
  • Inconsistent decimals down a column, hiding the comparison
  • A figure with unlabeled axes or an unexplained second series
  • Numbers in the text that disagree with the table by a digit
  • A table no script can regenerate, so replication review cannot verify it

Output format

【Exhibit】Table/Figure N — [what it shows]
【Self-contained?】yes / no — missing: [...]
【Reports】bias / RMSE / size / power / coverage / length / illustration
【Design+n+reps+level stated】yes/no
【Style】booktabs three-line / needs fixing
【Traceable to script+seed】yes/no
【Next step】ecta-writing-style

想直接用这个技能?

本站把开放许可(MIT / Apache 等)的技能按仓库打包整理到网盘,点一下转存到你自己的网盘,不用一个个从 GitHub 拉。许可未声明的技能只给原始仓库链接,不打包。