Ectheory Tables Figures
Documentsectheory-tables-figuresEctheory Tables Figures is an Agent Skill for documents published in the brycewang-stanford/Awesome-Journal-Skills repository on GitHub: a SKILL.md instruction file an AI agent can load to do this task.
Use for the exhibits in an Econometric Theory (ET) paper — Monte Carlo size/power/coverage tables, finite-sample and limit-behavior plots, with self-contained notes, ET figure-format specs (TIFF/EPS/PDF), and legibility at 50% reduction.
How to use this skill
Bring this guide into your coding agent with a prompt tailored to the tool you use.
- Open your project in Codex.
- Copy and paste the prompt below.
- Review files and risks before approving any action.
Inspect the Agent Skill at https://github.com/brycewang-stanford/Awesome-Journal-Skills/blob/HEAD/Econometric-Theory-Skills/skills/ectheory-tables-figures/SKILL.md and all supporting files. Report provenance, permissions, scripts, dependencies, and security risks. Propose an exact installation into .agents/skills/ectheory-tables-figures, but wait for my approval before writing files or running scripts.
Copying this prompt does not install or run the skill. Review third-party files before use.
Tables & Figures (ectheory-tables-figures)
When to trigger
- Turning Monte Carlo output into publication tables (size, power, coverage, bias, RMSE)
- Building plots of finite-sample distributions, convergence to the limit, or rejection curves
- Preparing figure files to ET's format and resolution specs
- Checking that exhibits are self-contained and legible after print reduction
What ET exhibits look like
ET is a theory journal, so most exhibits are simulation tables and diagnostic plots that illustrate the asymptotics, not empirical-result tables. Common exhibits:
- Size/power tables — empirical rejection rates under the null (vs nominal level) and under alternatives, across DGPs and sample sizes.
- Coverage / bias / RMSE tables — for estimators, across n and DGP, against a benchmark method.
- Distribution / convergence plots — empirical vs limiting density (e.g., normal, mixed-normal, Brownian functional); QQ plots; rejection curves as a function of the alternative.
- Rate plots — a statistic against n on a scale that reveals the convergence rate.
Construction standards
- Self-contained notes. Each table/figure note states the DGP, sample sizes, number of replications, nominal level, and what each column/curve is — readable without the main text.
- Honest contrast. Put your method beside the natural competitor in the same table; do not hide the comparison.
- Legibility. Exhibits must be legible at 50% reduction; avoid chartjunk, 3D, and dense color. Keep table precision sensible (e.g., 3 decimals for rejection rates).
- Figure files (ET specs). Supply TIFF (line art >=600 dpi, greyscale >=300 dpi), EPS (fonts embedded), or PDF. Embed fonts; vector output for line art.
- Numbering. Tables and figures numbered and called out in order in the text.
Checklist
- Each exhibit note states DGP, n, replications, nominal level, and column/curve definitions
- Size reported against the nominal level; power against stated alternatives
- Benchmark method shown alongside, not omitted
- Plots show convergence/limit behavior clearly; rate legible where claimed
- Legible at 50% reduction; no chartjunk; sensible decimal precision
- Figure files in TIFF/EPS/PDF with fonts embedded, at required resolution
- All exhibits numbered and referenced in order
Anti-patterns
- A size table without the nominal level, so over-/under-rejection cannot be judged
- Notes that require the reader to hunt through the text to decode the columns
- Cherry-picked DGPs hiding the regime where the method underperforms
- Raster figures at low dpi that blur at print reduction
- 3D bars or rainbow palettes obscuring a simple size/power comparison
Exhibit pass for Econometric Theory
Treat this skill as an executable review pass, not a prose hint. First lock the primitive assumptions, theorem statement, proof route, and example showing why the result matters; then judge whether the current manuscript answers the venue's real reader: econometric theorists who read for assumptions, theorem novelty, proof architecture, and relation to known asymptotics.
- Do the pass: For every table or figure, state the estimand or object, sample or case base, uncertainty display, and one sentence the exhibit proves for the venue audience.
- Return a ledger: give
claim / evidence / risk / manuscript locationrows, so the next agent can edit rather than rediscover the issue. - Sibling guard: compare against Journal of Econometrics for applied-method reach, Quantitative Economics for theoretical economics, Econometrica for general theory-plus-economics contribution; if a sibling owns the contribution, recommend re-routing before polishing format.
- Stop condition: do not give submission-ready advice until the pack's
resources/official-source-map.mdhas been checked for volatile rules and the manuscript has one concrete fix for the largest venue-specific risk.
Output format
【Exhibit】size / power / coverage / bias-RMSE / distribution / rate plot
【Self-contained note】DGP + n + reps + level stated? [Y/N]
【Benchmark shown】[Y/N]
【Legible at 50%】[Y/N]
【File format】TIFF / EPS / PDF, fonts embedded? [Y/N]
【Next step】ectheory-writing-style