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joe-tables-figures

joe-tables-figures

Use when building the Monte Carlo tables and theory-illustrating figures for a Journal of Econometrics (JoE) manuscript. Covers size/power table conventions, estimator-comparison layout, and figures that make asymptotic and finite-sample behavior legible.

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name: joe-tables-figures description: Use when building the Monte Carlo tables and theory-illustrating figures for a Journal of Econometrics (JoE) manuscript. Covers size/power table conventions, estimator-comparison layout, and figures that make asymptotic and finite-sample behavior legible.

Tables & Figures (joe-tables-figures)

When to trigger

  • Monte Carlo results exist but the tables are dense, unlabeled, or hard to compare across methods
  • Size and power are mixed into one block so distortion is invisible
  • Figures show output but not the behavior the theorems predict (rates, coverage, distributions)
  • You are formatting exhibits for a PDF-only initial submission and want them print-legible

What JoE exhibits must do

At the Journal of Econometrics the exhibits are the empirical backbone of a methods paper: they have to let a referee verify, at a glance, that the estimator is well-behaved and the test controls size. Initial submission is a single PDF (~40 pages, ≥1.5 spacing, 11pt), so tables and figures must be readable inline at that density; structured formatting and source files are handled at revision/acceptance. Build self-contained exhibits whose notes state the DGP, sample sizes, replication count, and nominal level.

Monte Carlo table conventions

  • Separate size from power. Report empirical size at nominal 5%/10% in its own panel; report size-adjusted power separately so a size-distorted test cannot masquerade as powerful.
  • One method per column (or panel), one DGP/$n$ per row block. The reader should compare your method to the nearest competitor down a column without hunting.
  • Report bias, RMSE, and CI coverage for estimators; mark the best in each row if it aids reading.
  • Notes are mandatory: DGP description, error distribution, dependence structure, $n$, replication count, and any tuning values. A referee should reproduce the table's meaning from the note alone.
  • Keep decimal places consistent; do not over-report precision that the replication count cannot support.

Figures that illustrate theory

  • Size/power curves across the parameter; coverage vs. $n$ to show asymptotics kicking in; QQ plots or densities of the standardized statistic against its limiting distribution.
  • Sensitivity plots over tuning parameters (bandwidth, lag length, penalty) to show robustness.
  • Plot confidence bands / Monte Carlo error; avoid chartjunk (no 3D, minimal color, legible at print size).
  • Use vector output (PDF/EPS) so exhibits stay crisp; ensure they survive grayscale printing.

Formatting notes

  • Number tables and figures, call them out in order, and give each a self-contained caption.
  • Math in captions/notes in LaTeX via the elsarticle class for consistency with the manuscript.
  • At submission everything lives in the single PDF; keep source and high-res files staged for acceptance.

Execution bridge (StatsPAI / Stata MCP)

Generate exhibits from the fitted result, not by retyping numbers. Full map: execution-with-mcp. Journal of Econometrics is a methods venue — estimator validity + simulation evidence are the contribution; pair estimates with diagnostics and Monte-Carlo where relevant.

  • 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.

Anti-patterns

  • A 12-column table with no row/column grouping and no notes
  • Power reported without empirical size (size-distorted power is meaningless)
  • Tuning-parameter sensitivity omitted, hiding fragility
  • Figures with default software styling, illegible in grayscale, or missing Monte Carlo error
  • Over-precise decimals implying accuracy the replication count cannot deliver

Output format

【Size table】separate panel, nominal 5%/10%? [Y/N]
【Power table】size-adjusted, vs. nearest method? [Y/N]
【Estimator table】bias / RMSE / coverage? [Y/N]
【Notes】DGP / n / reps / tuning stated? [Y/N]
【Theory figures】coverage-vs-n / power curves / limiting-dist check? [list]
【Print quality】vector, grayscale-safe, legible in single PDF? [Y/N]
【Next step】joe-writing-style
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