Skills Data Science Statistical Reporting for Econometric Journals

Statistical Reporting for Econometric Journals

v20260724
joe-tables-figures
A comprehensive guide detailing the rigorous standards for generating tables and figures intended for top-tier econometrics journals, such as the Journal of Econometrics (JoE). It covers best practices for Monte Carlo simulations, separating size and power reporting, comparing multiple estimators, and ensuring all exhibits are statistically rigorous, reproducible, and legible in a single-PDF print format.
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Overview

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
Info
Category Data Science
Name joe-tables-figures
Version v20260724
Size 4.53KB
Updated At 2026-07-28
Language