Tables & Figures — Exhibits that Carry the Policy Message (aejpol-tables-figures)
When to trigger
- Tables are dense, over-decorated with significance stars, or hard to read
- The paper lacks one exhibit a reader could take away as the policy result
- Figures show coefficients but not the policy-relevant magnitude or its uncertainty
- You are preparing the final exhibit set for an AEA submission
AEA / AEJ: Policy exhibit norms
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Report standard errors (or confidence intervals), not significance asterisks/boldface. Put SEs in parentheses below estimates; the reader judges significance from the SE/CI. This is the house convention to follow.
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Self-contained. Title and notes let an exhibit be read without the text: sample, units, estimator, clustering level, what is controlled, and what the number means in policy terms.
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Self-contained, not anonymized. Review is single-blind, so exhibits need not hide authorship; keep notes clean and neutral (avoid stray local file paths) for readability, not for blinding.
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Figures are the workhorse for policy communication: event-study plots with CIs, RDD plots with binned means and the fitted discontinuity, dose-response or cost-benefit curves with uncertainty bands. Vector output; ≥300 dpi raster only if unavoidable; readable greyscale.
The headline exhibit (AEJ: Policy-specific)
Every AEJ: Policy paper should have one exhibit a policymaker could screenshot: the policy effect in interpretable units with its welfare/cost-benefit reading where possible. Examples (illustrative formats):
- An event-study figure of the outcome around the reform, with the long-run effect annotated in policy units.
- A cost-benefit / MVPF figure: net cost per unit of outcome across policy variants, with bands.
- An incidence figure: who gains and who pays, by income/region group.
Table craft
- Three-line tables (
esttab/booktabs), no vertical rules; align decimals; consistent digits.
- Lead column = the policy-relevant specification, not a kitchen-sink spec.
- Put the policy-relevant magnitude (elasticity, cost-per-X, MVPF) in the paper's units, not only a raw coefficient; add a row translating the coefficient into the policy number where natural.
- Sample size, mean of the dependent variable, and clustering level on every table.
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.
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Tables:
etable (multi-model columns) or did_summary_to_latex straight from the
result_id — one variable definition, one set of numbers, body and appendix in sync.
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Figures:
plot_from_result / enhanced_event_study_plot / event_study_table —
axis units and the SE/clustering note baked in.
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Every note names the estimator + clustering (from the result's diagnostics) and
states the magnitude in interpretable units.
See a full fitted-result → exhibit chain in the JF execution walkthrough.
Checklist
Anti-patterns
- Significance stars and bold "***" — disallowed by AEA house style here
- A coefficient table with no translation into the policy magnitude
- A 12-column kitchen-sink table where the policy spec is buried
- Figures with point estimates but no confidence bands
- Notes too thin to read the exhibit without the text
- An exhibit whose notes are too thin to read without the body text
Exhibit-by-design-type quick guide
| Design |
Workhorse figure |
What the notes must state |
| DID / event study |
Event-study coefficients with CI bands; flat pre-period leads visible |
estimator (CS/SA), comparison group, clustering level |
| RDD |
Binned means + fitted discontinuity + bandwidth |
running variable, bandwidth, density-test result |
| Bunching |
Empirical vs. counterfactual density at the kink |
counterfactual construction, excluded region |
| RCT |
Treatment-control means / dose-response with CIs |
randomization unit, take-up, ITT vs. ToT |
| Welfare |
MVPF / cost-per-outcome across variants, with bands |
which estimates feed the ledger, assumptions |
Worked vignette (illustrative)
A tax-credit paper's main table reports a coefficient of 0.08 (s.e. 0.02) on the credit. Reworked for AEJ: Policy: the lead exhibit becomes a figure of employment around the credit's introduction with a CI band, the long-run effect annotated as "+3.1 pp employment (90% CI [1.9, 4.3])," and a companion row translating it into cost per additional job with its band — the number a policymaker takes away. No asterisks; SEs in parentheses throughout.
Output format
【Headline exhibit】figure/table + the policy magnitude it carries
【Significance reporting】SEs/CIs, no asterisks? [Y/N]
【Self-contained notes】sample/units/estimator/clustering/N/dep-mean present? [Y/N]
【Policy-units translation】coefficient → cost-per-X / MVPF / incidence shown? [Y/N]
【Next step】aejpol-writing-style