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Jel tables figures

Skill brycewang-stanford/Awesome-Journal-Skills/Journal-of-Economic-Literature-Skills/skills/jel-tables-figures

Use when building exhibits for a Journal of Economic Literature (JEL) survey — summary "who-found-what" tables, conceptual/framework figures, and meta-evidence exhibits that synthesize across studies. Designs survey exhibits; it does not produce original-estimate regression tables (a JEL survey reports no new estimates of its own).From its SKILL.md

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npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill jel-tables-figures

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SKILL.md

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Tables & Figures for a Survey (jel-tables-figures)

When to trigger

  • The synthesis is done and the reader needs to see the field at a glance
  • A controversy or a body of estimates would be clearer as a table than as prose
  • The organizing framework would land better as a diagram
  • You are tempted to paste a regression table — but this is a survey, not a primary paper

The three exhibit types a JEL survey actually uses

JEL exhibits summarize across the literature; they do not present the author's own estimation. The workhorses:

ExhibitPurposeDesign notes
Who-found-what summary tableone row per study (or per design class): question/estimand, method, sample, finding (direction + magnitude), credibility noterows ordered by the framework's cells, not chronology; columns let the reader compare comparable objects
Conceptual / framework figurerender the organizing spine — taxonomy tree, mechanism diagram, the simple unifying modelthis is often the survey's signature exhibit; it should be restate-able from memory
Meta-evidence exhibita forest-style plot or funnel of effect sizes, a timeline of methods, a coverage mapuse only when the estimates are commensurable; otherwise it manufactures false consensus

Building a credible summary table

  • Compare like with like. Group studies that estimate the same object; never put non-comparable estimands in one magnitude column (the cross-study version of the pooling error from jel-literature-synthesis).
  • Carry uncertainty and credibility. A finding column without a credibility/identification note invites a referee to ask "but how good is that study?" — answer it in the table.
  • Self-contained captions. A JEL exhibit is read on its own; the caption states what the table shows, the unit, and how to read a row, and points to the source studies.
  • Source every cell. Each entry traces to a paper in the evidence matrix; a survey table with an unsourced number is indefensible.

Meta-analysis caution

If you assemble effect sizes into a quantitative synthesis (forest plot, meta-regression), you are doing a meta-analysis, with all its assumptions — comparable estimands, publication-bias diagnostics, weighting. Only do this where the literature genuinely supports it; otherwise a qualitative who-found-what table is more honest than a spurious pooled number. JEL readers include the methodologists who would catch an invalid pooling.

Reproduced vs. re-drawn figures

When a figure from a surveyed paper is central, prefer a re-drawn synthesis figure (your own panel that places several studies on common axes) over copying one paper's exhibit. A re-drawn figure serves the survey's argument and avoids the consensus-by-accident of reprinting whichever paper had the prettiest chart; if you do reproduce an original figure, attribute it and secure any permission the AEA style guide requires.

Checklist

  • Each exhibit synthesizes across studies (no original-estimate regression output)
  • Summary-table rows ordered by the framework's cells; only comparable estimands share a column
  • Finding columns carry a credibility/identification note, not bare point estimates
  • The conceptual figure renders the organizing spine and is restate-able from memory
  • Any meta-evidence plot pools only commensurable estimates; bias diagnostics noted
  • Captions are self-contained (what / unit / how to read a row / sources)
  • Every cell sources to a paper in the evidence matrix
  • Exhibits are placed where the argument needs them, sized for readability in print

Anti-patterns

  • Pasting a regression table of the author's own new estimates — a survey reports no new results
  • A who-found-what table that pools incomparable estimands into one magnitude column
  • A forest plot implying a pooled consensus the literature does not support
  • Finding columns with no credibility note (every reader then asks "is that study any good?")
  • Decorative figures that do not encode the framework
  • Exhibits whose captions require the body text to be intelligible

Output format

【Exhibit set】<list: summary tables / conceptual figure / meta-evidence>
【Summary table】rows by framework cell; comparable estimands only? Y/N
【Credibility column】present for every finding? Y/N
【Conceptual figure】renders the spine; restate-able from memory? Y/N
【Meta-evidence】pools only commensurable estimates (or omitted)? Y/N
【Sourcing】every cell traces to the evidence matrix? Y/N
【Next step】→ jel-writing-style (weave exhibits into the synthesis prose)

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