Agent skill · Data & Analytics

jpube-tables-figures

Use when designing the exhibits for a Journal of Public Economics (JPubE) manuscript — bunching density plots, event-study and RD/RKD graphs, incidence and distributional figures, and self-contained tables. Makes the public-finance design visible; it does not run the analysis (use jpube-data-analysis).

brycew6m4,252★ · +31/wk · 3 repos on radarProfile →
claude-codeMIT
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jpube-tables-figures --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Path: Journal-of-Public-Economics-Skills/skills/jpube-tables-figures/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 909 · +31 this week
Language: Stata
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Tables & Figures (jpube-tables-figures) ## When to trigger - The identifying variation is buried in a regression table instead of shown in a graph - A bunching, RD, or event-study result has no picture - Tables are dense, under-noted, or not callable in order - You need exhibits that make a policy elasticity legible to a referee ## Why figure-forward at JPubE JPubE's identification often *is* a picture — a spike of excess mass at a tax kink, a jump at an eligibility cutoff, a clean break at a reform date. Because referees are public-finance specialists assessing design credibility, **the headline of a JPubE empirical paper is frequently one transparent graph** that lets the reader see the response before any regression. Build exhibits so the design is self-evident. ## Exhibit norms - **Lead with the design figure.** Bunching: observed density vs. smooth counterfactual around the kink/notch, with the excluded region marked. RD/RKD: binned scatter with the fitted discontinuity/kink and CIs. DID: event-study plot with leads and zero-line. - **Show, then estimate.** A figure that makes the response visible earns more trust than a coefficient; the table quantifies what the figure show

What's inside
Steps it walks through
  1. When to trigger
  2. Why figure-forward at JPubE
  3. Exhibit norms
  4. Execution bridge (StatsPAI / Stata MCP)
  5. Checklist
  6. Anti-patterns
  7. Lead-figure choice by design (decision grid)
  8. Exhibit pass for Journal of Public Economics
  9. Output format
More from Awesome-Journal-Skills
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About this skill
What does the jpube-tables-figures skill do?

Use when designing the exhibits for a Journal of Public Economics (JPubE) manuscript — bunching density plots, event-study and RD/RKD graphs, incidence and distributional figures, and self-contained tables. Makes the public-finance design visible; it does not run the analysis (use jpube-data-analysis).

How do I install it?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jpube-tables-figures --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going