name: jpube-tables-figures description: 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).
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 shows.
- Distributional / incidence plots where the contribution is about who bears a tax or gains from a transfer.
- Self-contained notes. Each table/figure note states the sample, data source (and restricted-access caveat), the estimator, the inference (clustering level), and the units — readable without the text.
- Clean tables. Report the policy parameter (elasticity, MVPF, take-up) prominently; avoid 10-column kitchen-sink tables; put diagnostics in clearly labeled panels.
- Print quality. Vector output (PDF/EPS); legible at print size; minimal chartjunk (no 3D, restrained color); confidence bands shown.
Execution bridge (StatsPAI / Stata MCP)
Generate exhibits from the fitted result, not by retyping numbers. Full map:
execution-with-mcp. JPubE is public economics — tax/transfer/program designs; DiD/IV/RDD and bunching are central, magnitudes in policy units.
- Tables:
etable(multi-model) ordid_summary_to_latexstraight from theresult_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.
Checklist
- A design figure leads the empirical section (bunching / RD / event-study)
- The policy parameter (elasticity / MVPF / take-up) is prominent in the main table
- Every exhibit is callable in order and self-contained via its note
- Notes state sample, source + access caveat, estimator, clustering, units
- Distributional / incidence exhibit included where the contribution warrants
- Vector graphics, confidence bands shown, chartjunk removed
Anti-patterns
- Hiding a bunching or RD result inside a regression table with no plot
- Figures with no confidence bands or no marked counterfactual / excluded region
- Notes that omit the data source or the restricted-access caveat
- A 10-column main table where the key elasticity is one buried row
Lead-figure choice by design (decision grid)
The headline exhibit should let a referee see the response before any regression.
| Design | Lead figure | Must show |
|---|---|---|
| Bunching / notch | Observed vs. smooth counterfactual density | Excluded region marked, excess mass |
| RD / RKD | Binned scatter with fitted jump/kink | CIs, bandwidth, polynomial order |
| Reform DID | Event-study plot | Leads/lags, zero line, pre-trend flat |
| Incidence | Distributional bars by income/eligibility | Who bears the tax / gains the transfer |
A vignette: a draft hides a kink-bunching result (elasticity e = 0.25, illustrative) inside a six-column regression table. The exhibit fix promotes the density plot — observed mass spiking above the smooth counterfactual at the kink, excluded region shaded — to Figure 1, and demotes the regression to a quantifying table. The referee sees the identification, then reads the number.
Hedge: exact figure-count or color conventions are production matters — confirm against the current Elsevier artwork guidelines.
Exhibit pass for Journal of Public Economics
Treat this skill as an executable review pass, not a prose hint. First lock the policy instrument, affected margin, identification design, and welfare or incidence interpretation; then judge whether the current manuscript answers the venue's real reader: public economists who ask whether policy design, fiscal incidence, or welfare interpretation is credible.
- Do the pass: For every table or figure, state the estimand or object, sample or case base, uncertainty display, and one sentence the exhibit proves for the venue audience.
- Return a ledger: give
claim / evidence / risk / manuscript locationrows, so the next agent can edit rather than rediscover the issue. - Sibling guard: compare against JDE for development policy, JIE for cross-border policy, AEJ Economic Policy for broad policy readership; if a sibling owns the contribution, recommend re-routing before polishing format.
- Stop condition: do not give submission-ready advice until the pack's
resources/official-source-map.mdhas been checked for volatile rules and the manuscript has one concrete fix for the largest venue-specific risk.
Output format
【Lead figure】bunching / RD / RKD / event-study — present? [Y/N]
【Key parameter visible】elasticity / MVPF / take-up in main table? [Y/N]
【Notes self-contained】sample/source/estimator/clustering/units? [Y/N]
【Distributional exhibit】[present / not needed]
【Print quality】vector + bands + low chartjunk? [Y/N]
【Next step】jpube-writing-style