| name | mksc-tables-figures |
| description | Use when building the exhibits for a Marketing Science manuscript — estimate tables, model-fit tables, comparative-statics figures, and counterfactual/policy-simulation exhibits in INFORMS house style. Designs the exhibits; it does not run the estimation (mksc-data-analysis) or write the prose (mksc-writing-style). |
Tables & Figures (mksc-tables-figures)
When to trigger
- Estimate or counterfactual tables are cluttered or not self-explanatory
- Comparative statics / elasticities are buried in text instead of an exhibit
- A figure does not make the model's mechanism or policy result legible
- Exhibits are off INFORMS house style
The exhibits a modeling paper needs
A Marketing Science paper is read through its model and its counterfactuals, so the core exhibits differ from an experiments paper:
- Estimates table. Structural parameters (preferences, dynamics, supply) with standard errors; group by demand vs. supply; label normalizations. Report elasticities (own/cross-price) and implied margins, not just raw coefficients.
- Model-fit table/figure. Predicted vs. actual moments/shares/prices; in-sample and holdout. Make goodness-of-fit visible.
- Comparative-statics figure (analytical papers). Plot how equilibrium prices/profit/advertising move with the key parameter; annotate the counterintuitive region that is the contribution.
- Counterfactual/policy table. Baseline vs. counterfactual outcomes (prices, shares, profit, consumer surplus/welfare) with uncertainty intervals; decompose the driving mechanism.
- Identification/sensitivity exhibit where helpful (sensitivity of estimates to moments; first-stage strength).
INFORMS house style
- Number tables and figures consecutively; give each a self-contained caption that states the model/sample and what the reader should conclude.
- Define every symbol and notation used; report units and the estimand.
- Note the estimator and standard-error type in the table notes (e.g., "GMM; standard errors in parentheses").
- Keep figures clean and grayscale-legible; the model's intuition should survive black-and-white printing.
- Heavy supporting exhibits (full parameter sets, additional counterfactuals, derivations) belong in the online appendix to keep the main text succinct.
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. Marketing Science is heavily structural/analytical; the chain below serves its reduced-form / field-experiment lane — structural demand and analytical modeling are outside this causal-inference toolchain.
- Tables:
etable (multi-model columns) 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 effect size in
interpretable units.
See a full fitted-result → exhibit chain in the JF execution walkthrough.
Checklist
Anti-patterns
- A coefficient dump with no elasticities, margins, or interpretation.
- Counterfactual numbers with no uncertainty or baseline comparison.
- Figures relying on color that vanish in grayscale.
- Captions that name the table but not the conclusion.
Exhibit pass for Marketing Science
Treat this skill as an executable review pass, not a prose hint. First lock the demand/supply mechanism, fit evidence, and counterfactual decision margin; then judge whether the current manuscript answers the venue's real reader: quantitative marketing reviewers who read the model through the managerial counterfactual it makes possible.
- 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 location rows, so the next agent can edit rather than rediscover the issue.
- Sibling guard: compare against Journal of Marketing Research for empirical marketing breadth, Management Science for wider OR/MS reach, Quantitative Marketing and Economics for specialist modeling; 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.md has been checked for volatile rules and the manuscript has one concrete fix for the largest venue-specific risk.
Output format
【Estimates】params + elasticities/margins; SEs + estimator in notes
【Fit】predicted vs actual (in-sample/holdout) exhibit present?
【Comparative statics】figure for analytical claim, annotated?
【Counterfactual】baseline vs policy + uncertainty + mechanism
【Style】notation defined; captions self-contained; grayscale-safe
【Appendix】secondary exhibits relocated
【Next step】mksc-writing-style
