From jpube-skills
Estimates behavioral elasticities, welfare parameters (DWL, MVPF), and heterogeneity using administrative microdata for JPubE manuscripts. Handles bunching, RD/RKD, and sufficient-statistics mapping.
How this skill is triggered — by the user, by Claude, or both
Slash command
/jpube-skills:jpube-data-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- You are estimating a behavioral elasticity, take-up rate, or moral-hazard parameter
Public economics at JPubE is typically built on large administrative or register data — tax records (IRS/SOI), social-insurance files (UI/DI/SSA), health-program data (Medicaid/CMS), or whole-population European registers — because credible policy elasticities need population-scale variation around kinks, notches, and reform dates. The analysis should convert clean identification into a policy-relevant quantity, not stop at a coefficient.
A DI-reform evaluation recovers a labor-supply response to a benefit cut, then builds the MVPF: the mechanical fiscal saving is the denominator; the behavioral fiscal externality (induced earnings → recovered taxes, minus crowd-out) adjusts the numerator, giving MVPF ≈ 0.8 (illustrative). The skill's norms then bind: state the primitives held fixed (no GE wage response, fixed program rules); propagate the elasticity's SE through the MVPF by the delta method, reporting a CI on the welfare object; and show how MVPF moves if the key elasticity sits at the high or low end of the literature. The welfare statistic with its uncertainty — not the bare elasticity — is the deliverable.
| Estimated object | Welfare mapping | Watch for |
|---|---|---|
| Taxable-income elasticity | Marginal DWL / optimal top rate | Mean reversion, income shifting |
| Take-up / benefit response | MVPF numerator + denominator | Crowd-out onto other programs |
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.
claim / evidence / risk / manuscript location rows, so the next agent can edit rather than rediscover the issue.resources/official-source-map.md has been checked for volatile rules and the manuscript has one concrete fix for the largest venue-specific risk.【Data】source + restricted? + disclosure handled? [Y/N]
【Policy parameter】elasticity / take-up / crowd-out / moral-hazard wedge
【Welfare mapping】DWL / MVPF / sufficient stat — SEs propagated? [Y/N]
【Measurement choices】[income def, top-coding, rule coding, ...]
【Heterogeneity】policy margin: [...]
【Robustness done】[bin/bandwidth/estimator/sensitivity, ...]
【Next step】jpube-tables-figures
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin jpube-skillsStress-tests causal identification strategies for JPubE manuscripts against public-finance norms before drafting tables.
Builds a transparent welfare, cost-benefit, or optimal-policy framework from reduced-form causal estimates for AEJ: Economic Policy manuscripts.
Guides estimation, cost-benefit, and distributional analysis for JPAM manuscripts. Reports effects in policy-relevant units with robustness and honest uncertainty.