From jeem-skills
Builds a targeted robustness suite for JEEM manuscripts, checking whether headline estimates (damage, WTP, pass-through, treatment effect) survive specification, spatial, sample, and inference choices.
How this skill is triggered — by the user, by Claude, or both
Slash command
/jeem-skills:jeem-robustnessThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- The main estimate is in hand and you must show it is not a one-specification artifact
JEEM referees probe whether the welfare-relevant number is stable, spatially honest, and not the product of researcher degrees of freedom. Robustness here is not a wall of regressions — it is a targeted set of checks each tied to a specific threat, several of which are distinctively environmental. Map every plausible objection to the one check that answers it, and report so the reader sees the estimate barely moves.
| Threat to the result | The check that answers it |
|---|---|
| Spatial correlation in errors | Conley spatial SEs; vary the cutoff distance; cluster on geography |
| Hedonic market / buffer definition | vary the buffer radius, the boundary band, the housing-market boundary |
| Omitted amenities / sorting | parcel/boundary FE; amenity controls in steps; Oster δ for selection |
| Staggered-DiD bias | Callaway–Sant'Anna or Sun–Abraham; honest-DiD pre-trend bounds |
| Weather/climate aggregation | alternative bins/degree-days; alternative gridded products; placebo seasons |
| Monitor/station selection | reweight by coverage; restrict to dense-monitor areas; interpolation sensitivity |
| Valuation functional form | semi-log vs. Box–Cox hedonic; mixed-logit vs. conditional logit; WTP-space estimation |
| Inference too narrow | correct clustering level; wild-cluster bootstrap (few units); randomization inference |
| Multiple outcomes/subgroups | Romano–Wolf / List–Shaikh–Wooldridge MHT adjustment |
Three checks are close to mandatory at JEEM and should appear in the main results, not the appendix:
A paper that omits all three reads as not knowing the field's standards, regardless of how many other columns the robustness table has.
A pollution-mortality estimate is 3.1 deaths per 100k per unit (s.e. 0.9, default SEs). The suite: (i) Conley SEs at a 100 km cutoff widen the CI but keep it from zero; (ii) re-binning the pollution exposure barely moves the point estimate; (iii) restricting to dense-monitor counties yields 3.0; (iv) an honest-DiD bound on the staggered regulation pre-trend leaves the sign intact; (v) Oster δ implies selection on unobservables would need to be 2× selection on observables to nullify it. The welfare number barely moves — the JEEM target.
Each emphasis answers the threat that is first-order for that branch — do not spend the robustness budget on generic checks while the branch's signature worry goes unaddressed.
【Journal】Journal of Environmental Economics and Management
【Skill】jeem-robustness
【Primary spec】declared? [Y/N] — estimate: ___ (s.e. ___)
【Threat → check map】spatial: ___ | market-def: ___ | sorting: ___ | weather-agg: ___ | inference: ___
【Spatial inference】Conley cutoff / clustering: ___
【Design sensitivity】honest-DiD / RD bandwidth / weak-IV set: ___
【Estimate stability】range across checks: [___, ___]; checks that move it: ___
【Source status】verified URL / 待核实 / not asserted
【Next skill】jeem-tables-figures
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin jeem-skillsBuilds a spatially-aware robustness suite for JUE manuscripts, testing stability of estimates across spatial scale, boundaries, sorting, spillovers, and inference choices.
Organizes robustness checks for JEEA manuscripts around threats a general-interest referee would raise, ensuring headline results are stable to specification, sample, inference, and assumption perturbations.
Builds robustness suites for AEJ: Applied manuscripts to show headline estimates survive specification, sample, and inference choices.