From qe-skills
Audits and builds reproducible quantitative analysis for QE manuscripts: estimation, moment construction, data cleaning, computation, and inference.
How this skill is triggered — by the user, by Claude, or both
Slash command
/qe-skills:qe-data-analysisThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
- Estimation is running but you need a disciplined plan for moments, solvers, and inference
QE is the Econometric Society's empirically/computationally oriented journal, so the analysis is judged on quantitative credibility and reproducibility together. The ES Data and Code Availability Policy (DCAS-compatible) means the ES Data Editor runs reproducibility checks before final acceptance: raw data, code, and documentation must regenerate every result in the paper and approved appendices. Build the analysis so this is true from the start, not retrofitted. House norms: report standard errors and confidence/coverage sets (no significance asterisks), and for long-running or hard-to-access computations ship simplified/manageable versions and summary output files (QE explicitly encourages this).
qe-identification-strategy).run_all) regenerating every table and figure from raw inputs.renv.lock, requirements.txt/conda, Project.toml/Manifest.toml, recorded Stata ssc/net versions.| Probe | What clears it at QE |
|---|---|
| Optimum global? | multi-start grid + objective across starts |
| Recovers truth? | Monte Carlo with known parameters; bias, coverage |
| Computation accurate? | tolerances, grid-refinement check, residual errors |
| Estimates robust? | re-estimate under alternative moments |
| Data Editor can reproduce? | one run_all, pinned environment, logged seeds |
The defining QE failure mode is numerical accuracy left unvalidated — a counterfactual reported to three digits the grid cannot support. Treat numerical error like sampling error: bound it and report it.
A paper estimates an adjustment-cost parameter by simulated method of moments, targeting investment-rate variance and serial correlation. Suppose the headline counterfactual — removing a subsidy lowers aggregate investment 8% — shifts to 5% when the grid doubles from 100 to 200 capital nodes. That 3-point swing is a numerical artifact a referee will catch. Fix: refine the grid until the counterfactual is stable, show a global minimum across 50 starts, and attach a sensitivity matrix. (Illustrative.)
【Paper type】structural / empirical / experimental / simulation
【Estimation】objective + solver/tolerances + multi-start? [Y/N]
【Validation】Monte Carlo recovery / moment fit / design diagnostics
【Inference】SEs / coverage sets (no asterisks); clustering if any
【Reproducibility】master script + pinned env + seeds? [Y/N]
【Next step】qe-tables-figures
npx claudepluginhub brycewang-stanford/awesome-journal-skills --plugin qe-skillsAssembles a QE replication package meeting Econometric Society Data Editor reproducibility checks — raw data, code, documentation, README, and exemption requests under DCAS-compatible policy.
Executes and reports analysis for Management Science manuscripts: proves analytical results or estimates/validates empirical models, with replication package preparation.
Assembles data and code replication package for Quarterly Journal of Economics manuscripts. Builds a reproducible deposit for QJE's data-availability policy.