wber-identification
Use when the causal identification argument is the bottleneck for a The World Bank Economic Review (WBER) manuscript — RCT/program evaluation, DiD/event study around a reform, regression discontinuity, or IV in a developing-country setting. Stress-tests the data-to-estimate mapping AND the external-validity/policy-interpretation step to the WBER bar; it does not write prose or build the package.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill wber-identification --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Identification Strategy (wber-identification) ## When to trigger - A causal claim rests on OLS + controls, or TWFE on staggered reform timing - An RCT's estimand, balance, attrition, or spillover handling is not pinned down - An RD's density, bandwidth, or covariate-smoothness defense is missing - An IV's first stage is weak or the exclusion restriction is asserted, not argued - The design is clean but the *policy interpretation* (scale-up, GE, fiscal cost) is missing ## The WBER identification bar WBER demands the **same identification rigor as a top applied-micro field journal** — and then one more thing that siblings let slide: the **mapping from the local causal estimate to a development-policy lesson** must be argued, not assumed. A pristine ITT from one trial is necessary but not sufficient; the WBER referee asks "what does this imply for a finance ministry deciding whether to scale this?" So state the estimand, name the identifying assumption, show the diagnostic that could have failed, **and** address external validity, general equilibrium, and scaling. Inference must match the design (clustering at the assignment level; few-cluster corrections). Report standard errors an
- When to trigger
- The WBER identification bar
- Design paths
- Path A: RCT / program evaluation (own or admin data)
- Path B: Difference-in-differences / event study around a reform
- Path C: Regression discontinuity (eligibility thresholds, geographic borders)
- Path D: IV / shift-share
- The external-validity layer (the WBER differentiator)
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Referee pushback mapped to the identification fix
- Worked vignette (illustrative)
- Output format
What does the wber-identification skill do?
Use when the causal identification argument is the bottleneck for a The World Bank Economic Review (WBER) manuscript — RCT/program evaluation, DiD/event study around a reform, regression discontinuity, or IV in a developing-country setting. Stress-tests the data-to-estimate mapping AND the external-validity/policy-interpretation step to the WBER bar; it does not write prose or build the package.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill wber-identification --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.