jru-identification
Use when identifying a risk or uncertainty parameter is the bottleneck for a Journal of Risk and Uncertainty (JRU) manuscript — incentive-compatible elicitation in an experiment, or structural/empirical estimation of risk preferences, VSL, or insurance demand. Stress-tests how the data pin the primitive; it does not invent evidence or citations.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jru-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 (jru-identification) ## When to trigger - An experiment elicits a risk or ambiguity attitude but the mechanism may not be **incentive-compatible** (truthful revelation in doubt) - A choice-list / BDM / matching-probability design is used and a referee questions whether it measures the parameter cleanly - A structural model is estimated on field data and it is unclear *what variation* identifies the risk parameter (vs. beliefs, vs. constraints) - A VSL or insurance-demand estimate rests on regressions whose exclusion or selection assumptions are not defended ## The JRU identification bar At JRU "identification" means the **mapping from choices to the risk/uncertainty primitive** must be explicit and defended — whether that primitive is elicited in the lab or estimated from the field. Because the journal spans theory, experiment, and empirics, identification splits by branch. The unifying demand: the procedure must reveal the *intended* parameter and not confound it with utility curvature, beliefs, or constraints. ### Branch A: Experimental elicitation of risk / ambiguity preferences - **Incentive compatibility.** State the mechanism and why it elicits truth
- When to trigger
- The JRU identification bar
- Branch A: Experimental elicitation of risk / ambiguity preferences
- Branch B: Structural / empirical estimation (risk preferences, VSL, insurance)
- The confounds JRU referees probe most
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Referee pushback mapped to the identification fix
- Worked vignette (illustrative)
- Second vignette: separating curvature from weighting (illustrative)
- Stating what is NOT identified
- Output format
What does the jru-identification skill do?
Use when identifying a risk or uncertainty parameter is the bottleneck for a Journal of Risk and Uncertainty (JRU) manuscript — incentive-compatible elicitation in an experiment, or structural/empirical estimation of risk preferences, VSL, or insurance demand. Stress-tests how the data pin the primitive; it does not invent evidence or citations.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jru-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.