jle-identification
Use when the causal identification argument is the bottleneck for a The Journal of Law and Economics (JLE) manuscript — a law change (DiD/event study), a court/judge/case-assignment design, a regulatory threshold (RD), or an antitrust/enforcement event. Stress-tests the law-to-outcome mapping to the JLE credibility bar before exhibits are finalized; it does not write the prose or build the deposit.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jle-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 (jle-identification) ## When to trigger - A causal claim about a legal rule rests on OLS + controls, or TWFE on staggered statute adoption - A court/judge design's random-assignment defense, monotonicity, or exclusion is not pinned down - A regulatory threshold's density, bandwidth, or bunching response is unaddressed - An antitrust/enforcement event study has contaminated windows or no clean control market - You are unsure the design clears JLE's law-and-economics credibility bar ## The JLE identification bar JLE judges identification through a **law-and-economics lens**: the **mapping from a legal/regulatory source of variation to the causal estimand must be explicit, defended, and consistent with how the rule actually operates**. Referees here are economists who also know the institution — they will ask whether the statute really bound when you say, whether enforcement varied, whether the "control" jurisdiction had its own contemporaneous reform. State the estimand, name the identifying assumption, show the diagnostic that could have failed, and keep the claim inside what the legal design supports. Inference must match the design (cluster at the level o
- When to trigger
- The JLE identification bar
- Design paths
- Path A: Law change / staggered statute adoption (DiD / event study)
- Path B: Court / judge / case-assignment design (IV or as-good-as-random)
- Path C: Regulatory threshold / eligibility cutoff (RD / bunching)
- Path D: Antitrust / enforcement event (merger, decree, entry, ruling)
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Getting the legal timing and bindingness right (the JLE-specific failure)
- Worked vignette (illustrative)
- Referee pushback mapped to the identification fix
- Output format
What does the jle-identification skill do?
Use when the causal identification argument is the bottleneck for a The Journal of Law and Economics (JLE) manuscript — a law change (DiD/event study), a court/judge/case-assignment design, a regulatory threshold (RD), or an antitrust/enforcement event. Stress-tests the law-to-outcome mapping to the JLE credibility bar before exhibits are finalized; it does not write the prose or build the deposit.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jle-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.