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jbes-identification-strategy

Use when the methodological core of a Journal of Business & Economic Statistics (JBES) paper is the bottleneck — assumptions, regularity conditions, asymptotic theory, and Monte Carlo design for a new estimator, test, or algorithm. Stress-tests the method's validity, not a causal design.

Journal-of-Business-and-Economic-Statistics-Skills/skills/jbes-identification-strategy/SKILL.md

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# Method Validity & Asymptotics (jbes-identification-strategy)

## When to trigger

- The estimator/test is proposed but its assumptions and limiting theory are not nailed down
- The asymptotic distribution, consistency, or rate is asserted without full conditions
- The Monte Carlo design does not yet show where the method holds and where it breaks
- For an applied paper, what parameter your method identifies (and under what conditions) is unclear

## What "identification" means at a methods journal

At JBES the load-bearing question is usually not a causal-design story but **whether the method delivers valid inference for its target under stated conditions**. Because JBES demands methodological novelty with **clear empirical relevance**, the assumptions cannot be so strong that no real data set — including the paper's own application — satisfies them. The credibility ladder a referee applies, strongest first:

1. **Identification of the target** — the parameter/functional is identified from the population moments the method uses, under stated conditions.