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jole-data-analysis
Use when executing the empirical analysis for a Journal of Labor Economics (JOLE) manuscript — labor sample construction (CPS/ACS/registers), wage decompositions, standard errors, and robustness to labor norms, with replicability built in from the start. Operational guidance; pairs with jole-identification-strategy.
Journal-of-Labor-Economics-Skills/skills/jole-data-analysis/SKILL.md
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# Data Analysis (jole-data-analysis)
## When to trigger
- You are building the analysis sample from CPS/ACS/IPUMS, administrative, or register data
- You are running wage decompositions (Oaxaca / RIF) or AKM firm–worker models
- Standard errors, weighting, or robustness need to meet labor-referee expectations
- You want to make sure the empirical work will be replicable before you write it up
## Labor empirical norms at JOLE
JOLE publishes empirical / simulation / experimental labor papers **only if the data are documented and available for replication**, so build the analysis so it can be deposited later (data + programs + documentation) to the JOLE Dataverse (see jole-replication-and-data-policy). Beyond reproducibility, labor referees expect disciplined data work:
- **Sample construction is part of identification.** Document the universe, age/labor-force restrictions, top-coding handling, and how you treat zeros/imputed earnings (CPS allocation flags, ACS PUMS edits). Report sample sizes at each restriction.