Individual skill
jae-data-analysis
Use when running and reporting the empirical analysis for a Journal of Accounting and Economics (JAE) manuscript — building the archival sample, choosing fixed effects and clustered standard errors, executing the identification design, and demonstrating robustness for large-sample capital-markets/contracting/disclosure data. Executes and reports the analysis; it does not design the study (jae-methods) or frame the contribution (jae-contribution-framing).
Journal-of-Accounting-and-Economics-Skills/skills/jae-data-analysis/SKILL.md
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- Last checked
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# Data Analysis & Inference for JAE (jae-data-analysis)
## When to trigger
- The sample is built and it is time to estimate and report
- You are unsure how to specify fixed effects or cluster standard errors
- Reviewers will probe endogeneity, correlated omitted variables, or sample selection
- A reviewer says "the standard errors are understated" or "this is not identified"
## Build and document the archival sample first
JAE reviewers expect a transparent **sample-construction waterfall**: starting population (e.g., Compustat firm-years), each merge (CRSP, I/B/E/S, Execucomp, DealScan, Audit Analytics via WRDS), each exclusion (financials/utilities, missing data, penny stocks), and the final N at every step. Report descriptive statistics and a correlation table. **Winsorize** continuous variables (commonly at 1%/99%) and say so.
## Specify the estimator to match the panel and the design