jbf-data-analysis
Use when building or auditing the empirical data and estimation pipeline for a Journal of Banking & Finance manuscript, including financial datasets, bank panels, winsorization, fixed effects, robustness, and reproducible scripts.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jbf-data-analysis --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.
# Data Analysis (jbf-data-analysis) ## When to trigger - You are constructing the sample, variables, or estimation pipeline - Results need robustness, heterogeneity, mechanism, or economic-magnitude checks - Proprietary finance datasets require a reproducible but non-redistributable workflow ## Data construction 1. **Document every source**: CRSP, Compustat, Call Reports, BankFocus, Dealscan, TRACE, OptionMetrics, FDIC, SEC EDGAR, FRED, or private hand-collected data. 2. **Define the unit of observation**: bank-quarter, firm-year, loan facility, security-day, country-year, event-firm, etc. 3. **Show sample attrition**: raw data, filters, merges, missing variables, winsorization, final sample. 4. **Name variable construction rules**: scaling, deflation, lagging, exchange rates, identifiers, and industry/bank classifications. 5. **Separate proprietary raw data from shareable code** so the replication package can be legal and useful. ## Estimation checklist - Use fixed effects and clustering that match the design. - Report economic magnitudes in finance units: basis points, percentage of assets, capital ratio points, loan-spread basis points, abnormal returns, default odds. - Provide
- When to trigger
- Data construction
- Estimation checklist
- Reproducibility
- Bank-panel stress checks
- Dataset-to-question matrix
- Worked sample build (illustrative)
- Pipeline skeleton
- Economic-magnitude benchmarks for bank panels
- Referee data pushbacks
- Execution bridge (StatsPAI / Stata MCP)
- Output format
What does the jbf-data-analysis skill do?
Use when building or auditing the empirical data and estimation pipeline for a Journal of Banking & Finance manuscript, including financial datasets, bank panels, winsorization, fixed effects, robustness, and reproducible scripts.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill jbf-data-analysis --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.