tar-data-analysis
Use when running and reporting the estimation for a The Accounting Review (TAR) manuscript — the estimator, fixed effects, standard-error clustering, robustness, and the data-authenticity / code-access documentation TAR requires. Executes and reports the analysis; it does not design identification (tar-methods) or frame the contribution (tar-contribution-framing).
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tar-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.
# Estimation, Robustness & Data Authenticity (tar-data-analysis) ## When to trigger - The sample is built and it is time to estimate and report - You are unsure whether your standard errors, fixed effects, or estimator match the design - Reviewers will probe robustness, alternative measures, or sample-selection screens - You must assemble the data-authenticity / code-access package TAR requires - A reviewer says "the result is not robust" or "I cannot tell how the sample was built" ## Estimator and inference (large-sample archival core) - **Match the estimator to the design** set in `tar-methods`: OLS with high-dimensional fixed effects (firm, year, industry-year) for panel associations; DiD / staggered-DiD with a modern estimator for adoption shocks; 2SLS for endogenous regressors; RDD for threshold settings; logit/ probit/Poisson/Tobit for limited or count outcomes (e.g., restatement, going-concern, fraud). - **Cluster standard errors** at the level of treatment assignment / correlation (firm, or two-way firm-and-year); for few clusters use the wild-cluster bootstrap. - **Report fixed effects explicitly** and show how the coefficient moves as you add them — a result that survives
- When to trigger
- Estimator and inference (large-sample archival core)
- Robustness reviewers expect
- Data-authenticity & code access (a TAR-specific requirement)
- Execution bridge (StatsPAI / Stata MCP)
- Checklist
- Anti-patterns
- Output format
What does the tar-data-analysis skill do?
Use when running and reporting the estimation for a The Accounting Review (TAR) manuscript — the estimator, fixed effects, standard-error clustering, robustness, and the data-authenticity / code-access documentation TAR requires. Executes and reports the analysis; it does not design identification (tar-methods) or frame the contribution (tar-contribution-framing).
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill tar-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.