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robustness-table

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Generates robustness check code and formats results as a combined table. Use for sensitivity analysis.

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Source SKILL.md: https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills/blob/HEAD/skills/29-quarcs-lab-project20XXy/dot-claude/skills/robustness-table/SKILL.md

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Generate Robustness Checks and Table

Given a baseline regression, generate code for standard robustness checks and format the results as a publication-ready table.

Arguments

  • $ARGUMENTS — notebook reference and baseline specification description (e.g., "notebook-02 baseline OLS with GDP on life expectancy")

Steps

  1. Read the specified notebook and locate the baseline regression:

    • Look for estimation commands (Python: statsmodels, linearmodels; R: lm, fixest, felm; Stata: reg, reghdfe, ivregress)
    • Identify the dependent variable, independent variables, fixed effects, and clustering

  2. Ask the user which robustness checks to include:

    • Alternative control variable sets (drop/add controls)
    • Alternative fixed effects specifications
    • Different standard error clustering levels
    • Subsample analysis (e.g., by region, time period, income group)
    • Winsorized or trimmed dependent variable
    • Alternative dependent variable (e.g., log vs level)
    • Placebo tests (randomized treatment, pre-period outcome)
    • Alternative estimation methods (e.g., OLS vs Poisson, logit vs probit)

  3. Generate code cells in the notebook for each robustness specification:

    • Each cell should be self-contained (loads data, runs regression, stores results)
    • Use consistent variable naming for results collection

  4. Create a summary cell that collects all results into a single table:

    • Cell directive: #| label: tbl-robustness (or *| for Stata)
    • Cell directive: #| tbl-cap: "Robustness checks" (or *| for Stata)
    • Format: baseline in column (1), each robustness check in subsequent columns
    • Follow academic conventions: coefficient (SE), significance stars, N, R², FE indicators
    • Stata caveat: Do NOT use tbl- prefix for Stata text output — use a plain label (e.g., stata-robustness)

  5. Optionally export the table to tables/ as a standalone file (LaTeX or CSV)

  6. Sync the Jupytext pair:

    uv run jupytext --sync notebooks/<name>.md

  7. Show the embed shortcode for index.qmd:

    {{< embed notebooks/<name>.ipynb#tbl-robustness >}}

Error handling

  • If the baseline regression is not found, ask the user to point to the specific cell.
  • If the notebook uses a language not recognized, ask for guidance on the estimation syntax.