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.