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Econometrics skill for creating publication-quality LaTeX regression and summary tables. Activates when the user asks about: "regression table", "LaTeX table", "esttab", "stargazer", "modelsummary", "publication table", "format results", "multi-panel table", "journal table", "export regression results", "table formatting", "回归表格", "LaTeX表格", "结果导出", "论文表格", "回归结果格式化", "多模型表格"
Passed 22 of 23 test cases with the skill, and 16 of 23 without it.
and 3 more in the full report
6 fixed16 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
When generating LaTeX tables programmatically for co-authors who use diverse TeX installations, what decimal alignment strategy should be used to avoid missing package compilation errors caused by packages like siunitx?
| Checked | Without skill | With skill |
|---|---|---|
| Avoids siunitx column types such as S in LaTeX output. | Passed | Passed |
| Uses dcolumn (D{.}{.}{-1}) or standard c columns for numerical data. | Missed | Passed |
The instructions your model reads when the skill loads.
This skill generates publication-quality regression tables, summary statistics tables, and multi-panel layouts for economics journals. Covers the major table-making tools: esttab/estout (Stata), modelsummary/fixest::etable (R), and stargazer (R/Python).
| Tool | Language | Best For |
|---|---|---|
esttab/estout | Stata | Most flexible; Stata-native workflows |
modelsummary | R | Modern, clean API; many output formats |
fixest::etable | R | Fast tables from fixest regressions |
stargazer | R | Classic; widely used in econ |
statsmodels summary + manual | Python | Custom formatting |
* Stata — multi-model regression table
ssc install estout
* Run models
eststo clear
eststo m1: reg y x1, robust
eststo m2: reg y x1 x2, robust
eststo m3: reg y x1 x2 x3, robust
eststo m4: reghdfe y x1 x2 x3, absorb(fe_var) cluster(cluster_var)
* Export to LaTeX
esttab m1 m2 m3 m4 using "results.tex", replace ///
b(3) se(3) /// // 3 decimal places
star(* 0.10 ** 0.05 *** 0.01) /// // significance stars
title("Main Results") ///
mtitles("OLS" "OLS" "OLS" "FE") /// // column titles
label /// // use variable labels
keep(x1 x2 x3) /// // show only key vars
order(x1 x2 x3) ///
stats(N r2 r2_a, fmt(%9.0fc %9.3f %9.3f) ///
labels("Observations" "R-squared" "Adj. R-squared")) ///
test cases passed, vs 16 / 23 without
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