# Latex Tables

> Generates publication-ready LaTeX tables produced by code (Stata `esttab`/`outreg2`, R `modelsummary`/`fixest::etable`, Python `stargazer`/`pyfixest.etable`) and writes them directly to the paper's `tabs/` folder. Defaults to DIME's "full replicability" standard (no copy-paste from any console), `booktabs` styling, three-line tables, threeparttable notes, sensible significance stars, and `\Cref{}`-friendly labels. Aligned with DIME Analytics' [Exporting Analysis](https://dimewiki.worldbank.org/Exporting_Analysis) and [Submit Table checklist](https://dimewiki.worldbank.org/Checklist:_Submit_Table). Use when the user asks for regression tables, summary statistics, balance tables, descriptive statistics, mean-comparison tables, multi-spec tables, or any code-to-LaTeX-table workflow.

- Skill: `jonasweinert/latex-tables` (Agent Skill, multi-file: 8 files)
- Install (CLI): `npx skillmds@latest add jonasweinert/latex-tables`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jonasweinert/latex-tables/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: JonasWeinert (https://skillmd.com/u/jonasweinert)
- Updated: 2026-09-22
- Page: https://skillmd.com/skills/jonasweinert/latex-tables

---


# LaTeX Tables

Generate publication-ready LaTeX tables that come out of code (`esttab`, `modelsummary`, `pyfixest.etable`, `stargazer`) and `\input{}` cleanly into the paper. The default style follows DIME's "full replicability" tier: no manual editing between code and PDF.

## Operating Principles

1. **Tables are produced, never typed.** DIME identifies four [levels of replicability](https://dimewiki.worldbank.org/Exporting_Analysis): full, good, basic, and none. "None" (copy-paste from a console window) is unacceptable for any output that leaves the analyst. Default to **full**: code writes a `.tex` file that the paper `\input{}`s directly.
2. **One source of truth per table.** Every numeric cell, star, sample size, and footnote comes from the same script that ran the regression. Never edit the `.tex` file by hand — re-run the script and rebuild the paper.
3. **`booktabs` styling.** Three horizontal rules (`\toprule`, `\midrule`, `\bottomrule`), no vertical lines, consistent decimal alignment via `siunitx` `S` columns when precision matters.
4. **Notes via `threeparttable`.** Significance levels, standard-error type, sample restrictions, and clustering belong in a single notes block at the bottom — not in the caption.
5. **Cross-reference with `\Cref{}`.** `\label{tab:main}` + `\Cref{tab:main}` reads "Table 2" in body text and behaves correctly at sentence start.

## Decision Policy

This skill follows the repo-wide [Agent Policy](../../AGENT_POLICY.md).

**ASK before proceeding** (blocking):

1. Source language of the regression (Stata / R / Python) — determines the canonical table package.
2. Table type (regression / summary stats / balance / multi-panel / DiD-estimator comparison).
3. Standard-error type and cluster level (these belong in the table notes).
4. Output target (LaTeX `.tex`, Word `.rtf`, Excel `.xlsx`).

**DEFAULT + flag** (use this default; tell the user how to override):

- `esttab` (Stata), `modelsummary` or `fixest::etable` (R), `pyfixest.etable` or `stargazer` (Python).
- `booktabs` styling: `\toprule`, `\midrule`, `\bottomrule`; no vertical lines.
- Three-star convention `* 0.10 ** 0.05 *** 0.01`; pin once per paper.
- `threeparttable` for the notes block.
- Output path `paper/tabs/<name>.tex`; the paper `\input{}`s it.
- Within-R² (`r2_within`) reported instead of overall R² for FE models.

**DOCUMENT and proceed** (write into the decisions log of the table-generating script):

- The estimating equation, sample, cluster level, and FE included for each column.
- Variable label mapping (`coef_map` / `coeflabels`).
- Any subsample restriction shown in a column.

`PROCEED` items: tables produced by code (never copy-paste); generated `.tex` never hand-edited; rebuild path runs the table script before LaTeX.

## Pre-flight Checklist

Before generating code, confirm with the user — and write the answers in the script header:

- **Source language.** Stata, R, or Python? (Each has its own canonical table package.)
- **Table type.** Regression (multi-spec), summary statistics, balance / difference-in-means, descriptive cross-tabs, or model-comparison panel?
- **Sample.** Single or stratified? If panel, which fixed effects are on/off across columns?
- **Standard errors.** Cluster-robust at which level? Wild-bootstrap p-values?
- **Stars and notes.** Conventional `*** ** *` cutoffs (1/5/10), or journal-specific (some require none)?
- **Output path.** Almost always `paper/tabs/{name}.tex`; the paper `\input{}`s that file.
- **Compile target.** `\begin{table}` floating environment in body, or naked `tabular` snippet to be included from a parent macro?

## Decision Tree (which table package to use)

```
Source = Stata
└── esttab (from estout) is canonical.
    eststo store; esttab using "tabs/x.tex", booktabs label se ...

Source = R
├── fixest models (most common in 2024-26): use fixest::etable
└── Mixed model classes: use modelsummary (works across lm, glm,
    PanelOLS, fixest, brms, ...). modelsummary writes .tex via
    `output = "tabs/x.tex"`.

Source = Python
├── pyfixest models: use pyfixest.etable
├── linearmodels models: use compare(...) + manual to_latex(), or
    pass models through stargazer
└── statsmodels OLS / GLM: use stargazer (Python port).

Output for Word
└── Same packages with .rtf or .docx output (esttab supports rtf;
    modelsummary supports docx via flextable).
```

## Output Path Convention

```
paper/
├── paper.tex
├── tabs/                       # all .tex tables; never hand-edited
│   ├── table_main.tex
│   ├── table_balance.tex
│   ├── table_summary.tex
│   └── table_robustness.tex
├── figs/
└── code/
    ├── stata/
    │   └── make_tables.do
    └── r/
        └── make_tables.R
```

Body text:

```latex
\Cref{tab:main} reports our preferred specification.
\input{tabs/table_main.tex}
```

The `.tex` file should produce the entire `\begin{table} ... \end{table}` environment so you only have one `\input{}` per table in the paper.

## Common Pitfalls

- Hand-editing the `.tex` file after generation. The next run will overwrite or diverge from the published numbers.
- Mixing significance-star conventions across tables (`*` at 0.05 in one, at 0.10 in another).
- Using `\hline` everywhere; readers expect three-line `booktabs` tables.
- Vertical lines in regression tables — never necessary, always ugly.
- Putting key information in the caption (e.g. "Standard errors clustered by firm") instead of in the notes block, where it can be longer and less awkward.
- Using `_` in variable labels without `\_` escaping; LaTeX silently interprets them as subscripts.
- Including raw column names like `treat_post` instead of human-readable labels.
- Numbers with inconsistent decimal precision across columns.
- Missing N row at the bottom of regression tables; reviewers will ask.
- Not exporting at all — running the regression in interactive mode and screenshotting the result. (This is "no replicability" in DIME's framework.)

## Additional Resources

- `reference.md` — extended patterns: balance tables, summary stats, panel tables, threeparttable notes, siunitx S-column alignment, multi-panel tables, journal-specific deviations.
- `examples/` — runnable scripts that produce real `.tex` files:
  - `examples/make_tables_esttab.do` — Stata regression + summary + balance via `esttab`
  - `examples/make_tables_modelsummary.R` — R via `modelsummary` + `fixest::etable`
  - `examples/make_tables_pyfixest.py` — Python via `pyfixest.etable`
  - `examples/make_tables_stargazer.py` — Python `statsmodels` via `stargazer`
  - `examples/table_main_template.tex` — minimal copy-paste-able tabular for "good replicability" cases
  - `examples/table_balance_template.tex` — DIME-style balance table layout

## Requirements

- LaTeX: TeX Live 2022+ or MacTeX 2022+; packages `booktabs`, `threeparttable`, `siunitx`, `caption`, `cleveref`.
- Stata: `ssc install estout` (provides `esttab`, `eststo`, `estadd`, `estpost`).
- R: `install.packages(c("modelsummary", "fixest", "kableExtra"))`.
- Python: `pip install stargazer pyfixest pandas`.

## References

### DIME

- DIME Analytics, [Exporting Analysis](https://dimewiki.worldbank.org/Exporting_Analysis) — four levels of replicability.
- DIME Analytics, [Checklist: Submit Table](https://dimewiki.worldbank.org/Checklist:_Submit_Table).
- DIME Analytics, [Stata Coding Practices](https://dimewiki.worldbank.org/Stata_Coding_Practices) — `estout` family.

### Style

- AEA, [Manuscript Style Guide](https://www.aeaweb.org/journals/aer/submissions/accepted-articles/styleguide).
- Jansen & Persson, *Nice and fast tables in Stata for LaTeX and Excel* — https://osf.io/78nuc/.
- Lukas Püttmann, [`esttab` cheat sheet](https://lukaspuettmann.com/esttab/).
- `booktabs` documentation — https://ctan.org/pkg/booktabs.
- `siunitx` — https://ctan.org/pkg/siunitx (S columns for decimal alignment).