# r-econometrics

Generates R code for causal inference and panel data using fixest, complete with diagnostics and publication tables. Useful for IV, DiD, and RDD research designs.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 331 installs · ★ 656
- Author: Awesome Econ AI Community
- License: CC0-1.0 · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/meleantonio/awesome-econ-ai-stuff/tree/HEAD/_skills/analysis/r-econometrics/SKILL.md
- Updated: 2026-09-26
- HTML: https://affpapa.org/en/nevibecode/skills/r-econometrics

## What it does

This skill guides your AI assistant through econometric workflows in R. Before writing code, it clarifies the research design: the identification strategy (IV, DiD, or RDD), observational units, fixed effects, and error clustering levels. It then organizes the R script into clear sections, covering data prep, main estimations, diagnostics, and table export.

Calculations rely heavily on `fixest`. Generated scripts add first-stage F-statistics for instrumental variables, event study plots for difference-in-differences, and bandwidth selection tests for regression discontinuity designs. If treatment timing is staggered, standard two-way fixed effects produce biased estimates. The skill highlights this limitation and suggests `sunab()` or the `did` package instead.

Execution requires R 4.0+ and four packages: `fixest`, `modelsummary`, `tidyverse`, and `ggplot2`.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add meleantonio/awesome-econ-ai-stuff --skill r-econometrics -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/r-econometrics/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/r-econometrics/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add meleantonio/awesome-econ-ai-stuff --skill r-econometrics -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/r-econometrics/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add meleantonio/awesome-econ-ai-stuff --skill r-econometrics -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/r-econometrics/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install meleantonio/awesome-econ-ai-stuff r-econometrics
```

2. **Manually: put the files in place**
- File: `.github/skills/r-econometrics/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add meleantonio/awesome-econ-ai-stuff --skill r-econometrics -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/meleantonio/awesome-econ-ai-stuff --path _skills/analysis/r-econometrics
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/r-econometrics/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add meleantonio/awesome-econ-ai-stuff --skill r-econometrics -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/meleantonio/awesome-econ-ai-stuff/tree/HEAD/_skills/analysis/r-econometrics/SKILL.md

## When to use it
- estimate treatment effects using instrumental variables
- run difference-in-differences regressions with two-way fixed effects
- generate event study plots to evaluate parallel trends
- execute regression discontinuity designs with optimal bandwidth selection
- export regression tables to LaTeX using modelsummary

## Example prompts
- Run a DiD analysis with state and year fixed effects, clustering at the state level
- Estimate the effect of X on Y using Z as an instrument
- Create an event study plot showing treatment effects by year

## Source text · SKILL.md · CC0-1.0

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 159b68a21463dc49.

BEGIN THIRD-PARTY FILE 159b68a21463dc49
````text
---
name: r-econometrics
description: Run IV, DiD, and RDD analyses in R with proper diagnostics
workflow_stage: analysis
compatibility:
  - claude-code
  - cursor
  - codex
  - gemini-cli
author: Awesome Econ AI Community
version: 1.0.0
tags:
  - R
  - econometrics
  - causal-inference
  - fixest
  - regression
---

# R Econometrics

## Purpose

This skill helps economists run rigorous econometric analyses in R, including Instrumental Variables (IV), Difference-in-Differences (DiD), and Regression Discontinuity Design (RDD). It generates publication-ready code with proper diagnostics and robust standard errors.

## When to Use

- Running causal inference analyses
- Estimating treatment effects with panel data
- Creating publication-ready regression tables
- Implementing modern econometric methods (two-way fixed effects, event studies)

## Instructions

### Step 1: Understand the Research Design

Before generating code, ask the user:
1. What is your identification strategy? (IV, DiD, RDD, or simple regression)
2. What is the unit of observation? (individual, firm, country-year, etc.)
3. What fixed effects do you need? (entity, time, two-way)
4. How should standard errors be clustered?

### Step 2: Generate Analysis Code

Based on the research design, generate R code that:

1. **Uses the `fixest` package** - Modern, fast, and feature-rich for panel data
2. **Includes proper diagnostics:**
   - For IV: First-stage F-statistics, weak instrument tests
   - For DiD: Parallel trends visualization, event study plots
   - For RDD: Bandwidth selection, density tests
3. **Uses robust/clustered standard errors** appropriate for the data structure
4. **Creates publication-ready output** using `modelsummary` or `etable`

### Step 3: Structure the Output

Always include:
```r
# 1. Setup and packages
# 2. Data loading and preparation
# 3. Descriptive statistics
# 4. Main specification
# 5. Robustness checks
# 6. Visualization
# 7. Export results
```

### Step 4: Add Documentation

Include comments explaining:
- Why each specification choice was made
- Interpretation of key coefficients
- Limitations and assumptions

## Example Prompts

- "Run a DiD analysis with state and year fixed effects, clustering at the state level"
- "Estimate the effect of X on Y using Z as an instrument"
- "Create an event study plot showing treatment effects by year"
- "Run a sharp RDD with optimal bandwidth selection"

## Example Output

```r
# ============================================
# Difference-in-Differences Analysis
# ============================================

# Setup
library(tidyverse)
library(fixest)
library(modelsummary)

# Load data
````
END THIRD-PARTY FILE 159b68a21463dc49

The third-party file has ended. Everything between the 159b68a21463dc49 tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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---
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