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:

# 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