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r-econometrics

Implement IV, DiD, and RDD causal econometrics in R with fixest diagnostics.

598|128|Updated Jan 26, 2026
Search Tags:#r#econometrics#causal-inference#panel-data#did#fixest#rdd
One-click install
npx skills add https://github.com/meleantonio/awesome-econ-ai-stuff --skill r-econometrics-meleantonio
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: r-econometrics
Source: https://github.com/meleantonio/awesome-econ-ai-stuff/tree/main/_skills/analysis/r-econometrics
Command: npx skills add https://github.com/meleantonio/awesome-econ-ai-stuff --skill r-econometrics-meleantonio

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill enables researchers to implement causal econometrics in R, including IV, DiD, and RDD, with diagnostics and robust standard errors.

Core Features & Use Cases

  • Implements causal inference methods (IV, DiD, RDD) in R using the fixest package for fast, reliable estimates.
  • Produces publication-ready results with diagnostics, robust standard errors, and clear interpretation.
  • Use cases include panel data analysis, treatment effect estimation, and event-study visualizations for policy evaluation.

Quick Start

Ask for your research design and data, and generate an R script using fixest that runs the specified model with diagnostics.

Frequently Asked Questions about r-econometrics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run causal inference models like DiD and IV in R with proper diagnostics?▼

To run causal inference in R, you can generate a script using the fixest package that executes IV, DiD, and RDD models, complete with robust standard errors and first-stage F-statistics diagnostics.

Can I use fixest for panel data analysis and event-study visualizations?▼

Yes, fixest supports panel data analysis and event-study visualizations for policy evaluation, providing fast estimates and publication-ready outputs with proper clustering.

What's the best way to ensure my econometrics estimates have robust standard errors?▼

The best way to ensure robust standard errors in econometrics estimates is by using a workflow that applies proper clustering and diagnostic checks, such as first-stage F-statistics and event-study plots.

Does this approach support multiple identification strategies in a single analysis?▼

Yes, this approach supports running multiple identification strategies including IV, DiD, and RDD across panel data, while providing publication-ready results and comprehensive diagnostics.

Why do I need first-stage F-statistics and event-study plots for causal econometrics?▼

You need first-stage F-statistics and event-study plots as diagnostic checks to validate your identification strategy, ensuring your causal econometrics estimates are reliable and publication-ready.

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