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python-panel-data

Fit fixed-effects and random-effects panel models in Python with linearmodels.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Panel data analysis in econometrics often requires correct panel structuring, fixed effects specification, clustering, and diagnostics. This skill guides economists through Python tools (pandas, linearmodels, statsmodels) to build robust panel models and interpret results.

Core Features & Use Cases

  • Load panel data and set up a MultiIndex to reflect entity and time dimensions.
  • Estimate fixed-effects or random-effects models with proper clustering and diagnostics.
  • Generate readable results tables and optional LaTeX outputs for reporting.

Quick Start

Provide your dataset and I will generate a ready-to-run Python panel regression script with fixed effects.

Frequently Asked Questions about python-panel-data

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

FAQPage Schema
How do I run a fixed-effects panel regression in Python?▼

You can run a fixed-effects panel regression in Python by loading your data into pandas, setting a MultiIndex for entity and time dimensions, and fitting the model using linearmodels to generate interpretable results tables.

How do I set up panel data in pandas for econometric analysis?▼

To set up panel data in pandas, load your dataset and configure a MultiIndex reflecting the entity and time dimensions, ensuring the structure is ready for fixed-effects or random-effects model estimation.

Can I estimate a difference-in-differences model using linearmodels?▼

Yes, you can estimate difference-in-differences designs using linearmodels by structuring your panel data with a MultiIndex and fitting a two-way fixed-effects model to analyze treatment effects over time.

What is the best way to perform panel data diagnostics in Python?▼

The best way to perform panel data diagnostics in Python is to fit fixed-effects or random-effects models with proper clustering using linearmodels, which produces readable outputs and optional LaTeX tables for reporting.

Do I need to clean my data before fitting a random-effects model in Python?▼

Yes, you need to clean your data and set a proper panel index before fitting a random-effects model in Python, ensuring the dataset accurately reflects entity and time dimensions for robust econometric analysis.

Does linearmodels support clustering for panel data regressions?▼

Yes, linearmodels supports clustering for panel data regressions, allowing you to estimate fixed-effects or random-effects models with proper clustering and generate diagnostics for robust econometric results.

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