python-panel-data

What problem does it solve?

It solves the problem of estimating econometric models on panel datasets without getting panel indexing, fixed effects, and clustered standard errors wrong.

Core Features & Use Cases

• Panel Structure Setup (pandas MultiIndex): Organizes data into a proper panel format so models run on the intended entity and time dimensions.
• Fixed/Random Effects Estimation (linearmodels): Fits PanelOLS and RandomEffects models to produce credible coefficient estimates with appropriate effects.
• Inference & Diagnostics: Supports clustered covariance settings and helps interpret results with assumptions and robustness ideas.

Example Use

Estimate a two-way fixed effects model (e.g., firm and year effects) for a treatment implemented at the entity level over time, using clustered standard errors.

Quick Start

Ask the skill to estimate a two-way fixed effects (entity and time) model for your panel dataset and return a readable regression summary with clustered standard errors.