This repository contains a week-by-week collection of notes, formulas, data examples, and simple code materials from a university-level course on Panel Data Econometrics.
The aim is to summarize both theoretical and practical aspects of panel data analysis, including models like Pooled OLS, Fixed Effects, and Random Effects — supported by Python examples when possible.
Each week includes:
- A markdown summary or lecture-style notes
- Key formulas and model structures
- Example datasets (CSV)
- Optional Python notebooks for practical exploration
These materials are based on a university econometrics course covering 14 weeks of panel data theory and applications.
Stay tuned — new content will be added weekly!