Learn Difference-in-Differences (DiD) in Python using PyFixest and Great Tables. Covers the 2x2 design, TWFE regression, inference comparison, publication-quality tables, event studies, and parallel trends testing based on Corral and Yang (2024).
A beginner-friendly tour of seven panel-data estimators — POLS, Between, First-Differences, Fixed Effects, Two-Way FE, Random Effects, and Correlated Random Effects (Mundlak) — applied to a two-period worker wage panel.
Replicating the N-shaped Kuznets curve with panel data fixed effects in Python using PyFixest, from pooled OLS through two-way FE, turning point analysis, and determinants of regional inequality across 180 countries
Comparing standard error estimators in panel data regressions using Python and linearmodels --- from conventional to clustered, Driscoll-Kraay, and fixed effects
An introduction to exploratory spatial data analysis using PySAL, covering choropleth maps, spatial weights, Moran's I, LISA clusters, space-time dynamics, and a Venezuela-Bolivia comparative analysis for 153 South American regions
Applying Multiscale Geographically Weighted Regression (MGWR) to reveal how economic catching-up varies across Indonesia's 514 districts, with each variable operating at its own spatial scale
Building a composite Health Index from Life Expectancy and Infant Mortality using manual PCA with simulated data for 50 countries, then verifying against scikit-learn
Building a comparable Human Development Index across two time periods using pooled PCA with real sub-national data for 153 South American regions, and contrasting with per-period PCA to show why pooled standardization is essential for temporal comparisons