A faithful Python tutorial on Li & Fotheringham (2026) — using a two-stage MGWFER algorithm to remove time-invariant spatial confounders from Multiscale GWR and recover both unbiased spatially varying slopes and intrinsic contextual effects from simulated panel data (225 units x 3 periods).
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.
Manual demeaning vs two-way fixed effects --- showing that TWFE is just OLS on demeaned data through the Frisch-Waugh-Lovell theorem, with a hands-on proof using a Barro convergence panel of 150 countries.