Comparing standard error estimators in panel data regressions using Python and linearmodels --- from conventional to clustered, Driscoll-Kraay, and fixed effects
Dynamic panel Bayesian Model Averaging with the Bayesian Dynamic Systems Modeling (BDSM) R package, applied to cross-country economic growth determinants --- handling reverse causality through lagged dependent variables, fixed effects, and weak exogeneity.
Bayesian Model Averaging and Double-Selection LASSO applied to the Environmental Kuznets Curve using synthetic panel data with a known answer key, demonstrating how both methods recover the true predictors of CO2 emissions.
A hands-on guide to spatial panel data modeling using the SDPDmod package in R --- from Bayesian model comparison through static and dynamic SAR/SDM estimation with Lee-Yu bias correction to direct, indirect, and total effect decomposition --- applied to cigarette demand across 46 US states (1963--1992).
A hands-on guide to the fwlplot package in R --- from understanding the Frisch-Waugh-Lovell theorem through simulated confounding to visualizing fixed effects in real panel data --- showing what "controlling for" looks like as a scatter plot.
A hands-on guide to the scatterfit package in Stata --- from understanding the Frisch-Waugh-Lovell theorem through simulated confounding to visualizing fixed effects in real panel data --- showing what "controlling for" looks like as a scatter plot.
A guide to Difference-in-Differences with staggered treatment --- from TWFE pitfalls through Callaway-Sant'Anna group-time ATTs, doubly robust estimation, and HonestDiD sensitivity analysis --- applied to minimum wage effects on teen employment.
Three principled approaches to variable selection---BMA, LASSO, and WALS---applied to synthetic cross-country CO2 emissions data with known ground truth, demonstrating methodological triangulation for robust inference.
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