A beginner-friendly tutorial on the synthetic control method in R, using the Basque Country case study to estimate the economic cost of conflict on regional GDP per capita from 1970 to 1997.
Identify latent group structures in panel data using the Classifier-LASSO method (Su, Shi, Phillips 2016), revealing that the pooled democracy-growth effect of +1.055 masks a +2.151 effect in 57 countries and a -0.936 effect in 41 countries.
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.
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.