econometrics

Double LASSO in Python: Does Abortion Reduce Crime?

Python companion to the R and Stata Double LASSO tutorials — same data, same five estimators, plus a hands-on introduction to the DoubleML library (DoubleMLPLR, DoubleMLIRM, and learner-robustness across LASSO, RandomForest, XGBoost).

Double LASSO in Stata: Does Abortion Reduce Crime?

Stata companion to the R Double LASSO tutorial — same data, same five estimators, replicating the Belloni-Chernozhukov-Hansen 284-control extension of Donohue and Levitt's abortion-and-crime panel with pdslasso, rlasso, and cvlasso.

Double LASSO for Causal Inference: Does Abortion Reduce Crime?

A beginner-friendly walkthrough of Double LASSO for causal inference, replicating Fitzgerald, Lattimore, Robinson and Zhu's (2026) analysis of the Donohue–Levitt abortion–crime question with 284 candidate controls and state-clustered standard errors.

Introduction to Panel Data Methods in Python

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.

Regional Inequality and the Kuznets Curve: Panel Fixed Effects in Python

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

Identifying Latent Group Structures in Panel Data: The classifylasso Command in Stata

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.

What Does TWFE Actually Do? Manual Demeaning and the FWL Theorem

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.

Standard Errors in Panel Data: A Beginner's Guide in Python

Comparing standard error estimators in panel data regressions using Python and linearmodels --- from conventional to clustered, Driscoll-Kraay, and fixed effects

Dynamic Panel BMA: Which Factors Truly Drive Economic Growth?

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.

Taming Model Uncertainty in the Environmental Kuznets Curve: BMA and Double-Selection LASSO with Panel Data

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.