Python

Estimating regression models with high-dimensional fixed effects using PyFixest, from simple OLS through two-way FE, instrumental variables, panel data, and event studies

Estimating causal treatment effects using Difference-in-Differences with the diff-diff package, from the classic 2x2 design through staggered adoption with Callaway-Sant'Anna and HonestDiD sensitivity analysis

Understanding the Frisch-Waugh-Lovell theorem to isolate causal relationships by partialling-out confounders in a simulated retail store dataset

Computing causal bounds under unmeasured confounding using Manski and Tian-Pearl bounds with the CausalBoundingEngine package in Python

Estimating the causal effect of a job training program on earnings using DoWhy's four-step causal inference framework with the Lalonde dataset

Estimating the causal effect of a cash bonus on unemployment duration using Double Machine Learning with the Pennsylvania Bonus Experiment

A beginner-friendly, comprehensive introduction to Random Forest regression for continuous data, evaluated end-to-end with 5-fold cross-validation and out-of-fold predictions on Bolivian satellite imagery

An interactive geocomputational notebook to study spatial clusters and outliers

A geocomputational notebook to study spatial heterogeneity using the GWR and MGWR frameworks.

An introduction to how to construct, explore, and export spatial connectivity structures (W) using Python.