python

High-Dimensional Fixed Effects Regression: An Introduction in 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

Introduction to Difference-in-Differences in Python

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

The FWL Theorem: Making Multivariate Regressions Intuitive

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

Introduction to Partial Identification: Bounding Causal Effects Under Unmeasured Confounding

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

Introduction to Causal Inference: The DoWhy Approach with the Lalonde Dataset

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

Introduction to Causal Inference: Double Machine Learning

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

Introduction to Machine Learning: Random Forest Regression

Predicting municipal development in Bolivia using Random Forest regression on satellite image embeddings

Econometrics powered by AI

Learning econometrics should be a more accessible and interactive experience.

metricsAI

An introduction to econometrics with Python and AI in the cloud

DS4Bolivia

A Data Science Repository to Study GeoSpatial Development in Bolivia