Double Machine Learning

Double Machine Learning with 401(k) Data: From Eligibility Effects to Complier Analysis

Does access to a workplace retirement savings plan make American households save more, or do the households that get it simply earn more? This Python tutorial uses double machine learning, which lets flexible prediction models account for income and other differences, on 1991 survey data. It comes with an interactive app that runs in your web browser.

Causal Machine Learning for Policy Evaluation: From ATE to IATE to a Better Assignment Rule

If a job training program helps unemployed people find work, who gains the most, and who should be offered a place first? This Python tutorial uses causal machine learning on simulated jobseeker data with known true effects to move from the average effect to personal effects and a better way to assign training. It comes with an interactive app that runs in your web browser.

Introduction to Causal Inference: Double Machine Learning

Does a cash bonus help unemployed workers find jobs faster? This Python tutorial uses double machine learning, which lets flexible prediction models strip out the influence of background characteristics, on data from a real experiment in Pennsylvania. It comes with an interactive app that runs in your web browser.