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.
Did legal abortion lower crime in the United States, as a famous 2001 study claimed? Instead of hand-picking a few control variables, we let a data-driven method choose among 284 candidates and check whether the original finding holds up. This R tutorial comes with an interactive app that runs in your web browser.
Did the carbon tax that Sweden introduced in 1991 cut carbon emissions from transport, and did it hurt the economy? This Python tutorial builds a look-alike Sweden from other wealthy countries and finds transport emissions about 11 percent lower each year, with no sign of slower economic growth. It comes with an interactive app that runs in your web browser.
Does mining wealth help or hurt local development, and do good local institutions make the difference? This Python tutorial uses causal machine learning on simulated district data with known true effects to measure how the impact of mining and mineral prices varies from place to place. It comes with an interactive app that runs in your web browser.
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.
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.