mlsynth

Introduction to the Synthetic Control Method in Python with mlsynth

How much did Proposition 99, the 1989 California tobacco program, reduce cigarette sales? This beginner Python tutorial teaches the synthetic control method, which builds a look-alike California from other states, finds about 19 fewer packs sold per person each year, and then tries hard to break that result. It comes with an interactive app that runs in your web browser.

Bayesian Spatial Synthetic Control in Python: California's Proposition 99 with scspill and mlsynth

Did the 1988 California tobacco law cut cigarette sales, and did it also affect neighboring states such as Nevada? This Python tutorial builds a look-alike California from other states in three steps, the last one letting nearby states be affected too, and finds that the drop in California holds up. It comes with an interactive app that runs in your web browser.

The Synthetic Control Ladder in Python: A Guided Tour of mlsynth on the Brexit Referendum

How much did the 2016 Brexit vote cost the British economy? This Python tutorial builds a look-alike United Kingdom from other wealthy economies with six related methods, finds output about 3 percent lower by the end of 2018, and shows how default settings can quietly change the answer. It comes with an interactive app that runs in your web browser.

Bouncing Back Better? Evaluating the Economic Impact of the Aceh Tsunami

How did the 2004 tsunami affect the economy of Aceh, Indonesia, over the long run? This beginner-friendly Python tutorial uses simulated data, nighttime lights, and several causal methods to compare damaged and undamaged areas before and after the disaster.