Uncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption

no code implementations • 10 Oct 2022 • Matias D. Cattaneo, Yingjie Feng, Filippo Palomba, Rocio Titiunik

We propose principled prediction intervals to quantify the uncertainty of a large class of synthetic control predictions (or estimators) in settings with staggered treatment adoption, offering precise non-asymptotic coverage probability guarantees.

Prediction Intervals Uncertainty Quantification +1