Causal inference when you can't experiment: difference-in-differences and synthetic controls
Linear Digressions
English - March 09, 2020 01:39 - 20 minutes - 9.52 MB - ★★★★★ - 350 ratingsTechnology data science machine learning linear digressions Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Previous Episode: Better know a distribution: the Poisson distribution
When you need to untangle cause and effect, but you can’t run an experiment, it’s time to get creative. This episode covers difference in differences and synthetic controls, two observational causal inference techniques that researchers have used to understand causality in complex real-world situations.