173 IV2 Reverse causality intuition

This video explores reverse causality, a common source of endogeneity in econometrics where the presumed cause and effect variables influence each other simultaneously. We delve into how this bidirectional relationship, also known as simultaneity, compromises standard regression analysis, leading to biased and inconsistent estimates. Real-world examples like education and income, exercise and health, and police and crime illustrate how OLS regression struggles to disentangle these interwoven influences. Understanding reverse causality is crucial for accurate policy implications, as demonstrated by the police and crime example. Visit AxiomTutoring.com and subscribe to @AxiomTutoringCourses.