Purpose: A popular idea in the social sciences is that contexts with high income inequality undermine people's well-being and health. However, existing studies documenting this phenomenon typically compare a small number of higher-level units (countries/regions). Here, we use local income inequality indicators and temporal designs to provide the most highly powered test to date of the associations between income inequality and self-reported happiness and health in the USA METHOD: We combined county-level income inequality data (county-level Gini coefficients) with the responses from the General Social Survey (GSS) Cross-sectional dataset (13,000 + participants from ≈1000 county-waves) and Panels (3 × 3000 + participants from 3 × ≈500 county-waves); we used the GSS happiness ("not too happy," "pretty happy," or "very happy") and health ("poor," "fair," "good," or "excellent") variables.
Results: Multilevel-ordered logistic models and equivalence tests revealed that the within-county effects of income inequality on self-reported happiness and health were systematically equivalent to zero. Additional analyses revealed that the within-state effects were identical, that using alternative measures of state income inequality led to the same conclusions, and that lagged effects (between + 1 and + 12 years) were never significant and always equivalent to zero.
Conclusion: The present work suggests that-at least in the USA-income inequality is likely neither associated with self-reported happiness nor with self-reported health.
Keywords: Equivalence testing; Health; Income inequality; Multilevel modeling; Well-being.
© 2022. The Author(s).