New Evidence on the Relationship between Inequality and Health

TLDR: In this paper, the authors apply a new methodology to calculate a variety of income inequality measures based on aggregate income and household size data from various Federal data sources, and find statistically significant evidence supporting the income inequality hypothesis and the relative deprivation hypothesis, which suggests that greater income inequality adversely affects health status in the United States.

Abstract: The relative income hypothesis suggests that an individual’s health is impacted by the income of others. However, prior studies suffer from mixed empirical findings that could be due to a lack of annual individual income data with sufficient sample size. We apply a new methodology to calculate a variety of income inequality measures based on aggregate income and household size data from various Federal data sources. Our proposed methodology provides a way to express various income inequality measures as a function of the ratio of mean to median household income under the assumption that individual income is log-Normally distributed. This approach produces a variety of precise annual income inequality measures at different levels of geography, thus solving the sample size problem by incorporating externally calculated inequality measures. Combining the 2001-2012 editions of the U.S. Behavioral Risk Factor Surveillance System with annual regional income inequality measures derived from our methodology enables us to estimate both the contemporaneous and the lagged effect of income inequality on individual health outcomes. In general, we find statistically significant evidence supporting the income inequality hypothesis and the relative deprivation hypothesis, which suggests that greater income inequality adversely affects health status in the United States.