The Consequences of Economic Inequality: Health, Well-Being, and Intergenerational Mobility

Paper Session

Saturday, Jan. 7, 2017 2:30 PM – 4:30 PM

Hyatt Regency Chicago, Plaza B
Hosted By: American Economic Association
  • Chair: Joseph E. Stiglitz, Columbia University

Income Inequality and Well-Being in the United States: Evidence of Geographic-Scale- and Measure-Dependence

John Ifcher
Santa Clara University
Homa Zarghamee
Barnard College
Carol Graham
Brookings Institution


U.S. income inequality has increased dramatically in recent decades. Yet, the impact of this rise is not well-understood. An emerging literature examines the relationship between income inequality and subjective well-being (SWB). The results are inconsistent: some studies find a negative relationship, while others find a positive or insignificant relationship. We develop a stylized framework that includes multiple distinct channels (e.g., choice set and inequity aversion) through which income inequality could impact utility. The framework allows for either a positive or negative relationship depending on dominant channels. We then estimate the relationship between income inequality and well-being controlling for own and median income. Well-being data comes from the Gallup Daily Poll and includes (i) evaluative SWB (e.g., best possible life); (ii) hedonic SWB (e.g., stress); and (iii) health measures (e.g., disease). Income-inequality data comes from the American Community Survey and includes ZIP-code, county, MSA, and state Gini indexes. Using the four Ginis enables us to examine whether the dominance of positive or negative channels is consistent across reference groups. We find that stress and worry increase unambiguously with income inequality. In contrast, the relationship between income inequality and well-being is bifurcated when best possible life, enjoyment, or happiness is used as the dependent variable (increasing with ZIP-code Gini and decreasing with MSA and state Ginis), suggesting that positive channels dominate locally and negative channels dominate regionally. Using the health measures as dependent variables, the same bifurcated pattern generally holds. Lastly, we attempt to reconcile our empirical results with our theoretical framework to understand which channels are operant for various reference groups and measures of well-being. Our results highlight the important distinction between evaluative and hedonic SWB. Further, positive and negative hedonic SWB do not lie on a continuum and can be asymmetrically impacted by economic phenomena.

Top Incomes and Human Well-Being Around the World

Richard V. Burkhauser
Cornell University
Jan-Emmanuel De Neve
University of Oxford
Nick Powdthavee
University of Warwick


The share of income held by the top 1 percent in many countries around the world has been rising persistently over the last 30 years. But we continue to know little about how the rising top income shares affect human well-being. This study combines the latest data to examine the relationship between top income share and different dimensions of subjective well-being. We find top income shares to be significantly correlated with lower life evaluation and higher levels of negative emotional well-being, but not positive emotional well-being. The results are robust to household income, individual’s socio-economic status, and macroeconomic environment controls.

The Decline in Intergenerational Mobility After 1980

Jonathan Davis
University of Chicago
Bhashkar Mazumder
Federal Reserve Bank of Chicago


We document a pronounced decline in intergenerational mobility that corresponds to a major inflection point in inequality. Specifically we estimate an intergenerational rank-rank slope in income of around 0.26 for cohorts in the NLS66 who entered the labor market during the 1970s. We contrast this with an estimate of around 0.4 for cohorts in the NLSY79 who entered the labor market during the 1980s and 1990s. This rise in rank persistence over time is the equivalent of moving from the 38th most mobile city in the US to the 338th most mobile city based on Chetty et al. (2014). We find similar time patterns when we use a group-based estimator of the intergenerational elasticity (Aaronson and Mazumder, 2008) using Census data.

Inequality, Relative Income and Newborn Health

Anna Aizer
Brown University
Florencia Borrescio-Higa
Adolfo Ibanez University
Hernan Winkler
World Bank


A major concern over rising inequality is its potential to reduce intergenerational mobility, leading to even greater inequality in the next generation. We estimate the impact of rising inequality over the period 1970-2010 on offspring health at birth, a measure of human capital that has been shown to be highly correlated with future education, IQ and income. We define inequality both at the aggregate level and at the individual level: as a group-level measure (the Gini coefficient for each state or county), and as individual level measures of relative income (relative deprivation, rank, and relative income distance). We document a strong negative relationship between the Gini and newborn health in the cross section, but find that including a modest set of controls, or limiting variation to changes in inequality over time within an area, or instrumenting for inequality eliminates the relationship between the Gini and newborn health completely. However, this null result likely reflects heterogeneity in the effect of rising inequality. When we estimate the impact of relative income on newborn health, we find negative and significant effects of having relatively less income than one’s neighbors on birth weight, even after controlling for area fixed effects and instrumenting for differences in the income distribution.
Jeffrey Butler
University of Nevada-Las Vegas
Hilary Hoynes
University of California-Berkeley
Ilyana Kuziemko
Princeton University
Jeffrey Larrimore
Federal Reserve Board
JEL Classifications
  • D3 - Distribution