Ethno-racial inequality in poverty is an enduring but misunderstood problem. Most prior research relies on the flawed official poverty measure, data with underreported income, and models omitting essential predictors. Using… Click to show full abstract
Ethno-racial inequality in poverty is an enduring but misunderstood problem. Most prior research relies on the flawed official poverty measure, data with underreported income, and models omitting essential predictors. Using the Current Population Survey, we adjust for benefit underreporting and estimate levels and trends in both relative and Supplemental Poverty Measure poverty rates for ethno-racial groups relative to White individuals in the U.S. from 1993 to 2017. We then focus on the five most recent years (2013–2017) and decompose Black–White, Latino–White, and Asian–White poverty gaps. We expand prior decomposition analyses by better incorporating employment and geographic context and better measuring immigration. Our findings show ethno-racial inequalities in poverty declined from 1993 to 2017 but remained large. Our estimates of relative poverty reveal that millions more Black and Latino individuals are poor than with the official measure—even after adjusting for benefit underreporting. By 2013–2017, Black and Latino individuals remain about twice as likely to be poor as White individuals. By contrast, the evidence is mixed on Asian–White differences. Decomposition results show employment explains the largest share of the Black–White gap, whereas immigration matters most for the Latino–White and Asian–White gaps. Geographical context also explains a significant portion of each racial gap and is particularly central to Asian–White gaps. Compared to prior decompositions, which would explain roughly half of the Black–White gap in poverty, our models explain more than three quarters. Beyond the novel empirical description, this study encourages structural, political, and critical race theories of poverty over behavioral explanations.
               
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