Socioeconomic mixing, in neighborhoods that are diverse in race, ethnicity and income, benefits everyone

To some extent, we take for granted that integration and equal opportunity should be valued for their own sake. But its worth noting that achieving greater integration along both racial/ethnic and income dimensions is important to achieving more widespread prosperity and combatting poverty.

A growing body of sociological and economic research have demonstrated the high costs associated with racial and income segregation. While a comprehensive review of this literature is beyond the scope of this paper, we highlight here some of the key research findings that bear on the economic consequences of neighborhood diversity. Neighborhoods of concentrated disadvantage are not simply places where many households suffer from their own individual problems. The segregation of poverty (or a marginalized racial group) creates its own additional, collective burden on residents of these communities.

Galster and Sharkey undertake an extensive literature review of data on neighborhood effects of poverty. They find that segregation is associated with lower cognitive development and weaker academic performance, greater likelihood of teen pregnancy and risky behaviors, reduced physical and mental health, lower incomes and lower probability of employment, greater likelihood of being affected by or engaged in crime. Looking at more than 100 studies which they regard as quantitatively rigorous they conclude:

. . . the findings on the number of (methodologically rigorous) studies that have found substantial, statistically significant effects of spatial context (for at least some set of individuals) and those that have not, by outcome domain. The tally makes it clear that the preponderance of evidence in every outcome domain is that multiple aspects of spatial context exert important causal influences over a wide range of outcomes related to socioeconomic opportunity, though which aspects are most powerful depends on the outcome and the gender and ethnicity of the individuals in question.
(Galster & Sharkey, 2017)

Part of this burden is evident in day-to-day quality of life issues, such as greater exposure to crime. Studies of the “Moving to Opportunity” program, in which families were given assistance to move from low-income to middle-income neighborhoods, showed a marked improvement in self-reported well-being. Moving to a neighborhood whose poverty rate was 13 percentage points lower was associated with an increase in self-reported quality of life equivalent to an increase of $13,000 in household income (Ludwig et al., 2012). But perhaps the most serious effects of concentrated disadvantage are the ways in which it acts to reproduce inequality and quash economic opportunity and mobility—the very promise of the American dream.

High-poverty neighborhoods put their residents at a significant and immediate economic disadvantage. They typically have fewer local jobs than other neighborhoods, and often are distant from, or poorly connected to, other major job centers. These communities also often lack social networks that allow residents to find job openings (Bayer, Ross, & Topa, 2004).

For these and other reasons, people who grow up in high-poverty neighborhoods, on average, have worse economic outcomes than people who grow up in other kinds of neighborhoods, even if their family backgrounds are identical. The Equality of Opportunity Project has shown that inter-generational income mobility is significantly higher in metropolitan areas with lower levels of income segregation(Chetty, Hendren, Kline, & Saez, 2014)). The effect is so strong that, for children whose families move from high-segregation to low-segregation metropolitan areas, each additional year spent in the high-segregation region before the move is associated with less income as an adult.

Chetty and Hendren find that across metropolitan areas both income and racial ethnic segregation have a negative effect on children’s income as adults (Chetty & Hendren, 2016) (Chetty & Hendren, 2016)

“. . . our analysis strongly supports the hypothesis that growing up in a more segregated area – that is, in a neighborhood with concentrated poverty – is detrimental for disadvantaged youth. “

But they go on to say that it’s not because of their parents access to jobs, but because of the children’s exposure to a different set of peers.

“Areas with less concentrated poverty, less income inequality, better schools, a larger share of two-parent families, and lower crime rates tend to produce better outcomes for children in poor families. Boys’ outcomes vary more across areas than girls’ outcomes, and boys have especially negative outcomes in highly segregated areas. One-fifth of the black-white income gap can be explained by differences in the counties in which black and white children grow up.”

Other studies have found similar effects. For example, black children who grow up in high-poverty neighborhoods that transition to low levels of poverty have incomes that are 30 to 40 percent higher than black children with similar backgrounds who grow up in neighborhoods that remain at high levels of poverty (Sharkey, 2013) Observing the results of a natural experiment that relocated families from public housing in Chicago, Eric Chyn found that children who moved even relatively short distances to neighborhoods with somewhat lower poverty rates also experienced noticeable gains in earnings (Chyn, 2016)

Another analysis suggests that the educational level of ones neighbors has an effect on a child’s economic future nearly as large as that of the educational level of a child’s own parents. The effect of neighborhood educational level on children’s future earnings have been estimated to be two-thirds as powerful as the influence of the children’s own parental educaton (Rothwell & Massey, 2014).

The effects that are observed at the neighborhood level appear to compound to produce the variations in economic results we observe across metropolitan areas. Quillian shows that increases in segregation at the metropolitan level are associated with lower rates of high school completion for poor and black students. (Quillian, 2014) Quillian uses data from the Panel Study of Income Dynamics, a federal survey program that gathers longitudinal data on a representative group of Americans over several decades. Poor and black students that live in more segregated metropolitan areas are less likely to graduate from high school after controlling for other observable factors that influence individual success, such as the level of their parents’ education. Significantly, higher rates of segregation do not appear to have any statistically significant effects on the high school completion rates of whites or the non-poor. Taken together, these findings suggest that increasing racial and economic integration improves the educational outcomes for black and poor students without any negative effect on the educational outcomes of white and non-poor students.

A recent study prepared by the Urban Institute and the Metropolitan Policy Center estimated the cumulative economic and social costs associated with segregation in that metropolitan area. They found that the annual estimated cost of segregation in Chicago was more than $4 billion annually in lost income, and meant that fewer residents achieved a college education, while more were victims of crime, including homicide. (Acs, Pendall, Treskon, & Khare, 2017)

Taken together, the weight of social science evidence shows that racial/ethnic and economic segregation have profound consequences for individuals, for neighborhoods and entire cities. Much of the persistence and severity of poverty is due to the continued segregation. More integrated neighborhoods and more integrated cities enjoy better economic results, and produce better lifetime opportunities for their children. These findings point up the critical importance of the role of the nation’s racially and ethnically diverse, mixed income neighborhoods.

References

Acs, G., Pendall, R., Treskon, M., & Khare, A. (2017). The Cost of Segregation: National Trends and the Case of Chicago, 1990–2010. Washington, DC: Urban Institute. Retrieved from http://www. urban. org/research/publication/cost-segregation.

Bayer, P., Ross, S. L., & Topa, G. (2004). Place of Work and Place of Residence: Informal Hiring Networks and Labor Market Outcomes (Working paper No. 2004–07). University of Connecticut, Department of Economics. Retrieved from https://ideas.repec.org/p/uct/uconnp/2004-07.html

Chetty, R., & Hendren, N. (2016). The impacts of neighborhoods on intergenerational mobility ii: County-level estimates. National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w23002

Chetty, R., Hendren, N., Kline, P., & Saez, E. (2014). Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States. National Bureau of Economic Research. Retrieved from http://www.nber.org/papers/w19843

Chyn, E. (2016). Moved to opportunity: The long-run effect of public housing demolition on labor market outcomes of children. Unpublished Paper. University of Michigan, Ann Arbor.

Galster, G., & Sharkey, P. (2017). Spatial Foundations of Inequality: A Conceptual Model and Empirical Overview. RSF, 3(2), 1–33. https://doi.org/10.7758/RSF.2017.3.2.01

Ludwig, J., Duncan, G. J., Gennetian, L. A., Katz, L. F., Kessler, R. C., Kling, J. R., & Sanbonmatsu, L. (2012). Neighborhood effects on the long-term well-being of low-income adults. Science, 337(6101), 1505–1510.

Quillian, L. (2014). Does Segregation Create Winners and Losers? Residential Segregation and Inequality in Educational Attainment. Social Problems, 61(3), 402–426.

Rothwell, J. T., & Massey, D. S. (2014). Geographic Effects on Intergenerational Income Mobility. Economic Geography, n/a-n/a. https://doi.org/10.1111/ecge.12072

Sharkey, P. (2013). Stuck in place: Urban neighborhoods and the end of progress toward racial equality. University of Chicago Press. Retrieved from http://books.google.com/books?hl=en&lr=&id=R-b_NlPJeuUC&oi=fnd&pg=PR5&dq=patrick+sharkey+stuck+in+place&ots=xJkeq39Kje&sig=0lmKDBM6OxHGMNk0jBga4EtDFqM