IAMECON congratulates its interns on their pending UT Graduation!
May 20, 2019
The State of Antitrust Regulation
June 15, 2019
IAMECON congratulates its interns on their pending UT Graduation!
May 20, 2019
The State of Antitrust Regulation
June 15, 2019
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The relationship between a city’s segregation and its intergenerational income mobility

For policy makers and sociologists, segregation has long been a phenomenon of interest. As economists, we wanted to test the relevance of segregation for various economic measures using the recently published longitudinal dataset from the Opportunity Atlas project.

The Opportunity Atlas is a map of economic mobility in the United States and is a research collaboration between the US Census Bureau, Harvard and Brown University. The Atlas followed people who were born between 1978 and 1983 until they were in their mid-30s to illustrate how their outcomes depended on their family circumstances and where they grew up. Importantly, the data is quite granular and goes down to a census tract level. Outcomes featured in the Opportunity Atlas are incarceration rates, household incomes, college completion rates, wages and employment rates (Opportunity Atlas). 

To analyze the relationship between segregation and economic mobility, we downloaded the white-black dissimilarity index from CensusScope, a dataset from the Social Science Data Analysis Network. The dissimilarity index is a demographic measure that identifies “differences in residential patterns of one racial or ethnic group in relation to another” (Brown University). If the dissimilarity index in a city is 65, it means that 65% of white people would need to move to another neighborhood in the same metropolitan area to make the whites and blacks distribution perfectly homogeneous (CensusScope). Essentially, the higher the dissimilarity index, the more segregated the city is. 

We plotted the dissimilarity index of Metro Statistical Areas (MSAs) in the United States against the Opportunity Atlas’ “Intergenerational upward Mobility” score which is the “mean rank (in the national child income distribution) of children whose parents are at the 25th percentile of the national parent income distribution” (Chetty, 2014). For example, the Austin, TX MSA is 40, meaning that children whose parents were at the 25th percentile of the national parent income distribution, on average ended up at the 40th percentile themselves. 

We calculated that the correlation coefficient to be -.26 and found the relationship to be statistically significant. In their 2014 paper titled “Where is the Land of Opportunity? The Geography of Intergenerational Mobility in the United States,” Chetty et. al used the Theil index for segregation and also found that higher economic mobility areas are indeed correlated with less residential segregation. Four other factors they found related to economic mobility included (1) less income inequality, (2) better primary schools, (3) greater social capital, and (4) greater family stability. 

The authors of the paper then state that “segregation patterns are sufficiently stark that one can directly see the differences in segregation between the least and most upwardly mobile cities using the color-coded dot maps produced by Cable (2013) using Census data.” We decided to look at a map of Austin’s historical segregation to better understand how historical segregation relates to economic mobility. 

Below on the left, we have the map made by the Home Owners Loan Corporation in 1934 that deemed the areas where African Americans lived as the red “Hazardous” areas that were not eligible for government-backed mortgages (Austin American Statesman). On the right, we have today’s Opportunity Atlas – that shows the level of annual earnings for children born into the families with lowest 25th percentile of annual income (i.e. economic mobility). As the map and the data both demonstrate, there is a strong link between a city’s historical segregation and its current economic intergenerational mobility.