Featured Article
HUD USER Home > PD&R Edge Home > Featured Article

Economic Mobility: Measuring the American Dream

Map depicting economic mobility in the United States through colors ranging from pale yellow to dark red. Darker colors, concentrated in the South, indicate areas in which children from low-income families are less likely to move up in the income distribution, and lighter colors, prevalent in the Midwest, represent areas in which the prospects for economic mobility are higher.
Economic mobility, the opportunity for children born in poverty to achieve the American Dream, varies across the United States. Image courtesy of Raj Chetty.
Does the neighborhood you grow up in impact your income as an adult? With recent studies showing rising levels of income inequality in the United States, the question of economic mobility has become increasingly more important.

Last month, economist Raj Chetty spoke at HUD on the topic of economic mobility in the United States. Chetty was awarded a McArthur genius fellowship and is one of the youngest tenured professors at Harvard University.

Chetty has been working with economists Nathaniel Hendren, Patrick Kline, and Emmanuel Saez on a project called “The Equality of Opportunity Project.” The data published last summer in the New York Times demonstrates that economic mobility varies greatly across geographic regions of the United States.

What is economic mobility?

Using IRS data for over 40 million children and parents, Chetty’s research seeks to answer the question: Is the United States really the land of opportunity? The research measures mobility based on the odds of a child from the bottom 20% of the income bracket reaching the top 20%. Chetty explains this measure as a quantifiable articulation of the American Dream: do children born in poverty have the opportunity to make it to the top?

The overall results of the study demonstrate that the United States ranks particularly low compared to other developed countries. As Chetty states, “Your chance of achieving the American Dream is nearly twice as high in Canada relative to the United States.”

More striking however is the difference in economic mobility between geographic areas within the United States. The research looks at economic outcomes for children who grew up in the bottom 20% based on region. The interactive map demonstrates the average outcome for “commuting zones” or areas relatively close to particular metro area. The visualization calls attention to differences in opportunity geographically across the United States for low-income children.

While those in higher income households tend to not be impacted by location, geography matters for children growing up in poverty. Metropolitan areas such as Memphis, Tennessee, Charlotte, North Carolina and Atlanta, Georgia rank lowest in economic mobility. In Memphis, only 2.8% of children born in the bottom fifth will ever reach the top fifth. In these areas, being raised in poverty significantly affects the chance of achieving the American Dream.

Race and Segregation

According to the National Poverty Center, 58% of America’s poor (26 million people) are racial or ethnic minorities. In looking at the economic mobility heat map, the low-mobility areas in the deep South coincide with areas that traditionally have a high African-American population.

A follow-up article in the New York Times explains that the relationship between race and economic mobility is complicated. Indeed, economists found that low-income white children growing up in areas like Charlotte, NC are equally likely to become low-income adults as their black counterparts. The author concludes that race is not a determinant of economic mobility on an individual level.

Chetty proposes that the relationship between race and mobility might reflect the historical legacy of segregation in areas with larger African American populations. Chetty notes that “Racial segregation tends to go hand-in-hand with income segregation.” This isolation of low-income neighborhoods can impact a child’s chances of succeeding on several levels, from school quality to building social networks.

Furthermore, many of the rural areas with low mobility scores have large populations of Native American or American Indian residents. The bottom ten regions include Mission, South Dakota, home of the Sioux reservation, Gallup, Arizona, home of the Navajo, Hopi and Apache reservations, and several areas in Alaska with large indigenous populations. The intergenerational poverty documented on reservations is visible in Chetty’s economic mobility data.

Policy Implications

As a natural follow-up question, economists looked at which factors predict high rates of upward mobility across areas. The major correlates with high economic mobility Chetty identifies are racial segregation, income inequality, school quality, family structure and social capital. Considering these indicators of upward mobility, where can policy makers effect social change? In order to improve opportunity for low-income children, what are the implications for public policy?

Transportation Policy

As indicated in the New York Times article, high rates of segregation are often found in areas with large urban sprawl. Chetty notes that, “Areas with shorter commutes, denser areas with less sprawl, have much higher rates of upward mobility.” In places such as Atlanta, public transportation has been limited for low-income families. Thus, improvements in transportation could increase economic opportunity and thus upward mobility in urban areas.

Education Policy

Previous research by Chetty, Friedman and Rockoff shows a causal effect between quality teachers and economic mobility. The research above shows that money invested in schools and small student/teacher ratios are strongly correlated with economic mobility. If a single teacher can have an impact on a child’s life, improving the quality of a school could change economic mobility outcomes.

Moving to Opportunity

Chetty dedicated a particular part of his presentation to discussing HUD’s Office of Policy, Development & Research Moving to Opportunity program, a unique experimental design which provided randomized housing vouchers to low-income families to move to lower poverty neighborhoods. This landmark experiment starting in 1994 provided vouchers to 4,600 families with children living in public housing. The results of the study have been analyzed in long-term and short-term impacts, and utilized in numerous reports and policy briefs. The initial findings of the study showed improved physical and mental health outcomes compared to the control group, but relatively no effect on economic outcomes.

Chetty challenges the findings of the MTO experiment by noting that the targeted housing vouchers specifically moved families to areas with lower poverty rates. He hypothesizes that lower poverty rates may not be correlated with improved economic mobility:

Neighborhoods vary in many dimensions: average income, schools, racial integration, public services provided…It is not actually obvious that if you improve the neighborhood in terms of poverty rates that you will improve kids outcomes in terms of upward mobility.

In Chetty’s research, the economists define a neighborhood’s quality based on the outcomes of children in the bottom 20%. In other words, a “good” neighborhood is not necessarily a neighborhood with low poverty rates, but a neighborhood which produces better outcomes for children. These neighborhoods would rank high in upward mobility, as well as school quality and civic engagement.

Chetty suggests that if the same policy mechanism was applied to areas with less segregation, efficient public transportation, and better quality education, young people might be more likely to move upward economically. By looking at upward mobility and intergenerational outcomes, the housing vouchers program could be targeted to provide better opportunities to low-income children.

The data available from the Equality of Opportunity Project is available online to the general public. Raj Chetty’s full presentation can be viewed on the HUD YouTube channel.