While the two previous chapters explored why there are large differences in life expectancy at the neighborhood level in New Orleans and across the metro area, this chapter draws from decades of research and policy debates to grapple with the implications for the future of New Orleans neighborhoods. The 15th anniversary of Hurricane Katrina offers an auspicious moment to reflect on the relationship between neighborhoods and racial inequality. Six months into a devastating pandemic, as governments, major institutions, nonprofits, and businesses take steps to center issues of racial justice, the moment is equally ripe for action. This chapter reflects on the role of place-based policy and practice in reducing racial and neighborhood inequality.
If neighborhoods matter for inclusive regional prosperity, what would it take to reduce inequalities of health and well-being? Answering this question requires attention to inequalities beyond the neighborhood level, the dynamics of residential mobility, and the ways that these dimensions intersect with racial inequity. While the focus here remains on neighborhood differences in life expectancy and economic opportunity before the pandemic, many of the same underlying factors contribute to the disproportionate impacts of COVID-19 on people of color and the places they live — and provide context for imagining a more equitable, more inclusive recovery.Racial disparities and the impacts of COVID-19
Chapter 1 gave a snapshot of how income levels vary by neighborhood and correspond with life expectancy, but income mobility also differs by neighborhood. By linking childhood incomes with incomes in adulthood, the “Opportunity Atlas” shows how children who grew up in households with the same income levels might, on average, experience different degrees of upward income mobility depending on where they grew up.[note] In addition to illustrating neighborhood differences in economic opportunity, this data also illustrates how racial and geographic inequality can have effects that extend across generations.Data from the Opportunity Atlas
The Opportunity Atlas defines upward income mobility in a specific way. For children born around 1980 who grew up in greater New Orleans and in low-income households (defined as the 25th percentile of the national household income distribution, about $27,000), their household income as adults in 2014-2015 rose to the 38th percentile on average.[note] This is slightly lower than the rate of upward mobility for low-income children nationwide, whose adult incomes rose to the 41st percentile on average. But more importantly, as with life expectancy, income mobility varies widely across the metro.
For the 10 percent of census tracts with the lowest rates of income mobility, the average adult income for children at the 25th percentile reached only the 29th percentile by adulthood. For the 10 percent of census tracts with the highest rates of income mobility, children with similar socioeconomic status had an average adult income at the 53rd percentile. In other words, adult incomes rose substantially for low-income children from some neighborhoods but rose barely at all for their peers in other neighborhoods.
The Opportunity Atlas also illustrates how differences in income mobility by race persist regardless of childhood household income or childhood census tract. On average, low-income black children experienced less upward mobility in adulthood than white children who grew up at the same time, in households at the same income level, and in neighborhoods with similar average rates of upward mobility for all children.[note] These differences contribute to maintaining the racial income gap across generations.
Differences in economic opportunity are associated with life expectancy. Our analysis of the life expectancy (USALEEP) and income mobility (Opportunity Atlas) data shows that, while there are outliers and exceptions among New Orleans neighborhoods, long lives tend to go hand in hand with socioeconomic opportunities.
Given the pervasive gaps in income mobility and life expectancy, what is the best way to target interventions that reduce neighborhood inequality? This is an old question without a conclusive answer. Since the 1960s, the distinction between “people prosperity” and “place prosperity” has been central to the design of urban policy. People-based interventions target disadvantaged individuals and families, regardless of where they live. Housing assistance in the form of portable vouchers is a classic example of people-based housing policy since it follows the recipient and is not tied to a specific site of affordable housing.[note] In contrast, place-based interventions prioritize disadvantaged places, either through providing assistance and incentives to residents or businesses within a geographically defined area or through targeted investments in infrastructure, the built environment, or other neighborhood-oriented public resources.
Nationally, the most recent major example of place-based policy lies in the 8,764 Opportunity Zones that were designated across the United States in 2018. Louisiana has 150 Opportunity Zones, covering areas as diverse as portions of the Claiborne Corridor, New Orleans East, the Lower 9th Ward, the CBD, Fat City and Lakeside Mall, Arabi, and Gretna. Opportunity Zones are qualified low-income census tracts where investors are eligible to receive capital gains tax incentives. The program seeks to unlock long-term investments in disadvantaged areas. Despite a frenzy of interest, their long-term impact remains unclear — early signs suggest that Opportunity Zones may be channeling capital into communities in a way that hasn’t necessarily promoted equitable development. What is clear is that pushes to innovate place-based policy were already gaining steam in national and local policy circles in the years leading up to 2020.[note]Conventional arguments for people- and place-based approaches
The history of urban policy is not characterized by linear progress, but it has a rhythm. Debates over the merits and mechanics of people- and place-based policy historically have tended to resurface when geographic and racial inequalities come into sharp, mainstream focus. Nationally, the same themes appeared as policymakers turned to address black inner-city poverty at the peak of the Civil Rights and War on Poverty eras (1960s) and to remake federal public housing programs (1980s-1990s). Even the aftermath of Hurricane Katrina and the levee failures brought out well-worn arguments about whether the federal government should finance the rebuilding and protection of New Orleans or instead ease the permanent relocation of the displaced — especially those who hypothetically might find more opportunities and fewer environmental risks in other parts of the country.
A tumultuous 2020 has again laid bare legacies of segregation and exclusion through racial disparities in loss of life to COVID-19; uneven exposure to pandemic job loss, business closures, and financial instability among communities of color; and systemic police violence against black people. Many proposals for an equitable, long-term recovery agenda incorporate place-based frameworks for addressing historical and current disinvestment, lifting up under-valued neighborhood assets, and working across sites and levels of governance. While equitable recovery requires a place-based emphasis, previous experiences with place-based policy have been under-resourced, piecemeal, and insufficiently shaped by the communities they intend to serve.
Even before COVID, an increasingly defining feature of hybrid, “place-conscious” policy frameworks has been to avoid viewing people-based and place-based approaches as an either/or choice.[note] For a start, policy and program designers should recognize, first, that individual and family outcomes are structured by neighborhood conditions, as well as opportunities at the regional level. Additionally, neighborhoods are not fixed but are instead constantly changing, and the dynamics of residential mobility must be considered in designing interventions.
Place-based inequality remains entangled with racial inequality, although many questions remain regarding the role of neighborhoods in causing inequality. These questions have long played a central role in how research, public policy, and philanthropy has sought to address racial inequalities. The analysis presented in the previous two chapters draws from scholarship on “neighborhood effects.” This research seeks to measure the effect of neighborhoods on individual outcomes like health, economic mobility, or education. Neighborhood conditions are thought to influence individual outcomes through various pathways, including the physical environment, institutions, and social interactions. A lot of the evidence suggests that “place matters”: neighborhood conditions influence a wide range of individual and family outcomes related to socioeconomic opportunity and health.Neighborhood effects are easy to imagine but hard to measure
Research on neighborhood effects and its breathless reporting in the media (e.g., headlines like “ZIP Code destiny” or “Change of address offers pathway out of poverty”) has pushed back against harmful stereotypes, armed advocates with evidence to fight systemic inequality, and influenced urban policy at all levels. However, too often, the way questions about neighborhoods are asked and answered do little to disrupt the stigma of disadvantaged places and the reductive implication that the poor should simply move to high-opportunity areas. A narrow focus on the effects of concentrated disadvantage within places can shift the emphasis away from the drivers of geographic inequality across places.
As reflected in the touchstone “Moving to Opportunity” experiment, a common assumption is that exposure to mixed-income neighborhoods, rather than the capability to choose and to shape the conditions where one lives, is a primary pathway toward improving outcomes for low-income individuals. In this framing, the problem is that disadvantaged neighborhoods, which are the primary focus of neighborhood effects research, lack the qualities of middle- and high-income neighborhoods, which are themselves rarely subjected to the same scrutiny. The implications of this body of research can oversell the beneficial effects of mixed-income neighborhoods while undercutting the assets that exist in relatively disadvantaged neighborhoods and sidestepping the root causes of inequity.[note]The “Moving to Opportunity” study
According to a national study, for African American children who grew up in neighborhoods of concentrated disadvantage in the 1970s and 1980s, roughly three-quarters grew up to live in similarly disadvantaged neighborhoods. The relative rarity of individuals moving out of disadvantaged neighborhoods calls into question interventions that narrowly focus on individual mobility without some place-based component. Low-income families already move at relatively high frequencies, but they tend to move into and out of low-income neighborhoods. Often, these moves are driven by housing instability or financial insecurity. Such moves can pry apart neighborhood-based social networks and undermine neighborhood-focused interventions.
Even if a people-based, mobility-oriented solution had easily understood benefits, contemporary housing markets constrain choice. The realities of housing affordability undercut the feasibility of meaningfully scaling up efforts to reduce inequality by moving people to neighborhoods with better opportunities and higher life expectancies. The chart compares housing affordability with neighborhood life expectancy. In addition to showing that living in higher life expectancy neighborhoods cost more on average, it also suggests that a typical resident of neighborhoods with low life expectancy would struggle to afford housing in neighborhoods with high life expectancies. Residents of neighborhoods with the lowest life expectancies are already “housing cost burdened” (30 percent or more of gross income goes to housing costs). Meanwhile, residents of high life expectancy neighborhoods pay more for the privilege, but their incomes, net of housing expenses, remain far higher than the incomes of residents of neighborhoods with lower life expectancies.
Life expectancy and income mobility at the neighborhood level may be a simple, compelling way to quantify life chances, but these outcomes reflect complex relationships and inter-connected, multi-layered, historically entrenched geographies of inequality. Re-shaping cities to promote healthy neighborhoods will require a greater attention to systems that produce health, involvement of a wide range of stakeholders, and a focus on health inequalities within urban areas. Re-leveling longstanding patterns of investment and disinvestment requires connecting all neighborhoods to the opportunities in the regional economy — without inviting further exclusion and displacement.
While these issues present clear challenges, there’s room for optimism as we begin to imagine an equitable recovery from the pandemic’s economic and health crises. Ultimately, the value of new neighborhood-level data on life chances lies in empowering a more diverse range of stakeholders to engage with the interconnected nature of place-based inequality. On that note, here are some closing takeaways from our findings for the New Orleans metro and from other recent studies.
Neighborhood inequality took a long time to weave together, and it will take sustained effort to untangle. It took generations of segregation, discrimination, and public policy to design neighborhood inequality. This inequality continues to be remade every day — especially when it amplifies the impacts of crises like Hurricane Katrina, the Great Recession, and COVID-19. It continues to have generational consequences as long as people’s life chances are based on where they live. These conditions can’t be unraveled overnight. Place-conscious approaches should advance a long-term perspective, with durable investments to match the longstanding and persistent nature of disinvestment in urban neighborhoods. To be sure, simply pouring investment into struggling neighborhoods does not necessarily confront systemic inequities, especially if local businesses and workers do not reap the benefits in the form of enhanced community wealth. Place-conscious approaches build on existing assets and capacities, reflect the priorities of residents who know their neighborhoods best, and connect strategies in a way that is robust to varied timelines and uncertainty.
Interventions focused inward on neighborhoods are necessary but not sufficient to reduce racial and place-based inequality. Neighborhood conditions are shaped by policies and economic factors that occur outside of neighborhoods. Inequality may be amplified by geography, but rarely is geography its root cause. Community stakeholders and policymakers increasingly recognize the necessity for cutting across multiple levels of governance (neighborhood, local, region, national). For example, expanding employment opportunities may mean creating jobs within specific neighborhoods or removing barriers between residents and jobs elsewhere in the region. Job creation has stronger economic impacts in distressed places, especially where they link residents to opportunities that the labor market does not always adequately provide. In this way, reducing neighborhood inequality fits as a priority for regional economic development.
Multiple dimensions of inequality come together at the neighborhood level. Eliminating gaps in life expectancy requires reducing inequities outside of the domain of health and health care. Evidence increasingly stresses the “causes of the causes” of unequal health outcomes, like differences in income, wealth, and education.. Integrated strategies that weave together multiple domains that determine well-being — health, safety, education, and employment — are likely to have magnified impacts. Of course, integrated approaches must also face headwinds and tailwinds beyond the neighborhood level. Since long-term processes of economic, social, and political reform can change the rules of the game, recoveries from crises like Hurricane Katrina, the Great Recession, and COVID-19 are important moments: They are inflection points where underlying pathways of change can either shift or accelerate.
However, discerning whether and to what extent neighborhood effects contribute independently to economic, social, and health inequality has proven to be a vexing challenge. In part, this is an issue of measurement.[note] Where people live is not random, and residential mobility complicates how we measure the effect of place or the impact of place-based policy.[note] For many “neighborhood effects” researchers, this acts as a central challenge to understanding whether neighborhood conditions are a cause or a consequence of health or socioeconomic inequality.
Where a person chooses to live is shaped by individual characteristics like preferences, financial constraints, or proximity to work and school. The result is that similar kinds of households tend to live in similar neighborhoods. Relatively wealthy households have a choice among perceived high-opportunity, high-amenity neighborhoods while lower-income households often struggle to find neighborhoods with affordable housing and transportation options. Do neighborhoods have an independent effect on individual outcomes, or is neighborhood inequality a result of the tendency of individuals with similar outcomes to co-locate in the same neighborhoods — whether by choice or circumstance? Researchers call this problem “selection bias.”
Selective residential mobility can have important stakes for research and policy. However, framing these stakes as an either/or question can distract from deeper questions about the underlying conditions that drive uneven neighborhood investment, shape residential mobility, and maintain the close relationship between these dynamics and race. Given the historical dimensions of neighborhood inequality (Chapter 2) and the complex interactions among different demographic, health, and socioeconomic factors at the neighborhood level (Chapter 1), whether “place matters” should not depend on a measurement problem.
It’s important that place-conscious policies be “data-driven”, based on sound research, and evaluated with due attention to the complexity of place. Residential mobility and selection bias pose challenges to mainstream approaches to measuring the causal effect of neighborhoods on individual outcomes and to evaluating place-based programs and policies. These challenges provoke integrative, multi-disciplinary, and multi-level approaches to data and analysis.
There are limits to treating neighborhoods as the sole unit of analysis. Additional research could do better to clarify how different neighborhood outcomes interact with residential mobility dynamics; how place-based inequality is a multi-layered phenomenon that is not strictly (or even mostly) determined by individual or neighborhood-level factors; and whether neighborhood inequality contributes to, mediates, or merely reflects broader processes of social inequity.
Integrated data systems, which link administrative data from multiple programs, can leverage the efficiencies of place-based, multisited organizational partnerships. Linked data can support rigorous program design and evaluation while enabling continuous on-the-ground learning outside of a conventional program evaluation context.
A “data-driven” approach also means bringing numbers into dialog with community-based knowledge, qualitative data, and comparative perspectives. As better research and better data with more local detail continues to trickle out from national sources like USALEEP, stakeholders are better equipped to work across systems in reducing place-based inequality. At the same time, building the capacity of stakeholders in low-income neighborhoods to own and use their own data is an important tool in the toolbox to ensure that everyone has the ability to shape decisions about their own neighborhood.
Since the initial weeks of the pandemic, racial disparities have been widely reported by media, research, and health organizations, as well as by The Data Center. While the analysis below does not directly focus on COVID-19, several patterns of inequitable outcomes are, by this point, well-documented, for example:
COVID-related deaths remain higher for black people. As of early June, in Orleans Parish, black residents accounted for 77 percent of COVID-19 deaths but only 60 percent of the population. In New Orleans, black-white disparities are far more skewed when accounting for COVID deaths outside of the acutely vulnerable population of assisted living facilities.
On average, black New Orleanians are more likely to live in lower-income, more crowded, and multi-generational households. These conditions can limit the ability to isolate elderly family members with the greatest risk and contribute to the spread of the virus.
As unemployment has skyrocketed for all workers, workers of color have been especially vulnerable to job loss. This is because workers of color are concentrated in the hardest-hit industries, like restaurants, hotels, and retail. Because these jobs also tend to pay lower wages with fewer benefits, many laid-off workers do not have the financial resources to weather a prolonged loss of income.
Workers of color are also disproportionately concentrated in low-earning, high-contact “essential” jobs – such as retail, health care, and transportation and logistics – where working from home is not possible. These workers often rely on public transit and may work in settings where effective social distancing can be difficult to maintain.
Black Louisianans have long experienced disproportionate barriers in access to health care, as well as systemic bias in interactions with the health care system, that further complicate the ability to manage infections.
On a surface level, each of these conditions contributes to the disparate harms of the pandemic. Underlying these disparities is the fact that “social inequities are patterned by place” and thus deeply related to the legacy of segregation, uneven investment, and the processes that maintain neighborhood inequality. The next section turns to differences in economic opportunity by neighborhood. This is both a key determinant of inequitable life expectancies and an underlying factor in COVID-19 disparities.