A Profile of Wealth in the New Orleans Metro

Robert Habans Haleigh Tomlin

Published: Jun 18, 2024

Introduction

In the United States, the typical White family has about six times as much wealth as the typical Black family and five times as much wealth as the typical Hispanic family.¹ This racial wealth gap has been generations in the making, and it reflects social and economic injustices of the past, uneven opportunities in the present, and hopes for a future of shared prosperity. Wealth inequality also has immediate stakes: Black and Hispanic households disproportionately lack financial resources to grow businesses; to weather shocks from recessions, health care expenses, disasters, or unexpected job losses; to transfer economic and financial success across generations; to reap compounded returns on investment; and to reinvest their capital in under-resourced communities. Quantifying the wealth gap and its drivers makes it easier to describe the equity issues communities face in clear and actionable ways. Using an original method to estimate detailed breakdowns at a local level, this brief gives a profile of household wealth in the New Orleans metro², highlighting key differences by race and other household characteristics. To further explore the data generated through this method, future publications will examine additional drivers and disparities of wealth in our region.

As in many places across the U.S., organizations in the New Orleans metro are working to make pathways to wealth, economic opportunity, and financial security more inclusive.³ The Data Center recognized the need for wealth estimates in our region through an engagement with the Urban League of Louisiana to provide data and research support to the SEE Change Collective, an initiative to build Black and Latino wealth in the Greater New Orleans area. These efforts need locally relevant data to maximize their impact, and national organizations (the Black Wealth Data Center and the Urban Institute for example) have stepped in to make data on wealth more accessible. Nonetheless, the availability of local wealth estimates remains limited.

To overcome the lack of local data on wealth and contribute to like-minded efforts mentioned above, The Data Center developed model-based statistical estimates of assets and debts for households in the New Orleans metro. Drawing from multiple federal data sources, these estimates are best interpreted as carefully controlled approximations – rather than as direct survey responses from residents – that adjust national patterns in the distribution of wealth to match the population of the New Orleans metro (see Appendix for additional description of the method). We make do with limited information a little like how a meteorologist issues a weather forecast without perfect knowledge of future atmospheric conditions. The predictions may not be exact, but they can be useful for making decisions.

Why local wealth estimates?

There were a few motivating factors to produce these statistical estimates of wealth. First, estimates of differences in wealth give perspective to the challenge of shared prosperity within the New Orleans region. Unlike other snapshot measures of racial equity such as those reported in the New Orleans Prosperity Index and elsewhere, measures of wealth uniquely reflect how the sum of economic and financial resources are distributed across society. The wealth gap tends to be reported at the national level, and even if local estimates generally reflect national trends, they can resonate more with audiences whose interests are primarily local.

Detailed local wealth data can also pinpoint disparities for different segments of the population to provide actionable information to those working to close the racial wealth gap and at other points along the frontlines of systemic inequity. For example, information on differences in net worth over the life course and by socioeconomic status may help to design more efficient, effective, and equitable wealth-building interventions. We hope that incremental enhancements to the availability of local estimates of wealth will encourage more evidence-based efforts and targeted solutions to reduce racial wealth inequality.

Below, we use our original local estimates to paint a picture of wealth in the New Orleans metro. The profile highlights the racial wealth gap, wealth dynamics by age and in relation to other measures of economic opportunity, and the prevalence of households with low asset levels and high debt burdens. For background, we first briefly touch on the latest national data on wealth.

Wealth at the national level: Persistent racial disparities and increasing concentration

National data shows the growing concentration of wealth at the top and deep, persistent racial disparities. Since the 1990s, the wealthiest households have seen the largest increases in their level of wealth.⁶ According to the Survey of Consumer Finances, the median net worth for all families grew from $108,500 in 1989 to $192,700 by 2022 (both in 2022 dollars). But as shown in figure 1, wealthier families fared better over the same period, as median net worth of the top 10 percent of families grew from $1,593,200 to $3,795,000.⁷ The top 10 percent held 61 percent of all wealth in 1989 and 66 percent in 2022 – with 30 percent of all wealth held by the top 1 percent of families.⁸

Meanwhile, differences in median wealth by race have remained large (figure 2). In 2022, the median Black family had $44,900, the median Hispanic family had $62,100, and the median White family had $284,300 in net worth. Non-Hispanic White households make up 65 percent of U.S. households but hold 85 percent of the total wealth. Black households, who make up 12 percent of the total, hold less than 4 percent of the nation’s wealth; and Hispanic households account for 14 percent of the total but only 2.3 percent of wealth.⁹

Net worth reflects the balance of all assets minus all debts, and the mix of assets and debts also varies by race. The two largest asset classes that make up net worth are home equity and retirement accounts.¹⁰ White households are more likely than Black or Hispanic households to hold these asset classes and at higher dollar values, although home equity and retirement accounts often make up a larger share of assets for the Black and Latino households that have them.¹¹ Surveys also show that White families are more likely to hold financial assets, like stocks and mutual funds. While relatively few households have significant business equity or real estate holdings aside from their residence, these are often a large component of wealth for high-net worth households. (See the Appendix for detailed national estimates for specific asset and debt classes by race and ethnicity.)

Disproportionate access to wealth building activities like saving, purchasing a home, and starting a business are part of the long-standing systemic inequities which fuel the persistent wealth gap between White and Black households. Most of the nation’s household wealth is in the form of real estate ownership, but Black-owned property remains undervalued relative to White-owned property, hindering the ability of Black households to gain equitable returns from homeownership.¹² Black people also continue to face persistent barriers in access to the banking and financial system¹³, which has made the task of building Black communities’ trust in banks a key barrier to closing the racial wealth gap.¹⁴ Differential access to types of wealth-generating activities and asset classes also contributes significantly to the wealth gap we see today. See the Appendix for detailed national estimates for specific asset and debt classes by race and ethnicity.

Wealth in the New Orleans metro: Local estimates

Adjusted to represent the local population, estimates of household wealth for greater New Orleans offer a greater level of detail in how wealth varies for residents in our region. Due to limitations in the source data, most of the figures that follow focus on Black and White households, which together make up 88 percent of households in the metro in 2018, the most recent year high-quality data was available.

The racial wealth gap

There are many ways to illustrate the racial wealth gap in the New Orleans metro. Figure 3 compares the distribution of wealth for Black and White households and shows not only median net worth but also the net worth of the wealthiest and least wealthy Black and White households. We estimate median net worth at $14,000 for Black households, $21,000 for Hispanic households, and $185,000 for White households, but relative disparities exist at every level. Estimated net worth for the 30th percentile White household exceeds that of the median (50th percentile) Black household. Only above the 70th percentile does Black household wealth exceed median White household wealth. Stated more directly, only relatively affluent Black households match or exceed the net worth of a typical White household. One way to think about the racial wealth gap is the area between the lines on the graphic in figure 3 – without any Black-White gap, this area would be zero.

While the wealthiest households of our region are far more likely to be White, some Black households also have considerable wealth. Likewise, low net worth – and the economic insecurity that can accompany it – is not exclusively the fate of Black households. Figure 4 shows another way of illustrating the racial wealth gap. It presents breakdowns by race for different parts of the wealth distribution. We show the top 10 percent, the bottom 50 percent, and the 40 percent in the middle.¹⁸ Without any racial disparity, each of these segments of the wealth distribution would look the same and match the demographic makeup of households – shown below, for reference. White households are slightly over-represented in the “middle 40” percent. Black and Hispanic households are more likely to fall in the “bottom 50” with low-to-moderate levels of net worth, where combined they make up the majority of households. The largest imbalance exists among the “top 10” percent, where about 9 in 10 households are White.

Wealth and economic opportunity over the stages of life

Indicators like household income, poverty status, and employment often act as points of reference for discussions of the economic conditions of New Orleans area residents. These are like snapshots in time, but wealth builds gradually, stockpiling returns from economic opportunities realized at earlier stages of life and even across generations.¹⁹ This partly explains why measures of wealth are so compelling: We can identify many individual data points on economic prosperity – income and wages, education and economic mobility, financial resources and burdens, costs of living, and so on – but knowing their cumulative effect is difficult. Nonetheless, all of them eventually flow downstream into wealth. As one might expect, most of the wealthiest residents of the region are older, and most of the less wealthy are younger (figure 5). For this reason, the relationship between age and wealth provides important context for the wealth gap.

To show these dynamics, figure 6 illustrates how median wealth varies with age, with median income shown for comparison. For most younger householders, annual income exceeds net worth, and it is only later in life that the largest gaps in net worth appear. While income tends to peak during ages 35-54, wealth continues to build later in life, until aging households eventually begin to draw down their wealth over age 75. Estimates indicate that median net worth grows to exceed median annual income by age 50s and 60s for Black householders, late in their peak earning years, while this happens for White householders earlier in their peak earning years. It is also later in life when Black-White differences in net worth grow more extreme in dollar terms.

All else equal, we should expect older householders to have more wealth than younger householders. After all, many older adults with sizable net worth were once young adults with little net worth. The difference is that, while the potential for economic opportunity lies ahead for most younger people, it has already been realized for most older people. Older people are also more likely to own their home, and their savings and investments have had more time to grow.

As wealth dynamics change with age, Black and White households experience structurally different economic opportunities, leading to disparities in measures of income, educational attainment, and homeownership, for example. These factors also contribute to differences in wealth. But even when Black households achieve the same markers of economic success as their White peers at the same stage of life, the wealth gap persists.

To explore the link between economic opportunity and wealth outcomes, we highlight disparities that exist for adult householders at different stages of life. Figure 7 shows net worth by age group for householders with and without a four-year college degree. Regardless of race, college-educated householders tend to have more wealth than non-college educated householders of the same age and race. However, Black college graduates tend to have lower net worth than White college graduates at the same stage of life. For Black householders aged 55 and older with a college degree, median net worth is comparable to that of White householders without a college degree.

Home ownership represents a major asset for most American households,²⁰ and equity from owning a home is especially important to the net worth of Black and Hispanic households. Nationally, home equity accounts for over 60 percent of net worth at the median for Black and Latino homeowners, compared with about 40 percent for white homeowners.²¹ Disparities in home ownership rates contribute to the racial wealth gap. In the New Orleans metro, 49 percent of Black householders own their own homes, compared with 64 percent of White householders, as of 2022. Moreover, property values tend to be lower for Black households. In the New Orleans metro, the median value of owner occupied housing in 2018 was $120,000 for Black households and $175,000 for White households.

These uneven outcomes in the housing market are reflected in wealth disparities among homeowners (figure 8). Home ownership is strongly linked to higher levels of net worth for both Black and White households, but Black homeowners tend to have less than half the net worth of White homeowners in the same age group. The estimates also suggest that most Black households that do not own their own home have very low levels of net worth.

Low-wealth and debt-burdened households

Many households in the New Orleans metro have few assets, low net-worth, and burdensome levels of debt, putting their financial well-being in a precarious state. Figure 9 shows the share of households in the New Orleans metro with limited or negative net worth for different race and age cohorts. Here, we define the 25th percentile of net worth nationally, about $7,000 in 2018, as having limited net worth. We estimate that most younger Black householders (aged 25-44) – and nearly a third of older Black householders (aged 55 and up) – have limited or negative net worth.

Assets and debts have a complex relationship, and having debt does not necessarily mean having limited wealth. For example, home buyers and business-owners take on debt to purchase and grow their assets, and many affluent people carry high levels of debt. Nonetheless, the inability to service debt can undermine the financial stability of a household and impede its ability to growth wealth, especially when burdensome debt is not secured against the value of an asset (e.g., debt on a home or business).

One measure of debt burden is the “leverage ratio” of debts to assets. Figure 10 shows local estimates of leverage ratios for households that have both debts and assets, broken out by race and age. Unsurprisingly, younger householders tend to face higher debt burdens. However, Black householders tend to experience over twice the debt burden of White households of the same age cohort. White households actually tend to carry higher levels of debt, but with more limited assets, Black household debts tend to be more leveraged.

Conclusion

The estimates presented in this profile illustrate how wealth is distributed in greater New Orleans while touching on just a few of the countless factors that contribute to the racial wealth gap. In the final tally (figure 11), White households account for about 83 percent of all net worth in the metro. Very affluent and older White households drive the bulk of this total. Black households account for less than 10 percent of total net worth, an imbalance driven by the limited net worth of Black households. For reference, householders in the New Orleans metro were 54 percent White, 34 percent Black, 7.5 percent Hispanic, and 2.3 percent Asian in 2018. With generations of wealth inequality etched into our neighborhoods and social networks, Black households would face constrained access to investment capital, income mobility, and financial security – even if our current economic and social institutions were operating without bias or discrimination.

We see traces of the racial wealth gap in our everyday lives, but non-local factors like national economic conditions and federal policies play a major role in shaping the distribution of wealth. National shocks like COVID-19 and the Great Recession led to measurable but uneven shifts in levels of wealth and, by extension, the median racial wealth gap. Because both returns to wealth and barriers to economic mobility are compounding in nature, there is no single “fix” for the racial wealth gap – at least short of a dramatic shift in federal policies toward progressive taxation or redress for racial injustices.²² If the concentration of wealth continues unabated at the national level, the racial wealth gap in greater New Orleans is also likely to grow.

At the local level, organizations are working to increase access to wealth-building opportunities in underserved communities and to address inequities across various systems that determine economic opportunity and financial well-being, such as housing, education, lending, and employment. Solutions must have a focused but holistic approach to make meaningful progress in reducing the racial wealth gap,²³ and more detailed data can provide a more complete picture. For example:

• Considering the age dynamics of wealth, helping young adults get on the ramp to accruing assets may reduce disparities that widen later in adulthood. However, even successful interventions may not yield measurable impacts for years.
• Most wealthy households own their own home, tying housing equity to wealth equity. Efforts to support wealth-building for existing homeowners, first-time home buyers, and renters are likely to take very different forms. In recent years, as increases in home value have boosted the wealth of homeowners, entering the market has become more prohibitive for first-time buyers, and rent has increased, leaving non-homeowners further behind. These cost burdens disproportionately affect younger and less wealthy Black households.
• Wealth is broader than income, but research shows that there remains a strong link between the racial income gap and the persistence of the racial wealth gap.²⁴ The potential consequences for reducing the racial wealth gap further bolster the case for increasing income for Black residents of the metro and underscore the immediacy of broadening inclusion in the local labor market.²⁵
• In some cases, local estimates of wealth may offer new ways to explore the distributional effects of policies that are not nominally focused on wealth.²⁶ For example, investments in flood protection are often assessed on the basis of their cost relative to the value of reduced risk to property. Such benefit-cost analyses often have a subtle bias: They tend to put more weight on properties with a high market value and, by extension, the impacts on wealthier households who tend to hold them. Though the property of less wealthy homeowners tends to have lower market value, it often makes up a larger portion of their overall asset portfolio. Local data can shed light on how the distribution of assets relates to the distribution of costs and benefits, which can have the effect of advancing racial and wealth equity in decisionmaking.

The estimates presented in this brief are only one route to strengthening the availability of local, racially disaggregated data on wealth,²⁷ but they can help to inform wealth-building initiatives or to assess the consequences of other important policy decisions with respect to wealth equity. Better data is only a first step.

Acknowledgements

This report was supported in part by the Black Wealth Data Center (BWDC). The BWDC – launched by Bloomberg Philanthropies’ Greenwood Initiative – provides public and private sector leaders with data disaggregated by race to help advance racial wealth equity. The project also received generous support from the Urban League of Louisiana, the W.K. Kellogg Foundation, and the Kresge Foundation.

The Data Center wishes to thank Leah Hendey, David Asiamah, Luc Schuster, and Tyronne Walker for reviewing an earlier draft. For invaluable help in getting up and running with federal wealth data, the authors also wish to thank Amee Amin and Aaron Williams for offering guidance early in the project, and the Census Bureau staff who led a SIPP workshop at the 2023 Population Association of America Annual Meeting.

Appendix

Procedure for estimating detailed wealth breakdowns at a local level

Here, we briefly describe the procedure for generating local estimates but refer interested readers to the companion technical paper for additional details.

Most of what The Data Center publishes is based on data directly reported from federal government sources, but the national surveys commonly used to examine wealth inequality do not allow for local breakdowns. The metro-level estimates in this report are based on a statistical procedure designed to make detailed local breakdowns possible. Readers should know that these estimates, which combine information from two surveys, are approximate and subject to error.

The authors use a statistical model to predict the percentile ranking of households in the national wealth distribution. Predictive models are fit on a national data set derived from the Survey of Income and Program Participation (SIPP) for 2018. Assets and debts are predicted based on information reported in both surveys: common demographic and socioeconomic measures, income and work status, homeownership and home values, and state and metropolitan status. The results are used to generate estimates for the population of the New Orleans metro. The estimates are poststratified to be representative of the New Orleans metro, based on more reliable and more geographically detailed estimates for local population subgroups derived from American Community Survey microdata, also from 2018. Additional steps are taken to address the skewed distribution of assets and debts. These steps and other details of the predictive model and the procedure for generating local estimates are in the companion technical paper, which we offer both for transparency and as a contribution to broader efforts to make information on the racial wealth gap more locally relevant and more actionable.

The estimates are best interpreted as a reflection of national patterns in the distribution of wealth but adjusted to match the population of the New Orleans metro. Readers should be aware that using predictive models implies uncertainty, but this uncertainty differs from the sample uncertainty typically reported as margins of error for conventional survey-based estimates. In fact, the procedure is based on a framework (multilevel regression and poststratification) most commonly used to generate reliable estimates from national surveys, where small sample sizes otherwise would prohibit precise estimates for subnational areas or detailed population subgroups. Conservatively, we only report detailed race-by-age estimates for Black and White households because the number of observations in the American Community Survey is relatively large for these subgroups. Another limitation is that estimates from the model are driven by differences in the local composition of households with respect to factors that predict wealth, but they do not directly incorporate unique contextual aspects of the New Orleans metro that might affect wealth outcomes.

To “stress test” the detailed breakdowns, we checked to see if the numbers we report are plausible given limited available information and differences in the underlying data sources. Generally, we compared our local SIPP-based estimates with conventional estimates from SIPP for the entire nation and for Louisiana, although we note that state-level estimates are noisy for subgroups due to the small sample size. We also consulted estimates from many published studies, reports, and online web resources and found the following to be especially useful as points of reference: Survey of Consumer Finance website, Distributional Financial Accounts website, SIPP published reports, Black Wealth Data Center website, Urban Institute’s Financial Health and Wealth Dashboard.

Estimates of asset and debt holdings from national data sources

In the paper, we describe the makeup of net worth in terms of specific asset and debt classes. How these asset and debt classes are defined and reported varies across data sources. As a result of these differences, specific estimates also vary. For transparency, we provide detailed tables by race/ethnicity here, as well as links to find data from other sources.

• The following tables were estimated directly by the study authors using 2018 SIPP data – the same data used for the local estimates. They report the percentage of households having a given asset/debt class, the median value conditional on holding the asset/debt class, and the share of total net worth accounted for by the asset and debt class. These estimates have sample error, and we do not report the estimate when the coefficient of variation (i.e., the ratio of the sample standard error to the sample mean) exceeds 0.15.

• Estimates of asset and debt classes by race/ethnicity are available from the Survey of Consumer Finances. They can be found on the linked web page in a downloadable Excel file under tables 6, 9, and 13. Estimates are reported in 2022 dollars for the percentage of families holding the asset/debt class, the median value of holdings for families holding the asset, and the mean value of holdings for families holding the asset. Note that, in addition to differences in the categories and concepts used for reporting asset and debt classes, the Survey of Consumer Finances reports estimates for families while SIPP reports for households.

• Distributional Financial Accounts is a newer data product that provides quarterly estimates of aggregate wealth and the components of wealth. This data product combines information from the Survey of Consumer Finances with the Financial Accounts of the United States, which provide quarterly data on aggregate balance sheets of major sectors of the U.S. economy, to illustrate the aggregate makeup of wealth in the United States. These sources use different concepts of wealth, and the reported asset/debt categories reflect an attempt to reconcile the concepts. We reproduce the breakdowns of assets and debts reported for the third quarter 2022.

Github repository

Coming soon!

Endnotes

¹Federal Reserve Board’s Division of Research and Statistics, “Changes in U.S. Family Finances from 2019 to 2022.”

²As of 2023, the New Orleans metro no longer includes St. Tammany Parish. However, because we use data from before this change occurred, all metro-level estimates include St. Tammany Parish and reflect the eight-parish metro definition from 2013.”

³ SEE CHANGE Collective, “Closing the Racial Wealth Gap for Blacks, Hispanics and Latinos in Greater New Orleans.”

⁴ Eggleston and Klee, “Reassessing Wealth Data Quality in the Survey of Income and Program Participation.”

⁵ Kochhar and Moslimani, “Wealth Surged in the Pandemic, but Debt Endures for Poorer Black and Hispanic Families.”

⁶ Piketty, A Brief History of Equality.

⁷ Federal Reserve Board’s Division of Research and Statistics, “Changes in U.S. Family Finances from 2019 to 2022.”

⁸ Board of Governors of the Federal Reserve System, “DFA.”

⁹ This is based on data taken from the Distributional Financial Accounts for Q3 2022 and the American Community Survey for 2022. (Board of Governors of the Federal Reserve System)

¹⁰ Sullivan, Hays, and Bennett, “The Wealth of Households.”

¹¹ Sabelhaus and Thompson, “Racial Wealth Disparities”; Kochhar and Moslimani, “Wealth Surged in the Pandemic, but Debt Endures for Poorer Black and Hispanic Families.”

¹² Perry, Rothwell, and Harshberger, “The Devaluation of Assets in Black Neighborhoods.”

¹³ Florant et al., “The Case for Accelerating Financial Inclusion in Black Communities.”

¹⁴ Zinn, Neal, and Perry, “Building Trust in the Financial System Is Key to Closing the Racial Wealth Gap.”

¹⁵ Federal Reserve Board’s Division of Research and Statistics, “Changes in u.s. Family Finances from 2019 to 2022.”

¹⁶ Perry, Stephens, and Donoghoe, “Black Wealth Is Increasing, but so Is the Racial Wealth Gap.”

¹⁷ Perry, Stephens, and Donoghoe.

¹⁸ Comparable 50-40-10 breakdowns have been used in research on wealth inequality. (Piketty, A Brief History of Equality)

¹⁹ Chetty et al., “Race and Economic Opportunity in the United States.”

²⁰ Sullivan, Hays, and Bennett, “The Wealth of Households.”

²¹ This is based on Pew Research Center calculations that take the median value of a share in household net worth for households that own that type of asset. Ownership of their primary residence accounted for a median share of 45 percent of total net worth among all homeowners. (Kochhar and Moslimani, “Wealth Surged in the Pandemic, but Debt Endures for Poorer Black and Hispanic Families,” 27–28)

²² Perry, Stephens, and Donoghoe, “Black Wealth Is Increasing, but so Is the Racial Wealth Gap.”

²³ To give a local example, the Urban League of Louisiana’s SEE CHANGE Collective has developed a three-pronged action plan around homeownership, income and wages, and entrepreneurship to build Black and Latino wealth.

²⁴ Aliprantis and Carroll, “What Is Behind the Persistence of the Racial Wealth Gap?”

²⁵ The Data Center, “Potential Economic Impact of Increasing Income for Black New Orleanians.”

²⁶ National Science and Technology Council, “Advancing the Frontiers of Benefit-Cost Analysis.”

²⁷ Biu and Axelrod, “Addressing Data Limitations to Improve Racial Wealth Equity.”