Narrative
What factors contribute to the wealth gap in Los Angeles? How are they interconnected? This page examines our research questions through a series of data visualizations, backed by our research.
Table of Contents
Introduction
National trends reveal a persistent racial wealth gap in the U.S., characterized by a concentration of assets among White households and a scarcity among Black and Brown populations. Seeking to understand how these broad patterns manifest on a local scale, we focused our analysis on Los Angeles.
Los Angeles provides a critical lens for this study because it historically pioneered many of the legal and structural mechanisms that created the modern racial wealth gap, demonstrated through our timeline. As documented by historians and in reports like The Color of Wealth in Los Angeles, this region was a primary incubator for racially restrictive covenants and “redlining” practices that were later adopted nationwide. Furthermore, the city’s unique demographic landscape, comprising substantial Black, Latino, Asian, and White populations, allows for a more nuanced, intersectional analysis. The extreme disconnect we see today between the affluent “Westside” and the resource-stripped neighborhoods of South and East L.A. offers tangible, geographic proof of how historical policy decisions continue to dictate current economic outcomes. Our project, “LAyers,” examines this inequality not as a single issue, but as a complex stratification. We adopt an intersectional lens to map the historical, economic, and educational disparities that sustain the city’s racial wealth divide.
Rather than observing patterns in the financial status of individuals sorted by income alone, LAyers argues that inequality is a pattern produced by interconnected systems across geography, education and infrastructure. We posit that wealth disparity is driven by a broken “intergenerational transmission chain,” where historical barriers to housing wealth prevent current generations from accessing higher education and financial security. As Fabien Pfeffer (2018) notes, wealth facilitates access to education, which in turn generates more wealth; conversely, the lack of foundational assets traps communities in a cycle of stagnation regardless of individual effort.
Our analysis combines data from the Federal Reserve, American Community Survey and California Department of Education with key findings from sources listed in our annotated bibliography. We find that while top-tier neighborhoods like Beverly Hills report median household incomes above $120,000, parts of South and East Los Angeles – occupied by higher Black and Brown populations – report under $40,000. Yet as The Color of Wealth report highlights, income is only part of the story: even when income is comparable, the asset gap remains vast, with White families holding many times the liquid assets of their Black and Latino counterparts.
The main guiding question of our project is: How do different layers of systemic economic inequality within Los Angeles contribute to the overall racial wealth gap within the city, limiting economic mobility across generations? This distinction is crucial because as Aladangady and Forde (2021) highlight, the racial wealth gap has widened notably over the past few decades even when income gaps remain static; the average Black and Hispanic household earns about half as much as the average White household but owns only 15 to 20 percent as much net wealth. Through our visualizations and accompanying research questions, we outline each layer of these inequalities and show how external pressures intersect to create an overall picture of systemic and racial wealth disparity.
Our Research Questions
01.
How do systemic inequities in Los Angeles’ public education and housing policies contribute to the racial wealth gap and limit economic mobility?
02.
What patterns exist in neighborhood formation and delineation in Los Angeles and how do they reflect historical segregation and economic exclusion?
Broader Wealth Gap Patterns in the U.S.
To begin our narrative’s analysis, we decided to dive into broader wealth trends within the United States, setting a strong national foundation for our Los Angeles Analysis.
1. How is wealth distributed across the U.S.?
By utilizing cleaned Federal Reserve’s financial data taken from U.S. households, we constructed a stacked bar chart visualizing how wealth has been distributed across different segments of the U.S. population from 1989 to 2024. With a stacked bar format, viewers can see the cumulative total of national wealth while simultaneously observing the proportional contribution of each economic class over time.
This visualization reveals a striking yet persistent imbalance: the vast majority of national wealth is held by the top 10% of the population. Over the 35-year period that was recorded, these groups have experienced the most dramatic growth in net worth. While the total height of the bars (total national wealth) increases over time, the benefits are not shared; compound interest and asset appreciation has allowed the wealthy to accelerate away from the rest of the country.
In contrast, the bottom 50% contributes only a negligible fraction to the total wealth mass each year. Aladangady and Forde (2021) provide context for this, noting that families in the bottom percentile often hold zero or negative net worth due to debt, leaving them without the “financial buffer” necessary to withstand economic shocks. Meanwhile, the Middle Class (next 40%) shows only modest growth, failing to keep pace with the top earners.
Overall, this chart visualizes the foundational inequality of the United States. It demonstrates that the wealth gap is contrived from a solidified structure of asset hoarding. This national trend establishes the necessary context for our specific analysis of Los Angeles, where these broad disparities are further exacerbated by local histories of housing discrimination and racial segmentation.
2. How is wealth distributed by race across the U.S.?
By revisiting the Federal Reserve’s household financial data, we constructed a stacked bar chart to investigate how race intersects with the broader picture of U.S. wealth distribution. This visualization analyzes the progression of net worth across racial groups (White, Black, Hispanic, or Other) from 1989 to 2024, revealing the racial architecture beneath the economic trends.
As the chart illustrates, the increases in wealth over the last 35 years are far from equal. White populations consistently hold the overwhelming majority of the total wealth mass, reflecting a history of cumulative advantage in asset accumulation. In contrast, Black and Hispanic segments remain comparatively thin slivers across the timeline. This highlights a critical distinction central to our “LAyers” thesis: the gap is not merely about current wages, but about the lack of foundational assets, such as homeownership and inherited capital, that allow wealth to compound over generations.
However, a significant limitation within the Federal Reserve’s dataset is the use of the broad “Other” racial category. This grouping obscures essential distinctions by combining diverse populations (including Asian American, Pacific Islander, and Native American communities) into a single label. As emphasized in The Color of Wealth in Los Angeles, aggregating these groups hides unique disparities; for instance, Japanese and Chinese households often show vastly different wealth outcomes compared to Vietnamese or Filipino households. By failing to disaggregate this data, the national model risks masking the specific economic realities that different ethnic groups face.
This visualization confirms that economic growth has continuously disproportionately benefited White populations who have already held substantial wealth. Understanding the racialized context of the wealth distribution is crucial for our specific analysis of Los Angeles, illustrating how the “layers” of inequality we observe from the city, from housing zoning to school funding, are local manifestations of a persistent national structure that prioritizes White wealth accumulation.
3. How does education become a barrier to economic mobility?
The final visualization in this section uses the Federal Reserve’s household financial data to portray the relationship between educational attainment and wealth distribution over time via a stacked bar chart. By categorizing the population into four distinct groups – “College, Some College, High School, and No High School” – viewers can observe the distribution of wealth across the entire United States population, categorized by educational attainment.
Over time, the pattern has remained relatively consistent but increasingly stratified: individuals with a college degree hold the majority of the nation’s wealth, while those with lower levels of education hold significantly less. At first glance, this suggests that higher education correlates with economic opportunity. However, when viewed through the lens of sociologists like Fabien Pfeffer (2018), the causality of this issue is revealed to be far more complex.
Pfeffer’s research on “Growing Wealth Gaps in Education” challenges the assumption that education is the sole driver of wealth. Instead, he identifies a feedback loop: while education helps grow existing wealth, family wealth is often the prerequisite that determines who can access and complete that education in the first place. Pfeffer argues that wealth acts as an “insurance function,” protecting privileged students from risk and allowing them to persist in higher education, whereas students from lower-wealth backgrounds lack this safety net.
Therefore, our graph illustrates two simultaneous ideas. First, it confirms that the “College” demographic has the highest net worth, allowing them to accumulate and pass wealth through generations. Second, combined with Pfeffer’s findings, it suggests that this group is largely self-perpetuating. Even within the population of college graduates, a wealth gap is expanding based on family backgrounds – education is not an equalizer for the unequal distribution of wealth. As noted in our previous section on race, Black and Hispanic families historically hold a fraction of the assets of White families. As a result, even when students of color attain a degree, they often do so with higher debt burdens and less financial security, meaning their degree does not yield the same financial security as their wealthier, White peers.
In summary, education is a powerful tool for wealth accumulation, but primarily serves as a multiplier of advantage rather than a wealth equalizer. As we narrow our focus to Los Angeles in the following sections, we will explore how local systemic inequities reinforce these national patterns.
Education and Housing Outcomes in Los Angeles
As we continue with our analysis, we decided to narrow in on education and housing trends within one of the United States’ bigger cities, Los Angeles, showing how these broader trends display themselves on a more intimate level.
1. How do high school and college attendance rates vary according to race?
To begin our specific analysis of Los Angeles, we access reports from the California Department of Education to analyze the correlation between race and educational attainment, a primary indicator of future economic mobility. This bullet graph visualizes the performance of various racial groups against key benchmarks: high school completion (black lines) and subsequent college attendance (blue bars).
This data reveals that White and Asian students consistently exceed state averages for both high school graduation and college enrollment. In contrast, Black and Latine students who may graduate high school often show a significant drop-off in college attendance. This phenomenon is the result of a structure that compounds racial, housing and education inequities.
According to The Color of Wealth in Los Angeles, these disparities are directly linked to the segmentation of the city. Because public school funding and quality are often linked to local property taxes and parental fundraising, students in wealth-stripped neighborhoods like South LA face a resource deficit that wealthier districts like San Marino or West LA do not. Furthermore, USC sociologist Ann Owens (2016) finds that income segregation between school districts has risen by 20% among families with children, meaning that wealthy families are increasingly isolating themselves in affluent districts. This leaves lower-income Black and Brown students concentrated in schools with fewer AP courses, college counselors, and enrichment opportunities.
Connecting back to our national analysis, Pfeffer (2018) warns that wealth acts as an insurance function. White and Asian families, who hold the vast majority of liquid assets in Los Angeles, can afford to support their children through unpaid internships, tuition spikes, and housing costs during college. Black and Hispanic counterparts, often possessing fractions of the wealth of their White counterparts, lack this buffer. Thus, the gap we see in this graph is both educational and financial. The low net worth of Black and Hispanic families acts as a glass ceiling that prevents qualified high school graduates from transitioning into and completing the higher education necessary to break the cycle of poverty.
2. How does housing affordability vary across Los Angeles income levels?
Continuing our examination of the “layers” of inequality, we use American Community Survey data to analyze the Median Rent-To-Income Ratio in Los Angeles. This bar chart separates the population into income brackets to visualize the regressive nature of housing costs in the city.
This graph reveals that low-income households are frequently severely rent-burdened, creating a financial ceiling that is nearly impossible to break. While high income residents spend only about 16% of their earnings on rent, the lowest income bracket often dedicates over 40% or more of their income to cover housing costs. This pattern demonstrates how housing pressures add an extra layer of financial burden on groups that already face a significant amount of poverty, that need to save the most for economic mobility.
This rent trap is exacerbated by the racial wealth gap identified by Aladangady and Forde (2021). They note that without intergenerationally-accumulated assets, families cannot transition from renting to owning. In Los Angeles, this lack of cushion has historical precedent. Cruz-Viesca et al. outline how government-led housing initiatives, like the redlining and politics illustrated in our timeline, legalized race-based price discrimination in Los Angeles businesses and neighborhoods, establishing a century-long precedent of economic exclusion. These interventions limited the ability of Black and Latino residents to build generational wealth through property ownership (Cruz-Viesca et al., 2018). As a result, homeowners in Los Angeles are disproportionately likely to be White, a direct outcome of historically discriminatory policies that forced Black and Brown demographics into renting populations.
The economic impact of this exclusion is made clear by the fact that in Los Angeles, White households hold a median net worth of $355,000, whereas U.S.-born Black and Mexican households hold just $4,000 and $3,500 respectively (Cruz-Viesca et al., 2018). This local disparity mirrors broader national trends, where wealth is unevenly distributed toward White populations.
Ultimately, Los Angeles’ rent burdens highlight a system where the poorest residents pay the highest proportion of their income for housing. This is not just an economic issue but a racial one, stemming from historical redlining laws that barred Black and Latino families from the property market. This results in marginalized populations being continuously pushed to settle for expensive and exploitative renting practices, limiting them from generational home ownership and ultimately barring them from wealth accumulation.
Disparity by Geography Visualized
To better visualize the inverse relationship between housing income and rent spending, we decided to display a map that outlines the relationship of both factors within Los Angeles.
To visually reinforce the housing income trends we have found within Los Angeles, we utilized geospatial data from the American Community Survey. By integrating Folium, Pandas and Geopandas Python scripting libraries, we constructed an interactive map that portrays the relationship between Median Annual Household Income and the percentage of that income allocated to rent.
This visualization uses census tracts as the primary unit of analysis. The map on the left represents Median Household Income, where dark blue indicates high-income tracts and light blue indicates low-income tracts. Conversely, the map on the right depicts rent burden (percentage of income spent on rent), where light blue represents a low rent burden and dark blue represents a low burden.
Using the slider to compare the two maps reveals an inverse relationship in which areas with the lowest household incomes are consistently those with the highest rent burdens. This visualizes a key economic finding: poorer populations are not only earning less but are paying a significantly larger fraction of their earnings for shelter compared to their wealthier counterparts.
Viewers can see a distinct geographic polarization between the center of the city (characterized by light blue income and dark blue rent burden) and coastal enclaves like Beverly Hills or Manhattan Beach. This spatial separation is not merely a product of market forces but reflects the “hypersegregation” described by Massey and Denton (1993). They argue that racial and economic segregation interact to create a structural area where poverty is concentrated and perpetuated. The map suggests that residents in Mid-City and Central L.A. may be tethered to these areas not by the desirability of the housing, but because of their need for proximity to centralized service jobs and transit, despite the high cost relative to their markets.
This geographic disparity highlights the mechanism of wealth extraction in the rental market. As Desmond (2016) notes, low-income families are frequently trapped in a cycle where exorbitant rent burdens prevent the accumulation of savings necessary for a down payment. The visualization confirms that the highest rent strain is concentrated in historically redlined and minority neighborhoods. This adds a tangible geographic layer to our analysis: the inability to escape the rental market in these census tracts acts as a structural barrier to upward mobility, effectively reinforcing the regional and national racial wealth gap.
Conclusion
Taken together, the visualizations and analyses in this project demonstrate that the racial wealth gap in Los Angeles is not merely a collection of individual economic outcomes, but a result of overlapping systems. As we have outlined, long-standing disparities in wealth, education, and housing reinforce one another, making social mobility increasingly difficult for communities with the fewest resources. The lack of foundational assets highlighted by Pfeffer (2018) and Cruz-Viesca (2018) transforms education from an equalizer into a financial hurdle and turns the housing market into a mechanism of wealth extraction rather than accumulation.
Understanding these patterns is critical because, as M.E. Ryan argues, effectively combating structured inequalities requires us to shift our focus from individual behaviors to the institutional architectures that sustain poverty. We cannot resolve the wealth gap solely through income hikes or financial literacy when the underlying machinery – exclusionary zoning, unequal school funding, and predatory lending policies – remains intact. Ryan suggests that true equity requires aggressive structural interventions that dismantle these barriers, ensuring that the geography of one’s birth does not dictate their economic destiny.
Furthermore, as we look toward the future, we must remain vigilant against new layers of inequality that threaten to compound these historical disparities. Just as highways and industrial zones were historically placed in low-income neighborhoods, the rising demand for AI infrastructure presents a modern challenge. Through our project, we encourage viewers to be wary of the rapid expansion of data centers, which risk becoming vectors of “digital redlining” that consume vast energy and land resources, increasing living costs in communities already burdened by high rents and environmental stressors.
Ultimately, the “layers” of inequality in Los Angeles run deep, but are not immutable. By recognizing these disparities as interconnected parts of a cohesive system, we can begin to advocate for policies that do more than treat the symptoms. Targeted structural interventions are essential to stopping the cycle of wealth extraction and creating a future where economic mobility is a reality for all Angelenos and people in the United States as a whole, rather than a privilege for the few.
