The Rising Importance of Stock-Linked Assets in the Black–White Wealth Gap

Abstract

Introduction

Extensive research has developed three explanations for the persistence and magnitude of the Black–White wealth gap in the United States (Keister and Moller 2000; Killewald et al. 2017; Oliver and Shapiro 2006): (1) differences in household characteristics associated with wealth accumulation, such as earnings, education, and family stability (Keister 2004; Maroto 2018); (2) discrimination in the housing and credit markets (Baradaran 2017; Killewald and Bryan 2016); and (3) diverging rates and amounts of interfamily transfers to Black and White offspring (McKernan et al. 2014; Pfeffer and Killewald 2018). Although these explanations are well-supported by empirical evidence, they largely focus on wealth as a whole and omit the transformation of both macroeconomic conditions and household portfolios over time (Keister and Moller 2000). As financial markets have become key sites for organizing resource distribution, financial assets—particularly corporate stocks—have constituted a growing share of wealth among American families (Davis 2009; Lin and Neely 2020).

Several studies have documented a widening racial disparity in financial assets (Derenoncourt et al. 2022; Gittleman and Wolff 2004; Gutter and Fontes 2006; Oliver and Shapiro 2006). White households, on average, hold more of their wealth in financial assets than Black households. Because financial assets have appreciated at higher rates than nonfinancial assets in recent decades, scholars expect that racial differences in household portfolios will widen the Black–White wealth gap.

Although financial assets may contribute to some Black–White wealth inequality, the magnitude of this contribution remains undetermined. Particularly untested is how significant financial wealth is relative to traditionally important assets, such as home and business ownership. Furthermore, because wealthy and high-income households tend to allocate a higher proportion of their wealth to investment, it remains unclear whether the observed racial disparity in financial assets is mostly a reflection of wealth and income disparities or there is a racial difference in financial asset ownership even among Black and White households with similar income and wealth. If there is indeed a difference, to what extent does it contribute to the Black–White wealth gap?

To assess the impact of financial assets on racial wealth inequality, this study decomposes the average Black–White net worth gap by a set of mutually exclusive and collectively exhaustive components. Using data from the Survey of Consumer Finances and the Panel Study of Income Dynamics, we find that the contribution of directly held stocks and retirement accounts to the racial wealth gap has increased in both absolute and relative terms since the 1980s. The size of their contribution has surpassed that of traditional assets, such as homeownership and business equity, in the 1990s and accounts for 35% to 40% of the average Black–White wealth gap since the 2000s.

The contribution of stock-linked assets to the racial wealth gap remains salient when we remove the most affluent families from the sample, illustrating that the significance of these assets is not entirely driven by (financial) wealth concentration at the top. We also find that incorporating unrealized entitlement wealth, such as traditional pensions and Social Security, in the analysis does not alter the trend.

Importantly, a substantial disparity in stock-linked assets persists even when we compare matched samples of Black and White families with similar economic and household characteristics, indicating that the disparity is not driven merely by the differences in composition. Although the disparity is greater among Black and White households with higher home equity, income, and education, and an older household head, White households with lower levels of economic resources or a younger household head still own more financial wealth than their Black counterparts: the racial disparity cuts across class boundaries and life course stage.

Furthermore, we assess the impact of stock-linked assets on the racial wealth gap using a matched sample of Black and White households in the PSID. We find that the financial asset disparity could account for nearly a quarter of the Black–White difference in future net worth. Assigning the same amount of stock-linked assets and an equal rate of return to matched Black and White households in this sample would increase Black households' average future net worth from 57% to 67% of that of White households for this sample.

These results, together, indicate that stock-linked assets have become a dominant source of the U.S. racial wealth gap, and financial markets have become key domains in which the racial wealth disparity is maintained and augmented. Although homeownership, labor market inequality, and intergenerational transfers remain influential in generating the Black–White wealth gap, our results call for more studies that investigate the causes and consequences of financial asset disparities.

Our findings also reveal that the financialization of the economy has transformed wealth stratification in the United States. Because affluent White families possess more stocks through direct purchases and retirement benefits, they are advantaged in a distributional regime that channels a growing amount of resources to shareholders (Lin and Neely 2020). Black families, as well as White families with low net worth, are excluded from the surplus-sharing. The continuing stock market growth is linked not only to increased wealth concentration (Keister and Moller 2000) but also to greater racial wealth disparity.

Black–White Wealth Gap

A prominent feature of wealth in the United States is its extremely unequal distribution (Derenoncourt et al. 2022; Pfeffer and Waitkus 2021), particularly between non-Hispanic Black and White households (Killewald et al. 2017; Maroto 2016; Oliver and Shapiro 2006). White households accumulate wealth at a higher rate over the life course (Killewald and Bryan 2018) and experience lower wealth losses during recessions compared with Black households (Pfeffer et al. 2013; Wolff 2014).

Researchers have offered several explanations for this persistent Black–White wealth gap (Killewald et al. 2017; Oliver and Shapiro 2006). Because wealth is a consequence of multiple economic factors, an obvious explanation is the compositional differences between Black and White households, particularly regarding income, education, and family structure. Prevalent labor market discrimination and unequal access in the educational system have reduced Black workers' earnings, even relative to White workers with similar occupations and educational levels (Grodsky and Pager 2001; Pager and Shepherd 2008). Lower and less stable incomes inhibit wealth accumulation (Altonji and Doraszelski 2005; Barsky et al. 2002; Gittleman and Wolff 2004; Rauscher and Elliott 2016; Wolff 2022), a disadvantage compounded by mass incarceration and family instability. These factors reduce Black households' capacity to form family structures that facilitate wealth-building across generations (Maroto 2015; Raley et al. 2019; Turney and Schneider 2016; Vespa and Painter 2011).

Beyond compositional differences, studies have identified homeownership, access to credit, and residential segregation as key mechanisms generating racial wealth inequality (Taylor 2019). For many American families, most wealth is held in home equity, and the stability associated with homeownership serves as a cornerstone for wealth accumulation (Killewald and Bryan 2016; Ren 2020; Shapiro 2004). Yet, historically, policies in the United States have privileged White over Black homeownership (Baradaran 2017; Oliver and Shapiro 2006; Robinson 2020). Housing discrimination and residential segregation cause Black families' properties to appreciate at lower rates than those of White families (Flippen 2004; Krivo and Kaufman 2004; Levy 2022). Black households were also more often targeted by subprime loans, resulting in wealth depletion during the Great Recession (Hwang et al. 2015; Rugh et al. 2015; Rugh and Massey 2010; Wolff 2022).¹

Lastly, private transfers contribute to the racial wealth gap. Studies have shown that White individuals receive more financial support from family members per year than Black individuals (McKernan et al. 2014; Shapiro et al. 2013). In addition to direct monetary transfers, these supports come in the forms of tuition and down payments, bolstering career opportunities and homeownership (Hall and Crowder 2011). These transformative assets provide significant advantages for White young adults, who subsequently carry less debt and accumulate greater wealth over the life course (Dwyer 2018; Elliott et al. 2018; Killewald and Bryan 2018; McKernan et al. 2014).

Despite receiving ample empirical support, these explanations do not fully account for the Black–White wealth gap. Studies have shown that the disparity cannot be attributed entirely to parental characteristics (Killewald 2013) and that assigning White households' homeownership rates, returns to homeownership, educational attainment, returns to education, or income to Black households closes little of the racial wealth gap (Sullivan et al. 2015). These studies also tended to focus on total net worth, paying limited attention to how individual components contribute to wealth inequality beyond homeownership. This view treats various components of wealth as largely interchangeable and asset allocation as a process that occurs independent of wealth accumulation. It does not recognize that the acquisition and the returns of different assets are likely shaped by distinct institutional processes and that asset access and allocation affect wealth accumulation.

The Financialization of Wealth (Gap)

While wealth is generally understood as a combination of income accumulation, home equity appreciation, and family transfer/inheritance, several studies have noted the growing importance of financial assets. Since the late 1980s, the wealthiest 10% of households have increased investments in financial assets from roughly 10% to more than 20% of their total net worth; among other families with above-median net worth, this share has increased from less than 5% to more than 10% (Lin and Neely 2020). Because affluent families own more stock-linked assets, the level of wealth concentration in the United States tends to fluctuate with the stock market boom and bust periods (Keister and Moller 2000).

The transformation of household wealth reflects several institutional developments that constitute a financial turn in the U.S. economy in the last quarter of the twentieth century. First, retirement reforms in the late 1970s led many large firms to adopt defined-contribution plans with the goal of transferring uncertainties and expenses to individual workers (Cobb 2015; Shuey and O'Rand 2004). Meanwhile, U.S. corporations shifted their focus from market shares and stability to returns for shareholders (Dobbin and Jung 2010; Fligstein and Goldstein 2022; Lazonick and O'Sullivan 2000). Given that labor compensation is often the largest expense, mass layoffs and wage and benefit squeezes have become the primary strategy to increase profit margins (Cobb and Lin 2017; Jung 2014; Lin 2016). Between 1985 and 2014, the S&P 500 index increased from 200 points to roughly 2,000 points. Even after adjusting for inflation, the annualized return during these three decades was more than 5.55%, and up to 8.03% of all dividends were reinvested. By contrast, the same index yielded annualized returns of −2.72% between 1965 and 1984 and 1.24% when dividends were reinvested.

This tremendous growth was driven not solely by increased corporate profits but also by active state intervention. Since the stock market crisis of 1987, the Federal Reserve has signaled that it would backstop falling prices through increased monetary supply (Miller et al. 2002). In subsequent decades, similar policies were implemented to curb escalating financial and nonfinancial economic crises and the absence of consumer price inflation (Abolafia 2020). Consequently, the stock market and the financial sector were the first to recover during the Great Recession and the COVID-19 economic freeze.

Besides these institutional developments, scholars have argued for an emergence of finance culture among segments of American households (Davis 2009; Fridman 2016; Harrington 2008). With increased access to financial products, middle- and upper-middle-class families are more open to risk-taking and have adopted more active financial management strategies to extend their savings and consumption (Fligstein and Goldstein 2015).

Scholars have noted that White households disproportionately benefit from the transfer of economic resources to stock owners because they own more stock-linked assets than Black households (Derenoncourt et al. 2022; Gutter and Fontes 2006; Keister 2000; Oliver and Shapiro 2006). The disparity is driven partly by White households' greater economic resources for investment in the first place. The transformation of retirement benefits also increases the Black–White disparity in stock ownership. White households are more likely to obtain defined-contribution benefits, which tend to accumulate more wealth than defined-benefit plans (Poterba et al. 2007).

Further, studies have shown that Black households are disadvantaged in the financial market. Although various regulatory efforts have attempted to incorporate Black families into the credit market, these families are often offered worse terms when they are qualified for less costly loans (Baradaran 2017). The types of credit most available to Black households, such as credit cards and student loans, cannot be easily converted into wealth-building assets and are sometimes predatory (Seamster 2019; Seamster and Charron-Chénier 2017).

Relative to the credit market, the investment market has received less regulatory scrutiny against racial discrimination. For most of the stock market's history and before internet-based investment, the gatekeepers to the stock market were mostly White financial professionals operating in homogeneous, tightly knit networks. Prime investment opportunities were often reserved for affluent White clients (Neely 2022). The underrepresentation of minority workers and racialized practices at financial institutions could also generate distrust and avoidance among Black families (Bell 2001; Chiteji and Stafford 1999; Friedline et al. 2022; Lin 2015; Rucks-Ahidiana 2017). Black households that acquire stock-linked assets still face greater challenges to holding or expanding investments compared with White households because they experience greater income volatility and receive less financial assistance from parents and other kin (Berry 2006; Hardy and Ziliak 2014; Sharp et al. 2020). These disadvantages entail the need to liquidate stock-linked assets during market downturns, decreasing cumulative returns over time.

Although the racial disparity in financial assets is likely to contribute to the contemporary Black–White wealth gap, the level of its contribution has not been formally assessed. Furthermore, because Black and White households differ in several economic characteristics, it is unclear whether Black households indeed own fewer stock-linked assets than equivalent White households and whether the disparity in financial assets leads to disparities in wealth accumulation.

This article addresses these important questions by dissecting the Black–White wealth gap since the 1980s. We assess the absolute and relative contributions of financial asset disparities to the racial wealth gap. We then examine whether the patterns are sensitive to removing the most affluent households, incorporating entitlement wealth, and matching Black and White households based on wealth-related characteristics. Furthermore, taking advantage of the longitudinal design of the PSID, we assess whether the racial disparity in stock-linked assets could account for wealth accumulation inequality. Specifically, we construct a model predicting future net worth based on racial background, current net worth, current ownership of financial assets, and other household characteristics. We then estimate how much the average Black–White wealth gap could be reduced if Black households were assigned the same amount of financial assets and received an equal rate of return.

Empirical Setup

Data and Sample

The primary data sources are the 1989–2019 Survey of Consumer Finances (SCF) summary files and the 1984–2019 Panel Study of Income Dynamics (PSID). The SCF is a triennial cross-sectional survey collecting information on families' balance sheets and other characteristics. The PSID has followed a nationally representative sample of individuals and their descendants since 1968. Wealth-related items were surveyed every five years beginning in 1984 and biennially since 1999.

Both the SCF and the PSID have a multisample design. The SCF sample consists of two independent samples: (1) an area-probability sample capturing the general population; and (2) a list sample based on the IRS filing records designed to capture high-income households who tend to have lower response rates and are underrepresented in the area-probability sample. Similarly, the PSID has a 1968 national probability sample of U.S. households and their offspring, and a sample based on the Survey of Economic Opportunity targeting mostly low-income households in metropolitan statistical areas and some southern regions. More than half of the latter sample was dropped in 1997. Because of the sampling designs, researchers must apply weights provided by the data sources to obtain population-level estimates. We use the cross-sectional sample weights for the SCF sample. We use the family-level longitudinal weights for the PSID, computed as the average of the individual weight for all family members participating in the study in the given wave. The weights include attrition adjustments to correct for the loss of respondents. The PSID also provides cross-sectional weights, but only for a few years.

For both data sets, we restrict the sample to non-Hispanic White and non-Hispanic Black households with a head aged 25–65 at the time of observation.² The age bracket prevents the interference of education and retirement in our estimates.³ After we remove observations with a weight of 0, the SCF sample includes 174,745 observations, and the PSID sample includes 81,199 observations.⁴ All wealth and income measures are adjusted to 2019 dollars in the analysis.⁵

Online appendix A presents the weighted economic and demographic characteristics of the SCF and PSID samples. The PSID sample has significantly lower average wealth and income than the SCF sample. Likewise, the SCF households tend to be slightly older, have more education, and consist of more married couples with children than the PSID households. These discrepancies are likely due to the PSID's longitudinal design and the oversampling of high- or low-income households in each survey.⁶ Given these and other differences between the two surveys (see Juster et al. 1999; Pfeffer et al. 2015; Sierminska et al. 2008), we use both sources in our analysis to sandwich the population patterns and ensure that the findings are not dependent on a specific set of measurements.

Wealth Components and the Black–White Wealth Gap

Our analysis considers eight mutually exclusive and collectively exhaustive wealth components. Table 1 provides weighted summary statistics for each component by data source and racial group. Most components are net/equity measures (the asset value minus the corresponding liability), with the last two components capturing residual assets and liabilities with no corresponding debt or asset. The sum of all components equals net worth. The harmonization of components between the two data sources is based on Pfeffer et al. (2015).

We combine stocks and retirement accounts into one asset class because the two were not measured separately in the PSID until 1999. Furthermore, some affluent households use retirement accounts, such as Roth IRAs, as self-directed investment vehicles to avoid taxation. Retirement accounts include self-directed accounts, such as IRAs and Keoghs, as well as account-type pensions. When we analyze stocks and retirement accounts separately using the SCF, the contributions of stocks and retirement accounts to the Black–White wealth gap both increase substantially (see online appendix B). Although retirement account funds can be allocated to nonstock assets, industry reports have consistently shown that more than two thirds of such funds are invested in stocks (e.g., VanDerhei et al. 2018). Because households rarely borrow for stock purchases, we use the terms stocks and retirement, stock-linked assets, and financial wealth interchangeably.

Note that the SCF includes a variable (EQUITY) that attempts to approximate the total value of stock ownership for each household across different asset types (e.g., mutual funds, IRAs). However, the variable is constructed using a formula, and rather than being a direct measure of the value of stocks owned, the variable is constructed via a formula that has been revised a few times since 2004. For consistency across time and between the two surveys, we use a more general measure that includes nonstock financial investment. Online appendix C presents the results using this alternative measure. The substantive findings are similar.

Table 1 shows that, on average, White households own higher amounts of all wealth types than Black households. White households also tend to have higher levels of unsecured debts than Black households. The racial disparity is particularly large for primary residence, business equity, and stocks and retirement. Further, PSID households tend to have lower wealth, particularly financial wealth, which likely reflects the oversampling of low-income households.

Before assessing the importance of financial assets, we examine how the racial wealth gap varies across the wealth distribution and over time. A comparison of the wealth gaps at different points of the distribution can better demonstrate how the nature of racial wealth inequality has evolved in past decades (Maroto 2016). Figure 1 plots the differences between the White and Black wealth distributions by group-specific percentile (i.e., calculated separately by race). In general, White wealth percentiles are higher than the corresponding Black wealth percentiles, and the gaps increase exponentially at the upper end of the distribution.

When we compare the 1980s to recent years, we find that the increase in the racial wealth gap occurred mostly in the top quartile. At the 75th percentile, the gap increased from $287,000 to $385,000 in the SCF sample and from $216,000 to $268,000 in the PSID sample. At the 90th percentile, the disparity grew from $637,000 to $1.15 million in the SCF sample and from $479,000 to $741,000 in the PSID sample. These findings indicate that the recent expansion of the racial wealth gap occurred primarily between Black and White households with more economic resources. Moreover, Figure 1 shows that the median racial wealth gap (the 50th percentile) does not capture much of this expansion. Focusing on this metric may lead one to conclude that wealth disparities between Black and White families have remained stable over the past 30 years (SCF, from $135,000 to $138,000) or have declined substantially (PSID, from $92,000 to $75,000).

To consider the expansion of wealth inequality at the upper end, the following analysis focuses on the population-weighted average racial wealth gap. Because the distributions of wealth and stock-linked assets are highly skewed, we perform a sensitivity test to examine whether the empirical patterns are driven entirely by high-net-worth households.

Findings

The Increasing Significance of Stock-Linked Assets

To assess the importance of stock-linked assets in generating the racial wealth gap, we compare two average wealth gaps: (1) the difference in total net worth, including all wealth components described in Table 1; and (2) the difference in nonstock wealth, excluding stocks and retirement from the sum. Figure 2 presents both trends for the SCF and the PSID samples. Because White households own more in stocks and retirement than Black households, the second gap is lower than the first gap.

In the SCF and the PSID samples, stocks and retirement account for an increasingly large portion of the racial wealth gap. In 1989, the average racial wealth gap for the SCF sample was roughly $346,000, and the nonfinancial wealth gap was approximately $279,000. The gap between the two trends widened significantly in the following three decades. By 2019, the total wealth gap increased to roughly $749,000, while the nonfinancial wealth gap increased to only $496,000. In other words, stocks and retirement account for more than half of the increase in the racial wealth gap in the past 30 years.

The rising importance of stocks and retirement is even more pronounced for the PSID sample. In 1984, the total racial wealth gap was approximately $230,000, of which $212,000 was due to nonfinancial wealth. Since then, the total wealth gap increased to nearly $327,000, but the nonfinancial wealth gap remained at roughly $203,000. That is, the increase in the racial wealth gap during this period can be fully attributed to the disparity in stocks and retirement. The only exception was during the late 2000s housing bubble, when nonfinancial wealth accounted for a larger portion of the total wealth gap.

Comparing Wealth Components

The relative contribution of each component can be calculated as a proportion of the racial wealth gap, with all contributions summing to 100%.

Figure 3 presents the relative contribution of each wealth component to the racial wealth gap for both the SCF and the PSID samples. In both cases, home equity, equity from other real estate properties, and business equity together account for more than half of the racial wealth gap during the period studied. The contribution of real estate expanded during the housing bubble of the 2000s and has declined in subsequent years. The component “other debts” has a negative contribution to the racial wealth gap because White households consistently have higher amounts of unsecured debt than Black households.

The most notable trend, however, is that the contribution of stocks and retirement expanded substantially. For the SCF sample, the component accounted for less than 20% of the racial wealth gap in 1989, increasing to more than 37% in 2017. The expansion was even more dramatic for the PSID sample, increasing from less than 8% to nearly 38% from 1984 to 2019. For both samples, stocks and retirement contributed the most to the Black–White wealth gap across all wealth components by 2019, surpassing home equity and business ownership.

In online appendix D, we test whether the trend is sensitive to the exclusion of the most affluent households or the inclusion of entitlement wealth (e.g., Social Security and defined-benefit retirement). We show that the result is not driven solely by the wealthiest White households owning large quantities of stocks. Further, the greater adoption of defined-benefit plans among White households does not account for the growing significance of stock-linked assets in wealth disparities.

The  “Net”  Financial Disparity

Black and White households differ in family income, age of the household head, education, and household structure (see online appendix A). Thus, compositional differences are likely responsible for part of the financial wealth gap. If the gap is merely an outcome of income, housing, and marriage disparities, we should observe little difference in stock-linked assets between Black and White households that are otherwise similar in their economic circumstances.

The conventional approach to obtaining a “net” racial disparity is to estimate a regression model with an indicator for racial identity and a series of controls (e.g., Gutter and Fontes 2006). Yet, the distribution of financial wealth is highly skewed, and a significant number of households do not have stock-linked assets. Because White households dominate the top end of the wealth distribution (Keister 2014), the sample might not contain comparable Black households. Furthermore, financial wealth might not be linearly associated with age, income, and other wealth components, and the correct (or appropriate) functional form of each relationship is yet to be determined. The predictors could also interact with one another, adding to the complexity of model specification. In short, it is difficult to identify the most appropriate models for our task, and the resulting coefficients might not be readily interpretable.

To avoid model misspecification, we directly match Black and White households and compare their stock-linked assets with coarsened exact matching (Blackwell et al. 2009; Iacus et al. 2012), which proceeds in two steps. The first step is to match Black and White households that are highly similar in key characteristics related to financial wealth. Because there might be more Black or White families for a given combination of characteristics, the second step is to generate new weights that balance the matched samples. By excluding Black and White households that do not find a match in the other group (i.e., a lack of common support) and balancing the two groups with weights, we can compare a subsample of Black households with a subsample of White households that are highly similar in key characteristics.

Specifically, we pool yearly samples by decade and match Black and White households on home equity, income, head's age, head's education, and household structure (see online appendix A and Table 1).⁷ We match using home equity because it is a clear indicator of socioeconomic standing and a traditional focus in the wealth inequality literature. Home equity is also the largest component of nonfinancial wealth among many American households. For home equity and income, we divide the samples into 1,000 and 100 groups for the SCF and PSID, respectively (i.e., 0.1 percentile and 1 percentile).⁸ For age, we divide the samples into eight groups using five-year intervals. In addition, we exact-match the households on the basis of the head's educational background (four categories) and household structure (six categories). Thus, the matched Black and White households share highly similar home equity, income, and age simultaneously. They are also identical in their educational attainment and household structure (to the detail that these variables capture).

In online appendix E, we report the matching rates, illustrate how the procedure reduces the dissimilarities between Black and White households, and compare the matched and unmatched samples. In general, the matched samples tend to be younger and have fewer economic resources than the corresponding unmatched samples, suggesting that the estimates will be conservative because younger adults tend to hold fewer stock-linked assets.

The top panel of Figure 4 presents the average amount of stock-linked assets owned by the White and Black households in the matched and balanced sample, as well as the Black–White stock-linked asset gap. Unlike the conventional model-based approach, the figure compares the observed financial wealth in the two groups, not the predicted financial wealth. It shows that both White and Black households own more stock-linked assets over time. However, even when we compare Black and White households with highly similar characteristics, White households consistently own more stock-linked assets than their Black counterparts. For the SCF sample, the financial wealth gap ranges from $39,000 to $93,000. For the PSID sample, the gap ranges from $9,000 to $14,000. In general, White households own more than twice as many stock-linked assets as Black households, even when the two groups share important wealth-related characteristics.

The bottom panel of Figure 4 presents the contribution of financial asset disparities to the total racial wealth gap (similar to Figure 3 but for the matched samples only). It shows that financial disparities account for a substantial share of the net worth gap between comparable Black and White households, ranging from 36% to 52% of the total wealth gap in the SCF sample and 26% to 70% in the PSID sample.

Given that high-SES households own more stock-linked assets, one would expect to find the largest disparity between high-SES Black and White households and little (if any) difference between middle-class or low-SES Black and White households. Similarly, because wealth accumulates over time, one would expect larger disparities between older Black and older White households than between younger ones.

Figure 5 presents the results from the matched SCF 2010s samples. Because Black and White households are matched and balanced, households in a certain home equity, income, educational, or age group also have other similar characteristics. As expected, the figure shows that the racial disparity in stock-linked assets is larger among households with higher home equity, income, and education and with an older household head. College-educated Black households, on average, own half as much financial wealth as their White counterparts, even when the two groups are otherwise similar. Likewise, White households with a head aged 60–65 own more than twice as much in stock-linked assets as Black households in the same life stage with similar characteristics.

Yet, the figure shows that low-SES and young White households still own more stock-linked assets than their Black counterparts. Although the absolute gap is smaller, White households regularly own more than twice as much financial wealth as similar Black households. These results suggest that the racial disparity in financial wealth is not exclusive to high-SES or older households but rather cuts across class boundaries and life course stages.

The Impact of Stock-Linked Asset Disparity on Net Worth

where $Wt+2$ denotes household net worth two years after time t; $αj,t$ denotes the 1,898 fixed effects for groups of households matched at time t, each with a unique combination of characteristics (i.e., home equity, income, age, education, household structure, and period); and $Bt$ indicates whether the observation is a Black-headed household. The model also includes current net worth (⁠$Wt$⁠), accounting for the starting level of wealth and prior unobserved heterogeneity. We transform future and current net worth with the inverse hyperbolic sine function to address nonpositive values and skewness (Killewald et al. 2017).

In essence, we compare the future net worth of matched Black and White households, conditional on the specific combination of household characteristics and current net worth. We expect that Black households will have lower future net worth than their matched White households at time t + 2 (i.e., $β1$< 0), even when the two groups are highly similar at time t (Killewald and Bryan 2018).

where $Ft$ denotes the amount of stock-linked assets at time t, and an interaction term (⁠$BtFt)$ differentiates the association between current stock-linked assets and future net worth by race. We interpret $β3$ as the return of stock-linked assets to future net worth (Conley 2001) and $β4$ as the racial difference in the return. We expect that, net of current wealth, current amount of stock-linked assets is positively associated with future net worth (i.e., $β3$> 0) because of the higher returns to financial assets in the past decades. Given that Black households are systematically disadvantaged in the financial market (Baradaran 2017), we expect them to receive a lower return on their investment (i.e., $β4$< 0). If the racial disparity in wealth is explained partly by the racial disparities in ownership and return rates of stock-linked assets, $β1$ should attenuate in Eq. (4) relative to Eq. (3).

Table 2 presents the coefficients and household-clustered standard errors based on Eqs. (3) and (4). The estimates from Eq. (3) show that conditional on current household characteristics and present net worth, Black households have lower future net worth than White households (⁠$β1$= −0.566; p < .001). That is, Black households tend to accumulate less wealth than White households, even when the two groups are otherwise similar.

The coefficient $β1$ attenuates (p < .01) once we incorporate current stock-linked assets and its interaction term in Eq. (4). Yet, Black households still have lower future wealth than their matched White households (⁠$β1$= −0.401, p < .001). As expected, the value of current stock-linked assets is positively associated with future net worth (⁠$β3$= 0.0982, p < .001), conditional on a variety of household characteristics and current net worth. However, the association is lower among Black households than among White households (⁠$β4$= −0.0487, p < .05), suggesting that Black households are less able to obtain wealth through financial channels.

In online appendix F, we extend the analysis to the racial differences in net worth four, six, and eight years later. The sample size decreases owing to attrition, and the selectivity increases as we lengthen the interval between the dependent variable and the independent variables. By eight years, the sample size is reduced by more than 50%. Yet, the results from this auxiliary analysis are consistent with the main findings.

To assess the impact of stock-linked assets on the racial wealth gap, we use the coefficients in Eq. (4) to compare the Black–White wealth gaps in the following four scenarios:

1. The status quo, in which Black households own fewer financial assets and receive a lower return on these assets (⁠$β4$< 0).

2. The future racial wealth gap when Black households are assigned the same amount of financial assets as White households but receive a lower return on these assets.

3. The future racial wealth gap when Black households own fewer financial assets but receive an equal return on these assets (⁠$β4$= 0).

4. The future racial wealth gap when Black households are assigned the same amount of financial assets as White households and receive an equal return on these assets.

Figure 6 presents the predicted future net worth for the matched Black households as a proportion of the predicted future net worth for the matched White households in these four scenarios. Black households, on average, own only 56.74% of the net worth of similar White households when the two groups have different amounts of stock-linked assets and receive different returns. When we assign the same amount of stock-linked assets to Black households, their future wealth only increases marginally, to 60.19% of that among White households. This finding suggests that simply encouraging Black households to invest more net worth in stock-linked assets might do little to reduce the racial wealth gap.

The asset reallocation is ineffective because Black households tend to have significantly lower returns on their stock-linked assets. When we assign them the same rate of return as White households, their future net worth increases to 59.6%. And if we assign the same amount of stock-linked assets and the same rate of return to Black households, their future net worth increases to 67% of that among White households. This result indicates that nearly a quarter of the wealth disparity among similar Black and White households can be accounted for by the product of differences in ownership and return.

In brief, our exercise indicates that stock-linked asset ownership is consequential for the Black–White disparity in wealth, even when highly similar households are considered. Black households are disadvantaged in two distinct but related ways. First, compared with White households, they tend to own fewer stock-linked assets, which are associated with higher future net worth. Second, Black households receive significantly lower returns on their investments. These two disadvantages lead Black households to accumulate less wealth than their White counterparts over time, even when the two groups share similar household characteristics.

Online appendix G replicates the analysis using the full sample from the 1999–2019 PSID. The models include current home equity, income, age, education level, and household structure as controls. The population-wide results are consistent with the findings presented in this article.

Discussion

Studies have focused on racial disparities in household characteristics, homeownership, and familial transfer as important drivers of the Black–White wealth gap. Building on previous findings, we argue here that the nature of the racial wealth gap has transformed in the era of financialization. As financial markets become important sites for allocating economic resources, the racial wealth gap is increasingly connected to the differential integration into the stock market.

Our findings illustrate that stock-linked assets account for more than half the increase in the average wealth gap in the SCF sample and the entire increase in the PSID sample since the 1980s. The relative contribution of stock-linked assets to the racial wealth gap has also expanded—from less than 20% to nearly 40% of the Black–White wealth gap—surpassing contributions of traditional wealth components, such as homeownership and business equity. Even though affluent families tend to own more stock-linked assets, the pattern persists even when we remove high-net-worth families from the sample.

We also find that the expanding importance of stock-linked assets is not a result of a declining significance of entitlement wealth inequality. White households continue to own higher pension and Social Security wealth than Black households, and the inclusion of these items in the analysis does not alter the trend. Moreover, a substantial difference in financial wealth remains when we compare Black and White families with highly similar characteristics, suggesting that the disparity in stock-linked assets cannot be attributed fully to the differences in characteristics associated with wealth.

When assessing the impact of financial assets on net worth, we show that current stock-linked asset ownership is positively associated with future net worth and that the Black–White wealth gap is explained partly by the differences in stock-linked asset ownership and returns. When comparing a matched sample of Black and White households, we find that nearly a quarter of the racial disparity in future wealth can be attributed to White households' ownership of more stock-linked assets and receipt of higher returns than otherwise similar Black counterparts.

Our results indicate that more studies are needed to understand the mechanisms and institutions behind these racial disparities. Ethnographic research could reveal how racial backgrounds shape families' interactions with financial institutions and the broader investment community. Data from brokerage and asset management firms or from retail trading platforms could also be used to identify systematic differences in investment behaviors and return between Black and White households.

The finding that Black households tend to receive lower returns to their stock-linked assets than White households suggests that financial inclusion and technological advancement by themselves do not necessarily moderate racial inequality. Much like the democratization of the credit market, access to the investment market does not necessarily imply the removal of disadvantages for Black households. The individualized retirement system ignores that Black and White households are on unequal footing in their relationships with the financial industry, creating ample space for disparate outcomes.

Most studies on wealth inequality have focused on employment or wages. However, our findings indicate that stock-linked compensation (contributions to retirement accounts or stock options) could be consequential for wealth accumulation (Grigoryeva 2021). Inequalities in fringe benefits have increased at more than twice the rate of wage inequalities, and the benefit gaps between racial groups have widened in recent decades (Kristal et al. 2018, 2020). A sole focus on take-home pay could increasingly underestimate how the labor market may generate wealth disparity between Black and White households via the route of financial markets.

Several policies have been advocated to narrow the racial wealth gap. Most notably, Hamilton and Darity (2010) proposed that redistributive policies should allocate funds based on family wealth. However, their proposal for child development accounts (commonly known as baby bonds) that progressively increase up to $60,000 for the poorest families may be insufficient in reversing the expanding wealth gap. These trusts only grow at 1.5% to 2% per year, much lower than the yields in the stock market in recent decades.

In addition, Darity and Mullen (2020) proposed providing Black families with a one-time direct payout proportional to their population size, White families' wealth, or exploitation occurring during the enslavement era. Although reparations would certainly reduce the racial wealth gap and help to redress Whites' historical wrongdoings, our findings suggest that a one-time payment does not guarantee long-term economic equality. Because the current financial system continues to be the engine of White wealth, the reduction in the wealth gap from reparation would be temporary. A policy that would supplement the others proposed would be the establishment of a racial equity fund to manage reparation funds and distribute the returns to Black households in need or organizations effective in reducing racial inequalities.

Alternatively, the state may begin to untangle the retirement system and the financial markets by augmenting the U.S. Social Security and withdrawing monetary support for stock-linked assets. Although middle-class and affluent White households gained significant wealth from the stock market in recent decades, they also experienced fluctuations and uncertainties that disrupted their retirement timeline and added to economic anxiety. A Social Security reform funded by wealth or inheritance taxes could significantly reduce the racial wealth gap and wealth concentration, promote economic security, and decouple the retirement system from the financial market.

Acknowledgments

We thank Angelina Grigoryeva, Donald Tomaskovic-Devey, Jordan Conwell, Jennifer Glass, Robert Reece, Allison Lang, the members of the Inequality Working Group at the University of Texas at Austin, and the participants of the Workshop on Financialization and the Social Economy at UMass Boston for their comments on earlier versions of this manuscript. We also thank Steven Pedlow for assistance with the Survey of Consumer Finances.

Notes

References