5

Wealth, Credit, and Debt

This chapter focuses on the role of wealth, credit, and debt in the attainment, maintenance, and—in many instances—loss of economic and social status both within and across generations (i.e., intra- and intergenerational mobility). Wealth is itself a central dimension of social mobility in the United States but also a driver of other socioeconomic and racial/ethnic inequalities (e.g., Shapiro, 2017; Zucman, 2019). Over the last decades, research on inequality and mobility in wealth has expanded rapidly (Keister & Moller, 2000; Killewald et al., 2017). This research typically measures wealth as a household’s net worth: the total sum of all real assets (e.g., house, vehicle) and financial assets (e.g., savings accounts, stocks), minus any debts (e.g., credit card debt, student debt). Household net worth and household income are of course positively associated, but this association is far from perfect, with a correlation of approximately 0.60 between net worth and income (Killewald et al., 2017). Even when income is averaged across multiple observation years, wealth constitutes a partly distinct dimension of socioeconomic well-being and inequality. Therefore, when assessing mobility, wealth deserves attention alongside and in addition to differences in income or consumption (see also National Academies of Sciences, Engineering, and Medicine [National Academies], 2024a).

Recent work also shows that wealth mobility in the United States is lower than income and consumption mobility (Fisher & Johnson, 2023). This lower level of wealth mobility is coupled with a high degree of inequality in the concentration of wealth (at the top of the distribution; Pfeffer & Waitkus, 2021) and stark racial/ethnic gaps in wealth that have persisted for many decades and have grown again recently (Addo et al.,

2024; Derenoncourt et al., 2023). Indeed, distinctive features of wealth include its very high degree of inequality and its concentration at the top. The Gini coefficient of U.S. household wealth in 2022 was around 0.83 (the Gini coefficient of U.S. household income was around 0.61) and the top 1 percent of the wealth distribution owned about 35 percent of all U.S. wealth. In comparison with its peers, the United States stands out as the country with the highest levels of wealth inequality and top concentration in wealth (Pfeffer & Waitkus, 2021). Furthermore, racial/ethnic gaps in wealth are very large: The median net worth of Black families in 2022 was just 16 percent of the median net worth of White families, while the ratio of the means is 15 percent; the median net worth of Hispanic families was 22 percent of the median net worth of White families (Aladangady et al., 2023). Others have noted that “the 400 richest Americans […] have more total wealth than all 10 million Black American households combined” (Williamson, 2020, p. 1).

Amid the rapid expansion of research on wealth and mobility, the distinct role of credit and debt—and inequality therein—has often been neglected, especially in the understanding of differences in mobility-relevant risks and rewards associated with specific assets and debts. Even the composition of assets and liabilities can have disparate impacts on well-being (see Boen et al., 2021). The existing literature on wealth and economic mobility typically draws a conceptual distinction between wealth and credit and debt, but the use of measures of net worth, which subtracts debts from assets, tends to conceal or at least de-emphasize the distinct and separate role of credit and debt. This is problematic, as debt and credit play a major role in the economic well-being and mobility of U.S. families: as of the first quarter of 2023, American households held more than $17 trillion in debt, including approximately $12 trillion in mortgage debt, $340 billion in home equity–based debt, $1.6 trillion in student loan debt, $1.6 trillion in auto debt, $1 trillion in credit card debt, and $500 billion in “other” debt (Federal Reserve Bank of New York, 2023a). These figures suggest a ratio of total household debt to U.S. gross domestic product ($25.5 trillion in 2022) of 0.67, such that the total debt held by U.S. households amounts to about two-thirds the size of the entire yearly economic output of the country (U.S. Bureau of Economic Analysis, 2023). Moreover, despite variation with macroeconomic conditions and policy responses to the Great Recession and COVID-19 pandemic, both aggregate and per capita debt in each of these categories has generally trended upward over the past four decades (Federal Reserve Bank of New York, 2023b). Indeed, the aggregate household debt-to-income ratio in the United States is estimated to have grown from 0.63 in 1980 to 0.96 in 2017, reaching a high of 1.24 in 2007 (Ahn et al., 2018). These figures suggest that debt is, increasingly, a substantial and common element of household finances (Morduch & Schneider, 2017).

Notably, however, the figures exclude obligations such as civil and criminal legal debt, medical debt, unpaid bills, loans from nonfinancial institutions (employers, family, friends), and child support debt. Such debts are particularly salient for disadvantaged and minoritized households (Finnigan & Meagher, 2019; Fourcade & Healy, 2013; Ghaffary, 2019; Halpern-Meekin et al., 2015; Harris, 2016; Wherry et al., 2019).

Growth in household debt over the past few decades is thought to be driven, at least in part, by financial market deregulation, expanded access to credit, and the emergence of new credit products that have substantially increased options for borrowing, especially for population groups that have traditionally been excluded from mainstream financial markets. However, household debt is also thought to have led to repayment difficulties and associated economic insecurity for many households, particularly those experiencing adverse shocks to income or asset values and those with low or unstable incomes (Board of Governors of the Federal Reserve System, 2017; Campbell et al., 2011; Federal Reserve Bank of New York, 2017; Fourcade & Healy, 2013; Hyman, 2011; Wherry et al., 2019). These factors are relevant to both secured debt (e.g., mortgage, auto, and home equity loans) and unsecured, or uncollateralized, debt (e.g., education, credit card, personal finance, subprime [payday and title] loans; Ryan et al., 2011; Xiao & Yao, 2011a,b).

In light of these ongoing and, to some extent, parallel trends in both wealth and credit and debt, this chapter seeks to give full attention to each on its own, rather than only in their joint distribution. It starts by acknowledging net worth as important for mobility, calling attention to the many mechanisms by which it maintains the high economic and social status for those at the top end of the distribution, while limiting opportunities for those in the middle and bottom. Delving into the stratification of different classes of assets within the U.S. population, the chapter highlights the centrality of housing as a source of wealth for most adults and families; it is also a key structural factor in equalizing intergenerational mobility between racial/ethnic groups. In turn, credit, lending, and debt are the primary means by which individuals enter (or are excluded from) the housing market. Critically, the committee emphasizes that credit and debt are not monolithically “good” or “bad,” but instead context-specific mechanisms of mobility. Beyond housing, credit and debt provide many individuals with opportunities to take risks that engender wealth accumulation and upward mobility; yet, for others, they are insurmountable obstacles that hinder mobility, if not direct sources of downward inter- and/or intragenerational mobility. Finally, we acknowledge that wealth is unique in its importance as both a mechanism of mobility and an outcome (or measure) of mobility.

WEALTH

Wealth is a key force of mobility and driver of socioeconomic and racial/ethnic disparities. Over the last decades, research on inequality and mobility in wealth, especially focused on household net worth, has expanded rapidly; it demonstrates relatively low levels of wealth mobility in the United States, a high degree of inequality, and stark racial/ethnic gaps in wealth that have grown over time.

Intergenerational Wealth Transmission

Perhaps the most distinctive feature of wealth is that it can be passed on directly to one’s children and grandchildren. Unlike education, occupation, or income—the measures of socioeconomic status central to decades of research on social mobility—wealth can be transmitted quite simply by handing it over to one’s offspring, either in the form of gifts during one’s lifetime or as an inheritance (see National Academies, 2024a, for discussion on interhousehold transfers for measuring income and wealth). Accordingly, much scholarly attention has been paid to the role of gifts and inheritances in contributing to the intergenerational transmission of wealth; however, as pointed out later, direct monetary transfers are just one channel of wealth transmission. This section reviews the current evidence (mainly descriptive and correlational) on the level and shape of intergenerational correlations in wealth and on the main mechanisms of intergenerational wealth transfers (see National Academies, 2024a), and broader channels that contribute to the intergenerational persistence of wealth (for other recent reviews, see Hällsten, 2024; Lersch et al., 2024).

Most existing evidence on intergenerational wealth correlations in the United States is based on the Panel Study of Income Dynamics, as it is the only nationally representative household panel study that has collected measures of family wealth early enough—starting in the 1980s—and has continued to do so long enough to allow the comparison of the wealth holdings of parents and their adult children. The earliest contributions that estimated intergenerational wealth correlations were limited to measuring the wealth outcomes of adult children in their 30s—relatively early in their life course (Charles & Hurst, 2003; Conley & Glauber, 2008; Mulligan, 1997). One method for measuring the level of mobility is to use the magnitude of the relation between parental wealth and children’s wealth. These wealth relationships (or elasticities) were estimated (based on the association of the logged wealth of parents and their children) to lie between 0.28 and 0.37. Later, Pfeffer and Killewald (2018) drew on an older sample of adult children, estimating considerably higher elasticities—up to 0.54 for those aged 55–64—and correlations in relative wealth ranks of up to 0.44.

These updated estimates put the level of intergenerational persistence of wealth at a similar level to that of income. Measuring wealth during off-springs’ later adulthood is crucial as the intergenerational correlation of wealth (measured by the magnitude of relation between parental rank in the wealth distribution and children’s rank in the wealth distribution, called the rank–rank slope) rises substantially with age (Fisher & Johnson, 2023; Pfeffer & Killewald, 2018). Therefore, restricting the view to earlier life course stages would suggest that the intergenerational persistence in wealth was lower than that of income or consumption (see Brady et al., 2020; Fisher & Johnson, 2023). Also, since inequality in wealth is higher than inequality in income or consumption, estimates of wealth mobility are suppressed more than those of income and consumption mobility for mobility measures that depend on the level of inequality (e.g., elasticities, Gini index of mobility; see Fisher & Johnson, 2023).

Fisher and Johnson (2023) provided a comparative assessment of absolute upward mobility, finding that upward wealth mobility (i.e., the probability of children to exceed their parents’ wealth at similar ages) is considerably lower than upward mobility in income and consumption. Furthermore, the extent of upward mobility in wealth has decreased precipitously over time, from about half of all children born in the 1950s and 1960s being upwardly mobile in terms of wealth to just 28 percent for children born in the 1980s. Intergenerational wealth correlations have also been estimated for additional countries in just the last few years (see Hällsten, 2024, for a review). The international evidence suggests that the U.S. intergenerational correlation in wealth is higher than in other countries, meaning that levels of wealth mobility are lower in the United States. For instance, the estimated wealth rank correlation is 0.17 in Norway (Fagereng et al., 2021), 0.20–0.40 in Denmark (Boserup et al., 2017; Daysal et al., 2022), 0.30 in the United Kingdom (Gregg & Kanabar, 2022), and 0.30–0.40 in Sweden (Adermon et al., 2018; Black et al., 2020).

Intergenerational correlations in wealth have been shown to be largely linear across most of the wealth distribution, with the exception of the upper tail, where wealth is particularly stable (Black et al., 2020; Boserup et al., 2017; Pfeffer & Killewald, 2018). Intergenerational correlations below the very top can also be approximated well with indicators of housing wealth or even home values, reflecting the centrality of housing in not just the distribution of wealth but also its intergenerational transmission (Blanden et al., 2023; Daysal et al., 2022; Pfeffer & Killewald, 2018), which this chapter will discuss in greater detail.

Like most work on social mobility, scholarship on wealth mobility has been largely restricted to a two-generation paradigm (i.e., the standard assessment of similarity in positions between parents and their children). However, particularly for wealth, it is likely that family socioeconomic

status can also be transmitted across more than two generations, including through direct transfers from grandparents to their grandchildren (Mare, 2011; Pfeffer, 2014). A few contributions have assessed the persistence of wealth across three generations. For the United States, Pfeffer and Killewald (2018) found that three-generational wealth correlations were about two-thirds the size of the parent–child wealth correlation. They also show that only half of the grandparent–grandchild association flows through parental wealth, meaning that grandparental wealth is associated with grandchild wealth net of parental wealth. The relative importance of multigenerational wealth transmission appears to be even more pronounced in Denmark, where the size of the grandparent–grandchild wealth correlation is about three-quarters that of the parent–child correlation and most of the grandparent–grandchild association persists when parental wealth is controlled (Boserup et al., 2014). Conversely, multigenerational wealth transmission appears less pronounced in Sweden, where three-generational wealth correlations are about 40 percent the size of two-generational correlations but most of the grandparent–grandchild association flows through parental wealth (Adermon et al., 2018). Nonetheless, Hällsten and Pfeffer (2017) documented the substantial and independent influence of grandparental wealth and grandchildren’s educational achievement, even in Sweden.

Finally, and importantly, research has documented drastic differences in wealth mobility between White and Black individuals in the United States. Pfeffer and Killewald (2019) showed that Black children, in addition to being severely disadvantaged in terms of their wealth background, are also far more likely to be downwardly mobile in terms of their own wealth attainment compared with White children. For instance, among children who grow up in the middle quintile of the parental wealth distribution, 39 percent of Black children fall to the bottom wealth quintile as adults, compared with 16 percent of White children. The authors concluded that today’s Black–White wealth gaps arise from both historical disadvantages reflected in the unequal starting position of Black and White children, as well as contemporary processes—including continued structural discrimination—that make Black children more likely to be relegated to the bottom of the wealth distribution (see further discussion below). Fisher and Johnson (2023) also showed that the Black–White differences in wealth mobility are driven by the particularly disadvantageous mobility outcomes of Black women: Black women have especially high rates of downward mobility from the top of the wealth distribution and especially low rates of upward mobility out of the bottom.

Evidence on wealth mobility patterns among other racial/ethnic groups is still very limited. Keister et al. (2015) found that despite considerable disadvantages in childhood conditions and early young adulthood, Mexican Americans have gained greater access to wealth than Black Americans.

Much future work is needed to document the wealth mobility patterns of other racial/ethnic groups. Immigrant wealth mobility patterns are also likely to diverge from those of White families, based on the lower wealth starting positions, the potential need for reverse transfers from children to their parents, and remittances—all of which may limit immigrants’ wealth accumulation and mobility.

Trajectories of Wealth Accumulation

Intragenerational wealth trajectories—stability and change in wealth over the life course—are also key components of economic mobility. Economic studies of wealth accumulation processes often focus on the roles of income, consumption, capital gains, and financial transfers (Feiveson & Sabelhaus, 2019), with a paucity of evidence on the role of taxation, which will be discussed below. Few studies jointly consider wealth alongside other dimensions of socioeconomic well-being. Fisher et al. (2016) showed that the level of short-term intragenerational mobility in wealth is similar to the level of mobility in income and consumption, although the persistence at the top of the distribution is more pronounced for wealth than for income and consumption. Importantly, empirical research on intraindividual (and intrahousehold) wealth trajectories spanning many years (and waves of data) remains relatively rare because high-quality panel data on wealth accumulation are limited. Nonetheless, literature on key economic and social determinants of wealth mobility is growing (see further discussion below). Improved wealth data are greatly needed (see National Academies, 2024a), and efforts are currently underway to create measures of wealth and intergenerational wealth transmission in the United States (see “Wealth and Mobility Study” in Chapter 6).

A recent working paper by Goda and Streeter (2021) took a broad approach to examining wealth trajectories across life milestones, including marriage, homeownership, childbirth, divorce, disability, health shocks, retirement, and widowhood.¹ The authors found significant long-run increases in wealth associated with homeownership and retirement, and significant long-run reductions in wealth associated with divorce, health shocks, and disability. Relatedly, a longitudinal study by Kapelle (2022) showed how and why there are wealth differences between divorcees and continuously married individuals. Using data from the German Socio-Economic Panel Study and matching techniques in tandem with random-effects growth curve models, Kapelle (2022) found that divorce leads to declines in net worth primarily because of loss in housing wealth around the time of

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¹ Goda and Streeter (2021) used panel data from the NLSY79 sample of the National Longitudinal Survey and from the Health and Retirement Study.

divorce, although divorcees’ rates of postdivorce wealth accumulation are comparable to those of married individuals. Prior research has also shown that acute health events lead to changes in household wealth, with differential effects across racial groups: while health shocks affect both White and Black families, they have a disproportionately deleterious impact on the financial well-being of Black families as the family heads approach retirement (Thompson & Conley, 2016). Indeed, research suggests heterogeneity across demographics, socioeconomic status, and risk protection, and identifies populations and life stages most vulnerable to large wealth reductions (Goda & Streeter, 2021).

A novel study by Chen et al. (2019) used panel data from the Health and Retirement Study to examine longitudinal wealth trajectory patterns (after age 50) and the impact of socioeconomic status on these trajectories. Results identified four distinct latent classes of wealth trajectories: stable high (reference), low and increasing, stable low, and high but declining. Moreover, three key life course mechanisms shaped wealth trajectories: (a) disadvantaged socioeconomic status in adulthood, (b) accumulated exposure to risks, and (c) downward socioeconomic disadvantage were respectively associated with increased odds of stable low, low and increasing, and high but declining (relative to stable high wealth).

While research on racial inequality in trajectories of wealth is relatively rare, growing evidence calls into question the utility of the dominant life cycle model of wealth accumulation (see Modigliani, 1988) for understanding the wealth patterns among low-wealth racial groups, where people accumulate wealth by saving throughout their working years in anticipation of retirement, and then begin dissaving. For example, a study by Brown (2016) used ten waves of panel data from the Health and Retirement Study and random coefficient growth curve models, revealing stark racial/ethnic inequality in wealth trajectories among White, Black, and Mexican Americans. Brown (2016) noted substantial racial inequality in wealth by midlife: White households had accumulated an average net worth of $105,000, compared with less than $5,000 and $39,000, respectively, for Black and Mexican American families. In addition, White individuals experience much faster rates of wealth accumulation in their 50s and 60s than their minority counterparts, resulting in wealth inequalities that increase with age, consistent with a process of cumulative disadvantage. At the apex of their wealth trajectory (age 66), White individuals had roughly $245,000 more than Black individuals and $219,000 more than Mexican Americans (Brown, 2016).

Similarly, Killewald and Bryan (2018) showed that the advantage of White individuals compared with Black and Hispanic individuals in accumulating wealth increases over the life course. Half of this advantage can be accounted for by intergenerational advantage, arising from the

higher-wealth starting position of White individuals. However, by middle adulthood, intragenerational processes (i.e., disparities in wealth-enhancing traits, such as income, marriage, and homeownership) explain a greater share of racial/ethnic gaps in wealth accumulation (family size and structure could also be added to this list, as shown by Keister, 2004). Killewald and Bryan (2018) concluded that both past and present racialized processes explain today’s racial/ethnic gaps. More broadly, scholars who study racial inequities in wealth emphasize that factors related to historical racism (e.g., slavery, Jim Crow laws, unequal access to GI Bill and Social Security benefits, lending discrimination, racial covenants) and contemporary structural racism (e.g., segregation in housing, schooling, and jobs; discrimination in lending, health care, and the criminal legal system) likely play a role in the production and maintenance of wealth inequality (Brown, 2016; Darity & Mullen, 2020; Killewald et al., 2017; Oliver & Shapiro, 1995; Pfeffer & Killewald, 2019).

Avenues for Wealth Mobility

The bulk of empirical work has been dedicated to estimating the contribution of inheritances and bequests and inter vivos transfers to the maintenance of wealth across generations. This work generally finds that a large share (often half) of the intergenerational wealth correlation can be explained by these direct monetary transfers (see, e.g., Adermon et al., 2018). Empirical work has shown that wealth transmission does not arise from the genetic inheritance of traits, as intergenerational correlations in wealth are also high in adoptive families (Black et al., 2020; Fagereng et al., 2021).

While much of the literature is focused on inter vivos gifts and inheritances, wealth transmission also occurs through more indirect channels. For instance, more than half of the intergenerational transmission of wealth in the United States arises through channels earlier in life, including offspring’s educational attainment, acquisition of homes and businesses, and marriage (Pfeffer & Killewald, 2018). Studies of wealth reproduction therefore need to pay at least as much attention to early life, indirect investments by parents, as well as grandparents, in their offspring. Toney and Robertson (2021) show that the younger adult generation’s income level is significantly affected by its parents’ and grandparents’ wealth. Zang et al. (2024) show the impact of both parental and grandparental wealth on mediating factors between previous generations’ wealth and income, including an increased likelihood of college attendance and steady employment and decreased likelihood of nonmarital births and joblessness.

Beyond the inherent importance of wealth in direct, intergenerational investments, parental (and grandparental) wealth can also fulfill an

important insurance or safety net function (Hällsten & Pfeffer, 2017; Shapiro, 2004). The precautionary savings motive that neoclassical economics assumes as one of the main drivers of wealth accumulation within a generation may thus also extend intergenerationally: wealth serves to reduce risks intergenerationally, and it needs to be better appreciated as a mechanism by which some individuals have the opportunity to take risks—and potentially fail—while others do not.

Wealth as a Mechanism of Mobility

As noted above, wealth transmission also occurs through indirect channels, such as when family wealth supports children’s development, educational achievement, and degree attainment, as well as their early careers and labor market experiences. Accumulation of earnings can lead to higher income and wealth. A nascent but growing literature has established independent links between parental wealth and child development (see Gibson-Davis & Hill, 2021), such as positive behavioral (Ream & Gottfried, 2019; Shanks, 2007) and health outcomes (Boen et al., 2021). The strong relationship between parental wealth and children’s educational outcomes has been documented repeatedly (e.g., Conley, 1999; Doren & Grodsky, 2016; Jez, 2024; see also summaries in Gibson-Davis & Hill, 2021; Killewald et al., 2017). The relationship especially between parental wealth and children’s college attainment has also strengthened over time (Pfeffer, 2018). Beyond educational attainment, parental wealth also appears to shape the occupational attainment of the next generations (Conley, 1999; Pfeffer, 2011). While these earlier-life intergenerational influences of family wealth can be thought of as indirect channels of intergenerational wealth mobility, they are also the foundation for an even broader role of family wealth in processes of intergenerational mobility: family wealth fosters early life advantages that eventually support social mobility in other dimensions, such as educational, income, and occupational mobility. In this sense, wealth can both support and inhibit a variety of forms of economic and social mobility. For instance, Fisher and Johnson (2023) showed that children from higher-wealth backgrounds have a higher probability of intergenerational movement out of the bottom of the income distribution, as well as remaining at the top of the income distribution. Rodems and Pfeffer (2021) showed that high wealth can serve as a buffer against negative life events, as the probability to experience material hardship in the wake of an unemployment spell, earnings loss, and other demographic events is lower among those with high wealth. Understanding the indirect mechanisms through which wealth shapes other social mobility dimensions may also help elucidate racial/ethnic mobility differences. For instance, Fox (2016) found that parental wealth facilitates upward income mobility for White

children growing up in low-income families but does not have the same benefits for Black children growing up in low-income families.

Housing as a Primary Source of Wealth and Inequality

The composition of wealth portfolios differs greatly across the wealth distribution (Wolff, 2017). The wealth of the top 1 percent is dominated by financial assets. By contrast, the (lack of) wealth in the bottom 10 percent is dominated by debt. The debt held by the very bottom of the wealth distribution tends to be “productive debt” (e.g., business loans), reflecting their ability to borrow rather than a destitute overall economic position. For the average U.S. household and for a majority of households, housing assets (home equity) make up the largest wealth component (McCabe, 2016). However, home equity makes up a greater portion of total wealth for Black households than for White households (LaBriola, 2024).

Housing—including the value of the home, the resources and use value the home provides (compared with renting), and the housing and other amenities around the home (i.e., neighborhoods, neighbors, schools)—is a source of wealth and stability. As a mechanism of intergenerational transmission, the effects of housing are likely multifold (Choi et al., 2018; Pfeffer, 2018), including the transmission of home equity (Benetton et al., 2024), and the reduction of credit constraints, such as the ability to pay for college (Johnson, 2020; Lovenheim, 2011). In particular, in the United States, one’s relative ability to invest in housing typically translates into investments in the schools nearby, which benefit the household (in terms of equity) and also benefit one’s children (in terms of better school quality that produces mobility dividends; Goldstein & Hastings, 2019; Lareau & Goyette, 2014).

American housing policy has long promoted homeownership, codified in postwar lending practices, as a vehicle for increasing economic and social mobility and wealth-building specifically (Fischel, 2005; McCabe, 2016). However, as noted in Chapter 3 (Space and Place), housing sits atop an unequal geography of opportunity that systematically disadvantages certain groups and can hamper the wealth-generating effects of home-buying. Residential racial and economic segregation results in lower-value homes in places with fewer White people and fewer wealthy people.

Some housing policies and institutions have also created racially disparate impacts in the returns to homeownership for Hispanic and Black Americans relative to White Americans (Baradaran, 2017; Flippen, 2004; Killewald & Bryan, 2016; Rothstein, 2017; Taylor, 2019). Housing policy from the New Deal forward helped create a racially stratified housing market in the United States, through the support of federally backed mortgages and subsidization built on racially discriminatory lending practices (Quillian et al., 2020), resulting in significant gaps in the rates of homeownership by race and the large racial wealth gap noted above.

New rigorous research on redlining—the practice of categorizing the investment risk of residential areas based on race, ethnicity, and other non-housing characteristics—has been associated with long-term consequences for communities. Through federally sponsored redlining, many Black communities were considered too risky for investment and were cut off from access to credit through mortgages; they then subsequently became vulnerable to subprime markets and practices that extract more fees (Satter, 2009; Taylor, 2019). Communities that were designated as low-grade (C or D) on the original Home Owner’s Loan Corporation (HOLC) maps, over time, experienced lower rates of Black homeownership, property values, and rent, and higher rates of racial and economic segregation and vacancy in the decades following (Aaronson et al., 2021a). Specifically, across all neighborhoods, the HOLC map boundaries can account for between 15 and 30 percent of the difference in proportion of residents who were Black between the lowest (D) and next lowest (C) areas of risk (Aaronson et al., 2021b).

While Black households had restricted access to mortgages in the first half of the 20th century, still other Black individuals became homeowners through predatory inclusion in the decades after, through the practices of subprime lending and other risky financing (Rugh & Massey, 2010; Seamster & Charron-Chénier, 2017). Subsequently, the consequences of the foreclosure crisis of the 2000s were stratified by race and by neighborhood (Rugh & Massey, 2010). Conversely, housing market appreciation during this same period largely benefited White homeowners, and recent research has found that such housing market dynamics can account for nearly three-quarters of the increase in the median White–Black wealth gap between 1984 and 2019 (LaBriola, 2024).

While most of the research on racial disparities in homeownership has focused on the impacts of lending practices and institutions, recent work also points to the risks of acquiring properties without the protection of institutionally regulated mortgages. While not an entirely new practice (see Pietila, 2010; Satter, 2009), informal and unregulated housing markets still exist, especially in low-income, mostly Black communities in places such as Detroit and Baltimore (Jang-Trettien, 2022). Some practices in these communities—such as land contracts, contracts for deeds, or informally gifting properties within families—can lead homeowners to purchase properties without clear titles or with significant liens and structural problems with the homes (Jang-Trettien, 2022).

While racial inequality in homeownership is essential to understanding economic mobility and wealth, more than one-third of families—and most low-income households—rent their homes (e.g., the National Low Income Housing Commission). However, by prioritizing homeownership, housing policy has fallen short of the needs of renters to obtain housing security, let

alone wealth (DeLuca & Rosen, 2022). Low-income renter households pay more of their income toward housing than their more affluent counterparts but do not realize the benefits of policies such as the mortgage interest tax deduction; its reduction through the Tax Cuts and Jobs Act of 2017 led to more equitable distribution of taxes (see Ambrose et al., 2022). Most of the government spending for homeowners goes to the top fifth of households by income (Fischer & Sard, 2017). The affordable housing crisis has hit renters especially hard, and federal policy has not responded adequately: unlike the Supplemental Nutrition Assistance Program and other entitlement programs, housing assistance in the United States is not guaranteed by income; only about one of four income-eligible households receives rental assistance. In part, this is because of the stagnant supply of housing choice vouchers and the shift in federal housing policy since the 1970s toward market-based rental subsidies (relying on private-market landlords) rather than the construction of public housing units (Hackworth, 2007; Rosen, 2020; Schwartz, 2015). As such, renters—especially those who are racial minorities—are more vulnerable to housing insecurity than homeowners.

CREDIT AND DEBT

As clearly demonstrated in the case of housing and homeownership, access to credit and the ability to borrow are key resources that enable income and consumption smoothing, facilitate investments in human capital, and allow the cost of goods and services to be allocated over time. As such, borrowing provides opportunities to improve economic and social wellbeing, particularly over the long term. At the same time, debt repayment may strain current household resources, resulting in reduced consumption and, potentially, economic stress, distress, and hardship, with negative implications for health and well-being, particularly among disadvantaged households (Drentea, 2000; Drentea & Lavrakas, 2000).

Credit and Debt Are Not a Monolith

Households borrow in heterogeneous contexts and via heterogeneous credit mechanisms, reflecting differences in financial resources as well as in the timing of and reasons for borrowing, with implications for amounts borrowed, types of debt accrued, loan terms, and ability to meet the terms of the loan. Berger and Houle (2019) provide a framework for considering the role of household debt vis-à-vis individual agency in borrowing (i.e., the degree to which decisions to borrow reflect deliberate, future-directed intent versus constrained resources for meeting immediate economic needs), magnitude borrowed (amount of debt in absolute terms and relative to income or assets), and cost of borrowing (interest rates and fees, which are closely

tied to loan type). Dwyer (2018) further categorizes debts by the extent to which they are accrued via prospective credit offer versus retrospective obligation, as well as whether they are owed to market or state actors. Prospective offers from state institutions include federal mortgage and student loans; prospective offers from market institutions include private-sector mortgages, and home equity–based, education, auto, and unsecured (credit card, personal finance, payday, title, pawnshop) loans. Retrospective obligations to state institutions include criminal and legal fines and fees, other monies owed to government (tax penalties; fines, fees, and interest, including that owed for unpaid taxes and child support arrears; reimbursement for social welfare benefit overpayments) and past-due public utility/amenity bills. Retrospective obligations to market institutions include medical debt, past-due rent and other bills, and child support arrears owed to custodial parents.

Just as with wealth and asset portfolios, specific types of credit and debt are unevenly accessed by different population groups. Most notably, economically disadvantaged and racial/ethnic minority families are disproportionately likely to take on high-cost unsecured debt in order to meet basic expenses (Shah et al., 2012) and in response to adverse economic (Barr, 2012; Sullivan, 2008) and health shocks (Babiarz et al., 2013), reflecting lower levels of income and assets, and connoting lesser agency in borrowing and lesser access to low-cost (prime) credit mechanisms. They are also disproportionately likely to face retrospective debt obligations to both state and market institutions. In contrast, more advantaged and White populations are disproportionately likely to accrue debt for prospective investment in human capital and asset acquisition, and to do so via lower-cost mechanisms (Dwyer, 2018).

Indeed, whereas access to credit has expanded for all segments of the population, economically disadvantaged and racial/ethnic minority populations are disproportionately more likely than their higher-income counterparts to borrow for consumption rather than investment and to hold retrospective debt obligations to both government and market actors, and to be unbanked (Boel & Zimmerman, 2022; Houle & Addo, 2022; Servon, 2017; Tach & Greene, 2014; Wherry & Chakrabarti, 2022). They also tend to receive higher-cost (including subprime) loan terms and experience higher rates of delinquency and default in each major loan category—home, education, auto, and unsecured—although disparities in unsecured debt burden are particularly large (Avtar et al., 2021; Houle, 2014a; Houle & Addo, 2022; Mills et al., 2022; Seamster & Charron-Chénier, 2017; Wherry & Perry, 2021; Williams et al., 2005). Notably, whereas less-advantaged and racial/ethnic minority households tend to hold less total debt, on average, than more advantaged households, they also tend to face higher relative debt burdens as a result of both lesser income and assets and less-beneficial loan terms (Avtar et al., 2021; Houle, 2014a; Mills et al., 2022; Sullivan

& Kaufman, 2012). These factors raise important questions regarding the extent to which credit and debt—and particular types thereof—may promote or impede upward (or downward) economic and social mobility, both overall and for population groups with greater and lesser degrees of social and economic (dis)advantage.

Indirect Pathways to Mobility

Whereas a substantial body of research has established that wealth is linked to inter- and intragenerational patterns of economic and social (dis)advantage and mobility, comparatively little is known about whether and how access to credit and (particular types of) debt may be linked to intra- and intergenerational mobility. Indeed, the committee is aware of no study to explicitly examine such links; however, as discussed below, a small group of studies have examined links between access to credit and key mechanisms for economic and social mobility, such as investments in children’s human capital, college attendance and completion, and young adult earnings (Braxton et al., 2024; Lochner & Monge-Naranjo, 2012; Mayer, 2021; Ringo, 2019; Sun & Yannelis, 2016). Yet, a growing body of research examining relations among credit and debt, inequality, and adult and child well-being implies, albeit indirectly, that debt patterns have the potential to influence economic and social mobility (Dwyer, 2018). As noted above, the ability to borrow at reasonable terms vis-à-vis one’s financial situation may enable investments in human capital (e.g., education) for oneself or family members. This has the potential to lead to greater income and assets (e.g., a home, the primary source of wealth for Americans), which in turn can increase in value over time and thereby provide wealth gains and associated opportunities for transferring wealth, as well as opportunities for borrowing at reasonable cost to make subsequent investments or respond to adverse economic shocks. Conversely, borrowing under economic duress, potentially with limited agency and at high cost, may adversely affect subsequent consumption, savings, and investment. Each of these possibilities may have implications for intra- and intergenerational well-being and, thereby, economic and social mobility.

Research to date points to several overarching patterns. First, household debt is relatively common across the U.S. income distribution, but it is disproportionately associated with investment at higher income levels and with immediate consumption at lower income levels (Dwyer, 2018). Second, lower-income households are increasingly experiencing high debt burdens, which grow over the life course (Dwyer, 2018). Third, although middle-income American households appear to have particularly high levels of debt relative to lower-income (and also higher-income) households (Fitzgerald & Leicht, 2014; Hodson et al., 2014; Houle, 2014b; McCloud

& Dwyer, 2011; Sullivan et al., 2001), this may, at least in part, reflect inadequate measurement and omission, in both the surveys and administrative (credit report) data used to measure debt. Indeed, many forms of debt that are common among low-income households—including alternative financial services loans (payday loans, title loans), civil and criminal legal debt, medical debt, unpaid bills, loans from nonfinancial institutions (employers, family, friends, pawn shops), child support debt, and other debts owed to government—are frequently missing from these data sources (Finnigan & Meagher, 2019; Fourcade & Healy, 2013; Ghaffary, 2019; Halpern-Meekin et al., 2015; Harris, 2016; Wherry et al., 2019). Fourth, common adverse experiences such as chronic health conditions, adverse health shocks, family disruptions, criminal and civil legal judgments, and unstable employment and income are associated with high levels of unsecured debt among low-income households, many of which struggle to repay these debts (Berger & Houle, 2016; Houle & Keene, 2015; McCloud & Dwyer, 2011). Fifth, unsecured debt is associated with economic hardship, financial strain and distress, and poorer health and well-being, particularly among disadvantaged populations (Berger & Houle, 2016, 2019; Berger et al., 2016; Dwyer et al., 2011, 2016; Keese & Schmitz, 2014; Loibl et al., 2022; Sun & Houle, 2020).

Despite a large and long-standing research literature linking economic resources, such as income and wealth, to the health and well-being of both adults and children, only recently have scholars begun to examine the potential effects of (particular types of) debt on well-being. On the whole, research to date has produced inconsistent findings with respect to the magnitude and direction of relation between debt, generally defined, and adult well-being. However, studies investigating links between particular types of debt and adult well-being predominantly suggest that higher-cost unsecured debt, which is primarily used for consumption, is adversely associated with adult well-being, particularly among disadvantaged populations and those with greater debt burden. These findings span financial stress and anxiety (Drentea, 2000; Norvilitis et al., 2006; Worthington, 2006), decision-making (Lea et al., 2012; Shah et al., 2012), health and mental health (Berger et al., 2016; Bridges & Disney, 2010, Brown et al., 2005; Drentea, 2000; Drentea & Lavrakas, 2000; Drentea & Reynolds, 2012; Jenkins et al., 2008; Keese & Schmitz, 2014; Reading & Reynolds, 2001; Turunen & Hiilamo, 2014; Walsemann et al., 2015), and marital quality and relationship strain (Dew, 2007, 2008). Notably, however, there is no consistent evidence that lower-cost secured (particularly mortgage) debt, which is primarily used for investment, is similarly associated with adverse outcomes, and some evidence (Moulton et al., 2022) suggests that ability to borrow against one’s home may facilitate disease management. Moreover, research suggests substantial heterogeneity in associations between student

loan debt and well-being across population groups and by factors such as loan amounts and terms, types of educational institutions attended, and subsequent educational attainment (see Dwyer, 2018, for a summary).

It is also possible that parental debt may influence child well-being either directly via consumption or indirectly via parental stress and accompanying characteristics of parenting behaviors and the quality of children’s caregiving environments. The committee is aware of only three studies that examine relations between debt and child well-being directly. Berger and Houle (2016), using child fixed-effects regressions, found associations of mortgage and educational debt with better child socioemotional development, potentially reflecting greater parental educational attainment, wealth, and neighborhood quality, and between greater unsecured debt and poorer child socioemotional well-being, potentially reflecting greater parental stress and/or constrained consumption. Berger and Houle (2019), using a hierarchical linear modeling strategy, found unsecured debt to be associated with growth in child behavior problems over time, with effects being particularly concentrated among younger children and children from less-advantaged families. They found no associations of home, education, or auto debt with children’s socioemotional developmental trajectories. Finally, Nepomnyaschy et al. (2021), using cross-sectional regressions to assess associations of resident mothers’ unsecured debt, nonresident fathers’ unsecured debt, and nonresident fathers’ child support debt for children at age 9 and 15, find associations between nonresident fathers’ child support debt and greater child behavior problems, with larger effect sizes at age 15 than 9, but no associations of resident mothers’ or nonresident fathers’ unsecured debt with behavior problems at either age (controlling for nonresident fathers’ child support debt).

Finally, several studies point to plausibly causal relations of parental access to credit with investments in their children’s human capital, their children’s college attendance and completion, and their earnings in young adulthood, each of which is thought to be a key mechanism through which economic and social mobility may occur. Lochner and Monge-Naranjo’s (2012) review of the literature linking credit constraints with children’s educational attainment, for example, indicates that access to credit has played an increasingly important role in college enrollment decisions in recent decades, but also that constrained credit during early childhood may adversely affect investments in children’s human capital to an even greater degree than access to credit during later childhood and adolescence affects college-going. Mayer (2021) demonstrates that constrained access to (prime) credit limits parents’ investments in their children’s human capital vis-à-vis homeownership and access to high-quality schools. Sun and Yannelis (2016) and Ringo (2019) further provide evidence that greater parental credit constraints result in lesser college attendance and completion for

their children. And, most recently, Braxton et al. (2024) show that greater parental access to credit during children’s adolescence is associated with greater earnings for their children during young adulthood. At the same time, however, they also found that expanded access to credit for disadvantaged families can suppress intergenerational economic mobility because, whereas expanded access to credit (increased credit limits and decreased cost of bankruptcy) offers increased opportunities for human capital investment, it also reduces incentives for saving among disadvantaged families, which are more likely than advantaged families to reach their credit limits and struggle with repayment and, in response, may decrease human capital investments in children. Together, this evidence suggests that access to credit may both promote and suppress opportunities for economic and social mobility. Moreover, research shows a strong intergenerational correlation between parents’ credit scores during their children’s childhoods and their children’s credit scores as adults (Hartley et al., 2019).

Credit “Worthiness”

While much of the above discussion focuses on the potential mobility-related consequences of debt as burden, or as a negative asset, credit is an increasingly important social and economic “attribute” that determines individuals’ access to valuable social and economic opportunities and resources across multiple domains (Dwyer, 2018). Specifically, individuals’ credit worthiness—as largely determined by their credit score—is a de facto measure of social and economic worthiness when it comes to access to fundamental drivers of mobility, such as employment and housing (see also Goodman et al., 2020; Hartley et al., 2019). Individual and household debt may affect employment and, particularly, housing opportunities in a context in which employers and landlords perform credit checks to inform hiring and rental decisions. The existing literature on employment suggests that credit checks are not typically the deciding factor in hiring decisions but are often taken into consideration, which may constrain employment options for those with poor credit scores. At the same time, research evaluating legal bans on employer credit checks has produced mixed results on whether such policies increase or decrease employment among disadvantaged populations (see, e.g., Ballance et al., 2020; Friedberg et al., 2021).

Returning to the issue of housing, landlords’ increasing reliance on credit scores as a screening criterion for access to rental properties presents an understudied but potentially important dimension for understanding the role of debt and credit in shaping economic mobility. Evidence of income-to-rent ratios above 2 or 3 and proof of steady employment have long been common tenancy requirements; however, landlords increasingly use credit scores to decide whether applicants for rental housing are acceptable

tenants (DeLuca et al., 2023; Desmond, 2016; Galvez, 2010; Reosti, 2021; Rosen et al., 2021). Moreover, credit checks may serve as a proxy for other stigmatized traits, such as race or housing subsidy status, allowing landlords to discriminate by these traits legally (Rosen et al., 2021). As in other domains, such as criminal justice processing and hiring practices, the use of credit scores in housing decisions may reinforce racial and class-based hierarchies (Brayne & Christin, 2021; Doleac & Stevenson, 2020; Dressel & Farid, 2018; Fourcade & Healy, 2013; Kiviat, 2019; Starr, 2014). As scholars have long noted, credit scores have stratified access to homeownership, exacerbating inequality by race (Avery et al., 2009; Baradaran, 2019; Wherry et al., 2019). In the aftermath of the 2008 housing market crash, credit histories of renters have become increasingly available to landlords (Frazier, 2021). Frazier (2021) reported, “In 2011, Experian introduced RentBureau, a service that offers rent-payment history to landlords. […] TransUnion debuted SmartMove. […] Equifax also offered screening reports. Next came the rent-payment platforms [… that] track who has paid on time and funnels that data back to the credit bureaus, which aggregate it and sell it back to landlords” (p. 20). Landlords also use eviction history as a screening criterion, and some research suggests that eviction itself reduces access to credit, creating a negative feedback effect (Humphries et al., 2019).

Having one’s rental applications rejected—sometimes repeatedly—is a demoralizing and sometimes expensive experience. Worry about rejection may affect the housing searches of low-income families and increase the chances that they rent lower-quality housing units in neighborhoods with lesser economic opportunity (Bergman et al., 2024; DeLuca et al., 2013, 2023; Reosti, 2021; Rosen, 2020), given that landlords of low-end rental units, which are disproportionately likely to have housing code violations, may less frequently require credit checks (Rosen et al., 2021). In addition, whereas having a poor credit history is problematic, so is not having a credit history at all; almost 20 percent of the American population is considered credit invisible or unscorable (Consumer Financial Protection Bureau [CFPB] Office of Research, 2015). Brevoort et al. (2018) discusses the differences in credit invisibility. Rates of “no credit history” are higher among residents of low-income neighborhoods, where 30 percent of residents are credit unscorable, on average (compared with 4 percent of residents in high-income neighborhoods). Moreover, Black and Hispanic populations face credit reporting barriers at nearly double the rate of White and Asian populations (CFPB Office of Research, 2015). Nonetheless, far too little is known about how widespread is the use of credit checks in the private rental market and whether credit checks are a primary cause or mechanism through which to understand restricted housing and

neighborhood opportunities—and thus economic mobility—of low-income and racial minority households.

POLICY IMPLICATIONS

Besides established tax policies that provide income supplements (e.g., Earned Income Tax Credit, Child Tax Credit), existing tax instruments support asset-building (e.g., home mortgage interest deduction, preferential treatment of trusts and college savings accounts, lower tax rates on capital income). However, few existing policies seek to target the intergenerational persistence of wealth explicitly.

One important exception is the taxation of inheritances (i.e., estate tax). The main normative argument in favor of inheritance taxation is, indeed, to prevent the creation of a wealthy elite that inherits its status across many generations (Beckert, 2008). So far, empirical studies of the potential effects of inheritance taxation have focused on the question of whether and to what degree it may impact the level of wealth inequality; these studies have found that, in the long run, inheritance taxation helps reduce overall wealth inequality (Nekoei & Seim, 2023). It remains an open empirical question whether inheritance taxation can also limit the extent to which the top-most wealth positions in the country remain in the same families for generations. If there are indeed any direct effects of today’s system of inheritance taxation on wealth mobility, they should be expected to be quite limited in scope, as only a miniscule fraction of wealthy households is impacted by the estate tax: the expected number of 2023 estate tax returns that will be subject to the U.S. estate tax is estimated at just 4,000 estates. That means, just about 0.14 percent of decedents will be subject to an estate tax (Tax Policy Center, 2024). At the beginning of the 21st century, before the implementation of the Economic Growth and Tax Relief Reconciliation Act of 2001, this number was more than ten times higher, with 50,000 estates taxed (Tax Policy Center, 2024) and much higher in many prior periods that were marked by lower estate tax thresholds and higher estate tax rates (Joint Committee on Taxation, 2015). With that, the United States is one of several nations in which the estate tax has first risen and then fallen in importance (Genschel et al., 2023). Generally, though, estate taxation may play a crucial role in financing other interventions geared at enabling wealth mobility that will be discussed further below. In addition to impacting only a very small fraction of the population, the potential direct impact of estate taxes on wealth mobility may also be limited by their timing. The average age of receiving an inheritance is around age 50 (Piketty, 2014)—that is, an age at which much of offspring wealth has already been accumulated and, at least, in part shaped by the advantages arising from their parents’ wealth (see also Pfeffer & Killewald, 2018).

A potential policy response to the limited impacts of inheritance taxation is taxing wealth earlier than at the point of death—namely, through direct wealth taxation. Unlike other nations (e.g., see Limberg & Seelkopf, 2022), the United States has never implemented a comprehensive system of wealth tax, and its constitutionality is debated by law scholars (Ackerman, 1999). Nonetheless, the potential revenue flowing from progressive wealth taxation would be large (Saez & Zucman, 2019) and, similar to the revenue raised through estate taxation, could fund other policies geared at building wealth and supporting wealth mobility.

Some of these wealth-building policies can be classified by the point of the wealth distribution they target: homeownership policies help build middle-class wealth, asset-building policies (such as matched savings account) can lift off the bottom of the wealth distribution, and increased regulation of credit and debt markets can rule out exploitative credit products that keep households indebted. Beginning with housing policy, as stated above, the federal tax and policy environment has been quite beneficial for many middle-class families in allowing them to gain access to homeownership and to accumulate home equity.

Many policies attempt to increase affordable housing. Examples include the Federal Housing Administration (and low–down payment mortgages), government-sponsored affordable housing goals, and affordable mortgage programs through state housing finance agencies that target households with weak credit profiles (see Hayes, 2020; Mehrota et al., 2024; Moulton, 2022). However, both the access to homeownership and families’ ability to use it for wealth accumulation have been deeply stratified, particularly along racial lines. For instance, the GI Bill’s housing provisions (in the form of the home loan guarantee program) have been shown to benefit White individuals to a much greater degree than Black individuals (Agbai, 2022). This policy-induced racial inequity in access to housing wealth continued and even magnified among the descendants of the GI Bill generation (Meschede et al., 2022). Racially biased housing policy or racial bias in its implementation continued throughout the century in myriad ways, restricting access to homeownership for Black families and other racial minorities (Satter, 2009; Taylor, 2019). The resulting Black–White homeownership gap also meant that Black households were less likely to profit from the long upswing in home prices. As a consequence, the long-term housing market appreciation of the last half-century alone can explain nearly three-quarters of the overall growth in Black–White wealth inequality (LaBriola, 2024). Conversely, the loss of housing wealth during the Great Recession starting in 2008 impacted non-White families disproportionally (Pfeffer, 2018). Insufficient regulation of the mortgage credit market facilitated the emergence of predatory lending through the use of subprime mortgages and, importantly, allowed financial providers to target neighborhoods with

a higher representation of Black and Hispanic households (Hwang et al., 2015; Rugh & Massey, 2010). Finally, U.S. tax policy has supported homeownership through the mortgage interest deduction, a tax expenditure that is highly regressive because it benefits higher-income households. And although initial analyses suggest no direct racial bias in the home mortgage interest deduction, through their underrepresentation at higher income levels, racial minority households also benefit less from this tax provision (Cronin et al., 2024).

Asset-building policies typically offer financial instruments that are designed to induce poor households to save, such as through matched savings accounts (Sherraden, 1991). Randomized controlled trials have shown that these instruments may indeed help poor households build up a small amounts of savings, such as $500 (Schreiner & Sherraden, 2007). However, given the vast inequality in wealth, it appears unlikely that these assets could transform the opportunities of the next generation in such a way that asset-building policies could alter patterns of intergenerational wealth mobility meaningfully.

Credit and debt policy is tasked with achieving a delicate balance between promoting access to credit while also protecting consumers (particularly those of subprime credit products) from exorbitant and, in some cases predatory, costs of borrowing. Thus, designing equitable and efficient credit regulation policies is challenging. Such policies can generally be described as falling into four broad domains: (a) information regulation, such as “truth in lending” laws that govern lender disclosure of precise loan terms; (b) price regulation, such as usury (interest rate) and small-dollar loan laws that constrain total costs and fees that can be charged on particular types of loans (payday loans, auto-title loans)—in some cases, policies ban these types of loans; (c) risk regulation, such as debt restructuring (e.g., bankruptcy) and, more recently, debt forgiveness policies; and (d) access regulation, which aims to prevent discriminatory lending policies via “fair lending” laws (Campbell et al., 2011; Fleming, 2018; Horn, 2017; Johnson & Leary, 2017). Whereas research has examined some of the short-term impacts of such policies on factors such as loan-taking, loan amounts, and repayment patterns (Agarwal et al., 2015; Rigbi, 2013; Seira et al., 2017), the committee is aware of no rigorous studies to examine these policies’ long-term effects on financial stability or human capital development. Thus, there is no existing evidence base on which we can assess the potential influence of such policies on economic and social well-being and, in turn, mobility. These areas are ripe for future research (Horn, 2017; Johnson & Leary, 2017). Likewise, future research is warranted to better inform how the use of credit histories, scores, and other data can improve underwriting and targeted access to (prime) credit for disadvantaged and underserved groups (Blattner & Nelson, 2021; Meursault et al., 2022), as well as the

efficacy of alternative approaches to credit-building, such as lending circles (Wherry et al., 2019).

Besides the targeted wealth policies described above, universal policies that provide a wealth transfer to all or most families or young people have recently gained interest. Zewde (2020) discusses how public and private pension policies, educational financing, progressiveness of taxation, and health care financing can help and hinder the impact on inequality over the life course. External events such as recessions can create disparities across the life cycle cohorts as people experience events at different ages, especially if participants experience differential rates of return. For instance, capital endowment programs would provide a universal wealth transfer to all young adults (e.g., $125,000 paid out at age 21 or age 25; Ackerman & Alstott, 1999; Piketty, 2020).

Baby bond programs (Hamilton & Darity, 2010), another universal wealth transfer policy, would provide children up to $50,000 at birth, depending on their parents’ wealth, and would guarantee them a 2 percent annual rate of return until they turn 18. In 2023, Connecticut was the first U.S. state to implement a statewide baby bond program. Washington, DC, and California have also passed baby bond legislation, and such legislation has been proposed in 14 more U.S. states recently. Of course, it will take time to assess the impacts of these programs.

Although baby bond policies are race neutral, recent simulations suggest that they could be very effective in reducing or even eliminating the Black–White wealth gap (Dvir-Djerassi, 2024; Zewde, 2020). As such, policies that involve direct wealth transfers (such as baby bonds) to all or part of the population have been successful in terms of reducing racial wealth gaps (see also Darity et al., 2024, for the importance of reparations, and National Academies, 2024a, for other wealth transfers). Reparatory policies have been used in the United States and in other countries—for example, for Holocaust victims (U.S. Department of State, 2020), American Indians (Trosper, 1994), Japanese internment victims (Bilmes & Brooks, 2024), and victims of armed conflict in Colombia (Bogliacino et al., 2025)—and they have been proposed for Black American descendants of enslaved people (see, e.g., Darity et al., 2024). However, continued processes of structural discrimination that continue to push the next generation into lower wealth positions also need to be addressed (see, e.g., Killewald & Bryan, 2018; Pfeffer & Killewald, 2019).

Finally, acknowledging that wealth advantage is transmitted to the next generation throughout their life course and through multiple channels, broader policies and reforms could consider reforming the institutions that currently require families to rely on wealth to facilitate their offspring’s success. For instance, educational reforms that expand low-tuition, public higher education would reduce the reliance of families to draw on their

own wealth and/or to take on debt in support of the advancement of their children and the nation (see Chapter 4). That is, an alternative policy approach to increasing intergenerational wealth mobility is making accessible resources that support individuals’ mobility, such as higher education, that currently rely on private wealth. Inheritance, gift, and wealth taxation are potential avenues for meeting the associated revenue needs. Future research should study the potential of the existing taxation system and new tax policies for these purposes.

SUMMARY, KEY CONCLUSIONS, AND RECOMMENDATIONS

A growing body of research consistently documents relatively low levels of wealth mobility in the United States, coupled with a high degree of inequality in the concentration of wealth (at the top of the distribution) and stark racial/ethnic gaps in wealth that have grown over time. Compared with its peer countries, the United States also stands out as the country with the highest level of wealth inequality and top concentration in wealth.

Wealth is an important component of intergenerational mobility in the United States. Perhaps the most distinctive feature of wealth is that—unlike education, occupation, or income—it can be transmitted directly to one’s children and grandchildren. However, the transmission of wealth can take place not only directly through transfers and bequests, but also indirectly through advantages that accrue to children in their early development, educational, and labor market experiences. These indirect channels of wealth transmission also undergird wealth’s role in sustaining other forms of social mobility. Family wealth has broad intergenerational impacts that accrue through multiple mechanisms. In addition to monetary advantages, family wealth can provide a safety net or buffer that allows individuals with access to wealth the privilege of taking risks. The intergenerational behavioral implications of assets and debts are one frontier for future research on wealth and debt.

Like most other scholarship on social mobility, most existing studies on wealth are limited to a two-generation framework (i.e., the standard assessment of similarity in positions between parents and their children). However, both family assets and debts can exert influences beyond immediate offspring. As a result, increased consideration of the role of at least grandparental wealth and debt is crucial.

Housing is a key source of wealth and stability, including the value of the home itself, the resources a home provides (as compared with renting), and the homes around the home (i.e., neighborhoods). Housing assets (home equity) are the primary source of wealth component for the average U.S. household and for a majority of households. As a mechanism of

intergenerational transmission, the effects of housing are likely multifold. One such mechanism is the ability of homeowners to take on additional debt (through home equity–based lending) that they can use to support their children’s postsecondary educational attainment in a context of high and rising college costs.

Conclusion 5-1: Wealth is transmitted across generations. This transmission occurs partly directly, through transfers and bequests, but also indirectly, through advantages that accrue to children in their early development, neighborhood, educational, and labor market experiences; these indirect channels of wealth transmission undergird wealth’s role in sustaining other forms of economic and social mobility. In addition to monetary advantages, family wealth can provide a safety net or buffer that allows individuals to take risks.

Recommendation 5-1: Researchers should examine the intergenerational behavioral implications of assets and debt to better understand the indirect channels through which wealth is transmitted.

Recommendation 5-2: Researchers should expand the traditional two-generation mobility framework by considering the role of grandparental wealth and debt.

Wealth accumulation and intergenerational wealth transmission are shaped by multiple institutional and structural features of U.S. society that have not been and are still not race neutral, with the segregated housing market and racialized lending practices being just one prime example. The sources of disparities among racial/ethnic minority groups have shifted in scope over time but require ever more critical analysis, as direct forms of legal exclusion from asset accumulation have morphed into less explicit but potentially equally impactful ways of reproducing racial/ethnic wealth gaps, such as via weakened homeownership rights or predatory lending practices (see Dyer et al., 2008 for a discussion of the issues surrounding heirs’ property). Uncovering these institutions, policies, and practices remains an urgent task for future research. Moreover, although research has documented dramatic differences in wealth mobility between White and Black individuals, evidence on wealth mobility patterns among other groups is still very limited.

Conclusion 5-2: Wealth accumulation and intergenerational wealth transmission are shaped by multiple institutional and structural features of U.S. society that have not been and are still not race neutral.

Recommendation 5-3: Researchers should further examine the ongoing role of institutions, policies, and practices in reproducing racial/ethnic wealth gaps and expand beyond White and Black populations to generate evidence on wealth mobility patterns for other racial/ethnic groups.

Credit and debt provide many individuals with opportunities to make investments in human capital and core assets, such as a home, as well as opportunities to take risks that engender wealth accumulation and upward mobility. However, for others, credit and debt are insurmountable obstacles that hinder upward mobility; they may even be direct sources of downward inter- and/or intragenerational mobility. In other words, credit and debt are not monolithic; their particular types can carry both important benefits and challenges to the individuals that access them. It is therefore important to study the circumstances in which credit and debt are productive and for whom. Student debt, which accounts for a sizeable share of the debt burden of U.S. households, is one type of debt that represents this tension well: while generally considered a “productive” form of debt, as it can enable the pursuit of higher education and the earnings benefits that arise from a college degree, student debt has contributed greatly to the maintenance of racial inequity in wealth and indebtedness.

Conclusion 5-3: Credit and debt are not monolithic. For many individuals, they provide opportunities to make core long-term investments and take risks that engender wealth accumulation and upward mobility. For others, they are hindrances to upward mobility, if not direct sources of downward mobility.

Recommendation 5-4: Researchers should study in what circumstances, how, and for whom different forms of credit and debt are helpful or harmful for economic and social mobility.

Few existing policies explicitly target the intergenerational persistence of wealth. However, a variety of different interventions is possible. One approach is to adopt policies that target different points of the wealth distribution: inheritance and wealth taxation will impact only the very top of the wealth distribution; homeownership policies will help build middle-class wealth; and the regulation of credit and debt markets, as well as asset-building policies such as matched savings accounts, can lift the very bottom of the wealth distribution. A more universal approach would be to provide a wealth transfer to all families, young people, or the descendants of enslaved people through policies such as universal wealth grants, baby bonds, or reparations for slavery, respectively. These policies can create a more widely shared economic basis for families to invest in the success of

their children. Although initial assessments of some of these policies are underway, far more needs to be known about their relative effectiveness.

Finally, acknowledging that wealth advantage is transmitted to the next generation throughout the life course and through multiple channels, broader policies and reforms could consider reforming the institutions that currently make families rely on wealth to facilitate their offspring’s success. For instance, as discussed in Chapter 4, educational reforms that expand low-tuition, public higher education would reduce families’ reliance on their wealth or debt in support of the advancement of their children.

Conclusion 5-4: Targeted policies can address the intergenerational transmission of wealth at different points of the wealth distribution, from the top (through inheritance and wealth taxation), to the middle (chiefly through housing policies), to the bottom (through credit market regulation and asset-building policies). More universal policies (e.g., universal stakeholder grants, baby bonds, reparations) can build a common stock of wealth for all. However, more needs to be known about the relative promise of each of these approaches and of the mechanisms for funding them.

Recommendation 5-5: Researchers should study the relative costs, benefits, and long-term effects of (1) policies that target the intergenerational transmission of wealth at different points in the wealth distribution (top, middle, and bottom); (2) universal policies that seek to provide wealth transfers to all families or young people or provide reparations for slavery; and (3) broader institutional changes that would reduce the necessity of families to rely on their private wealth to support the success of the next generation. Researchers should also study the potential of the existing taxation system and new tax policies to support these initiatives.

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