Economic and Social Mobility: New Directions for Data, Research, and Policy (2025)

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PREPUBLICATION COPY – uncorrected proofs 1 Introduction Intergenerational mobility is a central measure of the nation’s economic well-being. While measures of economic growth capture average levels of material well-being, and measures of inequality capture the distribution of economic outcomes across the population, economic and social mobility measures the chances that people have to achieve economic prosperity regardless of their family backgrounds. Complementing measures of inequality of outcomes, intergenerational mobility provides information about equality of opportunity. A mobile society can foster economic efficiency by supporting human capital formation for all its members, regardless of family circumstances, and by providing labor market opportunities to people from diverse backgrounds. A mobile society could also support fairness by reducing barriers based on family income, offering opportunities that are not constrained by circumstances at birth. Mobility is not a desirable social goal in isolation. Rather, it makes sense as a policy goal only in combination with a sufficient level of economic growth that supports an adequate standard of living across generations. Upward mobility and the egalitarian pursuit of prosperity are recurring motifs in American cultural narratives, ranging from Horatio Alger’s 19th-century tales of “rags-to-riches” trajectories, to The Jeffersons’ “moving on up” to overcome their working-class roots, and even to contemporary memes of the multi-billion-dollar business that started in a garage. The prospect of upward mobility, and the promise that individual effort, hard work, and talent will lead to economic well-being, have been a staple of the political discourse across the political spectrum since the founding of the republic (Sandel, 2020). However, a sole focus on individual opportunity—driven by individual abilities and efforts—risks neglecting the social and institutional contexts that shape these opportunities. For instance, pervasive economic inequality hampers the development of human capital among children raised in poverty by limiting their access to resources. Economic segregation across neighborhoods exposes disadvantaged communities to underfunded schools; environmental CH 1 - 1 

PREPUBLICATION COPY – uncorrected proofs hazards; pollution; and limited amenities such as parks, libraries, and health care facilities. Inadequate access to insurance against risks, such as illness or job loss, undermines disadvantaged families’ ability to support their children’s development. Financial and informational barriers to college thwart access to higher education among poor families. In sum, to understand the dynamics of intergenerational mobility in the United States, it is important to consider the social and institutional factors that support or hinder the development of individual abilities. For all the value placed on equal opportunity in the American context, intergenerational mobility in the United States is relatively low compared with other affluent democracies. The degree to which adult children’s earnings depend on family circumstances, known as relative mobility, is higher in the United States than in other wealthy countries (Corak, 2013b; Durlauf et al., 2022; Krueger, 2012). Additionally, the likelihood of adult children surpassing their parents’ income level in the United States, known as absolute upward mobility, has declined over time, a trend similar to other wealthy countries (Berman, 2022; Chetty et al., 2017; Manduca et al., 2024). The decline in upward mobility has coincided with an increase in inequality, and some scholars suggest it might be driven, at least partially, by growing income disparities (Berman, 2022; Chetty et al., 2017). Limited absolute and relative intergenerational mobility in the United States compared with peer countries invites a research agenda toward understanding this reality and developing evidence-based strategies for improving mobility. Developing such an agenda requires a clear understanding of the factors that influence mobility and their mechanisms, and how these factors can be affected by policy interventions. It also requires adequate data capable of tracing families across generations. CHARGE TO THE STUDY COMMITTEE In this context, the National Academies of Sciences, Engineering, and Medicine was asked by the Gates Foundation to carry out a consensus study on improving economic and social mobility in the United States. The specific charge to the National Academies was as follows: An ad hoc committee of the National Academies of Sciences, Engineering, and Medicine will undertake a study that will review and assess what is known about the factors that influence economic and social mobility in the United States, the mechanisms through which these factors operate, how they are affected by policy interventions, and how these CH 1 - 2 

PREPUBLICATION COPY – uncorrected proofs relationships and mechanisms vary across and within different population groups. The study will identify key, actionable knowledge gaps; discuss promising conceptual, methodological, and data approaches; and make recommendations for policy-relevant research and evaluation. To conduct this study, the National Academies appointed the Committee on a Research Agenda for Improving Economic and Social Mobility in the United States. The study committee included 14 experts with backgrounds in areas such as economics, sociology, demography, statistics and methodology, public policy, and evaluation. DEFINITIONS: WHAT IS MOBILITY AND HOW IS IT MEASURED? The work of this committee focused on intergenerational mobility—namely, the association between parents’ economic status and adult children’s economic status. High intergenerational mobility suggests that individuals have a fair chance of achieving success regardless of their social origins. In contrast, limited mobility indicates that both poverty and privilege will persist from generation to generation, suggesting limited opportunity to achieve a standard of living independent of family (of origin) resources—and especially one that is better than the parents’ generation (for in-depth reviews of theoretical, substantive, and methodological issues related to intergenerational mobility, see Black & Devereux, 2011; Fox et al., 2016; Jäntti & Jenkins, 2015; Torche, 2015a, 2015b). As we discuss in the next two sections, intergenerational mobility has two dimensions: absolute and relative. Ensuring equal opportunity does not mean eliminating all economic similarities between parents and children (Jencks & Tach, 2006; Swift, 2004). The key issue is the mechanisms that pass advantage or disadvantage across generations. When children are held back by their parents’ limited financial, cultural, or social resources—or when adults face ethnic or racial discrimination that blocks fair rewards—the resulting intergenerational persistence reflects unequal opportunity (Chetty et al., 2014b, 2020, 2024; Darity, 2005; Oliver & Shapiro, 2006). It is true that some sources of intergenerational continuity are partially unavoidable and fall beyond the realm of public policy—for example, family priorities and values. As philosophers have acknowledged, “the family is an obstacle to equality of opportunity” (Rawls, 1971, as cited in Swift, 2004, p. 7). However, while this committee acknowledges that there are channels for intergenerational economic persistence that may be difficult or undesirable to alter via social CH 1 - 3 

PREPUBLICATION COPY – uncorrected proofs policy, we believe that there is vast opportunity to promote mobility in the United States by dismantling economic and institutional barriers to economic prosperity. Various measures of economic advantage can be used to measure intergenerational mobility, including earnings, income, occupational status, social class, wealth, and educational attainment. In the past, economists predominantly focused on pecuniary measures such as earnings and income, while sociologists focused on occupations, resources operationalized as social class, occupational status, and occupational prestige (Blau & Duncan, 1967; Hauser et al., 1975; Lipset & Bendix, 1952; Nam & Powers, 1968). Research on occupational mobility has provided valuable insights about social mobility. Measures of social class distinguish groups based on the occupational resources they control— for example, employers, professional workers, managers, skilled manual workers, and unskilled manual workers. Measures of social class are relevant because they consider the specific kinds of labor market assets that people have access to and shape opportunity and inequality. Furthermore, given the different assets they control, social classes will be differently affected by economic and institutional factors such as technological innovation or labor market and welfare policies (Breen & Whelan, 1996). Sociological measures of occupational status and prestige rank occupations based on the average income and educational levels of people who hold those occupations. These rankings provide a one-dimensional hierarchy of socioeconomic advantage correlated with “permanent income” (i.e., income over the long run, purged from short-term fluctuations and changes over the life course) (Torche, 2015a). Furthermore, in contrast to the challenges of collecting data on income across generations, which is prone to measurement error, occupational data are highly reliable and can be reported about parents and children with little error (Warren & Hauser, 1997). Recent research has focused increasingly on economic measures such as earnings and income to measure mobility (Chetty et al., 2017; Deutscher & Mazumder, 2021; Sakamoto & Wang, 2020). The current emphasis in economic mobility is supported in part by (1) the growing availability of administrative data, which measures income of parents and children with limited error, and in part by (2) evidence that, in the United States, there is much economic inequality within social classes and occupational groups. Indeed, within-occupation earnings disparities account for a substantial portion of growing economic inequality since the 1980s (Mouw & Kalleberg 2010; Weeden et al., 2007). CH 1 - 4 

PREPUBLICATION COPY – uncorrected proofs Measures of economic and social or occupational mobility are both relevant and complementary. Labor market resources including occupational positions are central determinants of individual earnings and families’ incomes. This report focuses on economic mobility because much empirical evidence on factors that shape one’s chances of mobility—for example, family structure, education, neighborhood of residence—use income and earnings rather than occupation as a measure of economic resources. The concept of intergenerational mobility, measured by income, earnings, or occupations, encompasses two types: absolute and relative; each provides different measures of the persistence of advantages and disadvantages across generations. Absolute Mobility Absolute mobility focuses on upward or downward changes in income across generations. It captures the probability that adult children will reach an income threshold defined by parental income. The most common measure of absolute mobility is the likelihood that children will earn more than their parents in real dollars—in other words, that they will experience upward mobility. Absolute mobility is especially salient in public debates because it provides a tangible benchmark against which individuals gauge their economic status. Typically, people assess their financial standing by comparing themselves with their parents, and parents often evaluate their children’s success based on their ability to surpass their own earnings. Measures of upward mobility were first reported in the United States by Isaacs et al. (2008). They found that about two-thirds of Americans exceeded their parents’ income. More recent studies have shown a pronounced decline in the proportion of adult children who outearn their parents over time (Chetty et al., 2017; Davis & Mazumder, 2022). For example, the likelihood that adult children outearned their parents was 90 percent for those born in 1940 but 50 percent for children born in the 1980s (Chetty et al., 2017). Estimates of declining upward income mobility in the United States are consistent with declining trends observed in other affluent countries (Berman, 2022), albeit not at levels observed in the United States (Manduca et al., 2024). The decline in upward mobility in the United States has occurred in the context of declining economic growth and growing economic inequality since the 1970s. Some research suggests that the rise in inequality is the central factor CH 1 - 5 

PREPUBLICATION COPY – uncorrected proofs driving the declines in upward mobility. According to one estimate, reducing economic inequality to its 1940 level would reverse more than two-thirds of the decline in upward mobility between cohorts born in the 1940s and 1980s (Chetty et al., 2017). Figure 1-1 demonstrates the international comparisons of absolute upward mobility. As shown, the United States has low levels of absolute upward mobility compared to a selected set of wealthy democracies. FIGURE 1-1 International comparisons of absolute upward mobility. NOTES: The upward mobility rate is calculated as the percentage of children in each birth cohort whose family income at age 30, adjusted for inflation, was at least as high as their parents’ family income at age 30. Incomes are measured using a combination of register and survey data in each country, as follows: Canada: Intergenerational Income Database; Finland: total- population register-based longitudinal data provided by Statistics Finland; Netherlands: Netherlands register data; Norway: full population data from Statistics Norway; Sweden: full population of Swedish nonimmigrants; United Kingdom (UK): analysis follows the “copula and marginals” method as described by Chetty et al. (2017) (the Family Expenditure Survey and the Family Resources Survey provide information on marginal earnings distributions, and the British Cohort Study provides data for the copula); United States (USA): analysis follows the “copula and marginals” approach introduced by Chetty et al. (2017) (copula constructed from Internal Revenue Service tax records; parent incomes are sourced from the 1940–2000 decennial censuses and the 2010 and 2015 American Community Survey; child incomes are sourced from CH 1 - 6 

PREPUBLICATION COPY – uncorrected proofs the 1968–2021 Current Population Survey Annual Social and Economic Supplements). See Manduca et al. (2024) for further details. SOURCE: Maduca et al. (2024). Copyright American Economic Association; reproduced with permission of the American Economic Journal: Applied Economics. Relative Mobility Relative mobility measures the strength of the association between parents’ and adult children’s incomes. A strong intergenerational association (or persistence) reflects low mobility, a situation in which having high-income parents predicts a high level of economic well-being and having low-income parents predicts poverty among adult children. A weak association, in turn, identifies a society in which the chances of achieving economic prosperity depend little on parental prosperity. Higher relative mobility suggests a more open society, where success is less influenced by family background. Like inequality, relative mobility is a concept that describes entire societies rather than specific individuals—”rags to riches” and “riches to rags” biographies exist in every society; relative mobility measures how prevalent these biographies are in a particular society. Unlike absolute mobility, measures of relative mobility require that for any upward move to happen, a downward move must “free up” a space in the socioeconomic hierarchy (Hout, 2004, 2015). It is important to highlight that relative mobility is conceptually distinct from inequality: inequality focuses on the dispersion of income across the population (i.e., on the income distances between the poor and the rich). Mobility, in turn, captures how likely it is for people to change income positions across generations. The most common measure of relative persistence (and hence, lack of mobility) is the intergenerational income elasticity, which ranges approximately between zero and one. Lower values (closer to zero) of income elasticity indicate less persistence and greater mobility, while values closer to one signify strong replication of advantage or disadvantage across generations. Because measures of relative mobility are more abstract than those of absolute mobility, Box 1-1 defines intergenerational elasticity and other measures of relative mobility. BOX 1-1 Measuring Relative Mobility The most common measures of relative mobility are intergenerational elasticity, rank– rank slope, and intergenerational correlation. CH 1 - 7 

PREPUBLICATION COPY – uncorrected proofs Intergenerational elasticity captures, approximately, the average percent change in children’s earnings associated with a 1 percent change in parents’ earnings. It is the coefficient in a regression model predicting log-transformed adult children’s earnings or income based on log-transformed parents’ earnings. For example, an elasticity of 0.4 indicates that a 10 percent increase (decrease) in parents’ earnings will lead, on average, to a 4 percent increase (decrease) in children’s earnings. Elasticities include information about both the association between parents and children and changes in the income distribution across generations. An increase in inequality across generations will increase the elasticity, and a decline in inequality will reduce it (and conversely, an decline in mobility will increase inequality). To control for changes in inequality across generations, researchers have used alternative measures such as the rank–rank slope and the intergenerational correlation. The rank–rank slope is the coefficient in a regression predicting the percentile rank of children’s earnings from the percentile rank of parents’ earnings. A rank–rank slope of 0.4 indicates that a 10-percentile-point increase in parents’ earnings rank results in a 4-percentile- point increase in children’s rank. By using earning ranks rather than earning levels, this measure is unaffected—at least mechanically—by changes in inequality across generations. The intergenerational correlation in log earnings adjusts the intergenerational elasticity by the standard deviation of parents’ and children’s income. The choice of measure of relative mobility is consequential in contexts with different levels of economic inequality. For example, intergenerational persistence is stronger in the United States than in Sweden and the United Kingdom when using elasticity but similar using the rank–rank slope (or the correlation coefficient) (see Corak et al., 2014; Eberharter, 2013), suggesting that the low level of mobility in the United States is due to higher levels of inequality (see Figure 1-2). These measures of relative mobility use a single estimate to capture intergenerational persistence. Naturally, reducing the mobility process to a single measure of linear persistence is a simplification. Recent work has used alternative strategies for capturing the pattern and not only the overall level of intergenerational association. These include matrices cross-classifying parents’ and children’s income quintiles, models allowing for nonlinearities in the intergenerational association, and quantile regression models examining income dispersion around the regression line (Corak & Heisz, 1999; Couch & Lillard, 2004; Eide & Showalter, 1999; Peters, 1992). CH 1 - 8 

PREPUBLICATION COPY – uncorrected proofs Based on these approaches, it is possible to examine whether average persistence is stronger for the rich or the poor, and whether the dispersion in children’s income, intergenerational mobility, and equality of opportunity varies across the socioeconomic hierarchy. For example, Eide and Showalter (1999) found much more variance around predicted children’s income for poor than for wealthy parents in the United States. Mitnik et al. (2023) found that intergenerational persistence is stronger among the upper-middle class than among the bottom half of the earnings distribution. Both findings signal stronger earnings persistence at the top than at the bottom. SOURCES: Black & Devereux, 2011; Fox et al., 2016; Torche, 2015a. Abundant research exists on the intergenerational income elasticity in the United States. Estimates of earnings elasticity measuring the strength of the intergenerational association have proliferated over time as administrative data become available and methodological approaches become more sophisticated. Early measures of intergenerational elasticities yielded low values of 0.15–0.20 (Becker & Tomes, 1986; Behrman & Taubman, 1985), leading to the conclusion that earnings were not strongly transmitted across generations. However, we now know that this finding was an artifact of using single-year measures of earnings and small, homogenous samples. The use of techniques that account for different sources of measurement bias has led to much higher elasticity estimates—between 0.40 and 0.60. Mobility scholars have offered 0.47 as a “preferred estimate” (Corak, 2006), and a range between 0.50 and 0.60 as plausible (Solon, 2008). A recent analysis by Mitnik et al. (2023) estimates intergenerational earnings elasticity of 0.49–0.55. Relative mobility is lower in the United States than in many other affluent democracies, suggesting that the United States is not a particularly open society where individuals have an equal chance to succeed regardless of their social origins. Indeed, the 0.47 value of the earnings elasticity in the United States at the turn of the 21st century compares with values between 0.15 and 0.41 in other wealthy nations (Corak, 2013b). Figure 1-2 shows the so-called Great Gatsby Curve, first described by Corak (2013b) to illustrate the correlation between levels of economic inequality when individuals were growing up and the extent of relative mobility they experience as adults (restricted to fathers and sons). This figure shows that the United States is both the more unequal and the least mobile country among wealthy democracies. CH 1 - 9 

PREPUBLICATION COPY – uncorrected proofs FIGURE 1-2 International comparisons of relative mobility (intergenerational income elasticity). NOTES: Income inequality is measured as the Gini coefficient, using disposable household income as provided by the World Bank. Higher intergenerational income elasticity indicates lower relative intergenerational mobility. SOURCE: Narayan et al. (2018). Licensed as a Creative Commons Attribution. The question about whether relative mobility has declined in the United States over the last half century amid growing inequality remains unsettled. Some evidence suggests a reduction in relative mobility starting with the cohorts coming of age since the 1980s (Aaronson & Mazumder, 2008; Bloome & Western, 2011). Other studies report stability in relative mobility from the mid-20th century onward (Bloome, 2015; Bloome et al., 2018; Hauser, 2010; Hertz, 2007; Lee & Solon, 2009). Recent research using population-level tax data suggests that relative intergenerational mobility has changed little in the recent past. For example, the probability that a child reaches the top fifth of the income distribution as an adult given that their parents were in the bottom fifth of the income distribution is 8.4 percent for children born in 1971 and 9.0 percent for those born in 1986. Likewise, children born to the highest-income families in 1984 were 74.5 percentage points more likely to attend college than those from the lowest-income families, while the CH 1 - 10 

PREPUBLICATION COPY – uncorrected proofs corresponding gap for children born in 1993 is 69.2 percentage points (Chetty et al., 2014b). The most recent analysis of mobility trends using population-level data based on tax records finds divergent change in mobility by race (Chetty et al., 2024). By evaluating change affecting cohorts born between 1978 and 1992, this study found that relative mobility—measured as the association between the income ranks of parents and adult children—declined for White individuals but increased among African American individuals, resulting in a smaller Black– White income gap for people growing up in low-income households. This study also shows that the intergenerational persistence of poverty has increased for White children, from 25 to 30 percent, and declined for Black children, from 40 to 34 percent, although a Black–White gap persists. Chetty et al. (2020) demonstrate that the Black–White gap exists mainly for Black men, while Black women experience similar mobility levels (both absolute and relative) as White women. Evaluation of long-term relative mobility based on occupations since the 19th century provides a relevant context for understanding recent trends. Recent research suggests a long-term decline in the intergenerational occupational association (or persistence)—that is, an increase in mobility—since the 19th century (Jácome et al., 2022; Ward, 2023). These studies challenge the common notion that the United States was a “land of opportunity” characterized by high levels of occupational mobility in the late 19th and early 20th centuries (Feigenbaum, 2018; Ferrie, 2005; Long & Ferrie, 2013; Parman, 2011; Song et al., 2020). One reason for this discrepancy is that earlier studies focused narrowly on White men. These studies of long-term occupational mobility further suggest that the increase in mobility has been driven by gains among African Americans during the 20th century. As concluded by Jácome et al. (2025), “the United States starts the 20th century much further from the ‘American Dream’ ideal of a mobile society but also improves more significantly when the full population is considered rather than only White men” (p. 348). Despite these recent gains for African Americans, Black men still earn considerably less on average than White men, and they experience less upward mobility than their White counterparts from similar socioeconomic backgrounds (Collins & Wanamaker, 2022). These recent studies highlight the importance of using nationally representative samples that include all racial/ethnic groups as well as women to obtain representative mobility estimates. CH 1 - 11 

PREPUBLICATION COPY – uncorrected proofs In sum, absolute and relative mobility capture two distinct dimensions of opportunity across generations in the United States. Absolute mobility focuses on both the chances that adult children will surpass their parents in terms of economic well-being (upward mobility) and the chances that children will achieve income levels lower than their parents (downward mobility). Relative mobility captures whether adult children have a similar chance to do well regardless of their parents’ resources. A country can have high upward absolute mobility yet low relative mobility. For example, rapid economic growth may allow most adult children to earn more than their parents, but if growth disproportionately favors wealthy families, then the children of rich parents may still end up better off than children from poor families. Researchers have argued that relative and absolute mobility are only weakly correlated (Berman, 2022; Bloome & Opacic, 2024; Deutscher & Mazumder, 2023). However, at least one study (Chetty et al., 2014a) found a strong empirical correlation between relative and absolute upward mobility in the United States. Both relative and absolute mobility are important, as they address different dimensions of equal opportunity and answer different policy questions. Limited absolute and relative mobility might be harmful for the United States. Low absolute mobility means there is limited opportunity for young cohorts to do better than their parents, which might reduce well-being and even induce frustration and social conflict. Meanwhile, a lack of relative mobility means that one’s success is largely determined by one’s parent’s rather than by one’s effort or experience. The implications is wasted human potential and inefficient allocation of resources, which could be harmful for growth in the long term (Narayan et al., 2018). INTERGENERATIONAL MOBILITY AND ECONOMIC INEQUALITY Economic inequality has increased sharply since the 1970s in the United States. In 1967, the 20 percent of households with the highest income received 42 percent of the total national income. By 2022, this share had increased to 51 percent. Similarly, the income share of the poorest 20 percent of households declined from 5.6 percent to 3.5 percent of the total national income over the last 50 years (Guzman & Kollar, 2023). High levels of inequality are a concern in part because they might hamper intergenerational mobility, especially relative mobility. Several theoretical mechanisms suggest an association between high levels of inequality and reduced relative mobility (Durlauf et al., 2022). Wider inequality in the parental generation implies wider disparities in parental investments and less progressive human capital investments, CH 1 - 12 

PREPUBLICATION COPY – uncorrected proofs which results in less mobility (Durlauf et al., 2022; Ermisch et al., 2012; Neckerman & Torche, 2007). Higher inequality is partly driven by higher returns to schooling in the labor and other markets, which is also correlated with intergenerational rigidity (Solon, 2004). Additionally, inequality may exacerbate residential segregation by income, resulting in a more skewed composition of peer groups and more segregated learning environments along socioeconomic lines (Durlauf, 1996; Reardon & Bischoff, 2011). An additional pathway of influence linking high inequality with reduced mobility might be the political process, if economic concentration strengthens the influence of the wealthy through political contributions and lobbying, thus reducing the scope for redistributive policies (Burtless & Jencks, 2003; Campante, 2011). These mechanisms are theoretically plausible but not necessary. While not yet observed empirically, it is possible that a highly unequal society, given sufficient political will, could invest in human and financial capital for children from low-income families and limit the intergenerational transmission of advantage among the wealthy. In this way, inequality in one generation would not necessarily determine opportunities in the next, and it will not necessarily lead to limited relative mobility. Additionally, a society that fosters robust and sustained economic growth could still promote meaningful absolute mobility, even if relative mobility remains modest. To date, the evidence about an association between inequality and mobility is not conclusive, however. While empirical findings vary and are limited by data availability, there is no consistent evidence that mobility has declined as inequality has increased. Furthermore, it is exceedingly difficult to prove a causal link between growing inequality and declining mobility. Any impacts of growing inequality on mobility would likely take a long time to materialize and would be mediated by changes in institutions, policies, and investments favoring different socioeconomic groups (Nybom & Stuhler 2024, Torche, 2015b). Indeed, it might take decades for persistently high inequality to permeate institutions and policies in a way that substantially alters intergenerational mobility. The mechanisms linking inequality and mobility are, however, plausible. While some level of inequality is inevitable and probably desirable to provide the right incentives to work hard, innovate, and invest in human capital (Krueger, 2012; Welch, 1999), the high levels of inequality that have characterized the United States over the last 50 years might result in diminished opportunities for children from low-income backgrounds to develop the skills necessary to share the fruits of economic growth. CH 1 - 13 

PREPUBLICATION COPY – uncorrected proofs MOBILITY IS NOT WITHOUT RISKS Efforts to achieve upward mobility may carry risk. As with inequality, we presuppose that some degree of risk-taking is required for people to bolster their economic and social standing—for example, by taking out students loans to fund postsecondary education, obtaining credit to start a business, or seeking new employment or training to switch careers. Problems might arise when the level of risk individuals must assume carries the threat of downward mobility for a substantial proportion of the population. The level of risk assumed by individuals depends on insurance systems, which after expanding in the 1960s and 1970s have been reduced since the 1980s. As a result, the last 40 years of American social policy have seen an increase in risk. They have also seen the responsibility for risk—in the financial, health care, educational, and retirement spheres—shift from governments, businesses, and other social institutions onto individuals and families (Hacker, 2019). Risk associated with investments and unexpected shocks has been partially privatized—that is, transformed from a collective into an individual responsibility (Grusky et al., 2019; Hacker & Pierson, 2002; Pierson, 1994, 1996; Starke, 2007). Weaker insurance mechanisms supporting family well-being and workplace security have led to greater financial instability for many families. This results in downward mobility related to painful experiences such as a plant closing, divorce, or skill obsolescence (Newman, 1999). The committee emphasizes that not all sources of inequality and risk are harmful in themselves or pose a barrier to intergenerational mobility. We claim, however, that high inequality and excessive risk of economic downturn resulting from investments or unpredicted shocks prevent upward mobility and strengthen the association between parents’ resources and adult children’s well-being. Indeed, many policies designed to improve mobility are indistinguishable from policies designed to address inequality in resources or to strengthen the social safety net and reduce the exposure to risk, especially among vulnerable populations. KINDS OF EVIDENCE ABOUT MOBILITY CONSIDERED IN THE REPORT Mobility captures the relationship between adult children’s outcomes and the conditions in which they were raised, a process observed over a span of at least two decades—from the child’s birth to early adulthood. Because of this extended timeline, evaluating factors that CH 1 - 14 

PREPUBLICATION COPY – uncorrected proofs directly affect mobility is much more challenging than assessing the determinants of specific outcomes, such as adult children’s high school graduation or homeownership. As a result, direct evidence on the correlates or determinants of mobility is scarce. One example of such evidence is cross-country comparisons, which show that higher inequality in the parental generation is associated with lower relative mobility among adult children (Corak, 2013a) and that strong redistributive policies via taxes and transfers are correlated with higher upward mobility from poverty (Parolin et al., 2024). Another example is research showing that higher government spending across U.S. states is linked to increased mobility (Mayer & Lopoo, 2005). Most evidence on the factors shaping mobility is indirect, focusing on factors that are related to mobility rather than mobility itself. For example, research shows that providing information about college funding to low-income youth significantly increases college enrollment (Dynarski et al., 2021). Given the large economic payoff of a college education, a policy that provides information about college funding to low-income youth would likely increase their upward mobility. This is considered indirect evidence because the researchers do not directly measure intergenerational mobility; instead, they focus on a factor along the pathway connecting parental resources with adult children’s outcomes. The committee considered various types of direct and indirect evidence about intergenerational mobility, including descriptive, correlational, quasi-experimental, experimental, and qualitative evidence. • Descriptive evidence provides information on the characteristics of mobility, its correlates, and contextual factors. For instance, the proportion of adult children earning more than their parents over time offers descriptive evidence about trends in upward mobility (Chetty et al., 2017), while data on racial/ethnic wealth gaps provides context for the analysis of disparities in wealth mobility (Aladangady et al., 2023). • Correlational evidence examines the association between variables of interest. For example, research shows that growing up with a single parent is associated with lower educational attainment (McLanahan & Sandefur, 1994). This association varies by race and ethnicity and is weaker for Black children than for White children (Cross, 2020, 2023). Correlational evidence does not imply CH 1 - 15 

PREPUBLICATION COPY – uncorrected proofs causality, as unmeasured factors may affect the relationship under analysis even when controlling for multiple factors such as parental education, age, or income. • Quasi-experimental evidence involves exploiting quasi-random events or natural experiments to assess the impact of mobility determinants. For example, Johnson (2020) found that increases in parental housing wealth raised the likelihood of children attending college, using neighborhood-level housing market booms and busts as a natural experiment and comparing homeowners with renters (Johnson, 2020). This is considered a natural experiment because fluctuations in the local housing market are plausibly driven by macroeconomic factors beyond families’ control and therefore provide a quasi-random source of variation in parental wealth. • Experimental evidence relies on the randomized assignment of a “treatment” to determine its effect, providing the strongest causal interpretations. For example, the Moving to Opportunity experiment, which provided housing vouchers to a random set of families in high-poverty neighborhoods, led to better health outcomes for parents and children in the treatment group than for those without vouchers (Ludwig et al., 2011, 2012; Pollack et al., 2019, 2023). • Qualitative evidence comes from in-depth interviews and ethnographic observations, capturing individuals’ lived experiences, understandings of their circumstances, and decision-making processes. This type of nonquantitative evidence reveals rich insights into the opportunities and constraints people face and helps to interpret and make sense of quantitative findings. Qualitative research can be essential for developing hypotheses and understanding the mechanisms behind observed associations. The committee viewed all these sources of evidence as valuable and complementary. The panel recognized that experimental evidence, which supports stronger causal claims, may not be available for many important (and sometimes broader) questions. However, other forms of evidence may offer critical insights. Throughout the report, we took care to specify the type of evidence we are considering and, where appropriate, to acknowledge the limitations of different evidence. CH 1 - 16 

PREPUBLICATION COPY – uncorrected proofs This report adds to other reviews of mobility evidence by incorporating qualitative research. The use of qualitative data in the social sciences has grown over time, as has its demonstrated value (Edin et al., 2024). Among other uses, qualitative research can interrogate important theoretical and policy assumptions; generate hypotheses for better-informed data collection or the refinement of econometric and structural models; identify potential causal mechanisms that explain the success of failure of different policies; and reveal the perceptions and beliefs held by those for whom policies are intended. The report considers qualitative evidence and offers some guidance on how to further develop it and integrate it into the infrastructure of mobility research in the future. CONCEPTUAL FRAMEWORK FOR THE ANALYSIS OF MOBILITY The committee developed a conceptual framework that relies on life course and ecosocial approaches to inform our analysis of research on intergenerational mobility. The life course perspective highlights how individuals’ lives unfold over time and are shaped by time and place (Elder et al., 2003, 2015; Shanahan et al., 2016). Ecosocial perspectives emphasize the role of economic, institutional, and community contexts, which may have both direct and indirect influences on intergenerational mobility (Bronfenbrenner, 1979, 2005; Glass & McAtee, 2006; Krieger, 2011; Parolin et al., 2024; Sharkey, 2016). Life Course Principles Several life course principles are relevant to understanding the process of intergenerational mobility, including lifespan development, historical context, timing of life events, human agency, and linked lives. Lifespan Development The lifespan development principle illustrates how individual-level mobility unfolds across distinct life stages, acknowledging that individual trajectories are shaped by a series of transitions and turning points (Heinz & Marshal, 2003). Transitions such as achieving educational milestones, labor market entry, and marriage act as pivotal points in social and economic trajectories. Focusing on individual trajectories from birth to late adulthood, CH 1 - 17 

PREPUBLICATION COPY – uncorrected proofs researchers can gain a nuanced understanding of the timing and cumulative impact of life events on the risks and opportunities for mobility. Historical Context Considering historical context is vital for understanding mobility dynamics and trends. Prior research has documented how historical conditions including macroeconomic cycles, demographic factors, institutional policies, and neighborhood contexts can impact risks and opportunities for mobility (Chetty et al., 2017; Elder, 1999). Timing of Life Events and Exposures The life course approach considers the specific timing of life events, such as completing education, entering the labor market, or having children, and exposure to macro-level events such as economic downturns or environmental hazards in influencing social and economic outcomes (Elder, 1999; Marshall & Mueller, 2003). The implications of these events for mobility depend on when they are experienced: The same event might have negative consequences at one stage of the life course and be neutral or even provide a positive turning point in other life course stages. Human Agency The principle of human agency acknowledges individuals’ capacity to make choices and exert a degree of control over their lives that shape their life trajectories, even in the face of social and environmental constraints (Hitlin & Elder, 2007). Mechanisms such as personal decisions, educational choices, career transitions, and financial planning may elucidate how individuals experience levels of economic well-being that differ from those of from their family of origin. Linked Lives The principle of linked lives emphasizes the interconnectedness of individual lives within social networks, including family networks in particular, but also networks of friends, colleagues, and members of local and interest-based communities. Based on linked lives, we expect the socioeconomic status of the family of origin to be the baseline against which the upward or downward mobility of adult children is evaluated. The principle of linked lives emphasizes families as the critical unit of analysis for the study of intergenerational mobility: the very concept CH 1 - 18 

PREPUBLICATION COPY – uncorrected proofs of mobility focuses on the link between parents’ resources when individuals were growing and children’s trajectories from early life to adulthood. Temporality Temporality is an essential feature of mobility that describes changes in social and economic statuses across various dimensions of time. The concept of intergenerational mobility captures, by definition, change (or stability) across generations. In addition to intergenerational dynamics, the understanding of mobility needs to consider biographical change as individuals age (i.e., intragenerational mobility) and change across historical time periods, both changes in the historical context and across birth cohorts. Status-Attainment Perspective One variant of the life course approach specifically applied to the understanding of intergenerational mobility is the status-attainment perspective. This perspective focuses on the socioeconomic association between parents and adult children, including critical milestones that mediate the intergenerational association (Blau & Duncan, 1967; Sewell et al., 1969). In its most parsimonious version, the status attainment model considers parents’ education and occupational status as measures of parents’ resources, adult children’s educational attainment and entry to the labor market as mediating factors, and children’s occupational status in adulthood as the outcome to be explained (see Figure 1-3). FIGURE 1-3 Status-attainment model of intergenerational mobility. CH 1 - 19 

PREPUBLICATION COPY – uncorrected proofs This parsimonious model has been substantially updated and enhanced since the 1960s. Some important extensions include adding psychosocial determinants of children’s educational and early occupational attainment, such as the influence of significant others and academic performance (Sewell et al., 1969) and expanding the model from a focus on men to incorporate women and family dynamics such as assortative mating (Beller, 2009; Chadwick & Solon, 2002; Mayer & Lopoo, 2005). The status-attainment model has been appropriately criticized for being overly individualistic and not considering social and institutional determinants and barriers to mobility, including macroeconomic circumstances, institutional regulations, and structural discrimination, among others (Chetty et al., 2014a; Darity, 2005; Horan, 1978; National Research Council [NRC], 2004; Pager & Shepherd, 2008). However, it provides a valuable tool for conceptualizing mobility because it combines inter- and intragenerational components into a life course framework and because it formulates educational attainment as a key mediator linking parents’ and adult children’s socioeconomic status. Life Course–Ecosocial Framework Figure 1-4 presents a life course–ecosocial framework for understanding mobility processes. Intergenerational mobility is defined as the association between the socioeconomic resources of the parental generation and the adult children generation. As described in the introduction, socioeconomic resources can be measured by a variety of resources including earnings, income, occupational status, social class, wealth, and educational attainment. SOCIAL CONTEXT Institutions Conditions Space and place Families Macroeconomic conditions Neighborhoods Education Demographic dynamics Schools Labor market Structural discrimination Community organizations Legal/criminal system Technology Friendship networks Financial Culture Health care CH 1 - 20 

PREPUBLICATION COPY – uncorrected proofs Variation by race and ethnicity, INDIVIDUAL-LEVEL FACTORS gender, nativity, and other social groups Parent’s Adult children’s socioeconomic socioeconomic resources Intergenerational mobility resources over the life course FIGURE 1-4 Life course–ecosocial framework to examine model of intergenerational mobility. Figure 1-4 highlights the role of the social context, represented across three dimensions: institutions, conditions, and space and place. Institutions Institutions represent societal systems with a structured set of rules, norms, and relationships that shape mobility processes in different domains, including family, education, labor market, legal or criminal justice, financial, and health care, among others. In the case of formal institutions, policies (e.g., minimum wage, tax rates, affirmative action, penal codes) shape mobility opportunity by increasing or decreasing key factors mediating the mobility process, such as education, wages and income, housing, and access to health care. The ways in which institutions affect individuals’ risks and opportunities for mobility vary depending on other conditions such as macroeconomic factors, demographic dynamics, and technological development; these conditions in turn shape institutional contexts. For example, the educational system responds to population changes—specifically the size of different cohorts entering the educational system. In turn, the educational system shapes demographic dynamics if, for example, availability of high-quality education affects fertility or immigration decisions. Similarly, family arrangements and dynamics depend on economic conditions, legal incentives and constraints, and population dynamics. Institutions also depend on and shape spatially located dynamics. CH 1 - 21 

PREPUBLICATION COPY – uncorrected proofs Conditions Conditions refer to contextual factors that shape and are shaped by institutional decisions over time. These include economic conditions, such as the decline of manufacturing jobs, rise of service sector, inflation, and unemployment trends that provide opportunities for upward mobility or increase the risk of downward mobility. Structural discrimination refers to barriers restricting access to opportunities, resources, power, and well-being of individuals and social groups based on race and ethnicity; gender; nativity; and other statuses such as sexual orientation, disability, and national origin. Discrimination operates on multiple levels, including cultural orientations; institutions such as the criminal justice system, health care, and workplaces; and interpersonal interactions. We identify structural discrimination as a condition affecting mobility precisely because of its pervasiveness across multiple domains (Brown, 2016; Homan et al., 2024; NRC, 2004; O’Brien et al., 2020; Pager & Shepherd, 2008). Inequalities manifested within institutions can reflect and reinforce discriminatory beliefs, values, and the unequal distribution of resources (Bonilla-Silva, 1997; Brown & Homan 2023; Hicken et al., 2021; Homan et al., 2021; Lee, 2024; Samari et al., 2021). The terms structural racism and structural sexism refer to the systematic exclusion based on race and gender, respectively, from access to resources, power, and opportunities across various societal domains (Brown & Homan, 2024; Homan, 2019; Mills, 1997; Pirtle & Wright, 2021). Similarly, structural xenophobia involves a climate of prejudice and political marginalization of the foreign-born or those in immigrant families (Samari et al., 2021). Demographic dynamics capture changes in the demographic composition of contexts due to demographic behavior such as immigration, fertility, and mortality. For example, immigration patterns have dramatically changed the contexts of various cities, states, and regions of the country over the 20th and 21st centuries in ways that affect the risks and opportunities for mobility among both native- and foreign-born individuals (Abramitzky & Boustan, 2022; National Academies of Sciences, Engineering, and Medicine, 2015; Sharkey, 2013). Other demographic changes, such as the decline in family size due to the postponement or abandonment of family formation (e.g., marriage and childbearing) have implications for mobility through intergenerational processes of child-rearing, educational attainment, and availability of resources (Zaidi & Morgan, 2017). CH 1 - 22 

PREPUBLICATION COPY – uncorrected proofs Technological change has further transformed institutional contexts in education, the labor market, and health care, requiring new knowledge for learning, working, and accessing care in an increasingly automated and digital world (Berger & Engzell, 2022; Galor & Tssidon, 1997; Goldin & Katz, 2008). Finally, cultural forces shape mobility across social groups, including, racial resentment, islamophobia, antisemitism, and anti-immigrant, and anti-LGBTQ sentiment (Bonilla-Silva, 1997; Brown et al., 2025; Everett et al., 2022; Hatzenbuehler, 2016; Homan, 2019; NRC, 2004; Pager & Shepherd, 2008; Samari et al., 2021). For example, literature on immigration has identified “contexts of reception” to describe acceptance or tolerance of newcomers, which may promote or constrain their mobility (National Academies, 2015; Waters, 1990, 2009). Space and Place The spatial dimension of mobility includes the set of people (neighbors, extended family, romantic partners), institutions (schools, libraries, police departments, hospitals), processes (social interactions, community organization, political activity), resources (public spending, community wealth), and hazards (crime, pollutants, water quality) in the environment outside the home, spanning from the immediate residential neighborhood to cities, commuting zones, and regions of the country. Social institutions and broad social conditions bear most directly on individuals’ mobility opportunities according to where individuals live, work, and engage with others in everyday interactions. For example, children living in a low-resource, disadvantaged neighborhood and attending a low-quality school experience few opportunities for upward mobility as adults (Chetty et al., 2014a). Mobility processes also depend on local resources within neighborhoods and schools in the form of job opportunities; highly educated neighbors; and high-quality teachers and advanced placement, and honors courses, among others. Sorting processes might reduce mobility by creating homogeneously wealthy or poor neighborhoods and schools (Grusky et al., 2019; Owens, 2017). Residential and educational segregation results in local social networks that are usually stratified by socioeconomic advantage and that can provide valuable mobility resources in the form of information, advice, mentorship, and connections to educational and work opportunities (Sharkey, 2016). CH 1 - 23 

PREPUBLICATION COPY – uncorrected proofs Individual-Level Factors The impact of contextual factors on mobility is mediated by individual-level attributes and attainments, including individual health, educational attainment, cognitive skills, and noncognitive skills, among others. The committee recognizes the relevance of individual attributes and individual agency in understanding pathways to mobility, but we also recognize that individual outcomes are shaped by institutional and contextual factors over the life course. When it comes to mobility processes, race, ethnicity, gender, and nativity matter. Unequal mobility trajectories along these attributes are well-documented (Abramitzky & Boustan, 2022; Alba, 2023; Beck et al., 2012; Bhattacharya & Mazumder, 2011; Brown, 2016; Chetty et al., 2020, 2024; Choi & Tienda, 2021; Karlson, 2023; National Academies, 2015; O’Brien et al., 2020; Ward, 2023), even if research has faced limitations due to small sample sizes for some groups and limited information on mediators of mobility for these groups in administrative data (Mazumder, 2018). Research has also demonstrated that human capital factors do not exhaust explanations about inequities across groups (Brown, 2016). Some researchers suggest that residual disparities that exist after accounting for resources and behaviors can be attributed to discrimination. However, such a conclusion operates under the untenable assumption that discrimination does not shape economic decisions and the acquisition of human capital in the first place, when research indicates that the opposite is true (Brown, 2012; Pager & Shepherd, 2008). With this evolution in understanding, it is becoming clear that focusing solely on individual factors leads to an incomplete understanding differences in mobility patterns. Research on mobility according to nativity status is another case in point. Immigrant mobility is often viewed through the lens of “immigrant integration,” or the process by which foreign-born populations come to resemble the native-born population along social, economic, and cultural dimensions, driven by socioeconomic improvements among the foreign-born during their life (intragenerational) and across generations. Several large studies have identified the factors that matter most for understanding immigrant integration prospects and the risks and opportunities of mobility, including human capital and other attributes at entry—notably educational attainment, labor market skills, English fluency, mode of entry (visa/legal status), age at arrival, and race; country of origin and parental earning capacity for the children of CH 1 - 24 

PREPUBLICATION COPY – uncorrected proofs immigrants; and the importance of settlement destination and subsequent geographic mobility (Abramitzky & Boustan, 2022; Alba, 2023; Beck et al., 2012; National Academies, 2015). KEY DOMAINS The conceptual framework outlined in Figure 1-4 is not intended to be exhaustive. Rather, it offers one way to organize the many multilevel factors that shape individuals’ chances for mobility over time and the extent to which these factors are embedded and interact with each other. Informed by this conceptual framework, the committee decided to focus on a few key domains, including early life and family; the space and place where people live and work; postsecondary education; and wealth, credit, and debt. Early life is a critical stage of the life course because it is highly sensitive to environmental exposures (Hertzman & Boyce, 2010) and highly consequential for individual long-term developmental, educational, and economic trajectories (Almond & Currie, 2011; Ben- Shlomo & Kuh, 2002; Heckman, 2006), shaping the transmission of inequality across generations (Torche & Nobles, 2024). The phrase space and place is used for key features of local and regional contexts that embed mobility dynamics. The committee’s understanding of spatial processes includes the immediate neighborhood contexts, as well as other relevant units such as cities, commuting zones, states, and regions of the country. Space considers people (neighbors, extended families), institutions (schools, police departments, hospitals), processes (social interactions, community organization), resources (educational spending, employment sources), and hazards (crime, pollutants) that are spatially located. As discussed, multiple institutions shape mobility opportunity. Among these, the committee focused specifically on postsecondary education not because it is the most important point in the emergence of inequities in education and training, but rather because it has received significantly less attention from research and policy compared to elementary and secondary education (i.e., K–12). Additionally, a college degree is an increasingly important determinant of economic well-being (Autor, 2014) and of noneconomic outcomes such as health, crime, family formation, and engagement with the criminal justice system. Finally, the committee’s emphasis on wealth, credit and debt is intended to supplement the historical focus of mobility research on labor market resources (mainly, educational CH 1 - 25 

PREPUBLICATION COPY – uncorrected proofs attainment) and rewards (mainly, earnings) and consider an alternative avenue for the persistence of economic advantage across generations. Research on wealth stratification and mobility is rapidly expanding (e.g., Keister & Moller, 2000; Killewald et al., 2017). This research shows that wealth is different from earnings and other labor market rewards in that (1) it is a stock rather than a flow, (2) it can be used as a buffer in case of economic emergencies, (3) it can be directly transmitted from parents to children via inter vivos transfers and inheritances, and (4) it is more highly concentrated than income or earnings (Killewald et al., 2017; Spilerman, 2000). As such, wealth provides a strong mechanism for the intergenerational persistence of advantage. Similarly, credit and debt are critical determinants of mobility risks and opportunities that do not depend directly on the labor market. For example, access to credit may promote upward mobility by allowing individuals to finance higher education or start a business, while excessive debt might induce downward mobility by causing repayment difficulties and economic insecurity. The factors reviewed in this report are limited by necessity. In particular, the committee did not devote a separate chapter to labor market institutions and dynamics. There is no doubt that labor markets are a key site for understanding determinants of intergenerational mobility. As seen in Figure 1-4, the labor market interacts with many of the other factors and domains in understanding mobility. Understanding how labor market dynamics shape mobility will be a critical piece of a policy-relevant agenda on social and economic mobility. However, based on the available evidence the committee decided to focus on foundational “premarket” factors that feed into the labor market and offer policy-relevant conclusions that can guide the next generation of research. Thus this report offers chapters on a variety of these domains, all of which directly impact labor market resources and opportunities: early life and family and postsecondary education (and the human capital that they facilitate); space and place (and the labor market opportunities that are available to a person based on where they live); and wealth, credit, and debt (as an asset that can be used to support human capital accumulation and labor market success). In this report, discussion about the labor market is addressed in these substantive chapters when appropriate instead of in a stand-alone chapter. An important consideration for this agenda is that much of the existing empirical research base concludes that a good deal of the differences in labor market outcomes seen today—by race, sex, educational attainment, or family income—reflect differences in human, social, and cultural capital that feed up into the labor market (e.g., Chetty et al., 2011, 2020; Deming, 2017; CH 1 - 26 

PREPUBLICATION COPY – uncorrected proofs Hanushek & Woessmann, 2008; Heckman et al., 2006; Neal & Johnson, 1996). Where someone grew up and who is in their social networks; the characteristics of their household and family life; and whether they attained a higher education degree and in which institution all have impacts on labor market outcomes. A case in point is discrimination. In Figure 1-4, discrimination is a contextual factor that can be present in the labor market—and all institutions. While considerable research indicates that discrimination persists in the labor market (Neumark, 2018), much discrimination appears to also operate prior to the market. For example, racial discrimination has large effects on parental human capital, housing and neighborhood, school quality, and access to credit (Pager & Shepherd, 2008). Unequal treatment within the labor market must be addressed and more research can help document this and potentially offer policy levers to address it. However, unequal outcomes will persist in the labor market until discrimination is addressed in all of these premarket domains. In particular, the next generation of policy-relevant research on social and economic mobility needs to better understand the role played by labor market institutions in promoting or inhibiting mobility. Examples include trade unions (see DiNardo & Lee, 2004; Farber et al., 2021; Freeman & Medoff, 1985; LaLonde et al., 1996); labor market policies, such as minimum wages (see Bailey et al., 2021; Card & Krueger, 1995; Congressional Budget Office, 2019; Derenoncourt & Montialoux, 2021; Neumark et al., 2014); and related policy domains that impact labor market participation, such as the affordability of child care or availability of paid family leave (see Morrissey, 2017; Council of Economic Advisors, 2014). Understanding the implications for mobility of the decline of middle-income manufacturing jobs available to lower- educated men is clearly important (Autor & Dorn, 2013). Another factor that must be better understood is the monopsonistic power of firms to set wages below market rates and how such markets impact wage growth and, by extension, mobility (Barr & Roy, 2008). ORGANIZATION OF THE REPORT This chapter has provided basic definitions, contextual information, and motivation for understanding and addressing economic and social mobility in the United States. Chapters 2–5 explore key domains that shape mobility. Chapter 2 focuses on early life and family; Chapter 3 on space and place; Chapter 4 on postsecondary education; and Chapter 5 on wealth, credit, and CH 1 - 27 

PREPUBLICATION COPY – uncorrected proofs debt. In each chapter, the committee assesses the evidence base critically, draws key conclusions regarding the state of knowledge, and makes recommendations for a policy-relevant research agenda. Chapter 6 includes discussion and recommendations regarding the data infrastructure required to support future research on economic and social mobility. Chapter 7 revisits the committee’s key conclusions and recommendations regarding the domains that shape mobility, discussing how they fit together to inform broad policy approaches to increasing economic and social mobility in the United States. CH 1 - 28