Introduction

CENSUS COUNT AND POLITICAL REPRESENTATION

We begin with the political implications of the census because the census, by design, is primarily used for political purposes. The census is decreed in the U.S. Constitution not for social science analysis, but for apportionment of legislative bodies, particularly Congress. Population redistribution based on the 2020 Census resulted in two additional congressional seats in Texas, one additional seat in Colorado, Florida, Montana, North Carolina, and Oregon, and one lost seat each in California, Illinois, Michigan, New York, Ohio, Pennsylvania, and West Virginia. The resulting redistricting requirements exacerbated existing political inequality. Given state legislative practices, Republicans controlled boundaries of 187 congressional districts (43 percent of Congress) and Democrats seventy-five districts (17 percent), with the remainder drawn by independent commissions or being at large districts since the state is represented by a single congressperson (Mekour 2022). This political tilt on redistricting has led to legal battles over the nature of the process—political or racial gerrymandering has been a claim in court cases in Alabama, Alaska, Arkansas, Georgia, Idaho, Illinois, Maryland, Michigan, Nevada, New Jersey, New Mexico, North Carolina, Ohio, and Texas. The accusation is that deliberate undercounts of parts of the population will coalesce with political prerogatives to create the most partisan state congressional delegations possible.

The goal of every census is to count everyone accurately and in the right place. Yet the census does miscount people. The pandemic broke out when the 2020 Census was under way. Pandemic disruptions of operations raised concerns about whether undercounts and overcounts in previous censuses worsened for the 2020 Census. Political meddling in the census by the Donald Trump administration also exacerbated the worries about data quality (Wines 2022). The Census Bureau’s Demographic Analysis, based on vital records and other administrative data, and Post-Enumeration Survey, based on a sample survey, conclude that the counts at the national level are largely accurate and that the 2020 Census overcounted household populations in eight states and undercounted household populations in six others. This is in contrast to estimates of no overcounts and undercounts at the state level in the 2010 Census (Cohn and Passel 2022). For example, Rhode Island, long projected to lose one of the two U.S. congressional seats, was able to keep both because the Rhode Island population was overcounted by about 5 percent, or roughly fifty-five thousand residents, more than enough to avoid losing the seat.

The 2020 Census continued to undercount historically undercounted populations, mainly disadvantaged groups, missing 3 percent of African Americans, 5 percent of Hispanics, and 6 percent of American Indians on reservations (U.S. Census Bureau 2022). The 2020 undercount rates were about the same statistically as in 2010, but increased significantly for Hispanics. Children up to four years old were undercounted by nearly 3 precent. Given that young children are disproportionately racial minorities and immigrants, the undercount of children is another factor in the undercount of immigrants and racial and ethnic minorities. The undercounts matter. Undercounted groups receive fewer federal dollars and less political representation than they are owed.

The article by Lisa Neidert, Reynolds Farley, and Jeffrey Morenoff (2025, this volume, issue 1) provides a review of several Supreme Court litigation cases for undercount and reveals that none of them was successful for adjustment for apportionment and redistricting. They point out further that undercounted states, municipalities, and school districts received fewer federal dollars because these dollars were allocated based on poverty and unemployment, the characteristics mostly common among the undercount population. They then zoom in to Detroit as a case study to demonstrate the undercount of Detroit’s population in 2020, the origins of the undercount and its financial impact. The Census 2020 showed a loss of thirty-one thousand residents in one year and a loss of about fifty thousand housing units. A virtual audit conducted by the city afterward found that the census showed consistently lower occupancy rates and the Census Bureau missed about 12 percent of the residential housing units. Omissions were more pronounced in the blocks with lower self-response rates. This study reveals that the list used during the census operation consisted of far fewer housing units than the master address file developed before the census and accepted by the Census Bureau. The authors question whether the undercount was due to erroneous omissions of legitimate housing units or misclassification of occupied housing units as vacant. The undercount, concentrated in more disadvantaged neighborhoods, deals a serious financial blow to Detroit—the city government may be losing about $5 million in state revenue sharing each year during the 2020s.¹ The census is typically thought of as a demographic survey instrument used to describe American society. We begin this volume, however, by emphasizing the political economy at the heart of the census and its direct impact on the American population.

EMERGENCE OF MULTIRACIAL POPULATIONS

The question on race has been included starting from the very first census, in 1790. Over time, racial classification of Americans has undergone tremendous change, reflecting increasing racial and ethnic diversity in the population. The 2020 Census asked two questions to collect the races and ethnicities of the U.S. population. The first is Hispanic or Latino origin, categorized into Not Hispanic, Latino, or Spanish origin; Mexican, Mexican American, Chicano; Puerto Rican; Cuban; or another Hispanic, Latino, or Spanish origin. The second is race, categorized into white, black or African American, American Indian or Alaska Native, Asian (specifically, Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, and so on), Native Hawaiian and Pacific Islander, and Some Other Race. Combining the two questions, the most prevalent racial or ethnic group was the non-Hispanic white population. It accounted for 58 percent of the population in 2020, a decline from 64 percent in 2010 (figure 1). Meanwhile, Hispanics and non-Hispanic Asians increased in prevalence over the decade. Applying the diversity index measure, Eric Jensen and colleagues (2021) find that the likelihood that two people chosen at random in the United States are from different racial or ethnic groups increased from 55 percent in 2010 to 61 percent in 2020.

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Figure 1.

Percent Distribution by Race-Ethnicity

Source: Authors’ calculations using U.S. Census Bureau 2023.

In 2000, the Census Bureau started to identify multiracial populations, that is, people who identify as members of two or more races. About 6.8 million people, 2.4 percent of the U.S. population, reported two or more races in 2000 (Jones and Bullock 2012). In 2010, as shown in figure 1, 2.9 percent reported two or more races (1.9 percent non-Hispanic and two or more races and 1 percent Hispanic and two or more races). In 2020, the share and size of the multiracial population increased substantially: 33.8 million Americans reported multiple race membership, and about 4 percent now identify as non-Hispanic multiracial and 6 percent Hispanic multiracial (figure 1). This sharp rise is unlikely attributable only to increases in children born to people in interracial relationships.

Who selected two or more races? Among those who reported two or more races, the largest combinations were white and Some Other Race, followed by white and American Indian and Alaska Native, white and black, white and Asian, and black and Some Other Race. Notably, the increase in multiracial populations was largely due to the increase in the Some Other Race population. The Hispanic or non-Hispanic Some Other Race population alone increased by 46 percent, from 6 percent of the total population in 2010 to 8 percent in 2020. The Some Other Race alone or in combination population increased drastically, by 733 percent over the same period (Jones et al. 2021). The Census Bureau attributed the rapid increase to the design improvement of the Hispanic and race questions. Indeed, the improved design drastically increased the number of Hispanics in the category of Some Other Race. In 1990, the last decennial census that allowed respondents to mark only one race, about 50 percent of the Hispanics identified white and less than half marked race of Other—a category similar to Some Other Race today. In 2010, when respondents were allowed to mark two or more races, the race question included a checkbox for white but left no room for detailed ethnicity or national origin answers for the white category. In 2020, for those who checked white, the questionnaire adds “Print, for example, German, Irish, English, Italian, Lebanese, Egyptian, etc.” These examples did not include any Hispanic group, which may have discouraged Hispanic whites from checking white alone and caused the decline in the Hispanic white alone population. As a result, over the decade between 2010 and 2020, the number of Hispanics who identified as white alone declined by 53 percent; more Hispanics identified Some Other Race alone, an increase of 42 percent; and Hispanics, identified as white, were much more likely to check Some Other Race simultaneously (Jones et al. 2021). These dramatic changes reveal the rapid change in classifications may sometimes be a product of survey design better matching personal identification.

In this volume, Ilana Ventura and René Flores (2025, issue 1) offer strong evidence of the role the design change plays in the dramatic rise of multiracial populations. They compare data from American Community Survey for 2000, 2010, 2020, and 2021, exploiting the design change for the 2020 and 2021 ACS questionnaires. They then compare the results with data from Current Population Survey for 2005, 2010, 2020, and 2021, none of which included a design change. The analysis shows that multiracial populations increased in the 2010s potentially because of increases in interracial fertility, especially among Asian and black Americans, but the increase in multiracial populations in the 2010s was too large to be explained by the natural growth alone, especially for Hispanics. In fact, they reveal that the increase for Hispanics can mostly be attributable to a large growth in the classification of Some Other Race—a result of design change. Overall, the design change doubled the number of multiracial people among the U.S. population as a whole and increased multiracial people by a factor of seven among Hispanics in the 2010s.

As Ventura and Flores show, multiracial populations did increase net of the design change, but by a relatively smaller amount. Several factors contribute to this difference. First, interracial marriage or unions continued to increase. Since 1967, the year the U.S. Supreme Court in the Loving v. Virginia case lifted the ban of interracial marriage throughout the country, the percentage of newlyweds who were intermarried jumped from 3 percent then to 17 percent in 2015 (Livingston and Brown 2017). Children born to interracially married couples grew rapidly as a result. Children born to interracial parents who were cohabiting or not in unions also increased. Based on the birth registrations from National Vital Statistics System of National Center for Health Statistics, Zhenchao Qian and Yifan Shen (2020) calculate that the births born to interracial parents, regardless of whether they were married, cohabiting, or single, increased from 10 percent in 2000 to 14 percent in 2016.

Second, not every multiracial person identifies with two or more races. Among children up to seventeen years old between 2008 and 2014, 72 percent of those born to black-white couples checked both white and black, but 16 percent marked only black and 12 percent only white; 48 percent of those born to American Indian–white couples checked both American Indian and white, but 23 percent marked only American Indian and 28 percent only white; 74 percent of those born to Asian-white couples checked both one Asian ethnic category and white, but 8 percent marked only Asian and 18 percent only white; and 60 percent of those born to Hispanic–non-Hispanic white couples checked a Hispanic category and non-Hispanic white, but 15 percent marked only a Hispanic category and 25 percent marked only non-Hispanic white (Lichter and Qian 2018). Racial classifications of children born to interracial couples depend on race, gender, and nativity of the minority partner, and couples’ educational attainment, among others (Qian 2004; Lee and Bean 2004). A continuous rise in interracial marriage and subsequent growth in multiracial populations may prompt more children born to interracial parents to report two or more races.

Third, are Americans rethinking their racial identities? Genetic ancestry tests have become popular in recent years, but few test takers fully accept what the tests reveal (Roth, Côté, and Eastmond 2022). In fact, testing often reinforces race privilege among those who already experience it (Roth and Ivemark 2018). White test takers do not necessarily seek to promote racial diversity but some may desire a bit of something nonwhite, a cultural cachet often associated with beauty, exoticism, and a marginal degree of social distinctiveness (Ferla 2023). Genetic ancestry tests, which accelerated in their use and given large technological change and lower costs of ancestry testing in the 2010s, may increase racial awareness and reveal surprising ancestral backgrounds, but they do not necessarily contribute to the increase in multiracial populations.

Fourth, America has changed from a mainly biracial society to a more diverse one (Alba 2020). Furthermore, race in Latin America is more fluidly defined. Immigrants from Latin America can be white, black, Asian, Amerindian, or some combination. In addition, recent cohorts of immigrants are significantly more likely to originate from Africa, Asia, the Caribbean, and Latin America. Immigration along with interracial marriage continues to expand the levels and diversity of multiracial populations in America.

Changes in family structures, schools, neighborhoods, workplaces, and friendship networks may prompt individuals to think more about their racial identities. They may change their racial classifications over their life course. In this volume, John Anders, Mary Campbell, Craig Carpenter, and Luna Chandna (2025, issue 1) underscore racial fluidity by linking the individuals appeared in both 2010 Census microdata and the 2010–2020 American Community Surveys. They restrict the sample to adults aged twenty-five or older at the 2010 Census, old enough to maximize the likelihood that respondents themselves filled out the questionnaires. As a result, changes in racial classification for an individual over time could reflect potential changes in social context over the life course (Doyle and Kao 2007; Agadjanian 2022). Anders and his colleagues find that ethnoracial identity remains very stable among non-Hispanic whites, with over 98 percent remaining non-Hispanic white over time. In contrast, nearly 7 percent of the individuals chose a different ethnoracial identity in a later ACS than in the 2010 Census. This means that disproportionately more nonwhites (including Hispanic nonwhites) change their racial classifications. For example, nearly half of the foreign-born Hispanics who reported two or more races in the 2010 Census identified as only Hispanic white in a later ACS. Hispanics, a panethnic and racially diverse group, are highly fluid in racial identity. Anders and his colleagues report that younger people are more likely to change racial identities than their older counterparts, in part because of greater concentrations of ethnoracial minorities among the younger population. Noticeably, ethnoracial changes are also more likely to occur among immigrants and individuals with low socioeconomic status, suggesting potential confusion of racial identities among the disadvantaged populations. This issue is likely to be less serious in the future as the Office of Management and Budget released the new standards in March 2024 for collecting information on race and ethnicity (Statistical Policy Directive 15). It now has only a single question, asking respondents to select as many options as apply to how they identify. The question includes the following seven race or ethnicity categories: American Indian or Alaska Native, Asian, black or African American, Hispanic or Latino, Middle Eastern or North African, Native Hawaiian or Pacific Islander, and white.

Individuals who report a multiracial identity are diverse in racial combination, but most of them claim a white background. Among the multiracial births in 2016, 82 percent had black-white, American Indian–white, Asian American–white, or Hispanic-white parents (Qian and Shen 2020). The dramatic growth in the multiracial populations that are partly white may have played an important role in the declining share of the non-Hispanic white alone population (Alba 2020). Multiracial populations are too heterogeneous to be considered as one racial group. Currently, the Census Bureau classifies multiracial populations as not white. However, multiracials, many of whom are multiracial whites, are different from members of single-race minorities (Alba, Beck, and Basaran Sahin 2018). They are diverse but on average more advantaged in parental education, income, and residential patterns than single-race minorities (Alba 2020). Indeed, multiracial populations challenge the conceptions and statistical accounting of racial classifications and will have important social and political consequences over time. We highlight here how these categories continue to change as our racial constructions ebb and flow to reflect new realities and nuance in racial formations.

INEQUALITY IN HOUSING, RESIDENCE, AND ACTIVITY SPACE

The Great Recession in the late 2000s witnessed the continuation of a long-term decline in long-distance migration and highlighted a unique increase in local moves within metropolitan areas (Stoll 2014). The increases in short-distance moves were attributable to high levels of unemployment and home foreclosures during the Great Recession. The local movers were likely to be young, less educated, and black and Latino, to live below the poverty line, and to have difficulties paying rents or staying current with mortgage payments. Homeownership rates fell sharply as a result. In this volume, Dowell Myers, Hyojung Lee, and JungHo Park (2025, issue 1) explore the trend and recovery in homeownership after the Great Recession. They highlight how changing cohort sizes of young adults over the 2010s complicate the recovery of housing markets. Being mindful that the homeownership rate is a prevalence measure, an accumulated status from the past, including homes owned by those who bought them many years ago, they focus on young adults, who are mostly current or recent buyers, to capture current housing preferences. Myers and his colleagues show that young adults who entered housing markets varied in population size because of different cohort sizes at birth among baby boomers, Generation X, and millennials. The authors reveal that fewer people coming of age in the late 2000s and the early 2010s, because of smaller birth cohorts of the late baby boomers and Generation X, created the narrative for lower homeownership preferences and discouraged planning for more homes or appropriate homes for the cohort of millennials, who are about one-third larger than Generation X by total population size. They show that oscillating birth cohorts, along with housing bubbles, restraints on mortgage applications, and pullback in housing construction during and following the Great Recession (2006–2016), created pent-up housing demand. Homeownership rates began to rise in 2017, but housing supply fell sharply behind the demand, drove acute housing shortages, and resulted in affordability problems. Young adults with greater economic resources and whites experienced substantially stronger recovery of homeownership than those with fewer economic resources and those from disadvantaged minority groups. Those with greater wealth and higher incomes were better able to secure housing despite the general increase in prices.

Homeownership continues to contribute to socioeconomic and racial residential sorting because individuals and families in the same neighborhoods share similar attributes (Logan and Parman 2017). Spatial differences in housing prices and homeownership rise and income segregation by neighborhood escalates (Bischoff and Reardon 2014). The influx of immigrants in recent years has increased racial and ethnic diversity in neighborhoods and communities. In 2021, number of immigrants reached forty-five million, accounting for about 14 percent of the total population (Migration Policy Institute 2023). Among them, 52 percent were from the Americas, 31 percent from Asia, and 6 percent from Africa. Not only were more immigrants from non-European countries but also more children were born on average to first-generation immigrants than to the native born (Camarota and Zeigler 2021). The number of children born to diverse immigrants has also contributed to a significant increase in the population of racial and ethnic minorities, especially at younger ages (Parrado 2011).

Immigrants have had a large impact on neighborhood residential patterns. Nima Dahir (2025, this volume, issue 1) focuses on how black immigrants, a group that experienced strong growth in recent decades, influence changes in black neighborhoods. Analyzing data from the 2000 Census and ACS from 2008 to 2012 and 2016 to 2020, she explores how neighborhood influxes of black immigrants are related to subsequent in- or out-migration of native-born blacks, whites, and ethnoracial minorities. Highlighting the importance of neighborhood ethnoracial heterogeneity at the baseline in 2000, Dahir shows that only in neighborhoods in which native-born blacks were a majority in the baseline would an increase in the black immigrant population trigger black native out-migration and white in-migration. The analysis also shows that black immigrants play a buffering role in a white neighborhood, preceding the arrival of native-born blacks, but have a reverse buffering role in black neighborhoods, preceding the arrival of whites. That is, black immigrants in general are a signal of neighborhood racial composition change. Dahir explores the potential mechanisms of what happens when black immigrants move into a neighborhood: making the neighborhoods less affordable to trigger an exit of blacks or moving into the neighborhoods where rent and home value began to grow. The findings underscore the unique role of black immigrants, a particular social position, in shaping neighborhood change and attenuating spatial inequality among ethnoracial groups.

The census has allowed us to learn a great deal about residential and income segregation. These are both important aspects of American society, but changes in technology and society have allowed people to interact in a variety of new ways. By the time of the 2020 Census, more than 90 percent of Americans owned some type of cellular phone, whereas in 2010 only 30 percent did (Wike et al. 2022). This rapid change in communication technology also comes with another benefit—the ability to track people as they move across space. Because cell phones are now commonly a part of the everyday wardrobe (“wallet, keys, phone”) we literally travel with a geographic system that can locate us performing our daily tasks, both work and recreationally.

Next, Siwei Cheng, Yongjun Zhang, and Jenna Shaw (2025, this volume, issue 1) offer an exciting perspective on another dimension of segregation by leveraging this new technology that the vast majority of Americans now use. Exploiting cell phone data, they determine where people live and where they work and play as a function of where they spend their time. These patterns reflect our daily routines, and they link our home locations (where we spend our time sleeping) to the other locations we visit through the course of our days. They note several surprising facts about American interactions across class and race (which they can proxy for with the composition of our home communities) beyond the home. First, they find, rather intuitively, that places of work and activities are significantly less segregated than neighborhoods. Americans truly do work and play in diverse environments. At the same time, the level of this interaction varies significantly over cities: although the trend is generally true, some cities have much larger baseline levels of interactions. Second, they find that black and white households vary in their levels of isolation in these activity spaces across the United States. In general, in the Northeast and Midwest, black and white citizens are more isolated in their activity spaces than in other parts of the country. Even though residential segregation has declined nationwide in the past forty years, this activity-level analysis of segregation reveals a new way in which racial distinctions and isolation occur. Third, they find that city-level inequality is related to the isolation of activity spaces nationwide. Unlike the high levels of racial isolation in the Northeast and Midwest, the isolation of the wealthiest and poorest in activity spaces is pronounced nationwide. This implies that not only do the rich and poor live separately, but the possibility of their social interactions with each other is also more limited than we may have anticipated in metropolitan areas. With the distinction of American cities as cosmopolitan spaces, they also retain a great deal of class distinctions that carry over from home to work and even recreation.

GENDER AND RACIAL INEQUALITY IN EDUCATION, TIME USE, AND EMPLOYMENT

Over the course of the twentieth century, the largest changes in labor-force participation, occupation, and earnings were for women (Goldin 2021). Beginning from a relatively small share of total employment, by the time of the 2010 Census, women made up more of the labor market than at any other time in history. Among younger women in large cities, they outearned their male peers, which led to concerns about the prospects of marriage for women who faced a relative dearth of men of marriageable age with similar credentials (Fry 2022; Dean 2022). Among young women, nearly half have a bachelor’s degree, which only slightly more than a third of similarly aged men have one (Reeves and Smith 2021). Other features of female-dominated employment led it to be less sensitive to the business cycle than men’s employment. First, women were overrepresented in service fields that did not contain cyclical demand, such as education and health. Second, women were in lower-paid occupations relative to men, which tended to have greater security of employment over the business cycle. Third, women valued flexibility benefits of jobs more than men did, allowing them to meet private demands for their time in a manner consistent with their desired labor supply.

Behind this is the gender gap in college completion, where women have outnumbered men in bachelor’s degrees since the 1980s. Given the financial crisis and the pandemic, there were reasons to believe that this situation may change. First, the declining value of the college degree may lead to lower rates of women’s completion than previously. Second, the pandemic-induced recession, unlike those that came before it, predominantly affected previously safe employment in services, education, and health, precisely the fields in which women were overrepresented (Fabrizio, Gomes, and Tavares 2021). Third, the growing marketing and proliferation off credentials, especially those by for-profit education providers, which targeted women (Cottom 2017). Fourth, student debt has increased dramatically, and given the persistent gender differences in earnings, the returns to college completion for women have declined (American Association of University Women 2021).

Did the shock of the pandemic and other secular changes in the labor-market change the trends in the tilt of bachelor’s degrees toward women? Claudia Buchmann, Rachel Dwyer, and Man Yao (2025, this volume, issue 1) seek to answer this question. Using administrative survey data, including the census and the National Center for Education Statistics, they find a number of interesting facts regarding the gender of higher education in the United States. The gender gap in bachelor’s degree attainment has stabilized. Although a gap in education completion remains, it has not changed in the last decade. What has continued to evolve is the gender gap in degrees above the bachelor level, particularly professional degrees. Buchmann and colleagues argue that this acceleration could be partly driven by the growth of for-profit educational degrees, which may exacerbate student loan inequality by gender. In addition, the returns to advanced degrees where women outnumber men has declined over time, which could become another area of increasing gender inequality in the future.

America has become more racially diverse as a result of the continuous influx of immigration from Latin America and Asia. Yet America’s racial minorities have long been denied the rights to white Americans. Slavery and Jim Crow segregation for blacks, status of “aliens ineligible for citizenship” for Asians, coerced relocation from tribal lands to reservations for American Indians, and becoming American citizens through conquest for Mexicans, Puerto Ricans, and Native Hawaiians are a few examples (Harrison and Bennett 1995). With various barriers and limited opportunities for upward mobility for racial minorities, racial diversity was synonymous with racial inequality. In the era of racial reckoning in the 2010s, bookended by the Great Recession and the pandemic, how did blacks, Latinos, Asian Americans, or other racial groups fare relative to whites across a broad range of social, economic, and political dimensions? Three articles in this volume provide some of the answers.

Next, Sarah James and Elizabeth Wrigley-Field (2025, this volume, issue 1) analyze data from American Time Use Survey (2003–2019) and compare daily time use among white, black, Latino, and Asian people. They explore how ethnoracial minorities are constrained in their choices to spend their time in various daily activities. They find that white people have the most pleasant elective leisure activities; ethnoracial minorities, especially Asians, report higher levels of daily activities that are rated unpleasant than whites; and blacks spend the most time alone and the most time doing affectively neutral activities, such as watching television. James and Wrigley-Field highlight several pathways including employment, place of residence, people to spend time with, administrative burdens, and psychosocial stress that could lead to such racial disparities in time use and quality of life in the United States.

Before the pandemic, the increasing inequality reflected not only the growth of income among the top 20 percent of the income distribution but also the stagnant wages at the bottom. Indeed, job growth in the 2010s was concentrated in the lower half. Although jobs proliferated, jobs with higher levels of pay did not. These same occupations in the retail, service, and health-care sectors became seriously constrained during the pandemic, and the recovery in the same industries saw extreme wage growth in the lower end of the distribution. As the labor market tightened and unionization increased (and saw larger gains in wages for union members than several previous decades) the labor market after 2020 looked remarkably different from the one that existed just a few years earlier.

One aspect of the low-wage labor market is the extreme volatility of work schedules. Employees in this sector, which is different from the gig economy, where volatility in labor supply drives hours of work, are given highly variable schedules. Variability is not only in schedules but also in hours of pay. This leads to the simultaneous feature of low pay and volatile pay for a significant share of the low-wage labor market (Guyot and Reeves 2020). Even more, these jobs are disproportionately held by women and racial minorities, and the volatility of the low-wage labor market may play a role in enduring inequality.

Julie Cai and Marybeth Mattingly (2025, this volume, issue 1) explore this topic in two ways. They follow a cohort of workers over a four-month period to explore both their work schedules and their wages. They find that work-hour volatility was relatively common and steady until the pandemic, when overall volatility spiked by nearly 50 percent. Nearly all of this increase was for workers who had already experienced volatility before the pandemic. Black and Latino workers had significantly higher baseline volatility before the pandemic, and the subsequent increase during the pandemic was relatively more modest given their higher starting level. Although volatility for workers declined to pre-pandemic levels by 2022 overall, for Asian workers it remained higher. For workers working the same average number of hours, working in more volatile work hours settings is related to lower wages. Additionally, a racial disparity emerges within volatile hours themselves. Despite consistent employment, black workers earn significantly less than white workers when their work hours are volatile. This relationship became even more intense for black workers during the Great Recession and the pandemic. As the labor market continues to evolve into the next decade, the precarity of low-wage employment continues to leave low-wage workers with higher uncertainty.

One common feature of contemporary labor markets is that job tenure and career have been redefined. Whereas previous generations of Americans could expect to work in a specific occupation for the majority of their working lives, contemporary labor-market observers note that workers in today’s labor market will have several careers by the time they retire (Broom 2023). This affects not only the way workers train and search for jobs, but also the expectations that workers have about employment more generally. Although we know a great deal about wages and work hours, we know much less about how long people stay in their jobs (job duration), how job duration changes over time, and how it varies among groups in the population. Searching for new employment, either from dissatisfaction with current employment or driven by the loss of a job, is costly. At the same time, periods of significant technological and economic change may give rise to new industries (and cause severe declines in others) that would be related to population level changes in job duration over time. Given the macroeconomic experiences of the Great Recession and the “creative destruction” of the internet and other technological changes, knowing how American job duration changes is important for understanding how our economy has changed.

Using the concept of expected job duration, how long one expects to hold a particular job with a given employer, Michael Lachanski (2025, this volume, issue 1) uses life table techniques to analyze changes in job duration for the past twenty-five years. Indeed, this is the first research on job duration in fifteen years. Drawing on the IPUMS Current Population Survey Job Tenure Supplement and the U.S. Census Bureau’s Quarterly Workforce Indicators and nonstable population theory, Lachanski uses the number of new job starts and stable employment positions to estimate the expected duration of employment in the private sector in two-year increments from 1996 to 2020. The main highline finding is that employment duration overall has been remarkably stable over this period. If anything, despite the rhetoric that employment has become more detached than in the past, Lachanski finds that expected tenure has increased from 1996 to 2020. When separating these effects by sex and race, he finds that women and men have similar durations of employment, which stands somewhat in contrast to the idea that women’s employment is less cyclical than men’s. By race, black workers have persistently lower employment durations than white workers, but not when conditioning on those who have been employed for one year. Latino workers have slightly longer durations over the entire period, both at initial job starts and conditional on being employed for a year. Lachanski’s exclusion of public-sector employment may be one reason for these findings, as women and black workers are overrepresented in public employment, which tends to be more stable than private-sector employment. Similarly, the data restrict us to those who are not self-employed, so the transitions to and between the gig economy are not observed in the data. Even with this caveat, the findings here challenge the narrative that employer-employee relationship duration has changed significantly over time.

LIVING ARRANGEMENTS

Vivek Murthy, surgeon general of the United States, warned in 2023 that Americans have become increasingly lonely and isolated. Lack of social connections is taking a toll on Americans’ mental and physical health. Over time, more Americans are unmarried: among adults aged eighteen and older, the percentage living with a spouse declined from 56 percent in 2001 to 50 percent in 2021 (U.S. Census Bureau 2021). Unmarried cohabitation, a less stable relationship than marriage, continued to rise for this population, from 4 percent to 8 percent over the same period. Given the trends in marital stability and the increasing educational gradient with health, knowing who lives alone and with others plays a critical role in helping us see how communities and households are changing. Popular press such as Bowling Alone by Robert Putnam have argued that America’s political dilemmas may have their roots in the increasing rate to which we live separately from each other, as this is seen as a key input to civic engagement, public political participation, and prosocial behavior. The pandemic revealed that the density of housing in the United States varied significantly by race and education, which had implications for the prevalence of COVID-19 among certain populations unable to engage in social distancing given the density of their communities (Yang, Choi, and Sun 2020; Zhai et al. 2023). However, despite the pandemic, the proportion of adults living alone barely budged, from 14 percent in 2001 to 15 percent in 2021. Lonely adults do not necessarily live alone and may not be able to afford living alone. They may live with parents, relatives, or nonrelatives. Social distancing and isolation during the pandemic may have exacerbated loneliness regardless of living arrangement.

The census is critical in determining who lives with whom. Household size and composition have always been important in census measurement. Intergenerational, nuclear, and single-person households all tell us different features about American families, economy, and society. Let us now focus on young adults age twenty to thirty-four, the group that have experienced most changes in living arrangement. Using data from the decennial censuses from 1980 to 2000 along with ACS 2008–2021 data, figure 2 presents this young population’s living arrangement: married, cohabiting, living alone, living with parents, living with other relatives, living with nonrelatives, in group quarters, and others. The proportion of those married declined sharply from 53 percent in 1980 to 27 percent between 2017 and 2021; meanwhile, the proportion cohabiting, unavailable in 1980, increased to 10 percent in the same period. The median age at first marriage reached an all-time high, twenty-eight and thirty, respectively, for women and men in 2023 (U.S. Census Bureau 2024). Marriage delay and retreat among young people was common. Although cohabitation, a shorter and more unstable relationship, grew, it did not offset the decline of marriage. Consequently, declines in unions were largely responsible for rising levels of singlehood. Although fewer Americans get married, most still expect to marry. In 2014, 76 percent of the Americans expected to marry at some point (Smock and Schwartz 2020). In the end, marriage has become more attached to socioeconomic status and a symbol of economic success (Gibson-Davis, Edin, and McLanahan 2005; Edin and Kefalas 2005). Whether to marry, when to marry, and how long to marry are increasingly divergent across racial-ethnic and social class lines. Men and women with economic resources are more likely to marry and stay married than their counterparts.

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Figure 2.

Living Arrangements Among People Age Twenty to Thirty-Four

Source: Authors’ calculations using Ruggles et al. 2024.

Despite marriage retreat and rising singlehood, the proportion of young adults living alone in the past four decades changed little, about 10 percent (see figure 2). This trend actually holds for all adults. In this volume, Hyunjoon Park, Matthew Sheen, and Paula Clark (2025, issue 2) explore trends in living alone among adults aged twenty-five to seventy-four. Although living alone was relatively uncommon in the middle of the twentieth century, when fewer than 15 percent of all households were single person, today more than 25 percent of all households are single persons living alone. Analyzing data from the censuses from 1980 to 2000 and ACS from 2010 to 2019 reveals several facts about the trend of living single. Stability in the share of American households living alone has been remarkable. Despite the public discourse that the share of single-person households may have social, economic, and political consequences, the authors show only modest change, at best, in the proportion living alone. More surprising, marriage appears to play a limited role in the stability of the trend. Even though the proportion of never-married men and women in prime age groups has increased, the share of those who live alone has declined, offsetting the increase in the share of nonmarried individuals in the same age group. That is, the link between marriage and cohabitation is weakening, which leaves us with a more nuanced story about where the trend in single living is coming from. Indeed, the only noticeable change in living alone over this period is older men aged sixty-five to seventy-four, and this is partly offset by declines in women in the same age group living alone. Population aging and longevity has changed the composition but not the population share of single-person households in the United States.

One notable finding from figure 2 is that single young adults became increasingly likely to live with their parents, from 17 percent in 1980 to 27 percent in the 2017 to 2021 period. Extended singlehood prolongs the emerging adulthood during which young people explore more and long, from romantic or cohabiting partnerships, in or out of college, to various work options and job episodes (Arnett 2004). Such frequent explorations introduce uncertainties and financial difficulties (Qian 2012). Intensified by the Great Recession, the pandemic, and attendant housing shortages and rising housing and rental prices, they often end up living with parents. After all, young adults living with parents had less education, lower income, and higher rates of unemployment than those who lived alone or were married (based on our calculations, results not shown). Disadvantaged young adults have to rely on their parents when they face tough setbacks in relationships, schools, or jobs.

Lucie Schmidt, Lara Shore-Sheppard, and Tara Watson (2025, this volume, issue 2) offer a unique perspective to explore the living arrangements of older Americans. Older Americans are more likely to live alone than any other elderly group in the world. However, differences by race and gender in the extent to which people live alone are evident. Highly educated older adults are more likely to own homes, access to wealth, and live independently than others, a phenomenon described as aging in place (Anderson 2024). This raises a related question: who among the older adults tend to live with children or grandchildren? The discussion on living arrangements of young adults above offers some clues. Schmidt and her colleagues provide a clear picture. They highlight racial and socioeconomic differences in patterns of older adults living with children. Older adults step in when children and grandchildren are in economic insecurity. Among older people between sixty-five and ninety, whites have much lower levels of coresidence with children than blacks and Latinos. The reason is mostly economic. Economically vulnerable older people are more likely to live with children to pool limited resources. Their analyses show that older people tend to live with their children and grandchildren and form multigenerational living if safety net policies are less generous, housing costs are higher, or older people are Latino, Asian, or foreign born. In contrast, older people tend to live with only grandchildren and form skip-generational living if female incarceration rates are higher or older people are toward the bottom of the predicted income distribution. It is clear that older people chip in and help when their children are incarcerated or their children and grandchildren are in dire economic need. Older people living with children are disproportionately racial minorities and at the bottom of the socioeconomic ladder.

Once again, black-white differences in living arrangements are strong, the same as seen along the socioeconomic lines. Blacks are much less likely to marry than whites and married blacks are more likely to divorce than their white counterparts. Black children are more likely to live with their mothers or grandmothers than white children. Using data from the Panel Study of Income Dynamics, Christina Cross (2019) shows that black children spent 55 percent of their childhood with a single mother, relative to 13 percent for white children and 19 percent for Hispanic. Such sharp differences can be traced at least in part to structural racism (Pager and Shepherd 2008; Rackin and Gibson-Davis 2018; Baker and O’Connell 2022). Structural disadvantages often lead to unstable and short-term relationships, which “may launch chains of disadvantage in relationships throughout the life course that then have cumulative effects on health over time” (Cherlin 2010; Umberson et al. 2014, 20).

THE EXPANDING CONCEPTS OF MARRIAGE, FAMILY, AND GENDER

Another major milestone in American families came in 2015 when the Supreme Court ruled in favor of marriage equality. The legalization of same-sex marriages in this landmark decision led to a rapid rise in number of same-sex households. In 2021, some 1.2 million same-sex couple households lived in the United States, 710,000 married and 500,000 unmarried (Scherer 2022). This doubles the count of same-sex households in 2010. However, data on same-sex individuals and households are sparse. Soon after the Supreme Court in 2020 held that the 1964 Civil Rights Title VII’s prohibition on employment discrimination based on sex encompasses discrimination based on sexual orientation and gender identity, Congress passed the LGBTQ+ Data Inclusion Act in 2022, which would require federal surveys to include data collection on sexual orientation, gender identity, and other sex characteristics on a voluntary basis. This requirement will fill the data void and help advance equity of the LGBTQ+ population. The Household Pulse Survey in 2021 marked the first time a Census Bureau sponsored survey included questions which identified the LGBTQ+ population. The HPS, which tracked American experiences during the pandemic, revealed the socioeconomic inequities this population faced. It shows that LGBTQ+ respondents exhibit more with anxiety and depressive symptoms than their counterparts do (Marlay, File, and Scherer 2022). The HPS builds the foundation for increased data collection of the LGBTQ+ population in future nationally representative surveys.

Gender minorities, individuals whose current gender does not align with their sex assigned at birth, are an understudied but a sizable population in the United States. In this volume, Christopher Carpenter, Maxine Lee, and Laura Nettuno (2025, issue 2) analyze data from HPS 2021–2023 and offer the first evidence on marital status and family outcomes of transgender and other gender minority populations. Their analysis shows that gender minorities are younger, less likely to be heterosexual, much less likely to be married, and more likely to have a spouse who has passed away than their cisgender counterparts. In addition, non-cisgender people are less likely than their cisgender women counterparts to have children in the household and more likely to live in households with more adults than their cisgender counterparts. Given that unions and marriages offer the social, emotional, and financial support for most adults, non-cisgender people’s higher levels of living alone, divorce, and widowhood, along with significant social stigma, discrimination, harassment, and violence, may indicate higher levels of challenge and loneliness.

RURAL AMERICA

The 2016 presidential election brought renewed focus to rural areas in the United States. Observers noted that previous administrations had paid relatively little attention to rural communities, which tended to be overlooked and considered stagnant places (Love and Loh 2020). The surprising political power of rural voters caused social scientists to begin exploring rural areas again, but some researchers had long been committed to understanding changes in rural communities over the last several decades (Lichter and Brown 2011). Even though the popular imagination and media narrative paint rural America as racially and class homogeneous, essentially the white working class, rural communities are actually extremely diverse. In fact, the United States puts rural communities into any of several categories: graying America, Hispanic centers, Latter-Day Saints enclaves, aging farmlands, Native American lands, evangelical hubs, working-class country, rural Middle America, and African American South (Ajilore and Willingham 2020). The names of these locations give some clues about the baseline diversity of rural communities in the United States. They are defined both by the relative aging, occupational structure, and racial-ethnic composition. They also differ extensively economically. Between 2010 and 2016, for example, graying America and Hispanic centers added more than sixteen thousand new businesses in their communities while rural Middle America and African American South lost more than that over the same period. They also have different socioeconomic outcomes. Recent research shows that economic mobility is not perfectly mapped onto these measures of economic activity. Even though both the African American South and rural Middle America have similar trajectories of business losses, they have vastly different economic mobility rates. Of all rural communities, the African American South has the lowest rate of upward intergenerational mobility, and rural Middle America has a mobility rate well above the mean for rural communities (Ajilore and Willingham 2020). Any focus on rural communities must account for their inherent diversity.

In this volume, Daniel Lichter and Kenneth Johnson (2025, issue 1) provide an in-depth analysis of the transitions and trajectories of rural communities over the last few decades. By 2020, fewer than 15 percent of all Americans lived in nonmetro areas. How are these communities alike and different? Using a 4D (depopulation, deaths, diversity, and deprivation) approach to the issue, they document the divergence and congruence of these four outcomes over time. For the first time in history, the vast majority of nonmetro counties, more than two-thirds, lost population. The acceleration of population decline in rural areas is now one defining feature of all nonmetro areas. Rural areas are also places that have seen diverse outcomes in mortality—exacerbated by the COVID-19 pandemic and the so-called deaths of despair that have been particularly harsh for white Americans in rural communities. This has led to accelerating declines in the white population in rural communities, which are increasing in their diversity due to more stable nonwhite populations and some inflows from immigrant groups (as opposed to inflows from urban areas). It is this increasing diversity that Lichter and Johnson relate to the political upheaval that has received considerable media attention. What has been overlooked, and what Lichter and Johnson document, is the increasing poverty (deprivation) of rural communities. At the same time, they establish the lack of any monolithic rural America. Renewed opportunities for urbanization (especially for rural communities on the outer edges of urban centers), increasing economic activity due to green economy initiatives, and the creation of recreational enclaves in rural communities have changed the trajectories, and even led to some gentrification, of rural communities from 1990 to 2020. The ability of some rural areas to incorporate or serve as key outlets for increasingly urban America has resulted in another portion of rural America that is increasingly isolated and in precipitous decline. To speak of a monolithic rural America is to avoid a discussion of their inherent diversity and dramatically divergent trajectories.

Finally, Bradley Hardy, Shria Holla, Elizabeth Krause, and James Ziliak (2025, this volume, issue 2) consider race and place by analyzing the rural-urban and black-white gaps in income from 1970 to 2020 using data from the Current Population Survey. Troubled by the narrative that rural areas are monolithic and racially homogeneous, they look at the tax system and resulting transfers to see how they have influenced trajectories of black and rural incomes over time. In doing so, they draw an analogy between rural and black communities as being subjected to the same socioeconomic forces such as lower quality schooling, community divestment, and lower levels of entrepreneurial activity. Since the 1970s, the U.S. tax system has changed significantly, as has the attendant social safety net. These changes would be particularly pertinent to black and rural communities given their lower average incomes before taxes and transfers. Some of the most prominent tax-based transfers would be the earned income tax credit and the child tax credit, and social safety net programs such as food assistance. These transfers have narrowed the racial and geographic gaps between the groups over time. Overall, improvement in outcomes has been significant, and the tax and transfer system have been important in stabilizing the incomes of black and rural households. At the same time, the inequality between black and rural households and the highest income households has grown. Similar to the increases in the inequality observed by others, the geographic gaps and racial gaps in income between the richest and the poorest have grown over time. The ability of the American tax and transfer system to lessen the impact of growing inequality has been stymied by more recent acceleration in high income earnings and the retreat from more progressive taxation policies. In particular, they show that black residents in rural areas have fared worse than those in urban areas, leaving black households in rural areas furthest behind in terms of income gaps.

CONCLUSION

In this double issue, researchers from multiple social science disciplines analyze data from various sources and provide updated and insightful snapshots of American society in the 2010s to the present. The decade of the 2010s is unusual. It started with America still recovering from the Great Recession and ended in the midst of a once-in-a-lifetime pandemic. In the intervening years, America witnessed Occupy Wall Street condemning and drawing attention to growing income inequality; Black Lives Matter underscoring persistent racism, racial injustice, and mass incarceration; the #MeToo Movement raising awareness of the endemic nature of sexual harassment and sexism in the workplace and beyond; the legalization of same-sex marriages advancing the rights of LGBTQ+ individuals; the urban-rural divide becoming widened again; and the elections of Donald Trump and Joe Biden to the White House, which intensified political polarization in America.

Although those changes occurred at the macro level, the degree to which they were felt within America varied significantly. Unemployment and home foreclosures during the Great Recession hit the young and disadvantaged populations hardest. The decade of the 2010s highlighted various dimensions of inequality and opportunity, including the role of place as a key correlate of socioeconomic mobility, and generated prospects of tackling some of the root causes. Yet before much improvement was made, the COVID-19 pandemic further exposed health disparities and widened social inequalities along race, gender, and class lines. Ironically, the same role that place has shown with mobility carried over to the duration and severity of the pandemic. The theme from the studies reported in this double issue is that inequalities persisted over the last decade and continued to disadvantage minorities, women, and young Americans. The variability of disadvantage remains acute in American society.

Inequalities are highly tied to race-ethnicity in American society. The undercount of blacks and Hispanics in the 2020 Census, especially in disadvantaged neighborhoods, may skew racial-ethnic inequality given missing information about those at the bottom of the socioeconomic ladder. It also has the potential to lead to political inequality, which may have a direct impact on the policies pursued to counter the negative effects of disadvantage. In addition, the growth of multiracial populations has changed the racial composition of the country. Multiracial individuals, mostly part white and part minority, are situated socioeconomically between whites and the minority group (Alba 2020). The shares of multiracial people and their classifications—being white, a minority race, or multiracial—may redefine racial boundaries and introduce variability in racial-ethnic inequality. America’s racial composition continues to revise and redefine itself, showing the porous nature of America’s racial divides.

Many studies in this double issue focus on race-ethnicity, a salient feature of American society and an important source of inequality. Racial-ethnic minorities continue to experience inequality. Blacks and Latinos tended to experience greater work-hour volatility, shorter job tenure, and lower wages than whites; they failed to catch up in homeownership after the Great Recession because of pent-up demand in housing that they did not have the resources to overcome; they, along with Asians, engaged in more hours than whites performing unpleasant daily activities. These examples make it clear that racial inequality manifests in nearly every aspect of life. Changes in racial composition and the growth of the racial-ethnic minorities in recent decades highlight urgent needs to tackle root causes of racial inequality. At the same time, immigration is redefining some of the typical ways we think of racial groups. For example, the increasing share of immigrants in the black population makes it increasingly difficult to cling to old notions of race within the black population itself.

Gender gaps in college completion remained relatively unchanged in the 2010s, but women’s gain above the bachelor’s degree level, especially professional degrees, widened. More women seek for-profit educational degrees and exacerbate student loan inequality by gender. Buchmann and her colleagues also show that women’s outnumbering men in holding advanced degrees declined over time, signaling persistent gender gaps in earnings that favor men. The COVID-19 pandemic led to an economic disruption that has been termed a she-cession due to the changes in women’s labor supply and labor-force attachment, which were atypical of most other economic downturns. The pandemic also drew attention to the wages and work conditions in the service sector, elementary education, especially retail, restaurants and hotels, health care, and childcare—all occupations dominated by women. In 2022, American women earned 82 cents for every dollar by men, a large jump relative to forty years ago when they earned just 65 cents (Aragão 2023). Yet the gender pay gap remained very much unchanged in the past two decades, despite women’s advancement in college completion. Job tenure does not vary much by gender but earnings gaps increase as men and women spend more time in the labor force. Indeed, throughout the life course, women with children carry a motherhood penalty even as men enjoy a fatherhood premium (Kochhar 2023). Gender discrimination in workplaces as well as gender inequality in division of household labor and childcare plays an important role (Ishizuka 2021).

Young people were also hit hard in the 2010s. More young people coming of age after the Great Recession means that more were unable to find steady jobs and own homes or afford rents, especially during a time when demand for homes far exceeds the supply. Fewer were getting married or entering unions, but many were unable to live independently. Continuing the trend started during the Great Recession, more young people lived with their parents in the 2010s (Qian 2012). Economic factors may be a primary reason for this phenomenon. Young people who lived with their parents were more likely to be unemployed, have lower income, have less education, or be racial minorities than their counterparts who lived alone or were married. Parents or older people who live with children often do so in order to pool resources or provide financial help to children or grandchildren in need. Economic hardship contributes to loneliness among young people, regardless of their living arrangement. Meanwhile, non-cisgender people tend to be younger and less likely to marry or enter a union. Compounded by social stigma and discrimination, they also experience higher levels of loneliness and social isolation (Marlay, File, and Scherer 2022).

Taken together, the studies in this double issue underscore continuation of inequality along race, gender, and class. They also underscore that the continuation is not linear, but rather nuanced and highly dependent on the window through which we seek to understand inequality—whether social, economic, political, or another dimension. The recent national elections show an increasing fractionalization of America politically and socially. Economic inequality in the 2010s, exacerbated by the COVID-19 pandemic, may have pushed political polarization to a new height. The divides concern issues as diverse as education, immigration, gun control, reproductive rights, and media access. The racial, gender, education, and economic correlates of political views are strong, and some observers have pointed to geographic differences in political behavior and policy choices as well (Brown and Mettler 2023). The census and all the relevant data can help us answer how various dimensions of inequality and young adults’ disadvantaged economic prospects have lined up with political divergence in the United States. Relatedly, the census can also help us place the current fixation with polarization in appropriate perspective: Is this a new development in American society? Is this a return to earlier types of polarization seen in the nineteenth century? Is there a way of moving ahead by reducing inequality? As the current decade continues to unfold, answers will reveal themselves only with time.