Equitable Growth announces Lily Roberts as new Vice President of Policy and Programs

CONTACT: 
Madison Moore, mmoore@equitablegrowth.org  

WASHINGTON – The Washington Center for Equitable Growth announced today that Lily Roberts has been named its new vice president of policy and programs. She joins the organization from the Center for American Progress, where she most recently served as managing director for economic policy.  

“We are thrilled to welcome Lily Roberts as our new vice president of policy and programs,” said Equitable Growth President and CEO Shayna Strom. “Lily brings deep policy expertise, strong leadership experience, and a clear commitment to translating economic research into action. Her ability to guide teams and shape policy strategies will be a tremendous asset as we continue to provide policymakers with evidence-backed ideas and proposals to promote shared prosperity and growth.”  

At CAP, Roberts played a central role in coordinating staff and policy teams around legislative priorities such as food assistance, health care access, anti-poverty policy, and women’s economic issues. Her work focused on raising wages, combating economic inequality linked to race, gender, and geography, and building wealth and stability for U.S. families. Earlier in her career, Roberts worked at Mathematica Policy Research, where she researched federal strategies to support low- and middle-income families. Roberts received her master’s degree from Case Western Reserve University and her bachelor’s degree from the University of North Carolina at Chapel Hill.  

“Equitable Growth plays an essential role in connecting academic research with the policy process,” said Roberts. “I’m excited to join an organization that centers evidence in its advocacy and works to ensure that economic policy improves outcomes for U.S. workers and families. I look forward to helping advance a policy agenda that delivers more shared prosperity and equitable economic growth.”  

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The Washington Center for Equitable Growth is a nonprofit research and grantmaking organization dedicated to advancing evidence-backed ideas and policies that promote strong, stable, and broad-based economic growth. For more information, see www.equitablegrowth.org and follow us on X @equitablegrowth and Bluesky @equitablegrowth.bsky.social.

How does early childhood care and education affect U.S. families and workers, and which policies support child participation and boost the quality of care?

Key takeaways

As states consider policy action in early childhood care and education, there is an existing—and growing—evidence base from which to draw lessons. This report summarizes the rigorous evidence on program and policy impact, identifying several key themes.

  • Demand-side policies. These policies equip U.S. families with the means to access early care and education, or ECE, programs, including subsidies and tax incentives. They are often effective at improving participation in ECE programs, particularly among directly targeted populations, and at supporting parental labor force participation. These approaches, however, are less effective at improving children’s outcomes and are often unable to serve or reach all eligible families. They also do not address the lack of affordable, high-quality care options for many U.S. families.
  • Supply-side policies. These policies focus on increasing the availability of ECE programs, over which policymakers can more directly mandate quality provisions. They can be effective at both improving children’s outcomes and facilitating parental employment but are often narrowly targeted and difficult to scale. While direct public provision of child care solves availability issues for those whose children get those newly created slots, the targeting and generally small scale of such programs often means that many children and families, even those who are eligible, do not have access.
  • Improving the availability of high-quality early care and education. Supporting children’s development and facilitating parental employment requires attention to both the demand and supply sides of the ECE market. Attention is needed in particular to bolster the care workforce, incentivize provision of care in areas of high need, and ensure high quality in settings families are accessing with public resources.

Overview

Many states and localities have pursued early childhood care and education, or ECE, policies because they recognizing the critical role that the care economy can play in supporting working families, both by facilitating parents’ employment and investing in children’s healthy development. Policymakers in Washington, DC and Iowa, for example, have implemented policies focused on caregiver compensation. New Mexico now provides subsidized child care for families living at up to 400 percent of the federal poverty level. And Vermont has expanded subsidy eligibility for middle-income families while increasing provider reimbursement rates.

Lawmakers in Kentucky and New York, and perhaps other states and localities down the road, will soon consider proposals to support capacity expansions among child care providers. To leverage evidence to inform these state-level efforts, this report synthesizes findings on ECE programs from high-quality research. It answers questions ranging from the most basic—such as what types of policies the existing research investigates—to the more in depth, including diving into the research on how child care subsidies affect working parents’ labor force participation rate.

From a policy perspective, the optimal deployment of public resources in support of early childhood care and education requires knowledge of what form ECE investments should take, including whether they target the demand- or supply-side of the market, what features these programs should have, and toward which children and families these programs should be directed. Importantly, public investment in increasing the provision of and participation in ECE programs could be leveraged to advance children’s outcomes such as skill development and school readiness, as well as parents’ outcomes, including labor force attachment and the allocation of family time and resources. Such investments have important implications for families, businesses, and communities through both channels.

The dual role that early care and education plays in both supporting children’s early learning and facilitating parents’ participation in gainful economic activities highlights the importance of understanding both the quantity of ECE programs(access to and availability of child care slots that meet families’ needs) and the quality of these programs (the effectiveness of ECE investments at improving children’s outcomes), which could be in tension with one another in policy designs. Achieving these goals rests crucially on a stable and qualified workforce such that investments in providers, caregivers, and staff are central in advancing both aims.

What follows is an effort to synthesize what the research says about what works and what does not in the design of ECE policies and to use the evidence base to inform policymaking efforts.

What policies fall under the umbrella of the care economy?

Broadly, the care economy refers to policies that affect individuals with caregiving responsibilities, including those that address:

  • Parental and caregiver leave
  • Workplace flexibility, including scheduling timing and stability and sick and personal days
  • Care for aging and disabled individuals, including home- and community-based services
  • Tax credits and in-kind transfers targeting families
  • Early childhood care and education

Many policies involve the public financing or provision of ECE programs—often federally funded and locally deployed—that interact with state and local pre-Kindergarten programs and other local ECE policymaking efforts. These include:

  • Child care subsidies, such as the Child Care and Development Fund and the Child Care and Development Block Grant, both of which support low-income, working families in paying for child care
  • Head Start and Early Head Start, the federally operated programs that primarily provide center-based preschool, in addition to home visitations, parent engagement, and nutrition and health services, for young children from low-income households
  • The Preschool Development Grant–Birth through Five, a competitive federal grant program to improve states’ early childhood systems and augment their current investments
  • Tax credits and employer-provided benefits that operate through the tax code and reduce the tax burden for individuals and businesses with child care expenses, either for themselves or their employees

What is the structure of the U.S. market for early childhood care and education?

The ECE market in the United States is a mixed delivery system with both formal and informal care provided in homes, centers, and schools, and funded by public and private sources, including parent-paid tuition or fees. Providers range from sole proprietorships with no additional employees to large, multi-site private child care operators.

In addition to the aforementioned federal ECE programs, many states operate public preschool programs. The National Institute for Early Education Research’s most recent State of Preschool Yearbook indicates that 45 U.S. states offered a state-funded, public preschool program, and more than 1.75 million children attended those programs in the 2023–24 school year—an increase of 7 percent over the prior year.1 Current enrollment in state preschool programs accounts for approximately 22 percent of all 3- and 4-year-olds in the United States. Enrollment has been increasing over time, though much of the growth has been among 4-year-old participants.2

The blended, and often fragmented, landscape of provider types and settings, funding sources, and levels of government complicates ECE policymaking. The market for early childhood care and education is also very local in that families seek care that meets their needs in terms of geographic location and commuting time, as well as linguistic and cultural matches and other practical features such as hours of operation and availability of transportation.3 The ECE market is therefore actually composed of many hyper-localized markets with implications for each other. While there are some features of ECE demand and supply that resemble Kindergarten through 12th grade schooling, the latter is predominately characterized by centralized, public provision with compulsory education requirements, ensuring access to the public system for all families.

What does ECE access and affordability look like in the United States over time and across states?

Many families rely on ECE programs in the United States, with about 55 percent of children under age 6 who are not yet attending Kindergarten participating in regular, nonparental care.4 These most recent data reveal a substantial decline of 5 percentage points from pre-pandemic levels of ECE participation, previously measured in the same nationally representative survey in 2019.5 The majority of participating children are in center-based care arrangements, including Head Start, preschool and pre-K programs, and child care centers. Notably, there are gaps in ECE participation by families’ socioeconomic status, with children from low-income families and those with less educated mothers participating less in formal center-based care and relying more on care provided by a relative.6

These gaps in ECE participation may be due in part to affordability challenges with child care. It is difficult to characterize child care prices over time and across geography as there are few consistent, comparable measures, though prices in the category of the Consumer Price Index that includes child care expenditures have risen much more rapidly than the overall CPI measures. (See Figure 1.)

Figure 1

Percent change in the overall Consumer Price Index for urban consumers and the CPI category that includes child care expenses, 2000-2005

There is considerable geographic variation in child care prices as well. The National Database of Childcare Prices relies on states’ market-rate survey data to construct county-level child care prices. These data suggest that child care prices in the United States for full-time care for just one child account for between 9 percent and 16 percent of families’ annual incomes, with prices in 2022 ranging from $6,500 to $15,600 for annual full-time care. The data show considerable variation based on the age of the child, care settings, and county population. Families face the highest prices for infant care, center-based care (relative to home-based care), and in urban, densely populated areas.7 (See Figure 2.)

Figure 2

Median annual price of child care for one child, by type of care and child age, 2018

Such data from household surveys allows for greater exploration of the variation in child care expenses by family characteristics but contains limited information on type and duration of care. Specifically, data from the 2023 Consumer Expenditure Survey, done annually by the U.S. Bureau of Labor Statistics, suggest that families with young children—those whose oldest child is under 6 years old—who report any child care expenses spend $3,300 annually.8

This average includes various forms of care but is useful in demonstrating variations by family incomes and family structures. Higher-income families, for example, spend considerably more than middle-income families, who spend more than twice as much as low-income families. (See Figure 3.)

Figure 3

Child care expenses by family income and children’s ages, 2023

While the income gradient flattens when looking at families who also have school-age children in their households, these data point to frictions in the ECE market for families with fewer resources. Previous analyses suggest that child care expenses as a share of household income are highest (among those paying for care) at the low end of the income distribution.9

What does the research say about demand-side ECE policies such as child care subsidies and tax credits?

The primary federal policy lever for improving families’ access to early care and education has been child care subsidies. Subsidies are targeted to low-income families, yet the data suggest that this support reaches only a fraction of income-eligible families—approximately 15 percent of those eligible based on national rules and 22 percent of those eligible based on state rules.10

There also are tax credits to offset child care expenses, including the Child and Dependent Care Tax Credit for working families and the Employer-Provided Child Care Credit aimed at employers with expenditures related to providing child care services to their employees. The 2025 budget reconciliation bill made some relatively modest changes to these tax provisions, including increasing the Child and Dependent Care Tax Credit for some families, raising the cap on how much of their pretax earnings employees can allocate for dependent care expenses, and bolstering the business tax credit for employers that offer child care.11

Impact of demand-side policies on access to ECE programs

The evidence on the effectiveness of demand-side policies in moving families into ECE coverage is robust. Giving families resources with which to take part in the ECE market is a viable approach to improving access to and expanding participation in ECE programs.

Yet these tools are often deployed in a limited way. Demand-side subsidies have typically not been used at a large enough scale to have a meaningful impact on the broader market for care. Because subsidies are usually targeted to the lowest-income households and do not cover all eligible families, overall coverage is low and their existence in the market does not generate substantial shifts in the behaviors of consumers or providers. Evidence suggests that more robust subsidy coverage would generate responses in the overall market.12

Impact of demand-side policies on parents’ employment

A large literature documents the effects of ECE availability, expansions, and subsidization on parental employment.13 Specifically, studies of the impact of child care subsidies on families generally find positive effects of access to these care “vouchers” on mothers’ employment, with concentrated effects among single and unmarried mothers, who are disproportionately eligible.14

Subsidies are targeted to low-income households and include work or gainful activity requirements. These policy levers can have implications for productivity once parents are in the workplace as well. Research documents that child care subsidies positively affect parents seeking additional education or job training and increase their full-time employment once employed.15 Educational attainment effects are concentrated among mothers with low initial levels of education and those who receive subsidies when their children are young, as infants and toddlers.16

Impact of demand-side policies on child outcomes

The research on the impact of demand-side policies on improving child outcomes over the short- and long-run suggests that these approaches are limited in their ability to improve children’s development and well-being. Studies leveraging longitudinal datasets to explore the effects of care subsidies on children’s early skills finds negative effects on both cognitive and behavioral measures of development, though these effects do not necessarily persist into or beyond the Kindergarten year.17 Additional evidence suggests that these negative effects are driven by differences in the quality of care, concentrated among families who would otherwise be in high-quality preschool, Head Start, and parental care.18

Evidence from Quebec’s child care reform largely mirrors the evidence on child care subsidies in the United States. This work finds pronounced maternal employment effects and negative effects on child outcomes, which correspond to likely declines in the quality of care that children experienced with changes to their care arrangements in the context of a rapid program introduction.19

What does the research say about supply-side ECE policies such as direct provision of slots, provider incentives, and workforce investments?

Supply-side policies typically take the form of the provision of direct preschool programs, such as Head Start, Early Head Start, and many public state and local pre-K programs. Increasingly, though, policymakers are considering targeted investments for providers through supply-side incentives or subsidies, a tool that was leveraged in the deployment of the 2021American Rescue Plan Act’s Child Care Stabilization and Supplemental Grants.20 The evidence base primarily relies on the former type of investment, with newly emerging research on the impact of provider and workforce supports.

Impact of supply-side policies on access to ECE programs

Supply-side policies that provide child care slots directly improve access to ECE programs for families and children who are eligible for or targeted by the particular program of interest. Because these programs are generally small relative to the broader market for early care and education, however, they do little to solve the lack of availability of high-quality care more broadly.

The ECE landscape is a patchwork of settings, providers, and funding streams, so it is important to note that intervention in one area of the market can have important implications for other segments of the market, including ramifications for the broader workforce when credentialing requirements or other qualifications are added or relaxed for a subset of the labor market.

One area in which these spillovers are evident is in the market for infant and toddler care when universal public preschool programs, typically serving 3- and/or 4-year-olds, are introduced or expanded. The introduction of public preschool in New York City, for example, reduced infant and toddler capacity at private child care centers concentrated in high-poverty areas and likely was due to the cross-subsidization of lower-cost preschool care to higher-cost infant and toddler care.21

Impact of supply-side policies on parents’ employment

A large and growing literature uses the introduction of new ECE programs or changes to families’ eligibility for public programs to estimate the impact of new child care slots on parental employment, and particularly among mothers. Evidence from the expansion of Kindergarten programs and the introduction of public preschool programs suggests that maternal labor supply is particularly responsive to increased access to early care and education.22 This literature generally points to more sizable effects among mothers most affected by increased ECE availability or affordability—that is, those whose youngest child is age-eligible under the policy or program and mothers who are unmarried or have lower levels of educational attainment.23 In addition to being more likely to be shifted into employment by a policy change, some programs, such as Head Start, disproportionately serve or directly target less-advantaged mothers.24

Studies of ECE investments in Canada, Germany, and Norway, for example, similarly document that mothers are responsive to such expansions in other countries as well.25 Though prior evidence suggested that mothers’ responsiveness to more recent ECE expansions in the United States had declined relative to earlier interventions and other country contexts,26 recent evidence confirms that parents do indeed remain responsive to these ECE expansions and greater public provision of early childhood programs in the United States.27

In particular, researchers have documented broadly realized increases in U.S. maternal employment concurrent with the introduction of public pre-K programs across states and among mothers of Kindergarten-aged children as full-day Kindergarten expanded across the country over the past 30 years.28 Lottery-based access to a universal public preschool program in New Haven, Connecticut, for example, induced sizable and persistent effects on parents’ earnings.29 And descriptive evidence from the introduction of Washington, DC’s public pre-K program similarly shows increases in mothers’ labor force participation.30

Impact of supply-side policies on child outcomes

Evidence suggests that publicly provided preschool programs can improve children’s outcomes over the short- and long-term, but that positive effects are not guaranteed. In particular, the landscape of alternative care options matters, with children who would not otherwise be in center-based care experiencing the biggest boost.

There are also complicated patterns of short- and long-term effects, with early cognitive test-score advantages often converging in the primary grades. In some instances, in which researchers can observe both short- or medium-term test scores, as well as later-life outcomes, a lack of test-score effects can still be consistent with improvements in long-run outcomes, including educational attainment.31 Recent evidence from Boston’s pre-K program shows large, sustained improvements in children’s outcomes, particularly in improved educational attainment.32

What does the research say about the role of care quality for child outcomes and policies aimed at improving quality in ECE programs?

While there is a body of evidence indicating that ECE policies and programs can improve children’s outcomes over both the short- and long-run, we know far less about the specific features of ECE interventions that drive improved outcomes. Assessing the critical components of effective ECE investments is complicated by three important challenges:

  • There is a lack of consistently measured and systematically collected data on the inputs to providing ECE programs and the outcomes of the programs.
  • It can be difficult to identify the critical components of program quality in the ECE program bundle.
  • Program quality is measured in comparison to the quality of alternative care arrangements in which young children would spend their time, which are quite varied and hard to measure.

With those challenges in mind, there is limited research exploring a few dimensions of quality in ECE programming.33 One area that the research has firmly established as important for children’s development is the quality of relationships and the nature of interactions between children and their caregivers. This body of evidence points to stable, healthy attachments in the child-caregiver relationship as vital to children’s development.34

Conversely, high rates of staff turnover in ECE settings are related to weaker development of language and social skills among children.35 Recent evidence also shows that centers with high turnover exhibited more critical safety violations and lower process quality.36

How effective are child care regulations and states’ quality standards?

Research has not thoroughly established the role of child care regulations in ensuring quality and promoting positive child outcomes. There are foundational safety and security requirements regulated at the state level, as well as comprehensive efforts to improve ECE quality through the Head Start Program Performance Standards and individual states’ accountability systems, known as Quality Rating and Improvement Systems.37 QRIS typically aggregate multiple measures—such as licensure, lead teachers’ educational attainment, and child-caregiver ratios—into a simplified rating system that they then make publicly available.

Rigorous evidence has not established links between QRIS and measurable child outcomes.38 Yet research indicates that receiving a low rating has an impact, leading programs to work to improve the measured dimensions. These scores can also be a factor influencing parents’ choices of ECE programs, with parents moving away from programs with lower ratings, particularly when there are other options available locally.39

Limited work has explored the impact of the regulatory environment on the provision and quality of early care and education.40 The authors document that regulations reduce the number of child care centers, particularly in low-income areas, but that such regulations boost the quality of child care services, with quality improvements concentrated in higher-income areas. This work suggests that improving quality in what has become a bifurcated market for early care and education requires both accountability for quality and targeted investments in high-need areas.

What do the data say about the composition of the ECE workforce and how it has changed over time?

The ECE workforce in the United States consists of approximately 1.5 million caregivers and early educators and is composed of primarily women.41 Relative to the broader workforce, these caregivers are disproportionately women of color.42 While 14 percent of U.S. child care workers are Black and 24 percent are Hispanic, these groups make up 6 percent and 8 percent, respectively, of the overall workforce.

The U.S. child care workforce was severely affected by the COVID-19 pandemic of 2020–2023 and the many care center closures that occurred in the aftermath of its onset. It also took longer to recover than most other segments of the U.S. economy, consistent with evidence that the industry is more exposed to economic downturns than other low-wage industries and that its employment is consistently hit harder.43 (See Figure 4.)

Figure 4

Percent change in employment, compared to February 2020, in specific industries and overall payroll employment

In addition, recent evidence suggests that the quality of the child care workforce—as measured by their wages, educational attainment, and cognitive skills—has declined over time, as outside employment options have improved and workers have left this industry for higher pay and better working conditions.44

What is the evidence on teacher-child or caregiver-child ratios in ECE settings?

All states are required to have regulations about group size and ratios in ECE programs. Notably, there is considerable variation across states. For infant care, ratios range from as low as three children per caregiver to as high as nine children per caregiver. For toddlers, the range is four to 12 children per caregiver, and it ranges from seven to 15 children per caregiver for preschool-aged children.45

While there is limited evidence on the impact of such regulations, evidence from other early childhood contexts demonstrates the importance of small class sizes for the realization of improved child outcomes over the short- and long-run.46

Are strategies to reduce ECE staff turnover through job-quality improvements or higher compensation effective?

ECE providers face challenges in hiring and retaining a qualified workforce, as it is an industry characterized by both its labor intensity and low wages. As mentioned above, the stability and quality of the workforce are essential ingredients in promoting positive child outcomes in ECE settings. Providers’ ability to recruit and retain capable, skilled caregivers is critical to delivering the quality of caregiver-child relationships and interactions that support healthy child development.

Indeed, evidence documents that improvements in compensation and working conditions for caregivers lead to higher-quality care environments and corresponding better child outcomes.47 Relatedly, recent experimental evidence demonstrates that early educators and caregivers respond to bonuses and incentives by staying in their jobs.48

Are there areas of ECE policy design for which we do not have a sufficient evidence base?

There are several important open questions in ECE policy conversations for which the evidence base is currently insufficient. One is the importance of various features of the regulatory environment for the supply and quality of child care provision. Another is the role of private equity in the ECE market.

To the first point, there is limited existing evidence on the importance of particular regulations, or the effects of relaxing those regulations, on the three main outcomes of interest—families’ access to care, parental employment, and children’s development—despite substantial variation across states in the nature and type of regulations affecting the market for early care and education.49 We also know little about the effects of regulation in shaping the workforce through both recruitment and retention channels.

There also has been a popular press focus on private equity in the ECE market, but governance structures and the administration of ECE programming are understudied, so there is a lack of evidence on the impact of such shifts. A larger literature speaks to the impact of private equity acquisitions in health care, specifically with respect to nursing home buyouts, but its application to the market for early childhood care and education is limited.50 The knowledge base would benefit from study of the same phenomenon in the child care industry.

Conclusion

The fragmented ECE landscape in the United States presents challenges for families, providers, and policymakers alike. As states and localities make efforts to improve access, affordability, and quality, existing evidence points to several lessons learned and a path forward in ECE policy designs.

While demand-side policies, such as child care tax incentives and subsidies, often improve participation in ECE programs and facilitate parental employment among those targeted by the benefits, they are often less effective at improving children’s outcomes and too small in scale to affect the overall ECE market. On the supply side, the direct provision of programs, with greater oversight of quality, can generate improvements in access, parents’ labor force participation, and child outcomes. Yet these efforts are also often narrowly targeted, and scaling such efforts has proven difficult. At the same time, investments in the ECE workforce show particular promise, with implications for the availability and quality of care.

In sum, addressing challenges in the market for high-quality early childhood care and education requires public investment in both the demand and supply sides to equip families with resources to access the ECE market, support a stable and qualified caregiving workforce, incentivize the  provision of care in underserved areas, and monitor the quality of care in settings operating with public dollars. Smart investments can fill gaps in the currently fragmented ECE system, ensuring that families and caregivers are not falling through the cracks and advancing the dual aims of supporting parents’ careers and children’s development.

About the author

Chloe Gibbs is a senior economist at the W.E. Upjohn Institute for Employment Research, policy fellow at the Stanford Institute for Economic Policy Research, and faculty affiliate of the University of Notre Dame’s Institute for Educational Initiatives, where she directs the Early Childhood Policy Lab. From 2022–2023, she served as a senior economist with the President’s Council of Economic Advisers at the White House. She holds a Ph.D. from the University of Chicago’s Harris School of Public Policy.

Analyzing recent U.S. economic policies using Equitable Growth’s Inequality Tracker

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Key takeaways:

  • The Washington Center for Equitable Growth’s Inequality Tracker uses trusted government data sources to create several windows into income and wealth inequality in the U.S. economy.
  • The tracker subdivides both income and wealth by type, allowing users to explore how components of income or wealth have contributed to trends in the economy.
  • Limiting the tracker to discrete economic eras of the United States, such as a business expansion or contraction, can explain which parts of the economy drove growth over that period.
  • The tracker allows users to explore different groups so they can disambiguate whether changes in wealth or income were broad-based or particular to a section of the distribution.

Overview

The Washington Center for Equitable Growth’s Inequality Tracker is a data visualization tool designed to help policymakers and economic analysts examine and analyze U.S. income and wealth inequality in the 21st century. The Inequality Tracker is a flexible tool for exploring recent U.S. economic trends such as the recovery from the Great Recession of 2007–2009, the increasing share of transfers in income, and the lagging fortunes of the upper-middle class.

In this column, I will detail some useful lenses for analyzing the U.S. economy and recent economic policies with the tracker, including:

  • Thinking in components of income and wealth
  • Analyzing across the business cycle
  • Disaggregating groups to find the real winners

I will illustrate how the tracker helps with these approaches using graphics pulled directly from it, which you can get by pressing the download image button above each graph. You can also get the data for each graph that way, using the adjacent button.

Thinking in components of income and wealth

One of the most unique features of the Inequality Tracker is the ability to look at how components of income and wealth each contribute to the overall patterns in inequality over time. The first graph below, for example, shows the path of income growth for the ninth decile of households—the 80th to 90th percentile—over the full course of the dataset from 2000 to 2023. (See Figure 1.)

Figure 1

Households in the 80th to90th percentile of the income distribution

The ninth decile, and the three deciles below it, all experienced less income growth over these 23 years than U.S. households below them or above them. Why did this upper-middle segment of households fall behind in this period? Figure 1 shows that the vast majority of income growth for this group over this period came from growth in their wage incomes. Yet this does not indicate that this group had higher wage growth than other groups.

The second graph below shows the composition of income for the group selected and begins to shed some light on why the ninth decile fell behind. Here, we can see that wages make up about 80 percent of income for households in the ninth decile. (See Figure 2.)

Figure 2

Households in the 80th to90th percentile of the income distribution

As Figure 2 shows, households in this decile received almost all their income from wages, so gains from wages over this period must have lagged gains in other components of income. But perhaps wages grew unevenly across the income distribution, and upper-middle class households missed out.

To check, we can look at the third graph below, which shows the compound annual growth rate in each component of income for the group selected and some comparison groups. So, for instance, Figure 3 shows that wages grew relatively evenly across the distribution of households but slower than other components of income. (See Figure 3.)

Figure 3

Households in the 80th to90th percentile of the income distribution

Together, these three graphs explain why the upper-middle deciles of the income distribution saw income gains 10 percentage points lower than the bottom 50 percent and the top 10 percent. This group is extremely dependent on one component of income—wages—that grew similarly across income brackets and grew slower than other components of income.

Analyzing across the business cycle

The example above looked at the entire time series available in the Inequality Tracker, from 2000 to 2023. But trends across smaller time periods also can help us evaluate specific policy regimes.

One narrative that was frequently debated during the economic expansion from 2009 to 2019 was the idea that the labor market should be run hot to shift the balance of bargaining power between workers and employers and generate wage gains for low- and middle-income workers. This narrative was especially prominent in the middle part of the 2010s, as slow wage gains produced an anemic recovery from the Great Recession of 2007–2009.

This policy program was pursued to some degree both by the Federal Reserve, which maintained a relatively dovish stance through this period, and by lawmakers in Congress and the Obama administration. Stimulus included implementation of the Affordable Care Act starting in 2014 and payroll tax cuts in 2011 and 2012. These policies and market conditions created a tight labor market: U.S. unemployment dropped to its lowest level in more than 40 years and prime-age labor force participation recovered to the level of the early 2000s.

Let’s look at this era of the U.S. economy, and specifically at what I call the middle 40 percent—households between the 30th and 70th percentile on the income distribution. This group fits my mental model of the middle class. They get more than 50 percent of their income from wages and are mostly households with more than $50,000 but less than $100,000 of total annual income. The graph below shows the evolution of this group’s income from the start of the Great Recession in 2007 to the end of the expansion in 2019. (See Figure 4.)

Figure 4

Households in the 30th to 70th percentile of the income distribution

There are two distinct eras of wage recovery for this group. Wages dipped dramatically during the recession and did not recover to 2006 levels until 2014. From 2014 to 2019, however, wages grew relatively quickly.

Next, we can look at the compound annual growth rate graph to get a sense of how wage growth in this period compares across the income distribution. Wages for the middle 40 percent group grew at an annual rate of about 3.7 percent in this time span, faster than comparison groups, although these groups also saw strong growth. (See Figure 5.)

Figure 5

Households in the 30th to 70th percentile of the income distribution

Remember from the first example above that 3.6 percent is a much faster rate of wage growth than what was common over the entire period from 2000 to 2023, where no U.S. households saw more than 2 percent annual wage growth. So, from this second analysis, it looks as though running the labor market hot was fairly successful at boosting wages, and especially so for households outside the top 10 percent.

Did the hot labor market reduce inequality though? According to the next graph below, which shows the share of all income earned by the selected middle 40 percent group, this strong period of wage growth did not result in this group capturing significantly more of aggregate income. Indeed, from 2013 to 2019, this group’s share of aggregate income fluctuated very slightly, between 27.3 percent and 27.7 percent of all income. (See Figure 6.)

Figure 6

Households in the 30th to 70th percentile of the income distribution

That’s the brutal math of inequality: Meaningful shifts in the distribution of income require large and sustained shifts in income growth.

Disaggregating groups to find the real winners

So far, we have looked at broad groups of households in the income distribution. Many households that are close in the distribution have similar outcomes in the U.S. economy, but the Inequality Tracker provides ample opportunities to disaggregate and look for exceptions.

Let’s briefly consider the distribution of wealth in the United States. Between 2000 and 2025, the share of all wealth earned by the top 10 percent of U.S. households in the distribution rose through about 2016, then declined through the COVID-19 pandemic of 2020–2023 before recovering somewhat in recent years. (See Figure 7.)

Figure 7

Households in the top 10 percent of the wealth distribution

The Distributional Financial Accounts—data that we use to create the wealth side of the Inequality Tracker—allows us to further disaggregate this top 10 percent group, which shows that there is actually considerable heterogeneity within the group. The 90th to 99th percentile of households follow a similar pattern as the top 10 percent through about 2010. After that, the two groups diverge. This group’s wealth as a share of total wealth has declined consistently since 2010. (See Figure 8.)

Figure 8

Households in the 90th to 99th percentile of the wealth distribution

The only possibility to explain this discrepancy is that the top 1 percent of households is pulling away from the next 9 percent. Figure 9 verifies that top 1 percent’s wealth has continued increasing as a share of total wealth, with a slight dip around the time of the COVID-19 pandemic. (See Figure 9.)

Figure 9

Households in the top 1 percent of the wealth distribution

Further exploration with the Inequality Tracker shows that this trend is attributable in large part to the higher share of equities in the wealth of the top 1 percent of households and high growth in equity wealth for that group compared to others.

Conclusion

The Federal Reserve’s Distributional Financial Accounts and the U.S. Bureau of Economic Analysis’s Distribution of Personal Income data series are important new tools for understanding the U.S. economy. Equitable Growth’s Inequality Tracker provides windows onto the data that you can use to think about how inequality is changing in the United States, how a component of wealth or income is performing relative to other components, how the composition of wealth and income is changing over time, and more. You can do even more by analyzing the official data yourself, but we hope the tracker will prove to be a useful jumping off point for developing intuition about the movement of income and wealth in the U.S. economy.

If you have questions about the data or need help analyzing data, we would love to help. Contact us at inequalitytracker@equitablegrowth.org.


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Accounting for capital gains in income significantly increases U.S. inequality

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The Washington Center for Equitable Growth’s recently launched U.S. Inequality Tracker uses data from the U.S. Bureau of Economic Analysis to show how income and wealth inequality have evolved in the 21st century. Our analysis of the data through 2023 shows that income inequality has been relatively stable over this time span, while wealth inequality has grown in that same period.

But the Bureau of Economic Analysis does not keep track of capital gains in the U.S. economy, or increases in the value of an asset, such as stocks and property. When an asset is sold, the profits or losses on that asset are called realized capital gains, whereas when an asset increases or decreases in value but is not sold off, it is referred to as unrealized capital gains. Capital gains in the United States are large and are distributed very unequally along the income distribution, with the bulk of them going to the very top.

Indeed, we find that adding capital gains to the BEA income series shows that the share of income earned by the top 10 percent of households between 2002 and 2021 actually increased by 5 percentage points, rather than the 1.1 percentage points shown in the BEA data alone.

To reach this finding, we worked with a team of economists—the Federal Communications Commission’s Cole Campbell and the University of Illinois at Chicago’s Jacob Robbins and Sam Wylde—who recently put out a working paper tracking capital gains. Their team shared estimates of U.S. capital gains from 2002 to 2021 for three income groups: the bottom 50 percent of households, the upper 40 percent of households (those in the 50th percentile to 90th percentile), and the top 10 percent of households. Their measure, which they call pure capital gains, includes both realized and unrealized capital gains.

In 2021, pure capital gains on assets held by U.S. households came in at $16.2 trillion, making them the single largest component of income in that year. But capital gains are highly volatile because of conditions in the stock market and can sometimes yield enormous losses, particularly amid economic downturns. Adding capital gains to other forms of income can thus both increase and decrease inequality. During recessions, when asset values plunge, adding capital gains to income measures will tend to decrease income inequality, with the reverse happening during booms.

To create more stable and interpretable income trends, we used the 5-year running average of pure capital gains to make our calculations about their impact on income inequality. Yet even this measure is volatile, as shown in Figure 1. During the Great Recession of 2007–2009, for example, they reached lows exceeding -$2.5 trillion in 2017 dollars, while they reached highs of close to $5 trillion in 2022. (2017 is the index year for the Personal Consumption Expenditures Price Index, which is a key measure of U.S. inflation and the official deflator for BEA’s Personal Income series, which we use here.) (See Figure 1.)

Figure 1

Five-year running average of pure capital gains in the United States, adjusted for inflation using the Personal Consumption Expenditures Price Index

Figure 2 below shows the share of income earned by U.S. households in the top 10 percent over time, both with and without pure capital gains. To make the numbers comparable, we use a 5-year running average of other forms of income as well, which greatly reduces the variation in this series.

When capital gains are not included, the share of income earned by the top 10 percent increased 1.1 percentage points over the two decades studied, from 36.9 percent to 38 percent. With capital gains, the difference is more pronounced, with the share of income earned by the top 10 percent of households increasing from 37.1 percent in 2002 to 42.1 percent in 2021. (See Figure 2.)

Figure 2

Share of income earned by the top 10 percent of U.S. households, with and without capital gains included, using 5-year averages of income types, 2002-2021

As Figure 2 shows, the series with capital gains included was quite volatile over this time, with the top 10 percent’s share dipping as low as 34 percent before bouncing back in the early 2010s. Unsurprisingly, this was a result of asset values crashing during the Great Recession.

These findings echo estimates from the Congressional Budget Office’s distribution of income report. This report, which is currently only updated through 2021, also tracks U.S. income inequality over time but uses a different income concept than the Bureau of Economic Analysis and includes realized capital gains. In the CBO data series on income after taxes and transfers, the top 10 percent’s share of income increased by 5 points between 2002 and 2021.

Overall, these findings reinforce that income inequality has been high but stable through the 21st century—but there are serious warning signs just beneath the surface. We pointed to two such warning signs in our initial analysis: First, income support programs have propped up U.S. households in a period of weak wage growth, and second, that these government transfers have been increasing as a share of income, implying that economic welfare has increased much more slowly for the bottom 50 percent than for the top of the distribution.

Rising levels of capital gains wealth is another warning sign. Capital gains significantly increase the wealthiest households’ share of income and are growing over time. All these warning signs suggest U.S. income inequality will rise further in coming years.


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Slow wage growth is the key to understanding U.S. inequality in the 21st century

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Introduction

The Washington Center for Equitable Growth today launched the U.S. Inequality Tracker, which tracks income and wealth inequality in the United States and highlights how particular components of income and wealth shape those trends. The tracker updates automatically—quarterly for wealth and annually for income—and follows income inequality from 2000 through the end of 2023 and wealth inequality from 2000 through the fourth quarter of 2024.

Although there are other dashboards on the internet that track inequality, including WID.world and realtimeinequality.org, none of them breaks down income by type. In contrast, Equitable Growth’s Inequality Tracker displays how income is divided between wage income, income in the form of income-support and in-kind transfers from the government, income from running a business, interest and dividend income from holding equities, and income from renting out property. These income data come from the U.S. Bureau of Economic Analysis’ Distribution of Personal Income dataset, which takes Personal Income data and divides it into 10 household deciles, or slices of the population that each hold 10 percent of households.

Equitable Growth’s Inequality Tracker also breaks out developments in wealth concentration, based on the Federal Reserve’s Distributional Financial Accounts. It shows how seven streams of wealth—including real estate wealth, equity wealth, and pension or retirement account wealth—have grown in the 21st century, contributing to the widening wealth gap in the United States.

This issue brief is primarily focused on the income data, where inequality has been stable over the past two decades, as opposed to wealth inequality, which has increased over the same period. Specifically, this brief looks at the past 23 years of income growth in the United States through the lens of the five streams of income mentioned above. Understanding how these streams of income add up to total income can yield new insight about the U.S. economy. In particular, analyzing the data shows the following:

  • Income inequality, as measured by the Gini coefficient, has changed little and is currently almost exactly at its average level for the 2000–2023 period.
  • This single-number summary, however, obscures important dynamics. Income growth has been highest for households in the bottom 50 percent of the distribution and households in the top 10 percent of the distribution. Those in the 50th percentile to the 90th percentile, representing the middle and upper-middle class in the United States, have seen weaker income growth.
  • In the 21st century, wages have grown slower than any other income source, making these two decades an outlier in recent U.S. economic history. This slowdown in wage growth largely explains why households in the 50th percentile to the 90th percentile have lagged other groups in income growth because this group is the most dependent on wage gains.
  • Although the bottom 50 percent of households have kept pace, more and more of their income comes in the form of in-kind transfers, such as from Medicaid and Medicare, which means their economic welfare is advancing slower than their incomes.
  • There is no substitute for a strong U.S. labor market. To reduce income inequality in the United States and increase the share of income that households earn from wages, workers need greater bargaining power.
  • Income inequality will likely increase because of policies pursued by President Donald Trump and the Republican-controlled Congress that erode the power of workers and cut benefits in major government programs, such as nutrition assistance, health care, and housing energy assistance.

Taken together, these findings are disconcerting. Although inequality has largely stopped expanding, the current level of inequality in the United States is high, and an analysis of the components of income suggest that there is significant weakness along the entire income distribution, outside of the top decile. The primary culprit is a labor market that no longer generates strong wage growth for U.S. households.

As others have pointed out, the macroeconomic impact of rising inequality is likely to be slowing growth. Lower-income households have high propensities to consume. Even modest erosion of their incomes could lead to significant drops in consumption. The likely result is a double whammy of weak and unevenly distributed economic growth.

U.S. income inequality in the 21st century

It is generally accepted that income inequality in the United States was high during the 1920s but declined through the first half of the 20th century, reaching relatively low levels in the 1970s. Yet income inequality rose again throughout the 1980s and 1990s, reaching levels similar to the 1920s, or perhaps a bit lower. Different datasets yield different answers about how steeply inequality went up in the 1980s and ‘90s, but the pre-1970s dip and subsequent rise is not disputed.

Likewise, it is generally accepted that in the 21st century, income inequality has advanced slowly or not at all, remaining steady at a high level. To measure inequality, scholars often use the Gini coefficient, a value ranging from 0 to 1 with values closer to 1 representing more inequality. As Figure 1 below shows, the average Gini coefficient of U.S. income over the period 2000 to 2023 was 0.457; in 2023, it was barely above this, at 0.458. (See Figure 1.)

Figure 1

Inequality, as measured by the Gini coefficient of personal income, in the United States, 2000-2023

As Figure 1 shows, inequality actually dipped sharply in 2020, thanks to federal COVID-19 pandemic policies that funneled money to U.S. households through an expanded Unemployment Insurance program, a more generous Child Tax Credit, and pandemic-era stimulus checks. These government transfers boosted incomes for many U.S. households, alleviating some of the rise in income inequality that accumulated in the 1980s and 1990s. In 2022, most of these programs expired, however, and inequality quickly returned to trend.

While the Gini coefficient provides a helpful one-number summary of inequality, it does not provide a comprehensive picture of how inequality is changing in a country. The BEA Distributing Personal Income dataset, meanwhile, allows for a much more granular examination of how income inequality has changed between 2000 and 2023.

The BEA data show that there have been clear winners and losers in the 20th century. Aggregate Personal Income, adjusted for inflation using the Personal Consumption Expenditure Price Index, grew 66 percent between 2000 and 2023. But growth over this period varied substantially by the decile of the income distribution into which a household fell. The lowest-income households, those in the first decile, experienced 80 percent growth over this period, while the 8th decile experienced the slowest growth, at just 59 percent. (See Figure 2.)

Figure 2

Total personal income growth between 2000 and 2023, by income decile

Rather than use deciles, some economists break the income distribution into three groups that are coincidentally quite useful for examining changes in the income distribution between 2000 and 2023. The first group is the bottom 50 percent, representing half of all households in the United States that have income equal to or less than median income. This group is the first five deciles in the BEA data. The second group is the subsequent four deciles, representing households with income in the 50th percentile to 90th percentile. We call these households the upper 40 percent. Finally, there’s the 10th decile, or the top 10 percent of households, those with the highest income.

In terms of these three groups, Figure 2 shows that the bottom 50 percent and the top 10 percent have both exceeded average income growth in the 21st century. At the same time, the upper 40 percent has fallen behind, with each decile in that group seeing smaller income gains than the average.

Similarly, this slow income growth in the upper 40 percent is reflected in each group’s share of Personal Income as well. The bottom 50 percent increased their income share by 0.7 percentage points overall, while the upper 40 percent saw their share fall by 1.5 percentage points. The top 10 percent saw the greatest benefits of all, increasing their income share by 0.8 percentage points. (See Figure 3.)

Figure 3

Share of all personal income earned by income decile in the United States, in 2000-2023

In other words, the headline story of no change in U.S. inequality as told by the Gini coefficient is a little more complicated under the hood. The upper-middle class has suffered some, while households at the bottom and the very top have done well. What is driving these dynamics?

Income growth has lagged for groups dependent on wages

Looking at streams of income sheds some light on this question. This is where the BEA Distribution of Personal Income dataset really shines. It allows analysts to further break down income into five streams. (In the BEA dataset, there are six streams of income, but Equitable Growth subtracts payments to the government to fund social programs, such as Social Security, from government transfer payments to reflect the balance of government transfers that U.S. households are receiving.) How these five streams combine to produce household income varies substantially by income decile.

Households at the bottom of the income distribution, for example, receive a significant amount of their income in the form of government transfers. These include both cash assistance, such as Social Security, and transfers in-kind, such as medical insurance coverage through Medicaid and Medicare. When accounting for income, it is common to include these latter programs as transfers that raise household income by the average per-capita expenditure of the program.

Receiving Medicaid, for example, adds a few thousand dollars to a household’s income, depending on the year. Even some relatively wealthy households receive transfers because of programs such as Social Security and Medicare, which are available to all seniors, regardless of income level.

For the first two deciles of the income distribution, government transfers are the largest single component of their income. For every other decile, the largest component of income is wages, which include employers’ contributions to social insurance and retirement plans. In fact, wages make up about 61 percent of Personal Income overall. Moving up the income deciles, transfers shrink as a share of income and wages expand as a share of income. (See Figure 4.)

Figure 4

Composition of Personal Income, by income decile, 2023

At the very top of the income distribution, other sources of income matter as well. Specifically, top income deciles make significant amounts of income from returns on assets. Importantly, these are not proceeds from the increasing value of assets but rather consist of interest and dividend income earned on asset holdings. (The increasing value of assets, generally called capital gains, are not included in this BEA dataset because capital gains generally are not a part of the National Income and Product Accounts. Pure capital gains have grown quickly over the past two decades, and adding either realized or unrealized gains to the BEA data would show increasing inequality in the 21st century.)

Two other categories of income appear in Equitable Growth’s tracker. Business income is defined as income earned by the sole proprietors of businesses. This income stream is much more important for high-income households. Finally, income from renting out property makes up a small but relatively steady proportion of income across the distribution.

Let’s now consider each of these income streams across the three income groups of households discussed above. Figure 4 shows that the bottom 50 percent of households rely on a mix of wages and transfers. The upper 40 percent rely mostly on wages, with a small role for asset income, while the top 10 percent has the most diversified income portfolio, with significant percentages coming from wages, assets, and businesses.

Figure 5 below shows the compound annual growth rate for each of these streams of income between 2000 and 2023. Wages are the slowest-growing component of income over this time, increasing just 1.74 percent per year. Income from all other categories was at least 2 percent per year, with rental income increasing by more than 5 percent per year. (See Figure 5.)

Figure 5

Annual growth in Personal income by category, 2000-2023

Low wage-growth largely explains why U.S. households in the upper 40 percent have suffered in the 21st century. The bottom 50 percent households have been supported by strong growth in government transfers, and the top 10 percent of households have benefitted from growth in business and asset income that exceeds wage increases.

This is not a result of wage growth being soft for specific deciles. Unlike in the 1980s and 1990s, when wage growth diverged for low- and high-income workers, growth in wage income has been relatively even for workers up and down the distribution in the 21st century. Since 2000, the compound annual growth rate of wages was 1.59 percent for the bottom 50 percent, 1.67 percent for the upper 40 percent, and 1.92 percent for the top 10 percent. (See Figure 6.)

Figure 6

Average annual growth of three categories of income across all 10 deciles of the U.S. income distribution, 2000-2023

Even though wage growth for the upper 40 percent compared favorably to wage growth along the rest of the income distribution, this group still fell behind because most of their income comes from wages and wages underperformed other categories of income.

As Figure 6 shows, other categories of income, such as assets and business income, show disproportionately high growth at the top end of the income distribution, which explains why this decile outperformed the upper 40 percent despite wages making up 54 percent of the 10th decile’s income. Indeed, growth in business income is low across the distribution, except for in the 10th decile (growth in the 2nd decile appears high, but the business income base in this decile is miniscule, making the estimate noisy). Similarly, income from assets grew much faster in the 10th decile than anywhere else.

The weak performance of wages in the 21st century is an outlier in recent U.S. economic history. Although wages also were the slowest-growing category of income in the 20 years between 1980 and 2000, they grew at nearly twice the rate that wages have grown in the 21st century: 3.26 percent per year versus 1.74 percent. In the 1960s and 1970s, when inequality in the United States reached relative lows, wages grew at nearly 4 percent per year, faster than rental and business income. (See Figure 7.)

Figure 7

Annual growth in Personal Income by category, measured across three time periods

As seen in Figure 7, recent growth in government transfers is not outside the norm. Transfers grew similarly from 1980 to 2000 as they did from 2000 to 2023. They grew even faster between 1960 and 1980, but this largely reflects the creation of large new transfer programs, including Medicaid and Medicare, which did not exist until 1966.

A shift to income from government transfers harms low-income households

The collapse in wage growth since 2000 has significantly harmed middle- and upper-middle-class households, which primarily depend on wages for their incomes. But they are not the only losers. While households in the bottom 50 percent have kept pace with, and even increased, their income share, their success is largely predicated on the government making up for declining wage growth with transfers. This is a bad sign for the future of this group for two reasons.

First, transfers are not guaranteed to grow indefinitely. Once benefits are extended to a population, further income gains can be produced by expanding them or if their values rise faster than inflation. The increases shown in Figure 7, for example, are largely due to a steady expansion of social programs by Congress. In the 2000s, that includes expansions of the Earned Income Tax Credit and the Child Tax Credit and the Affordable Care Act’s expansion of Medicaid, in which the federal government expanded the eligible population for Medicaid and shouldered most of the cost of enrolling these new households. In the case of the Affordable Care Act, there is still some low-hanging fruit to be plucked: Texas and Florida, among other states, have rejected Medicaid expansion, and if some of these states changed course, it would provide in-kind support for millions of Americans.

Medicaid expansion aside, however, growth in transfer payments seems unlikely in the near future. With huge tax cuts looming on top of comparatively high levels of debt relative to U.S. Gross Domestic Product, stable or even falling transfer payments are more likely. The House Republican budget resolution implies a nearly 30 percent cut to spending on Medicaid, a program that is heavily tilted toward low-income families. Under the reasonable assumption that those receiving Medicaid are concentrated entirely in the bottom 50 percent of households, current Medicaid spending at the state and federal level represents nearly 18 percent of this group’s income, according to the BEA data. Aside from Medicaid, current budget discussions suggest that other transfer programs, including the Low Income Home Energy Assistance Program and the Supplemental Nutrition Assistance Program, also are under threat.

Second, the growing share of transfers in the bottom 50 percent’s income implies that overall welfare—by which economists mean the overall well-being of a person—for this group is increasing more slowly than it is for other groups. Much of the increase in transfer payments comes from the expansion of in-kind services such as Medicare and Medicaid. In fact, according to BEA data, 48 percent of all growth in transfer payments in the 21st century is thanks to growth in Medicare and Medicaid.

These are not cash transfers to households. Rather, they are in-kind transfers that provide a service to households. Though Medicare and Medicaid are real substitutes for income—if households didn’t receive it, they would have to choose between not having health insurance or buying private insurance—economic research finds that people do not value in-kind transfers at their full cash value.

In other words, if the government spends $3,000 providing health care to a person, that person’s economic welfare increases by less than $3,000. Consequently, $20,000 of income that comes purely from wages provides more welfare to the recipient than $20,000 of income in which half is from wages and half is from government transfers. As Equitable Growth’s U.S. Inequality Tracker shows, transfers have increased as a share of income for the bottom 50 percent, from 31 percent of income in 2000 to nearly 39 percent in 2023, suggesting that economic welfare for this group has increased substantially less than Personal Income has.

Conclusion

Taken together, these arguments suggest that bottom 50 percent’s income growth in the 21st century is not as strong as it appears, and that it may even fall behind in the next few years. Yet the prospects are not especially good for the upper 40 percent either, who depend much more heavily on wage growth to grow their incomes.

Wages grow fastest when the labor market is tight, meaning that demand for labor is strong, attractive employment offers are drawing people into the labor market, and worker power is high. As many economists have documented, worker bargaining power cratered in the waning decades of the 21st century as union membership declined and policy shifted in business’s favor. That led directly to the increase in inequality in the 1980s and 1990s and largely explains why wage growth has been so poor in the 21st century.

The second Trump administration is actively attacking what little bargaining power workers still hold by ending bargaining rights for federal workers, dismissing a member of the National Labor Relations Board (the independent federal agency tasked with protecting workers’ right to unionize) and two Equal Employment Opportunity Commission members, rescinding a Biden administration executive order that increased the minimum wage for federal contractors, and more (though many of these actions are being legally challenged). Despite these attacks, as of this writing, the labor market remains relatively strong, but signs of declining business and consumer confidence could signal weakening in the near future.

In the face of reduced bargaining power and a flagging labor market, U.S. income inequality is likely to start increasing again. The Trump administration and the Republican-controlled Congress are pursuing cuts to multiple government transfer programs for which benefits are concentrated at the bottom of the income distribution. As discussed above, the bottom 50 percent is increasingly dependent on these income supports to keep up with income growth along the rest of the distribution.

In recent years, it has become conventional wisdom that inequality has declined slightly in the 21st century. While this view is not inaccurate, Equitable Growth’s new Inequality Tracker shows where things stand in more detail in the United States: Inequality is very high, relative to other eras of U.S. economic history, but it can still go higher.

Over the past 20 years, in the absence of wage growth, the government has propped up households in the bottom 50 percent with increased transfer payments. Meanwhile, without the benefit of higher transfer payments, the upper 40 percent has fallen behind. At the same time, the top 10 percent of the income distribution has continued to grow its income share thanks to gains in business and asset income. Unless wage growth returns to trend or the federal government undertakes significant expansions of social programs, this moment of stable inequality is unlikely to last.


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The distribution of capital gains in the United States

Authors:

Cole Campbell
, Federal Communications Commission
Jacob A. Robbins, University of Illinois at Chicago
Sam Wylde
, University of Illinois at Chicago

Abstract:

Booming stock, housing, and private business markets have driven large capital gains in the United States, averaging 20% of national income over the past two decades. Using internal IRS tax return data, this paper studies the distribution of these gains, and their contribution to income inequality and tax progressivity. We find capital gains to be highly concentrated, with 75.7% flowing to the richest 10% and 45.3% to the top 1%. Capital gains substantially increase inequality, raising the top 1% share of income to 21.0%, compared to 18% in their absence. Due to low realization levels, effective tax rates on capital gains are only 5%. Accounting for capital gains reduces the progressivity of the tax system, with flat rates across the Haig-Simons distribution. We document evidence of substantial heterogeneity in returns and cap rates across income groups. Richer individuals have higher owner and tenant occupied housing returns, own businesses that sell for higher multiples, and lower property tax rates.