Over the past 50 years, increases in women’s participation in the labor force and immigration have resulted in more women, Hispanics, and Asian Americans in the workforce. New data below from a forthcoming EPI report show that the working class is more diverse than ever before—no matter how you define it.

When defined by education, the working class is nearly half workers of color

The traditional definition of the working class comprises workers with less than a bachelor’s degree. Under this definition, in 1979, the working class was over 80% white. Today, workers of color collectively account for nearly half of the working class.

Working class by race and ethnicity

• 52% white
• 26.8% Hispanic
• 15.1% Black
• 4.7% AAPI
• 1.4% Native American

Working class by gender

• 56.4% men
• 43.6% women

When defined by income, the working class is similarly diverse

The working class could reasonably include more college graduates and traditional “white-collar workers” than were previously considered. That’s because the wage boost from getting a college degree is lower than it used to be, and underemployment—along with racial and gender pay disparities—can mean the economic status of graduates of color and women is more like some nongraduates.

By this broader measure, the working class can be considered the bottom 75% of U.S. households, regardless of education level or job type. This works out to a family income of below $150,000 per year.

Under this definition, the working class remains similarly diverse in terms of race and ethnicity. While men are still a majority of the working class, a larger share of women fit within this definition of working class, given lower pay in jobs predominantly held by college-educated women.

Working class by race and ethnicity

• 53.1% white
• 24% Hispanic
• 15.2% Black
• 6.5% AAPI
• 1.2% Native American

Working class by gender

• 52.5% men
• 47.5% women

However you define it, today’s working class is diverse by race, ethnicity, and gender. Improving economic conditions for today’s working class requires policies that meet the needs of all these workers.  

Source: Author’s analysis of pooled 2024–2025 Current Population Survey basic monthly microdata from EPI Microdata Extracts, Version 2026.8.13, https://microdata.epi.org.

This is the first brief in a series exploring comprehensive federal policy recommendations around AI and workers.

Introduction

Amid the seemingly endless predictions about AI, one point is essential to remember: How this plays out is not predetermined. Policy choices determine whether workers are helped or harmed by technological change. Even without AI, many workers already face harmful disruptions. Every year, 20 million workers are laid off in the U.S. economy1—due to employer mismanagement, once-profitable products becoming less so, offshoring, automation, and other factors. For individual workers, losing a job for any reason and for any period of time is traumatic and damaging in large part because we lack adequate social insurance programs to smooth those transitions.

As lawmakers debate how to best regulate AI deployment in our workplaces, today’s priority should be to strengthen the safety net for workers in any scenario and to acknowledge how AI is already affecting workers’ rights, protections, and livelihoods. Decades of underinvestment, coupled with attacks on unions and other labor supports, have left workers without an adequate safety net.

We can improve our current systems to better provide livable benefits for workers who lose their jobs because of large-scale economic shocks that are not their fault and outside their control. We can also learn from other periods of workforce disruption—the COVID-19 pandemic, trade-related shocks, and the 2008 recession—about which policy choices were effective and which fell short.

When workers lose their jobs due to factors outside their control, they are considered “displaced” or “dislocated.” If they meet certain requirements, these workers are eligible for unemployment insurance (UI). To strengthen outcomes for workers, this brief will provide recommendations to:

• increase UI benefit amount and duration
• expand and standardize eligibility to receive benefits
• align employer incentives with worker access to benefits
• center worker needs and power
• strengthen data infrastructure to support workers

These recommendations should be considered amid conversations focused on creating a stand-alone unemployment program geared toward AI-driven job loss. These discussions should weigh considerations and potential pitfalls, including:

• a blank slate for program design
• relevant roles for key stakeholders
• eligibility criteria challenges
• the allocation of resources, time, and awareness to be effective
• reauthorization vulnerability

If policymakers are serious about easing the impact of AI-related job transitions for workers, the priority solution should be strengthening already existing social insurance programs to reduce the economic consequences of losing any job and to provide adequate support to workers while they seek other employment.

Changes to the current system or establishing a new program will require robust resources, including time, money, and expertise. This investment can help all workers, regardless of their risk of AI-based displacement. With a strong safety net, workers who lose their jobs can get the assistance they need, including the opportunity to find work that is well suited to their skills and experiences, and businesses are more inclined to improve their practices because they know workers aren’t trapped in their current jobs by economic necessity.2 This moment presents an opportunity to strengthen the labor market for everyone and to ensure workers have the safety net they deserve.

How to strengthen our current system

Any effective approach to fixing the UI system must be comprehensive and should apply regardless of whether a worker is displaced due to AI. Numerous experts have weighed in on the best approach—including the National Academy of Social Insurance (NASI) Unemployment Insurance Taskforce,3 the National Employment Law Project (NELP),4,5 and The Century Foundation,6 among others. This brief draws from those recommendations to strengthen outcomes for workers. Other important issues, such as modernizing UI system technology and infrastructure, fraud detection and prevention, and the use of AI in benefit determinations and delivery, also shape worker outcomes but fall outside this brief’s scope.

Increase benefit amount and duration

First and foremost, UI should be designed to ensure that workers can afford housing, food, and other essentials during their period of joblessness. The percentage of wages that UI replaces for workers has declined over time and has not kept pace with inflation.7 In 2025, national average UI benefits replaced well under half of national average wages.8 This gap leaves workers across the income spectrum unable to maintain their standard of living and can push those whose earnings were close to the minimum wage into poverty.

Ensure benefit amounts are consistent across states

Benefit amounts vary across states. In Arizona and Florida, UI benefits replace less than 15% of average weekly wages.9 In some states, the weekly benefit amount is just $222 per week.10 While state variation in benefit amounts hurts all workers in stingy states, it weighs especially heavily on Black and Hispanic workers.

One recent study finds that differences in state rules cause the wage replacement rate for Black workers to be meaningfully lower than the rate for white workers, and that the discrepancies harm overall well-being.11 These disparities compound. Even among those likely eligible, Black workers are less likely than white workers to receive UI benefits—a gap explained primarily by structural factors, not a difference in eligibility, that has held steady for three decades.12

Wage replacement rates should be consistent across states. A recent federal bill has proposed changes to increase the replacement rate to 75% and provide additional weekly funding for dependents.13 Given growing wage inequality, the rate also should vary by income level. In one proposal, the lowest earners would receive benefits that represent 85% of their wages.14

Extend the duration of benefits across states

The duration of benefits also varies greatly from state to state. Until 15 years ago, eligible workers across the country had access to 26 weeks of benefits, a generally agreed-upon standard.15 After the Great Recession however, federal law barred states from cutting benefit amounts, so many states instead cut the duration of unemployment benefits to stabilize their trust funds and lower tax rates for employers.16 Some states now only provide 12 weeks of benefits, a short bridge to find a new job well-matched to workers’ skills and experiences.17 A minimum of at least 26 weeks of benefits should be a uniform requirement across states.

Workers cannot currently depend on the Extended Benefits program, which was intended to provide support during economic downturns by providing additional weeks of benefits during periods of high and rising unemployment. The triggers for Extended Benefits have not been effective, leaving workers to wonder if they are available. In their absence, workers must rely on temporary programs funded by Congress, which depend on political priorities.18 More reliable triggers, higher wage replacement levels, and a longer duration of benefits would make the Extended Benefits program more effective.19

Expand and standardize eligibility for benefits

Only certain workers are eligible for UI, leaving others stranded without benefits if they lose their jobs. Eligibility criteria and the base period used to calculate benefits are set by state law, rather than federal statute. This state-by-state variation can make it difficult for workers to know whether they qualify for assistance and plan accordingly.

Generally, the group of workers ineligible for benefits includes independent contractors, job seekers who have not been recently employed, and those who have exhausted their benefits. Some employers have incorrectly classified many workers as independent contractors, and this misclassification prevents those workers from requesting access to the UI benefits to which they would otherwise be legally entitled.20

UI should cover a broader range of workers, including part-time workers, independent contractors, job seekers who have not been recently employed, and seasonal and temporary workers. During the COVID-19 pandemic, Congress tasked states with implementing new UI programs for gig and platform workers who fell outside of the usual verification system, creating significant challenges.21 Barring changes to account for the unique situation of these workers, these same issues will arise again.22 By incorporating these workers into the UI system now, instead of waiting for a crisis, future challenges can be mitigated.

Policymakers should also consider stronger presumptive eligibility standards, under which workers are presumed eligible for benefits and paid promptly, with the burden placed on employers or the state to prove otherwise. Lowering the barriers for workers to receive benefits could meaningfully increase uptake among workers who currently go without benefits.

Align employer incentives with worker access to benefits

All eligible workers should be able to access UI benefits if they want them. State UI programs are generally financed through employer experience rating: Employers pay more taxes when they lay off more workers who are eligible for UI.23 Therefore, the system’s setup incentivizes employers to limit their tax liability by restricting eligibility for the program in different ways. This can include not hiring certain workers as employees, not proactively informing workers about their eligibility, attempting to reclassify workers as independent contractors, and other forms of suppressing UI program access.

A Bureau of Labor Statistics survey found that only about a quarter of workers who were unemployed in 2022 applied for benefits.24 Further, a recent survey found that 19% of recently unemployed workers encountered actions from an employer that were meant to deter them from applying, in addition to a quarter of all UI filers who said that their employer contested their benefits.25 Low-income workers more frequently reported employer contestations , and workers who reported contestations of their claims by employers were less likely to receive benefits and to experience greater material and psychological burdens during the filing process.26 There is a real opportunity to better align employer incentives to support workers in accessing UI benefits.

Presumptive eligibility, discussed above, would address some of these access barriers by shifting the burden of proof away from workers, but it would not resolve the underlying incentive employers have to minimize their tax liability. There have been many proposals for how to address this issue: broadening the tax base, payroll contributions from employees to UI, or increasing state taxes to fund programs.27 Most basically, employers could pay taxes based on the total number of workers they lay off, not just those eligible for UI.28 These questions are tied to broader considerations about how to finance a more effective program.

Center on worker needs and power

The UI system should be structured around ensuring that workers have the support they need as they seek reemployment. This requires a real investment in active labor market policy, including communicating with workers and unions about their needs in order to align training and placement. Congress should allocate funds to revitalize the Employment Service in the U.S. Department of Labor, which once played a key role in supporting reemployment.29 For example, in a 1986 New Jersey pilot program, job search assistance measurably helped dislocated workers return to work sooner and increased their earnings.30 A well-resourced and staffed U.S. Employment Service can leverage state labor market information—frequently used by employers—to help job seekers find opportunities aligned with their skill sets.31

Worker organizations can also play an important role in the delivery of benefits, including facilitating training and connections to job search assistance.32 In 2022, unemployed people who were members of a union were twice as likely to apply for UI benefits, and among applicants, 30 percentage points more likely to receive those benefits.33 This sizable gap suggests that when workers have organizational support navigating the UI system, they are far more likely to receive the benefits they are entitled to, reinforcing the case for involving worker organizations directly in UI outreach, filing assistance, and perhaps even delivery. Furthermore, unions routinely negotiate with employers, both in collective bargaining agreements and when bargaining before layoffs, to secure agreements that employers will not contest workers’ applications for UI benefits.

In some Northern European countries, unions are responsible for administering unemployment benefits, and scholars have found that this system leads to stronger unions and worker voice in the economy.34 Policymakers in the United States should consider how unions and other worker organizations could deliver unemployment benefits to workers.

Strengthen data infrastructure to improve outcomes

State workforce agencies collect quarterly wage records from employers to facilitate UI administration to gauge eligibility for benefits as well as benefit levels. States share wage records with the federal Census Bureau, and these data are included in longitudinal data sets that can follow workers over time. These data are used for both research and the administration of other policies (such as facilitating child support payments or tracking the performance of job training programs). Wage records provide an important but limited set of information that varies by state. A growing number of states have expanded their wage records to include additional information such as job titles, total hours worked, and job location.35

State-level data are a valuable source of information about what is happening to workers, but the lack of standardization across states makes it difficult to gain a clearer picture of employment. To remedy this, lawmakers should create standardized requirements for enhanced wage records to analyze who is losing their job and where workers are finding new opportunities.

The enhanced information coming from states would be especially useful with the advent of AI since no single federal data source can reliably track how AI adoption is reshaping demand for specific occupations in real time or identify when firms are reducing jobs through attrition. Further, workers would benefit from better information about opportunities that align with their skill set.36 Better integration with job posting data—including the National Labor Exchange—and reemployment systems would help workers navigate the job-search process.

Considerations for a stand-alone program

The UI system should be improved regardless of how AI affects employment and job opportunities. Additionally, some policymakers have suggested creating a stand-alone program geared toward AI-driven job loss. There is precedent for this approach. Congress has acted nine times since 1958 to create temporary, additional UI benefits, most recently during the COVID-19 pandemic.37 There is much to be learned from successes and challenges of these previous programs.

Some of these programs also included benefits or services beyond unemployment insurance for workers. For example, Trade Adjustment Assistance has, at various points, included relocation assistance, training programs, a health coverage tax credit, and wage insurance for older workers who took a lower-paying job.38 A new stand-alone program could similarly go beyond cash benefits, offering workers support to develop new skills, cover the costs of a transition, or find new opportunities.

Blank slate for program design

A new program can address the key structural issues with the current system discussed in the previous section. Any new program should be uniform across states so that benefit levels, duration, and eligibility are consistent for every worker regardless of where they live. A new program also presents the opportunity to build in the other improvements outlined above, including benefit levels set to a livable amount, expanded eligibility, and stronger data infrastructure. A new program could also adopt more fundamental changes to the claims process, such as the presumptive eligibility standards that Michigan moved toward during the COVID-19 pandemic.39

As discussed in the worker power section, a new program should be explicitly structured around building worker power, for example, by involving worker organizations in program administration or benefit delivery. Further, a new program can focus on effective job placement by leveraging relationships between employers, unions, and other worker organizations.

Finally, a new program should also be designed to avoid UI’s employer-financing structure, which—as discussed—in most states, disincentivizes employers from making sure workers get the benefits they are due. Left unaddressed, that same structure would allow employers to game or underreport AI-related job loss in a new program.

Relevant roles for key stakeholders

A successful program requires effective coordination among stakeholders. As with UI and previous stand-alone programs, states would likely retain a central role in delivering benefits and services, given their existing infrastructure and more direct knowledge of local labor market conditions. Local agencies can provide labor market information to workers, worker organizations, and employers to facilitate job placement. Any program should carefully consider how to balance flexibility for states to tailor the program to meet local needs, while maintaining strong, uniform standards across states.

As discussed, worker organizations and unions can play a central role in program administration. Worker organizations can support workers in accessing relevant benefits and training opportunities, ensuring that worker needs and outcomes are central to programmatic strategy and implementation.

Employers bear significant responsibility for the program’s success. They are often the first to know a layoff is coming and should proactively connect workers to available services, for example, by supporting on-site services when requested by state or local Rapid Response teams. Employers can proactively share specific information about their talent and skills needs with labor agencies and worker organizations, and hire workers during or after relevant training.

Eligibility criteria challenges

Creating clear and consistent eligibility criteria will be a significant challenge in establishing a stand-alone program for workers affected by AI-related job displacement. For instance, a program to compensate Department of Energy workers harmed by nuclear materials has faced significant challenges determining eligibility, including the complexity of reconstructing historical exposure to nuclear materials to establish causation.40 Challenges in establishing causation have also been an enormous barrier to worker relief through the Trade Adjustment Assistance program.41

In another example, some pandemic unemployment assistance benefits are still hung up over eligibility disputes years later.42 And from the start of the pandemic, there have been hotly contested debates about who should receive benefits.43 Moreover, concerns about fraud can also complicate eligibility determinations. In the wake of fraud during the COVID-19 pandemic, many states adopted stricter verification requirements to confirm eligibility.44 A new program focused on AI-driven job loss would need to balance similar integrity concerns against the risk of preventing eligible workers from receiving the benefits they are due.45

It is virtually impossible to systematically link job loss with AI adoption. In many instances, AI’s effects on a worker or industry may be indirect. For example, workers may lose their jobs in part due to AI adoption months or years earlier or because of broader economic disruption caused by AI’s impact on different industries. Even setting aside these implementation challenges, restricting eligibility to AI-driven job loss raises a separate concern: fairness. AI is not the only source of economic disruption. Global trade (including offshoring and outsourcing) and the green energy transition continue to displace workers across industries.

Other workers should be entitled to the same benefits as those directly displaced by AI. Drawing arbitrary boundaries around a single cause of job loss will create inequities, a risk compounded if states must independently interpret what counts as AI-driven job loss, therefore creating inconsistent standards nationwide.

Resources, time, and awareness to be effective

Standing up a new program will take significant time and resources. In addition to providing benefits, this includes making meaningful investment in technological systems and program administration, a particular challenge in light of years of underinvestment in modernizing UI systems.46 Federal and state governments need adequate resources for user experience testing, efficient application determinations, coordination with relevant partners, data collection and analysis, and programmatic evaluation. The challenges of implementing relief programs during COVID-19 are instructive. Slow initial payments, overwhelming caseloads that strained public servants, technological breakdowns, and significant confusion about eligibility requirements demonstrated the need to proactively develop systems that can respond more nimbly in times of crisis.47

Starting a new program also requires sustained public outreach, as new and stand-alone programs have historically struggled because of a lack of public familiarity. For example, over half of workers did not know they had access to emergency sick leave during COVID-19.48 In another example, when the Reagan administration made changes to the Trade Adjustment Assistance program, applications plummeted, perhaps because many workers believed the program had been abolished.49 Further, most workers did not know that other services including training, job counseling, and relocation assistance were available through the program.50

A stand-alone program could also come at the expense of the existing UI system, which the vast majority of states say is underfunded.51 From 1999 to 2019, federal funding for UI administration declined by 30% on an inflation-adjusted basis.52 If policymakers decide to divert resources that would otherwise go to the existing UI system, the system’s further deterioration could harm workers served by that system in both the short and long term.

Reauthorization vulnerability in Congress

If an AI-specific UI program requires congressional reauthorization, it will be vulnerable to the difficulty of coordinating bipartisan action in Congress. Several previous programs have been subject to a sunset date, requiring periodic reauthorization to continue accepting new claims. Sunsets and other reauthorization requirements leave workers vulnerable to congressional inaction, especially if the impacts of AI on the workforce play out over an extended time period.

For an example of a program caught up in this type of reauthorization limbo, Trade Adjustment Assistance lapsed multiple times, including most recently in 2022, leaving additional workers without access to the program. Another example is The Emergency Unemployment Compensation program, which was created in 2008 and lapsed five times between 2010 and 2013, before expiring for good at the end of that year.53 This immediately cut off benefits for 1.3 million workers and for more than 3.6 million workers by the following September.54

Financing and the path forward

The current worker safety net has failed to expand enough to cover the basic realities of today’s labor market, and inadequate benefit levels, incomplete coverage, and diminished worker representation are persistent problems. Deployment of AI and related technologies in the workplace adds urgency to addressing these issues.

Implementing the recommendations in this issue brief requires a significant investment that should be considered, along with program parameters and design. As AI drives up stock prices and generates wealth for a select few, policymakers are considering how the public should share in these gains. Ideas include increasing taxes for wealthy individuals, closing the gap between labor and capital tax rates, taxing AI use, and taxing data center development, with the proceeds from these new taxes financing programs that redistribute income more broadly across the economy. Considerations for potential taxation approaches will be discussed in a forthcoming brief.

This moment requires big thinking and corresponding action. While AI drives changes to the economy, improvements to the worker safety net are long overdue. We can learn from the past to improve the labor market for everyone.

Acknowledgments

Angela Hanks, Alex Hertel-Fernandez, Ben Zipperer, Gillian Gutierrez, Jacob Leibenluft, Janelle Jones, Josh Bivens, Michele Evermore, Patrick Oakford, Raj Nayak, and Stephen Nuñez.

Notes

1. Bureau of Labor Statistics, “Layoffs and Discharges: Total Nonfarm” [JTSLDL]. Accessed from FRED, Federal Reserve Bank of St. Louis, October 2026.

2. Patrick Oakford, Josh Bivens, and Celine McNicholas, Federal AI Legislation: An Evaluation of Existing Proposals and a Road Map Forward, Economic Policy Institute, September 2024.

3. National Academy of Social Insurance, Unemployment Insurance Task Force, Unemployment Insurance Task Force Final Report, July 2024.

4. Amy Traub, Boosting Economic Resilience: Seven Ways States Can Support More Workers with Unemployment Insurance, National Employment Law Project, July 2025.

5. Michele Evermore, AI Is New. The Challenge of Mass Unemployment Isn’t. National Employment Law Project, September 2026.

6. Michele Evermore and David Balducchi, A Roadmap for Unemployment Insurance Reform, The Century Foundation, October 2023.

7. National Employment Law Project, Policy Advocacy Brief: Benefit Amounts, November 2023.

8. U.S. Department of Labor, Employment and Training Administration, “UI Replacement Rates Report,” Benefit Accuracy Measurement data. Public data prepared by the OUI Division of Performance Management, Accessed August 7, 2026.

9. Megan Rivera, Why Unemployment Insurance Alone Is Not Enough in the AI Era, Washington Center for Equitable Growth, July 2026.

10. Julie Su, Andrew Stettner, and Michele Evermore, Our Unemployment System Needs Modernizing. Trump Is Doing the Opposite. The Century Foundation, September 2025.

11. Daphné Skandalis, Ioana Marinescu, and Maxim Massenkoff, Racial Inequality in the U.S. Unemployment Insurance System, Washington Center for Equitable Growth Working Paper, July 2023.

12. Elira Kuka and Bryan A. Stuart, Racial Inequality in Unemployment Insurance Receipt and Take-Up, National Bureau of Economic Research Working Paper no. 29595, December 2021.

13. Office of U.S. Senator Michael Bennet, “Bennet, Wyden, Beyer Reintroduce Bicameral Bill to Overhaul Unemployment Insurance” (press release), July 16, 2025.

14. Josh Bivens, Melissa Boteach, Rachel Deutsch, Francisco Díez, Rebecca Dixon, Brian Galle, Alix Gould-Werth, Nicole Marquez, Lily Roberts, Heidi Shierholz, William Spriggs, and Andrew Stettner, Reforming Unemployment Insurance: Stabilizing a System in Crisis and Laying the Foundation for Equity, a joint report of the Center for American Progress, Center for Popular Democracy, Economic Policy Institute, Groundwork Collaborative, National Employment Law Project, National Women’s Law Center, and Washington Center for Equitable Growth, June 2021.

15. National Academy of Social Insurance, Unemployment Insurance Task Force, Unemployment Insurance Task Force Final Report, July 2024.

16. National Academy of Social Insurance, Unemployment Insurance Task Force, Unemployment Insurance Task Force Final Report, July 2024.

17. Julie Su, Andrew Stettner, and Michele Evermore, Our Unemployment System Needs Modernizing. Trump Is Doing the Opposite. The Century Foundation, September 2025.

18. Michele Evermore, “There’s a Growing Bipartisan Consensus to Fix Unemployment Insurance” (commentary), The Century Foundation website, July 17, 2024.

19. Michele Evermore, “There’s a Growing Bipartisan Consensus to Fix Unemployment Insurance” (commentary), The Century Foundation website, July 17, 2024.

20. Ismael Cid-Martinez, Nina Mast, Margaret Poydock, and Valerie Wilson, Misclassifying Workers as Independent Contractors Is Costly for Workers and Social Insurance Systems, Economic Policy Institute, April 2026.

21. Julie Su, Andrew Stettner, and Michele Evermore, Our Unemployment System Needs Modernizing. Trump Is Doing the Opposite. The Century Foundation, September 2025.

22. Adam Grundy and Lucie Alleyne, “Nonemployer Businesses Are Key Contributors to Gig Activities and Economic Growth Nationally” (blog post), U.S. Census Bureau website, July 1, 2025.

23. Michele Evermore, “There’s a Growing Bipartisan Consensus to Fix Unemployment Insurance” (commentary), The Century Foundation website, July 17, 2024

24. Bureau of Labor Statistics, U.S. Department of Labor, “Most Unemployed People in 2022 Did Not Apply for Unemployment Insurance Benefits” (blog post), The Economics Daily (TED), April 14, 2023.

25. Amy Traub, Alexander Hertel-Fernandez, and Sanjay Pinto, The Unemployed Worker Study, National Employment Law Project, April 2025.

26. Alexander Hertel-Fernandez and Alix Gould-Werth, “Employer Contestations and Access to Unemployment Insurance: Implications for Benefit Receipt, Material Hardship, and Administrative Burden,” Social Service Review 100, no. 1 (March 2026): 38–68.

27. Michele Evermore and David Balducchi, A Roadmap for Unemployment Insurance Reform, The Century Foundation, October 2023.

28. Josh Bivens, Melissa Boteach, Rachel Deutsch, Francisco Díez, Rebecca Dixon, Brian Galle, Alix Gould-Werth, Nicole Marquez, Lily Roberts, Heidi Shierholz, William Spriggs, and Andrew Stettner, Reforming Unemployment Insurance: Stabilizing a System in Crisis and Laying the Foundation for Equity, a joint report of the Center for American Progress, Center for Popular Democracy, Economic Policy Institute, Groundwork Collaborative, National Employment Law Project, National Women’s Law Center, and Washington Center for Equitable Growth, June 2021.

29. Michele Evermore, AI Is New. The Challenge of Mass Unemployment Isn’t. National Employment Law Project, September 2026.

30. Stephen A. Wandner, Solving the Reemployment Puzzle: From Research to Policy, W.E. Upjohn Institute for Employment Research, January 2010.

31. Michele Evermore, AI Is New. The Challenge of Mass Unemployment Isn’t. National Employment Law Project, September 2026.

32. Alexander Hertel-Fernandez, “Solidarity Insurance: Reimagining Unemployment Insurance as a Platform for Worker Power.” (policy brief), Political Economy Research Institute, University of Massachusetts Amherst, July 2026.

33. Bureau of Labor Statistics, U.S. Department of Labor, “Characteristics of Unemployment Insurance Applicants and Benefit Recipients—2022” (economic news release), March 29, 2023.

34. Bruce Western, Between Class and Market: Postwar Unionization in the Capitalist Democracies (Princeton, N.J.: Princeton Univ. Press, 1997). 

35. Michele Evermore and Will Raderman, The Case for Enhanced Wage Records: Lessons from States, National Academy of Social Insurance and The Niskanen Center, January 2026.

36. Michele Evermore, “There’s a Growing Bipartisan Consensus to Fix Unemployment Insurance” (commentary), The Century Foundation website, July 17, 2024.

37. Katelin P. Isaacs and Julie M. Whittaker, “The Fundamentals of Unemployment Compensation,” Congressional Research Service, IF10336, updated January 12, 2026.

38. Jacob Leibenluft, Lessons from Past Trade Adjustment Policies to Support Displaced Workers in the Era of Artificial Intelligence, Washington Center for Equitable Growth, March 2026.

39. Michele Evermore, “Michigan Unemployment Claims Processing,” testimony on behalf of National Employment Law Project to a hearing before the Michigan Legislature, Joint Select Committee on the COVID-19 Pandemic, May 21, 2020.

40. U.S. Government Accountability Office, Energy Employees Compensation: DOL Generally Followed Its Procedures to Process Claims but Could Strengthen Some Internal Controls, GAO-16-74, March 2016.

41. Jacob Leibenluft, Lessons from Past Trade Adjustment Policies to Support Displaced Workers in the Era of Artificial Intelligence, Washington Center for Equitable Growth, March 2026.

42. Julie Kay, “‘No Accountability’: Pandemic-Era Unemployment Benefit Delays Persist, 5 Years Later,” WCNC Charlotte, April 3, 2025.

43. Annelies Goger, Tracy Hadden Loh, and Nicole Bateman, Debunking Myths About COVID-19 Relief’s ‘Unemployment Insurance on Steroids,’ The Brookings Institution, May 2020.

44. National Employment Law Project, ID Verification, November 14, 2023.

45. National Academy of Social Insurance, “Testimony of Michele Evermore, Senior Fellow, National Academy of Social Insurance,” testimony before the U.S. House of Representatives, Committee on Ways and Means, Work and Welfare Subcommittee, March 5, 2026. 

46. Julie Su, Andrew Stettner, and Michele Evermore, Our Unemployment System Needs Modernizing. Trump Is Doing the Opposite. The Century Foundation, September 2025.

47. Michele Evermore, AI Is New. The Challenge of Mass Unemployment Isn’t. National Employment Law Project, September 2026.

48. Emma Jelliffe, Paul Pangburn, Stefan Pichler, and Nicolas R. Ziebarth, “Awareness and Use of (Emergency) Sick Leave: US Employees’ Unaddressed Sick Leave Needs in a Global Pandemic,” Proceedings of the National Academy of Sciences 118, no. 29 (July 20, 2021): e2107670118.

49. U.S. Congress, Office of Technology Assessment, Trade Adjustment Assistance: New Ideas for an Old Program, 1987.

50. U.S. Congress, Office of Technology Assessment, Trade Adjustment Assistance: New Ideas for an Old Program, 1987.

51. Bipartisan Policy Center, “Administrative Failures Plague State Unemployment Insurance Programs,” July 1, 2020.

52. Bipartisan Policy Center, “Administrative Failures Plague State Unemployment Insurance Programs,” July 1, 2020.

53. Katelin P. Isaacs and Julie M. Whittaker, Emergency Unemployment Compensation (EUC08): Status of Benefits Prior to Expiration, Library of Congress, Congressional Research Service, CRS Product Number R42444, August 11, 2014.

54. U.S. House of Representatives, Ways and Means Committee Democrats, Unemployment Insurance (fact sheet), 2014.

Today, despite the ongoing economic and social toll of Trump’s draconian mass deportation policy, prime-age Latina workers continue to drive much of the strength in the employment rates of Hispanic workers. But we also see signs of weakness for younger workers between the ages of 16 and 24. New data released this year also show that Hispanic adults and their families share growing concerns about their employment security. We highlight each of these dynamics below.

Prime-age Latina workers are writing much of the employment story for Hispanic workers in 2026  

To trace the performance of Hispanic workers since last year, we examine 12-month moving averages of the employment-to-population ratio for prime-age Hispanic workers (ages 25–54) available in the EPI Data Library. There are a few reasons for this that are important to highlight. First, our 12-month moving average smooths much of the month-to-month noise due to sampling size limitations. We also focus exclusively on employment rates because it is not influenced by changes in labor force participation in the way that the unemployment rate is. Lastly, by focusing on prime-age workers—who are less likely to be out of the labor force due to schooling or retirement—our analysis is less influenced by changes in college attendance and the aging of the population.  

As seen in Figure A, the average employment rate for prime-age Hispanic workers stands at a historic high as of August 2026. These workers have managed to make inroads in employment despite a sluggish labor market experiencing weak-to-modest job growth.  

This story of resilience amid uncertainty continues to be largely attributed to prime-age Latina workers, who have managed to not just maintain their employment rate from 2025, but to build on last year’s gains. 70.7% of prime-age Latina workers had a job between September 2025 and August 2026—a new record high. While a significantly larger share of prime-age Latinos work relative to Latinas, their employment rate remains largely unchanged and below previous peaks.

Figure A

Prime-age Latinas are even outpacing their peers, who have historically enjoyed higher employment rates but have been more adversely impacted by the weaker labor market. Figure B shows that the average employment rate of prime-age Latinas continued to rise through August 2026, while that of their Black and white peers declined or flattened. This is because Latinas are more heavily concentrated in some of the economic sectors leading the charts in job growth, such as leisure and hospitality. Despite these gains, Latinas continue to be disproportionately affected by the gender pay gap due to the compounding effects of discrimination and occupational segregation. 

Figure B

Young Hispanic workers have not seen their employment situation improve over the last year 

Not all Hispanic workers have avoided a worsening employment situation in the last year. For example, the employment rates of young Hispanic workers between the ages of 16 and 24 have struggled to maintain consistent gains in the last year. While the average employment rate for young Latinos is now improving after a sharp drop last year, employment among young Latinas is falling along with that of other young workers and recent graduates.  

More broadly, this uneven progress may help us understand why more than half of Hispanic adults expressed concerns about finding or keeping a job last year. These growing employment fears remind us how difficult it is to achieve broad-based employment gains in a labor market struggling to regain its footing amid a mass deportation policy that will cost millions of jobs and an uncertain macroeconomic environment that continues to reproduce inequality. 

Key takeaways

• The Child Care and Development Fund (CCDF) was created to provide child care for low-income families while parents work or obtain education and training. But the program is so underfunded that it provides subsidies to just 16% of eligible children. 
• Child care is so costly that a full-time minimum-wage worker in Alabama would need to work 29 weeks, from January to July, and use every penny of their earnings to cover the cost of unsubsidized child care for one infant. 
• The Trump administration is proposing a new plan to divert CCDF funds from current recipients and give the resources to married couples with a stay-at-home parent. This will result in low-income working families losing CCDF funds, leading to increased child care costs for everyone and possibly resulting in the closure of some child care providers. 

Reporting in The New York Times describes an upcoming proposal from the Trump administration to use funds from the Child Care and Development Fund to provide “parent-based child care” in which a married parent could receive financial assistance to stay home to care for their children, while the other parent works. Providing additional income to support economically struggling families, including support for family members who want to be full-time caregivers for children, is a great idea. Pulling the funds to do so from the Child Care and Development Fund is not. 

The CCDF was created in the 1990s to provide child care subsidies for low-income families, so parents, primarily mothers, could work or go to school. The program is severely underfunded, however. It serves just 16% of all eligible children and just 17% of eligible children, age 5 and younger. That leaves hundreds of thousands of eligible children sitting on waitlists. Worse, some states don’t maintain a waitlist or have simply implemented an “enrollment freeze,” turning eligible applicants away rather than adding them to a waitlist. 

Who are the families that rely on subsidized childcare? 

Not adequately funding the CCDF hits low-income families, families with infants and toddlers, and families headed by single parents the hardest. To even be eligible for the program, federal criteria require families to earn less than 85% of the state median income. And states can make the income requirement even more stringent. For example, in seven states, a family with an income above 150% of the poverty line—just 47% of the state median income in Florida or 41% in Ohio—would not qualify for child care assistance. In 20 states, a family with an income above 200% of the poverty line would not qualify. This is just 55% of the state median wage in Michigan. 

The most recent data on the characteristics of families served by CCDF show that in 2023, 82% were headed by a single parent. In many states, an even larger share of families participating in the CCDF program are headed by single parents: 95% in Alabama, 93% in Illinois, North Carolina, and Ohio, and 92% in Pennsylvania. These are families with little choice but for the head of household—mothers in 75% of cases—to engage in formal employment if the family is to survive.

Then there are parents of infants and toddlers, pre-school-age children for whom child care is the most costly. The program provides subsidies for children up to age 13, but younger children are more likely than older children to receive subsidies. This reflects the fact that infants and toddlers have the greatest need for care, but parents often face a shortage of affordable qualified providers. This is in part due to younger children requiring more qualified providers than older children require and smaller child-to-staff ratios. In a Pulse Household Survey, 15% of all parents reported not working because they were caring for children, but for parents of the youngest children aged 0 to 4, it was 35%. 

Consequences of moving forward with the Trump–Vance plan

If married couple families are added to the list of eligible families without substantially increasing funding to provide subsidies to all eligible families, as is reportedly proposed, it will do significant harm to families of all types, whether they are married or not and whether they rely on subsidies or not.

With the new strain on available funds, families currently relying on the CCDF could lose the subsidies that allow them to provide even a modest living for themselves and their children. Without the subsidized care provided by the CCDF, these families could work full-time for most of the year just to pay for child care. In Alabama, for example, a minimum-wage worker working full-time would have to work 29 weeks—the equivalent of working from January to July—and use every cent of those wages to be able to cover unsubsidized child care for one infant. In North Carolina and Ohio, these workers would need to work from January to October. 

These are parents who want to work to support their families but cannot afford unsubsidized child care. They also cannot afford not to work.

Reducing the availability of child care funding for working mothers and fathers will not only hurt families who rely on child care subsidies, it will hurt all families who rely on child care. Siphoning these funds away from working families—disproportionately Black single mothers—will also deprive child care providers of a key source of revenue, potentially leading them to charge other families more for care, be forced to shed staff, or even close down. With families in so many communities across the nation already experiencing a child care crisis, this would exacerbate the shortage issue. 

We should fully fund the CCDF and provide needed support to all families

So many American families are already struggling to pay for the basic necessities, including rent, food, and gas. In an economy that requires dual-earner households where possible, child care subsidies provide struggling families with some basic support at a time when prices continue to rise, and safety nets, including health care subsidies, food assistance, and even heating assistance, continue to be cut. It’s notable that instead of providing real solutions to the affordability pressures many Americans face, Vice President Vance—who has championed this policy—and Trump’s Department of Health and Human Services are proposing what is effectively an attack on single parents, working parents, and working women in an effort to center married households and to push a political and cultural agenda about supporting supposedly “traditional” values. We must invest in families, regardless of their composition—married couples, single mothers, or grandparents caring for their grandchildren. We should fully fund the CCDF to ensure all eligible families are supported. 

Key takeaways

• Years of government funding cuts are undermining the U.S.’s position as a global leader in providing the reliable statistical information that businesses and policymakers need for sound decision-making.
• The Trump administration has accelerated the funding cuts and worked to degrade the effectiveness and independence of data-collecting agencies.
• The Bureau of Labor Statistics (BLS) is a prime example of an agency whose data collection in areas like employment and wages is integral to our understanding of the economy’s health and whether it is heading into a recession.
• A decline in response rates to one of the BLS’s key surveys was already underway but, absent funding increases and survey modifications, it will be harder for economists and policymakers to make timely sense of changes in the labor market.

Historically, the U.S. has been a leader in providing reliable and timely statistical information to support business strategy and policymaking. The value of information provided publicly and free of charge to businesses, households, and governments is immense. Yet underinvestment over the past 15 years is a key reason why the U.S. lost its position on the cutting-edge of public statistical services worldwide.

Since the beginning of the second Trump administration, this underinvestment has accelerated, and the administration has made intentional efforts to degrade the effectiveness and independence of the federal statistical agencies (FSAs). This accumulation of threats to the effectiveness of the FSAs will rapidly degrade the value of the key public good they provide, unless policy changes course sharply.

This blog post provides just one example of how cumulative underinvestment has blocked the ability of a key FSA to respond to developments, making its data less reliable over time. The Bureau of Labor Statistics collects a range of necessary data tracking the performance of the U.S. labor market. This BLS data are a key input into high-stakes decisions across the U.S. economy—including for both public and private actors. For example, the Federal Reserve relies on BLS data about unemployment rates, payroll job growth, wage growth, and price indexes to set monetary policy. The more volatile the BLS data are from month to month, the worse the information that guides Federal Reserve decisions.

Private industry also relies heavily on these statistics. A 2018 survey conducted by the National Association for Business Economists found that 95% of businesses responded “yes” to the question: “Are government data important for analyses and forecasting that drive business decisions?” Employment and unemployment data produced by the BLS were rated as the most important data source for informing business decisions.

Yet over the past 15 years, the BLS has gradually lost personnel and funding, which has been undermining their mandate of producing timely, accurate statistics on wages, prices, and the labor market. More recently, the Trump administration’s choices to freeze BLS hiring has further strained Census field staff charged with collecting household survey data. Worst of all, the Trump administration took the unprecedented step of firing the commissioner of the BLS simply because the agency accurately reported data that the administration happened to find politically inconvenient.

Even without further blatant political pressure on the BLS’s independence, the agency will encounter growing difficulty in doing its job effectively in coming years. One of their most important efforts is the fielding of the Current Population Survey (CPS), a survey of thousands of households across the U.S. taken every month, which provides detailed employment and wage information. The CPS is the source data for the monthly estimate of the nation’s unemployment rate, for example. This is in turn a key criterion for assessing whether the economy is heading into recession. In recent years—after the COVID-19 pandemic—the response rates for the CPS have sharply declined. These declines, if not countered with greater investment in response rates, may make it harder for economists and policymakers to make timely sense of changes in labor market, particularly for populations that already have small sample sizes, such as rural areas or detailed demographic groups.

The rest of this blog post highlights the problem of falling response rates, demonstrates that they have made some labor market measures more volatile month to month, and shows that these falling response rates have occurred over the same period as the retrenchment in resources for the BLS.

Nonresponse reduces sample size in the Current Population Survey

The Current Population Survey asks questions about employment and other labor market characteristics to 60,0000 households or about 110,000 individuals every month. Between 2005–2016, the Current Population Survey household survey was able to steadily receive responses from around 107,000 people, ages 16 and older. However, as noted by others and shown in Figure A, the number of households responding to the survey has declined since the mid-2010s and then fell precipitously after the COVID-19 pandemic. In the first few months of 2026, just over 75,000 individuals, ages 16 and older, had responded to the monthly CPS.

Figure A

The decline in response rate has likely occurred for a few reasons. The Bureau of Labor Statistics notes that the rate of refusals had been increasing as early as the 1990s, likely as the world became more connected with computers and the internet, leading to less reliance on in-person interactions to conduct business. Social trust has also gone down over the past few decades, and the share of adults who agree that “most people can be trusted” has decreased by more than 15% since 1984.

More recently, the COVID-19 pandemic, coupled with concerns for privacy and distrust in the government, may be the reason that the rate of decline grew in recent years. The COVID-19 pandemic forced many workers to transition to remote work, and concerns about contagion limited overall social interactions, making response collection increasingly difficult. Additionally, concerns about privacy or retribution from the state felt by groups like immigrants may make some people more reluctant to answer questions for fear of deportation. 

Finally, distrust in the federal government, fueled by recent overtly political activity, could be behind some of the reduction in response rates. For example, when the Bureau of Labor Statistics published two consecutive months of large negative revisions to the number of payroll jobs in mid-2025, the Trump administration leveled charges—which were baseless and never backed up by any evidence—that the BLS had manipulated the data for political purposes and fired then Commissioner Erika McEntarfer. People are less likely to trust government if they think publicized information and facts are politically motivated. 

Smaller sample sizes are linked to less precision in key labor-market estimates

If the size of sampled households is large enough, declining participation does not have to significantly affect the reliability of statistics produced from the survey. However, if declines in participation reduce usable sample sizes too much, this can lead to estimates with less precision, which can reduce researchers’ ability to parse a signal from statistical noise in a timely manner, especially for economically vulnerable groups.

For example, because the unemployment rate for Black workers is volatile, it can be difficult to accurately diagnose labor market softness for this group. If the sample size is too small to generate statistical precision in each month, researchers will require increasingly more months of data to be able to diagnose labor market softness, which could jeopardize the timeliness of proper policy responses to support the labor market.

Every month, the Bureau of Labor Statistics publishes statistical significance summary tables, identifying whether changes in labor force indicators are statistically significant at the 90% level. BLS publishes these statistical significance tests for dozens of indicators across several demographic groups, including for Black workers. We collected these tables over time and documented the margin of error needed in order to claim a 1-month change in unemployment was statistically significant, shown in Figure B.

While the margin of error that is needed to claim a change is statistically significant varies with the level of unemployment rate, the reduction in precision from lower response rates is evident when we hold the unemployment rate constant. The two red lines in Figure B identify the effect size needed to claim statistical significance for a change from a starting unemployment rate of 7.3%. In November 2017, when the sample size of the labor force was 63,346, a 0.66 percentage point change in unemployment would have been considered a statistically significant change. In April 2026, when sample size of the labor force decreased to 45,416 respondents, a 0.84 percentage point change in unemployment is required to claim statistical significance.

If the declines in survey participation are not random across the U.S. population, estimates may also be biased, which runs the risk of conveying inaccurate information about the state of the economy. For example, if nonresponse is more likely to occur among unemployed respondents compared with employed respondents, the statistics derived from these samples may suggest labor market softness when there is none. These concerns are already materializing: The Census reported that nonresponse had biased income statistics from the CPS Annual Social and Economic Supplement upward by 2%–3% since 2020.

Researchers and field staff at Census and the BLS are aware of potential concerns of bias in their estimates and do their best to weight estimates using population counts from administrative data and other sources so that these issues don’t happen. However, if sample size declines continue on this trajectory, the BLS will need to create new methodologies and sampling strategies, all of which will require funding.

Steady throttling of BLS funding makes all decision-makers—public and private—less well informed

The declining precision of estimates in the Black unemployment rate is just one of the key indicators affected by a BLS that lacks resources to respond effectively to growing data collection challenges. Achieving a larger sample size for key surveys requires a well-functioning and well-funded BLS with personnel who can take on the challenges of administering surveys in the 21st century. Yet this is the exact opposite of what is happening. Figure C shows that from 2005 to the present, the staffing at the BLS went from roughly 2,500 employees to just over 2,150, a drop of about 15%.

Figure C

Funding has followed a similar trajectory. Since its high-water mark in 2010, the BLS budget has declined from $810 million to $636 million in inflation-adjusted terms, a decrease of 20%. These cuts don’t hurt just the estimates generated by the Current Population Survey. In the past couple of years, the BLS has been forced to reduce data collection for the Consumer Price Index and to discontinue certain Producer Price Indexes in an effort to cut costs. At a time when affordability and price changes are top of mind for U.S households and businesses, depriving public and private decision-makers of accurate and timely information about prices makes little sense.

Increased funding would allow the BLS to maintain all their current functions and implement new procedures to address declining sample sizes. In 2023, BLS began to modernize the collection process of the CPS to improve response rates by allowing online self-completion of the survey and other collection process improvements for certain data products. This BLS initiative is happening in parallel to similar initiatives in several other countries undertaking modernization efforts. The United Kingdom, the Netherlands, Australia, and Canada have all received funding to launch similar modernization efforts for their own household surveys to address declining response rates. However, the BLS requests for increased funding for the modernization efforts have not been fully granted.

The decision to steadily defund the BLS is especially striking when weighed against the large economic benefits provided by the agency and other federal statistical agencies. The BLS provides up-to-date precise estimates of economic indicators that policymakers and business leaders alike rely on. Previous research finds that increased economic uncertainty can have negative effects on the economy, proving the important role that the BLS plays. Moreover, some economists have estimated in 2025 that the BLS generates economics benefits of about $25 for every $1 spent on the agency’s budgets. The 2025 FY BLS budget was approximately $636 million, meaning the BLS currently generates about $15.9 billion in economic benefit. Across all agencies, in FY 2022, the combined budget request for statistical agencies was $7.1 billion or 0.3% GDP, yet the benefits have been measured to be around $770 billion.

Conclusion

At a time when more information on the economic and social well-being of people and communities is needed, not less, funding the BLS should be a top priority. Addressing nonresponse will require substantial effort and creativity to counteract declining levels of social trust and anti-government sentiment. It will, for example, require public campaigns to convey that information provided to the BLS is confidential and safe, and changes in methodology to render the correct statistical adjustments, such that the statistics generated are unbiased. 

Rather than tackle these challenges head on however, the Trump administration put forward a proposal that would reduce the number of statistics about rural and less populous substate areas that could be published without running the risk of disclosing personally identifiable information. These proposals are a lazy solution to the real but solvable problem of making public data widely available and fully confidential. They would provide less information on the economic and social well-being of citizens, likely leading to delays in accurately diagnosing economic and social problems.

When agencies like the BLS are underfunded and understaffed, they aren’t able to conduct the critical functions of their agency or serve the public to the degree their mission entails. Funding for these organizations shouldn’t be up for debate, given how strong of an economic benefit they deliver.

Introduction

For Black Americans, public-sector employment has historically provided a pathway to better, more equitable and secure job opportunities compared with available private-sector jobs. The federal government has played an especially vital role in establishing a robust Black middle class in the Washington, D.C. metro area. According to the 2023 American Community Survey, roughly 2 out of 5 Black adults in the D.C. metro area were college graduates, Black median household income was nearly $90,000 and the Black homeownership rate was 52.8%. Postal service jobs have been particularly valuable to Black workers without college degrees because of the uniform wage and benefit structure (all postal employees who have the same job title and job tenure are paid the same nationwide) and higher pay relative to comparable private-sector employment. With a minimum education requirement of a high school diploma, the median hourly wage of a postal worker is 43% higher than the typical high school graduate. While federal employment has opened the door to social and economic mobility for generations of Black Americans, it has often been the battleground and served as a compass in setting higher labor standards and equal employment policies in the United States.

Opportunity. Backlash. Resistance. Change: A brief history of Black federal workers

The history of Black workers employed in the federal government dates to the Civil War when the federal government hired its first Black employee in the Treasury Department in 1863. In time, the federal government quickly became the largest employer of formerly enslaved people, with large concentrations in the military and the U.S. Postal Service (USPS). By 1912, the federal government was the largest employer of Black Americans in the nation, including highly skilled Black workers who were hired in high-ranking white-collar positions.

One of the earliest actions aimed at weakening the position of Black federal workers came shortly after the inauguration of President Woodrow Wilson. In 1913, Wilson racially segregated the USPS and Treasury department—the first federal agencies to employ, and in the case of USPS, promote Black workers to management positions. The administrative practice of segregating the federal workforce extended to the demotion of Black civil servants from white-collar positions, at-will firings, and refusal to fill open jobs with qualified Black candidates. Later that year, a group of Black workers formed the National Alliance of Postal Employees, the first industrial union in the federal service, to resist the administration’s racist tactics.

In the 1940s and 1950s, Presidents Franklin D. Roosevelt, Harry S. Truman, and Dwight D. Eisenhower each issued executive orders that took measured steps to undo the overtly racist and discriminatory federal employment practices put in place by Wilson. Those orders were largely directed at national defense industries, armed forces, and government contractors in response to the demands imposed by World War II. But, throughout the 1950s and 1960s, civil rights activists pushed the federal government to do more to expand its hiring of Black workers. In response, President Eisenhower’s Executive Order 10590 established the President’s Committee on Government Employment Policy (PCGEP) in 1955. The PCGEP involved federal agencies more fully in the government’s anti-discrimination agenda and called for departments to develop regulations in accordance with its mission to stop all discrimination in all federal employment. However, the group lacked the enforcement power necessary to accomplish that mission.

Over the following decades, job prospects for Black federal workers were most improved by a series of executive actions and legislation introduced in the 1960s and 1970s. On March 6, 1961, President John F. Kennedy’s Executive Order 10925 required the federal government and federal government contractors to practice non-discrimination in their hiring practices. Additionally, E.O. 10925 established the President’s Committee on Equal Employment Opportunity (PCEEO) to monitor non-discrimination on government contracts. In a move that distinguished the PCEEO from prior ineffective, enforcement-lacking efforts like Eisenhower’s PCGEP, Kennedy granted policy-making authority to the group led by Vice President Lyndon Johnson and Secretary of Labor Arthur Goldberg.

On January 17, 1962, Kennedy signed Executive Order 10988 which allowed limited collective bargaining for federal employees for the first time and opened the door to federal employee union membership under three different classifications: informal, formal, and exclusive recognition. Public-sector collective bargaining would play a central role in maintaining the quality and accessibility of federal jobs through labor contracts that fostered transparency with clearly defined policies and pay structures. Labor contracts also served to limit discriminatory outcomes while providing critical protections and recourse against other forms of exploitation or mistreatment.

The power of Kennedy’s executive orders was reinforced when Title VII of the historic Civil Rights Act of 1964, signed by President Lyndon Johnson, formally prohibited employment discrimination in the United States and established the Equal Employment Opportunity Commission (EEOC) to enforce the law. The Equal Employment Opportunity Act of 1972 extended Title VII protections to cover more employers and strengthened the enforcement power of EEOC by allowing them to litigate against employers, including federal agencies, who violated Title VII.

Within the span of the 1960s and 1970s, the federal government had established a clear definition of what it meant to be an equal opportunity employer, leveraged its purchasing power to compel private contractors to meet similar standards, extended limited collective bargaining rights to federal workers, and assigned the EEOC a central role in enforcing anti-discrimination law. Black federal employees also continued to support and advocate for one another, establishing the non-profit organization, Blacks in Government (BIG), in 1975. The progress made during 1960s and 1970s would be gradually chipped away in the decades that followed. 

Federal job losses since the 1980s

During the 1980s, the Reagan administration took a swipe at federal employees, unions, and anti-discrimination enforcement, but that record pales in comparison to more recent developments. While Reagan announced plans to make federal job cuts, and infamously fired 11,000 striking air traffic controllers in the early 1980s, federal payrolls actually rose by more than 200,000 during his presidency before dropping by 427,000 during the 1990s and taking another hit of 244,000 between 2010 and 2014. Since the 1980s, the postal service, a major employer of Black workers, has been under sustained assault, including attempts to undercut employee compensation and the agency’s solvency.

In 2025, the Trump administration took steps to implement massive cuts to the federal sector and reverse course in the government’s pursuit of equity by rescinding at least a dozen prior executive orders related to racial and/or gender equality and terminating workers in DEI departments within federal agencies. In a series of legally challenged actions, Trump fired decisionmakers at the EEOC and National Labor Relations Board (NLRB)—rendering two independent agencies responsible for enforcing workers’ rights non-operational for several months—while his newly created Department of Government Efficiency (DOGE) made severe staff reductions and eliminated entire federal agencies. Trump’s attacks on the federal workforce have also included attempts to limit the approval of collective bargaining agreements with federal workers. The actions of Trump and DOGE contributed to the loss of 288,000 federal jobs between January and December of 2025, based on data from the Bureau of Labor Statistics. Ironically, while federal jobs once provided Black workers relatively more job security, early evidence suggests the burden of federal job cuts has fallen disproportionately on Black women. The potential consequences of these actions go beyond job losses and include major implications for Black family incomes and racial and gender pay equity.

An accounting of the significance of federal sector employment for Black workers and families

As detailed in the history presented above, between 1941 and 1981, Black workers gradually improved their employment status in the federal government through collective and individual activism of groups like the National Alliance and Blacks in Government, within a context of official support for their rights through executive orders and landmark civil rights legislation. This improved employment status expanded the ranks of Black federal workers who were able to secure higher incomes. By 1970, the median household income for Black families was just $6,279 compared with a range of $7,178–$10,987 for those earning GS 5–8 salaries in the federal government. In fact, Black federal employees compensated between grades GS 5–8 were either close to or slightly above the national median of $9,867. This remains a factor today as the high concentration of federal employment and related professional job opportunities in the Washington, D.C. metro area helps to make metro D.C.’s Black median household income ($89,912 in 2023) one of the highest in the nation and well above the overall national median of $77,719.

Analysis of 2024 state-level data from the Office of Personnel Management (OPM) reveals that over 300,000 federal workers (excluding USPS) reside in the D.C. metro area, accounting for 60% of all federal workers in the District of Columbia and surrounding states of Virginia, Maryland, and West Virginia. Black workers are just over one-fourth of the federal workforce in the District of Columbia (28.8%), Maryland (27.9%), and Virginia (26%). While the D.C. metro area is home to the largest concentration of federal workers, over 90% of the federal workforce live and work outside the nation’s capital. Black workers account for at least one-fifth of the state’s federal workforce in 12 states beyond the D.C. metro area.

Implications of massive federal job losses and the unfinished business of equity

To understand the stakes of federal workforce contraction, it is necessary to compare the demographic and wage structure of federal employment with that of the broader labor market. As shown in Table 1, in 2023 and 2024, Black workers were 12.5% of the private-sector workforce, compared with more than a fifth (22.6%) of all workers in the federal sector—a share that also exceeds their representation in the entire public sector (16.4%) which includes state and local governments. Black women’s share of the federal workforce (12.8%) was double their share in the private sector (6.4%).

A national comparison of hourly wages at the median and for low-wage (10th percentile) workers demonstrates the clear monetary benefit of federal over private-sector employment. Figure A shows this is true across race and gender both at the middle and lower end of the wage distribution. The hourly wage of a typical (i.e., median) Black federal worker is more than 40% higher than that of the median Black worker in the private sector. Black federal workers—median and 10th percentile—also have higher wages than same gender white workers in the private sector. It is worth noting that these wage comparisons don’t account for the more generous benefits typically offered to federal and other public-sector workers, which further raises the value of their total compensation. The higher wages earned by federal workers largely reflect the higher share of college and advanced degree holders and higher rates of union coverage relative to private-sector employees. Less than 7% of private-sector workers are in a union or covered by a union contract compared with 35.9% of all public-sector workers and 29.5% of federal workers (see Table 1). While greater union coverage helps to boost wages and benefits for all workers, it is an even more important factor in raising wages of those for whom racial and gender discrimination further restrict individual bargaining power.

Another factor contributing to better pay outcomes in the federal government is the use of the Schedule (GS) pay scale which applies to over 70% of white-collar federal jobs. This helps to mitigate pay discrimination in the federal government by standardizing the qualifications and compensation associated with a specific position and consistent with experience, job performance, and local cost of living. On average, Black federal workers appear to experience only marginally improved pay equity over Black workers in the private sector, while the Black-white wage gap is much smaller in the public sector, overall.

In the federal sector, Black workers earn 12.6% less than white workers with the same levels of education, experience, union coverage status, gender, and state of residence, compared with 14.9% less in the private sector and just 3.8% less in the overall public sector (see Table 2). Although there is a sizable wage gap between Black women and white men across sectors, the federal sector gap (26.1%) is nearly 8 percentage points lower than the gap that exists in the private sector (33.9%). Given enforcement of the GS pay scale, remaining racial and gender pay gaps among federal workers likely reflect disparities in job positions and associated GS levels, a long-documented concern of Black federal worker advocates and activists. These disparities may stem from the underrepresentation of Black workers in higher-level, higher-paying positions, which can reflect differences across agencies in workforce demographic composition, occupational structures, and promotion rates. Notwithstanding the relatively higher economic position of many Black federal workers, these results epitomize the unfinished business of eliminating pay inequity and occupational segregation across all sectors of the labor market.

Conclusion

This brief summarizes the important role federal-sector employment has played in providing better job opportunities for Black Americans than have traditionally been available in the private sector. However, those outcomes have never been a given. A solid history of advocacy and activism by and on behalf of Black federal workers alongside others were critical in securing important wins through executive actions and policy change. Moreover, pushback against some of the most egregious violations of federal worker’s civil and worker rights have at times resulted in stronger, more broadly enforced labor and equal employment standards, improving outcomes to the benefit of all workers.

Key takeaways

• The 2025 Census data on earnings, income, and poverty may reflect how the Trump administration’s policy choices were beginning to impact the economic well-being of workers, families, and children last year.
• Last year’s economy was characterized by slowing job growth, rising wage inequality, and growing policy uncertainty. We expect to see little to no improvements in key economic indicators such as lower-end household income and supplemental poverty rates between 2024 and 2025.
• The 2026 story is still unfolding and is likely to be worse, given these factors: decelerating nominal wage growth, higher inflation, and the 2025 budget reconciliation law that will leave more families and children vulnerable to poverty.

Next week, the Census Bureau will release the latest data on earnings, income, and poverty for 2025. This data could show early signs of how the Trump administration’s policy choices impacted the economic well-being of workers, families, and children across the country. The initial strong recovery from the pandemic recession measurably slowed in 2025 as the labor market softened and the policy climate grew more uncertain. To help place the upcoming data release in context, we highlight key trends that have characterized the economic and policy landscape in 2025. Though the economy continued to soften as inflation worsened in 2026 and the safety net grew increasingly more difficult to access as a result of the Republican Budget Reconciliation Law, the data in the Census will only provide specific insights for living standards in 2025.

In summary, we find:

1. 1. The U.S. economy in 2025 grew more slowly than in 2024, adding fewer than half as many jobs—only 764,000 jobs compared with 1.825 million in 2024. The unemployment rate slowly rose over the course of 2025, and the hires rate was depressed, making it harder for young people in particular to break into the labor market. While the prime-age employment-to-population remained relatively resilient to labor market softening, prime-age Black workers experienced large declines in their employment rate.
   2. With more moderate inflation, strong nominal wage growth translated into decent average hourly wage gains between 2024 and 2025, but gains were not shared equally. Lower-end wage growth stalled in 2025, which could have implications for lower-end incomes and poverty rates.
   3. Because the Republican budget reconciliation law is making basic needs programs like SNAP increasingly more difficult for families to access, we don’t expect to see any significant improvements in supplemental poverty between 2024 and 2025. We expect to the see the full impact of the Republican law in the years ahead.
   4. While the release will only provide data for 2025, our examination of the economic and policy landscape for 2026 suggests that a weaker job market, safety net cuts, and high inflation will worsen outcomes.

The labor market recovery softened in 2025

Because the vast majority of people in the United States rely on labor market income for their economic well-being, the labor market data we already have for 2025 should provide some insights into what the Census data may tell us. Overall, job growth has slowed, and the unemployment rate has ticked up as employment rates softened, particularly for certain demographic groups.

After the tremendous rebound from the pandemic recession, the labor market cooled somewhat. Payroll employment growth went from 3.3 million in 2023 to 1.8 million in 2024 and then 764,000 in 2025. A slowdown would be expected after such a strong recovery, and the number of jobs needed to keep up with population growth declined with lower net immigration in the wake of Trump’s draconian mass deportation policies. Nearly 100,000 federal jobs (96,000) were lost in the massive DOGE cuts (when comparing annual averages, which obscure more massive downward trends later in the year), and even manufacturing employment faltered in Trump’s first year, falling by 156,000 jobs between 2024 and 2025. If not for job growth in health care and social assistance, overall payroll employment would have fallen outright.

This weakening led to a mild increase in the unemployment rate, from 4.0% to 4.3% between 2024 and 2025. Figure A displays the change in some key labor market indicators for certain demographic groups. While the overall unemployment rate rose modestly, the increase was far greater for young workers, ages 16 to 24. It’s likely that the depressed hires rate has made it harder for young workers to break into the labor market. Older workers experienced much milder increases in their respective unemployment rates.

The share of the population with a job—the employment-to-population ratio fell from 60.1% to 59.7%, a drop of 0.4 percentage points. Prime-age workers—those between 25 and 54 years old—were more resilient to the labor market softening. However, prime-age Black workers experienced a tremendous decline of 1.3 percentage points between 2024 and 2025. This weakness may show up in the income and poverty data released next week. At the same time, prime-age Hispanic workers experienced an increase in their employment-to-population ratio.

Figure A

Wage inequality increased in 2025

Employment changes alone have important implications for family and household income, but wages are also an important part of the economic story. Figure B illustrates several key price and wage changes between 2024 and 2025. Though the economy was a bit weaker, the labor market delivered strong nominal wage growth for private-sector workers, measured by the Current Employment Statistics. Nominal average hourly wages increased 4.0% between 2024 and 2025. Inflation moderated—remember this is before the spike in 2026—and therefore, real hourly wages rose a modest 1.5%.

Unfortunately, the gains were not broad based. Unlike the faster wage growth among lower-wage workers through 2024, lower-end wage growth stalled in 2025. While the fall wasn’t large, it reversed the trends experienced between 2019 and 2024. The stair-step increase in wage growth, as shown in the right half of Figure B, suggests a return to a K-shaped recovery, wherein higher-wage workers experienced much faster wage growth than those at the middle or the bottom. While stronger average wage growth and modest median wage growth may suggest modest improvements in median household income—though tempered by slower job growth—weaker low-end wages may translate into losses for lower-income households and possibly rising poverty rates, particularly for groups hit hardest by falling employment.

Figure B

Republicans weakened SNAP last year and any chance at poverty alleviation in the years ahead 

The end of the expanded social safety net in 2022 eroded all of the gains in poverty reduction experienced between 2020 and 2021. Since 2022, poverty has continued to climb. This unfortunate trend in poverty is unlikely to reverse course in the latest Census release for 2025. This is partly because the Republican budget reconciliation bill signed into law by President Trump in July of last year significantly cut and limited access to basic needs programs like SNAP, one of the most successful programs in our country’s fight against poverty and hunger. Because the implementation of these changes and spending cuts is still ongoing, we are unlikely to see the full impact of the Republican law in next week’s data.

In 2024 alone, SNAP lifted more than 3.5 million people out of poverty. Nearly 40% of these individuals were children (see Figure C). In fact, both SNAP and the National School Lunch Program (NSLP), which provides reduced-cost or free lunches to low-income children in public and nonprofit private schools, lifted more than 2 million children out of poverty in 2024. After refundable credits, these programs, along with Social Security, make up the most effective anti-poverty strategies for children in the United States.

Figure C

Instead of strengthening the country’s nutritional assistance programs to improve access and the adequacy of benefits amid growing food insecurity, the Republican reconciliation package cut funding for the U.S. Department of Agriculture (USDA), imposed strict and costly work requirements, and eliminated waivers for areas with chronically high unemployment. The ongoing implementation of some of these changes, including factors associated with staff limitations, has led to a decline in SNAP participation by more than 4.5 million people. This drop will not be entirely reflected in the upcoming poverty statistics since some of this decline occurred in 2026. Yet the cutting back of resources for USDA and SNAP initiated by congressional Republicans and the administration will continue to translate into higher poverty rates and increased food insecurity, as states struggle to implement the costly and harmful changes now required by the new law.

The administration has also taken steps to ensure that we don’t have the data we need to trace the painful impact of these changes on food insecure families. In September 2025, Trump’s USDA canceled the country’s leading survey that documented the magnitude and severity of hunger and food insecurity in the U.S. They claimed that the USDA survey and report  were “redundant” and “politicized.” Soon after this, the administration allowed SNAP benefits to lapse for the first time in the history of the program, while at the helm of the longest full government shutdown in U.S. history, lasting 43 days and creating a chaotic situation for SNAP beneficiaries, many of whom needed to turn to food pantries for help. 

As we will be reminded when the Census releases its poverty statistics for 2025, the impact of all these harmful policies hit Black and brown families with children particularly hard. This is because families of color are disproportionately more likely to rely on SNAP to avoid food insecurity, and children of color are also more likely to be burdened by poverty than their peers.

In 2021, the United States demonstrated to the world that it had the capacity to reduce poverty to historically low levels by expanding access to SNAP and other basic needs programs. In 2025, Trump and congressional Republicans showed the world that they were willing to gut basic needs programs to pay for tax cuts that disproportionately favor the wealthy. We should not be surprised when we fail at poverty reduction in the years ahead.

Next week’s data will be about the economic story of 2025. The 2026 story is still unfolding and is likely to have a worse ending.

As noted earlier, the earnings, income, and poverty statistics the U.S. Census will publish next week are for 2025. While we don’t yet know the full economic story for 2026, it is unlikely to be a more promising one. This is because the slowdown in job growth that began in 2025 has further solidified throughout 2026. This weaker job market continues to be particularly harmful to Black and young workers. The softer labor market in 2026 has also coincided with worsening inflation. Higher inflation is largely due to Trump’s ongoing war in Iran, which has already wiped out 1.5 years of real wage growth in a matter of months.

The policy landscape for 2026 also looks bleaker. The spending cuts to the U.S. social safety net that Trump signed into law in the summer of 2025 will continue to hurt the ability of families to access basic services like Medicaid and SNAP. This will leave increasingly more economically insecure families vulnerable to poverty and unnecessary hardship in the face of a worsening affordability crisis.

Raymond Windmiller, Executive Officer
Executive Secretariat
U.S. Equal Employment Opportunity Commission
131 M Street, NE
Washington, DC 20507

Re: Proposed Rule for Removal of Reporting Requirements (RIN 3046-AB37)

Dear Commissioners,

I write to submit this comment on behalf of the Economic Policy Institute (EPI), responding to the Equal Employment Opportunity Commission’s proposed rule to rescind and remove the requirements for filing the EEO-1, EEO-2, EEO-3, EEO-4, EEO-5, and EEO-6 reports1, and the recordkeeping and record preservation requirements related to these reports, under 29 CFR part 1602.

EPI is a nonprofit, nonpartisan think tank created in 1986 to include the needs of low- and middle-income workers in economic policy discussions. EPI conducts research and analysis on the economic status of working America, proposes public policies that protect and improve the economic conditions of low- and middle-income workers, and assesses policies with respect to how well they further those goals. For 18 years, EPI’s Program on Race, Ethnicity and the Economy (PREE) has been a nationally recognized source for expert analysis of the many ways that race, ethnicity, gender, class and policy decisions intersect to affect economic outcomes.

We strongly oppose the EEOC’s proposal to rescind the EEO reporting, recordkeeping and record preservation requirements. If implemented, this rule would undermine the Commission’s capacity to enforce federal laws against employment discrimination. Furthermore, this rule would deprive employers, researchers, policymakers and advocates of their ability to independently analyze and use this unique data source to develop and advocate for policies that support the EEOC’s mission of ending workplace discrimination.

The U.S. Equal Employment Opportunity Commission (EEOC) is a cornerstone in upholding the civil rights of U.S. workers. Established under the same law that officially prohibited employment discrimination (Title VII of the Civil Rights Act of 1964), the EEOC embodies the fact that effective federal laws against employment discrimination require consistent enforcement. For the last 60 years, EEO reports have been central to the agency’s capacity to enforce the law and to monitor and track the nation’s progress toward ending workplace discrimination.

That goal is still a work in progress, as documented in an extensive body of methodologically rigorous research by economists, sociologists and other social scientists. In what follows, we explain why the Commission’s proposal to rescind all EEO data collection would be counterproductive to reaching that goal and detrimental to the U.S. economy by:

• Summarizing the research on labor market discrimination that justifies the ongoing need for EEO reporting requirements;
• Describing how broad EEO reporting requirements help to rebalance power and information asymmetries between employers and employees; and
• Presenting estimates of how much discrimination costs the U.S. economy in economic output and average living standards.

Research and national data provide compelling evidence of persistent labor market discrimination against “minorities”

In their proposed rule, the Commission claims that EEO Reports “may encourage employers to discriminate against employees who are not considered ‘minorities,’ may promote racial stereotyping, and may encourage employers to engage in discrimination to avoid potential EEOC enforcement actions or to address perceived inequitable outcomes.” In addition to this being highly speculative, it is also inconsistent with what we know from research and national statistics. Large and persistent disparities in employment and pay of Black workers relative to white workers are among the most durable features of the U.S. labor market. Compelling empirical evidence points to discrimination as a significant factor in the persistence of those disparities.

EPI’s detailed expert analysis of Bureau of Labor Statistics (BLS) data shows that the significant racial disparities in unemployment that are observed at each level of education, across age cohorts, and among both men and women strongly suggest that education or skills differentials alone can’t account for the near constant 2-to-1 Black-white unemployment gap2.

These findings are consistent with field experiments revealing that Black job applicants with equivalent, and sometimes superior, credentials to white applicants are less likely to receive job callbacks3. One of the starkest audit study findings in this regard concludes that employers treated white applicants with criminal records more favorably than Black applicants without criminal records4. Researchers also found that when résumés of Black and Asian job applicants were stripped of clues of their racial identity, they received callbacks at a much higher rate than those that clearly indicated an applicant’s racial identity5.

While audit and correspondence studies have been criticized for not adequately capturing unobserved characteristics that might influence hiring decisions, newer studies have shown how robust these findings can be to such considerations6. In fact, subsequent field experiments reveal a pattern of hiring discrimination experienced by Black and Hispanic job seekers that remained remarkably constant over time, with white applicants receiving 36% more callbacks than Black applicants and 24% more callbacks than Hispanic applicants7.

EPI’s analysis has also shown that since 1979, less than half of the observed black-white difference in average hourly wages can be explained by differences in education, experience, or region—the main factors presumed to determine pay – and discrimination has consistently played a major role8. However, changes in this racial wage gap track closely with changes in policy, including civil rights enforcement, and with structural factors that affect wage inequality. According to trend analysis research, the narrowing of the gap from the late 1960s through the 1970s can be attributed to the passage of important civil rights legislation9, combined with the 1960s economic boom, active enforcement of anti-discrimination10 and affirmative action policy11, and the narrowing of the educational attainment gap between Black and white workers12. On the other hand, retrenchment on anti-discrimination policy was found to be a significant factor in the widening of the gap during the 1980s13. Since 2000, research has shown a troubling trend of larger discriminatory differentials among the more highly educated14.

Contrary to the Commission’s proposed justification for ending EEO reporting requirements, the research literature cited above offers no evidence of systemic discrimination “against employees who are not considered minorities”. The research, however, underscores the need for ongoing monitoring of employment and pay discrimination through the collection of EEO data.

Elimination of EEO data would worsen power and information asymmetries that undermine worker protections

In an essay published under EPI’s Unequal Power project, former EEOC Chair Jenny Yang explains that “in a system that places the primary responsibility for enforcing anti-discrimination laws on individual workers, who must file complaints with their employer or a government agency, the government plays a fundamental role in rebalancing the power disparities between workers and employers.”15 She further concludes that “policies that encourage employer transparency and require data collection to support prevention and accountability are essential to addressing the inherent information asymmetry workers face.”16

EEO data helps to provide the necessary transparency and accountability across major segments of the U.S. labor market, including private employers with 100 or more employees and federal contractors with 50 or more employees (EEO-1), apprenticeship programs (EEO-2), labor unions (EEO-3), state and local governments (EEO-4), elementary and secondary schools (EEO-5) and institutions of higher education (EEO-6)17.

While the Commission now argues that reporting requirements are too broad because they include non-discriminating employers along with those accused of discrimination, that feature is actually a strength of EEO data. As the nation’s only federally collected source of firm-level information on employment by race, ethnicity, sex, and job category, the EEO-1 provides EEOC investigators with the information they need to assess each individual claim within the context of a larger group of employers.

In addition to being used in this important first step of the charge intake process, these data can also identify potential patterns of systemic discrimination within an industry, occupation, or worksite location. This information helps to direct EEOC systemic enforcement and commissioner’s charges, enabling the EEOC to investigate and address discriminatory practices in cases where workers either lack information or fear retaliation for filing an individual charge of discrimination. Many state and local government Fair Employment Practices Agencies (FEPAs) also have data sharing agreements with EEOC, allowing them to utilize EEO data for local enforcement activities. Similar data collections are too costly for most FEPAs to undertake on their own. As such, EEO data address information and power asymmetries that make it difficult and costly for workers to identify and prove discrimination.

Elimination of EEO data would limit EEOC’s ability to support economic growth through reduced discrimination

Finally, the Commission claims that elimination of the EEO surveys is consistent with the policy underlying E.O. 14192, “Unleashing Prosperity Through Deregulation,” requiring agencies to be “prudent and financially responsible in the expenditure of funds . . . to alleviate unnecessary regulatory burdens placed on the American people.” However, the Commission is overlooking the cost discrimination imposes on the economy and the long-term consequences ending EEO data collection would have on the EEOC’s ability to reduce discrimination through the enforcement mechanisms described above.

Research shows that since the 1960s, the decline in workplace discrimination has contributed to a stronger economy and more inclusive labor force. A widely cited 2019 report concludes that reduced discrimination alone accounted for almost 8% of GDP per capita growth between 1960 and 201018. Extrapolating this estimate through 2024 and applying it to published national estimates of real GDP per capita, we estimate that reduced discrimination boosted average living standards by $4,932 per person since 196019. While it is difficult to precisely measure the EEOC’s impact apart from other forces, assuming the Commission’s role in reducing discrimination accounts for 10–25% of that growth, we estimate that EEOC enforcement, aided by EEO data, helped to boost average living standards by $493 to $1,233 per person since 1960. This estimated increase in average living standards applies to all people, not just those with proven claims of discrimination. Elimination of EEO data would compromise many of the EEOC’s tools for enforcing laws against employment discrimination, and as a result, undermine economic growth.

Conclusion

For years, the EEOC has been vastly under-resourced relative to the magnitude of its enforcement responsibilities, and EEO data is essential to directing those limited resources. Changes to the categories and definitions used in EEO forms over time represent the ways in which Commissioners have grappled with how to accurately capture individual markers of identity useful in detecting unfair influence over employment opportunities for members of legally protected classes.

Under prior administrations, EEOC has convened expert panels to evaluate EEO data collections. These panels were comprised of statisticians, economists, sociologists, legal scholars, and other practitioners with decades of expertise in statistical analysis, labor and civil rights law and the study of labor market discrimination. I have had the privilege of serving on two of these panels. In both instances, panel members expressed differing opinions with respect to data quality, what conclusions could be reliably drawn from the data, and how to best improve the data collection process. Undoubtedly, there were also likely differences in panel members’ political views, but I don’t ever recall any assertion that the problem discrimination had been sufficiently reduced to justify removal of EEO reporting requirements.

In conclusion, EPI strongly urges the Commission to withdraw its proposal to eliminate all six of the EEO surveys. Failure to do so would renege on the promise of our nation’s anti-discrimination laws for workers, their families and the economy.

Sincerely,

Valerie Wilson, PhD
Director, Program on Race, Ethnicity and the Economy
Economic Policy Institute

1. The EEO-2 remains authorized under Title VII of the Civil Rights Act of 1964 but has not been collected since 1981. In this case, our recommendation to continue the surveys is a recommendation to reinstate it.

 The EEO-6 remains authorized under Title VII but has not been collected since 1993. In this case, our recommendation to continue the surveys is a recommendation to retain this authorization and reinstate the survey to the extent that it is not superseded by the Integrated Postsecondary Education Data System (IPEDS) Staff Survey of the U.S. Department of Education.

2. Valerie Wilson and William Darity Jr., Understanding black-white disparities in labor market outcomes requires models that account for persistent discrimination and unequal bargaining power, Economic Policy Institute, March 2022.

3. Examples include: Michael Fix, George C. Galster, and Raymond J. Struyk, “An Overview of Auditing for Discrimination.” in Michael Fix and Raymond Struyk, eds., Clear and Convincing Evidence: Measurement of Discrimination in America, Urban Institute Press, 1993; Marc Bendick, Jr., Charles W. Jackson, and Victor Reinoso, “Measuring Employment Discrimination Through Controlled Experiments” in James B. Stewart, ed., African-Americans and Post-Industrial Labor Markets, Transaction Publishers, 1994; Michael Fix, George C. Galster, and Raymond J. Struyk, “An Overview of Auditing for Discrimination” in Michael Fix and Raymond Struyk, eds., Clear and Convincing Evidence: Measurement of Discrimination in America. Urban Institute Press, 1993; and Margery Turner, Michael Fix, and Raymond Struyk, Opportunities Denied, Opportunities Diminished: Racial Discrimination in Hiring, Urban Institute Press, 1991.

4. Devah Pager, “The Mark of a Criminal Record,” American Journal of Sociology 108 (March 2003): 937–75.

5. Sonia Kang, Katy DeCellesa, András Tilcsika, and Sora Jun, “Whitened Résumés: Race and Self-Presentation in the Labor Market,” Administrative Science Quarterly 61, no. 3 (March 17, 2016): 469-502.

6. David Neumark, “Detecting Discrimination in Audit and Correspondence Studies,” Journal of Human Resources 47 (Fall 2012): 1128–57. 

7. Lincoln Quillian, Devah Pager, Ole Hexel, and Arnfinn H. Midtbøen, “Meta-Analysis of Field Experiments Shows No Change in Racial Discrimination in Hiring Over Time,” Proceedings of the National Academy of Sciences 114, no. 41 (October 10, 2017): 10870-875.

8. Valerie Wilson and William Darity Jr., Understanding black-white disparities in labor market outcomes requires models that account for persistent discrimination and unequal bargaining power, Economic Policy Institute, March 2022.

9. Examples include: John Bound and Richard Freeman, “Black Economic Progress: Erosion of the Post-1965 Gains in the 1980s?” in Steven Shulman and William Darity, Jr., eds., Question of Discrimination: Racial Inequality in the U.S. Labor Market, Wesleyan University Press, 1989; David Card and Alan Krueger, “School Quality and Black-White Relative Earnings: A Direct Assessment,” Quarterly Journal of Economics 107 (February 1992): 151–200; and John Donohue and James Heckman, “Continuous vs. Episodic Change: The Impact of Civil Rights Policy on the Economic Status of Blacks,” Journal of Economic Literature 29 (December 1991): 1603–43. 

10. Examples include: Augustin K. Fosu, “Occupational Mobility of Black Women, 1958–1981: The Impact of Post-1964 Antidiscrimination Measures,” Industrial & Labor Relations Review 45, no. 2 (1992): 281–94; and James J. Heckman and Brook Payner, “Determining the Impact of Federal Antidiscrimination Policy on the Economic Status of Blacks: A Study of South Carolina,” National Bureau of Economic Research Working Paper no. 2854, 1989. 

11. Examples include: Charles Betsey, “Litigation of Employment Discrimination Under Title VII: The Case of African American Women,” American Economic Review 84, no. 2 (1994): 98–102; and Jonathan S. Leonard, “The Impact of Affirmative Action Regulation and Equal Employment Law on Black Employment,” Journal of Economic Perspectives 4, no. 4 (1990): 47–63. 

12. Examples include: Leonard Carlson and Caroline Swartz, “The Earnings of Women and Ethnic Minorities, 1959–1979,” Industrial & Labor Relations Review 41, no. 4 (1988): 530–46; James S. Cunningham and Nadja Zalokar, “The Economic Progress of Black Women, 1940–1980: Occupational Distribution and Relative Wages,” Industrial & Labor Relations Review 45, no. 3 (1992): 540–55; and Nadja Zalokar, The Economic Status of Black Women: An Exploratory Investigation. U.S. Commission on Civil Rights, 1990.

13. Jonathan S. Leonard, “The Impact of Affirmative Action Regulation and Equal Employment Law on Black Employment,” Journal of Economic Perspectives 4, no. 4 (1990): 47–63. 

14. Examples include: Donald Tomaskovic-Devy, Melvin Thomas, and Kecia Johnson, “Race and the Accumulation of Human Capital Across the Career: A Theoretical Model and Fixed-Effects Application,” American Journal of Sociology 111, no. 1 (2005): 58–89; and Valerie Wilson and William M. Rodgers III, Black-White Wage Gaps Expand with Rising Wage Inequality, Economic Policy Institute, September 2016. 

15. Jenny R. Yang and Jane Liu, Strengthening Accountability for Discrimination: Confronting Fundamental Power Imbalances in the Employment Relationship, Economic Policy Institute, January 2021. 

16. Ibid.

17. See endnote 1.

18. Chang-Tai Hsieh, Erik Hurst, Charles I. Jones and Peter J. Klenow. “The Allocation of Talent and U.S. Economic Growth”, Econometrica, Vol. 87, No. 5 (September 2019), 1439-1474.

19. Adewale A. Maye and Valerie Wilson, Trump is Making it Easier for Employers to Discriminate. This Stifles Equity and Hurts Economic Growth. Economic Policy Institute, May 2025.

Key takeaways:

• The CROWN Act is legislation that protects students, workers, and housing applicants from race-based hair discrimination.
• 30 states have enacted some version of the CROWN Act, building momentum for a federal version to pass in Congress.
• Expansions of civil rights laws like the CROWN Act are more urgent than ever given Trump administration efforts to weaken nondiscrimination protections.

In an era of Trump administration attacks on nondiscrimination protections and diversity, equity, and inclusion (DEI) initiatives, workers and students need the guardrails included in the CROWN Act more than ever.

The CROWN Act stands for Creating a Respectful and Open World for Natural Hair. It expands existing civil rights law to prohibit race-based hair discrimination in schools, housing, and workplaces. Far from being solely focused on aesthetics, the CROWN Act protects against implicit bias and policing of Black and brown bodies. It codifies hair discrimination as racism and prohibits employers, public schools, and housing agencies from imposing whiteness as the uniform for success.

The CROWN Act is now law in 30 states

Pennsylvania and Rhode Island became the most recent states to pass the law in 2025, joining a growing list of states that have passed some form of the CROWN Act. Similar to the limited protections in Kentucky (which only provides public service and employee protections), Missouri also recently passed a limited version of the law that only applies to educational institutions—not workplaces or housing.

Figure A

Since the start of the second Trump administration, five states (Florida, Mississippi, Ohio, North Carolina, and South Carolina) have introduced at least one version of the CROWN Act.

Expanding CROWN Act legislation at the local level can be a significant incremental step toward expanding protections more broadly. In at least three of the states that introduced legislation, local CROWN laws have been adopted in cities including Charlotte, North Carolina, Columbus, Ohio, and Miami Beach, Florida. Such local policies have proven helpful in laying groundwork for passage of state laws elsewhere; for example, localities in Pennsylvania and Missouri passed CROWN Act laws years prior to these passing at the state level.

It’s time to pass the CROWN Act in Congress

Representative Watson Coleman (D-NJ) and Senator Cory Booker (D-NJ) introduced a federal version of the CROWN Act in the House and Senate last February. Neither bill has received a vote. With 60% of states already having passed the CROWN Act, the policy clearly has enough popular support to pass both chambers and become law.

A federal CROWN Act would provide consistent nationwide protection against hair discrimination for workers—especially Black women workers who have larger pay disparities and who are intersectionally impacted by a history of racist laws. Over 38.7% of Black women workers live in states where they are vulnerable to hair-based discrimination, based on the most recent 2024 data. That’s a slight improvement from the 44% of Black women workers who lacked protections in 2023, thanks to six more states—Kentucky, Missouri, New Hampshire, Pennsylvania, Rhode Island, and Vermont—recently passing some version of the CROWN Act.

Table 1

Although some states did not have large enough populations of Black women to be tracked in the data presented in Table 1, Black students and workers in states with smaller Black populations remain susceptible to discrimination. In South Dakota, for example, a student was told to cut their locks or leave school. Black students have shared similar stories in states across the country with varying Black population density.

Expansion of the CROWN Act must be coupled with strong enforcement

In an anti-DEI political climate, preventing hair-based discrimination must be coupled with addressing a growing crisis in federal and state nondiscrimination enforcement systems. Current threats to the Equal Employment Opportunity Commission’s (EEOC) enforcement mission are eroding protections for Black and brown workers. The EEOC was established by the Civil Rights Act of 1964 (the same law that the CROWN Act would expand) and was designed to be an independent federal agency to protect workers and promote fairness and equity in employment. The EEOC’s role in reducing discrimination has helped to boost average income by $493 to $1,233 per person since 1960. Historically, the EEOC has been a key source of protection for Black and brown people and women: A third of all EEOC charges were related to race (29,338) or sex (26,941) last year.

Figure B

Last year, the Trump-appointed chair of the EEOC hijacked the agency’s mission by actively soliciting complaints from white male workers and encouraging “DEI-related discrimination” claims of “reverse racism.” In addition to assigning a new chair, the Trump administration has weakened the EEOC by removing the ability to collect full pay data, limiting gender data collection, and removing commissioners—preventing a quorum and disrupting proceedings.

The Civil Rights Act itself and the protections that the EEOC was created to enforce are at risk. And some states are following the Trump administration’s lead by weakening state-level civil rights laws and enforcement systems. For example, in 2025, Iowa became the first state in history to strip nondiscrimination protection from a protected class when it removed gender identity from its state Civil Rights Act. In response, many cities and counties expanded their local civil rights ordinances to ensure protections against discrimination based on gender identity, but in 2026 the state went a step further and banned local governments from protecting any class not explicitly listed in state law. These recent legislative changes explicitly targeted trans people for discrimination, but will also have the broader effect of preempting local governments from adopting any expanded civil rights protections in the future, including local versions of the CROWN Act.

In the meantime, discrimination has not stopped and continues to have a measurable impact on Black, brown, and women workers—especially related to opportunities for securing a job and workplace advancement. New research finds that 59% of white adults hold anti-Black prejudice, contributing to a greater likelihood that Black applicants are rejected from jobs compared with their white counterparts. Women are paid 18.6% less than men. The disparity increases when considering race: Black women are paid 68.3% and Hispanic women are paid 64.5% of white men’s pay.

It is imperative to both expand protections like the CROWN Act at the local, state, and federal levels and strengthen state civil rights enforcement, while working toward eventual restoration of the EEOC’s capacity to carry out its mission to protect against discrimination in the workplace.

The latest SHED survey also shows that the harm caused by the administration’s economic chaos has not affected all people equally. Structural inequities embedded in the U.S. economy and labor market have historically left communities of color disproportionately vulnerable to economic insecurity and poverty, and the Federal Reserve’s survey shows that this trend is continuing. While the overall financial well-being of most adults held steady in 2025, the financial well-being of Black adults declined. These individuals were also more likely to experience layoffs, leaving a higher share of Black adults and their families with increased fear of finding or keeping a job in 2025. The added employment uncertainty of Black adults also left them significantly more likely to report major concerns about making ends meet. The survey also shows that education largely failed to protect these individuals from the experience of increased economic fragility.

Black adults find themselves in the worst financial position in nearly a decade

In 2025, Black adults were most likely to report a decline in their financial standing. The share of Black adults “doing okay” or “living comfortably” declined by almost 5 percentage points last year to 60% (see Figure A). This is the lowest figure the Survey of Household Economic and Decisionmaking survey has recorded since 2015. The 2025 figure also reflects a steep decline from the high of 2023, when nearly 68% of Black adults answered questions about their financial well-being positively. We find that the bulk of the decline last year took place among the individuals who reported “living comfortably,” as this share declined from 23% in 2024 to 19.0%.

Figure A

Higher education largely failed to protect Black individuals from added financial insecurity under the Trump-Vance economy. While nearly all Black adults with varying levels of education experienced a deterioration of their financial position last year, the situation of adults with a college education worsened the most (see Figure B). The share of these individuals doing okay or living comfortably, for example, declined by nearly 7 percentage points last year.

Figure B

Black adults were more likely to experience a sharp increase in layoffs last year

By summer 2025, job growth had slowed considerably, and Black workers were among the first to experience this slowdown with a rising rate of unemployment. The uneven impact of these debilitating forces last year comes across clearly in the Federal Reserve survey. The share of Black adults who reported experiencing a job loss increased by about 3 percentage points between 2024 and 2025 (see Figure C). This reflects the largest increase among all racial and ethnic groups. In fact, Black adults were more than twice as likely as their white, non-Hispanic peers to report layoffs last year. This reality aligns with the broader labor market position of Black workers, who experienced a steeper rise in their unemployment rate in 2025 and who remained about twice as likely as their white peers to be unemployed. 

Figure C

As the pace of job growth slowed and the unemployment rate rose in the first year of the Trump-Vance administration, people’s concern with finding or keeping a job increased. But this increased employment vulnerability and insecurity fell most heavily on Black individuals and their families (see Figure D). More than half of Black adults said that finding or keeping a job was either a minor or major concern for them or their families last year. This figure increased by nearly 10 percentage points between 2024 and 2025. In fact, Black adults of all education levels reported increased concerns about finding or keeping a job last year. 

Figure D

Black adults and their families have grown increasingly more concerned about their economic security

The added employment vulnerability, combined with the impact of the ongoing affordability crisis, has also left more Black individuals and their families worried about their ability to make ends meet. More than 3 out of 4 (77.5%) Black adults reported that making ends meet was at least a minor concern for them and their families last year (see Figure E). This figure increased by about 8 percentage points between 2024 and 2025, leaving Black adults of all education levels more economically vulnerable last year. In contrast, the share of white, non-Hispanic adults who reported similar concerns declined marginally during the same period.

Figure E

We cannot address the affordability crisis without dealing with its root causes

The Federal Reserve survey points to the relationship between employment, economic security, and well-being. The uneven impact of the weaker job market last year resulted in increased employment and economic uncertainty for Black adults and their families. The survey findings are a reminder that ongoing discussions about the affordability crisis shouldn’t ignore the role of employment, wages, and income. Affordability remains an outcome of a race between income and prices, and we know that the pace of job and wage growth is a policy choice. While there is no silver bullet, we know that a broad basket of policies is needed, including a higher wage floor, increased union density, and macroeconomic policies that reduce inequality.