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50 million U.S. workers want to join a union: What if they could?

Ben Zipperer, Celine McNicholas, Jennifer Sherer — Wed, 15 Jul 2026 17:00:31 +0000

Imagine if one-in-three private-sector workers belonged to a union.

What would wages, benefits, and working conditions look like if more workers had access to a union contract and the labor movement gained strength to beat back billionaires and big corporations? What would it mean for our economy and democracy? And what policy changes are necessary to enable more workers who wish they had a union to get one?

On Wednesday, July 15, at 10:00 a.m. Eastern, the Economic Policy Institute hosted a virtual press conference with AFL-CIO President Liz Shuler to discuss new EPI research quantifying the economic, social, and democratic benefits of increasing union membership to 30%. Participants also shared a policy roadmap to boost union membership, including offering two new proposals to promote collective bargaining and grow union membership.

Later that day, authors of the new report, Director of Policy/General Counsel Celine McNicholas joined Deputy Director of EARN and Director of the State Worker Power Initiative Jennifer Sherer to charted the course, while Senior Economist Ben Zipperer broke down the numbers, in conversation with Executive Vice President Naomi Walker.

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This is the transcript of the July 15, 2026 EPI webinar, generated from the event’s captions and lightly formatted for readability. It may contain minor transcription errors — refer to the recording for the original audio.

0:05 Naomi Walker (EPI)

Earlier today, EPI, alongside AFL-CIO President Liz Shuler, released a major new report that answers a really big question. What would America look like if we tripled union membership? And the findings are striking for workers, for the economy, and for our democracy. The report includes state-by-state breakdowns, and also we have a foreword in it by Robert Reich, and I am thrilled to be joined by three of the report’s brilliant authors. Celine McNicholas, Director of Policy and General Counsel at EPI, Jennifer Sherer, Deputy Director of EPI’s EARN Network and Director of the State Worker Power Initiative, and Ben Zipperer, Senior Economist at EPI. So, let’s start with where we are. Last year, nearly 15 million workers, or 10% of all wage and salary workers, belonged to a union. And that’s a slight uptick from 2024, and it means that right now, there are more union members in the United States than there have been in 16 years. But here’s the gap. If every worker who wanted a union actually had one, union membership wouldn’t be 10%, it would be 48.7%. And can you imagine the power that workers and their unions would have then? And that is exactly what frightens corporate CEOs. Our vision of tripling union membership is not a pipe dream. It tracks with record high public support for unions, and so I am going to share a few polling numbers. First is 68% of people have a favorable view of unions, and when you look at the generations, majorities across every generation support union, from Boomers, Gen Xers, Millennials, Gen Z, And among young adults, 72% of them support unions, which is the highest of any group. Unions have support that crosses party lines, and 60% of Americans say that the decline in union density has been bad for the country, including 52% of young Republicans and 82% of young Democrats. So, tripling union membership is not a moonshot. It is just delivering what workers already want. and what the public already supports. So today, we’re going to dig into our vision for a country where at least one in 3 workers belong to a union. We’re going to talk about what’s at stake, what it would look like, what and who stands in the way, and what it’s going to take to get there. So again, Jen already mentioned this. Thanks so much to the folks who sent in questions in advance. We’ve woven some of those into today’s conversation, and we will hopefully have enough time at the end. for more questions. So let’s get into it. Ben, first question, everybody wants to know what this would mean for them. How would tripling union membership impact regular workers?

3:17 Ben Zipperer (EPI)

Yeah, so we show in the report that we released today that you outlined that if union membership rose by 20 percentage points from 10% today to 30%, it would increase hourly pay by nearly 15% for the typical or median worker. What that means for a full-time, full-year worker earning a middle-class wage, they would have their annual pay rise by more than $7,700. Unions… typically raise wages for the middle and the bottom end of the workforce. So, you know, assuming that that wage increase applies to the bottom 80% of the workforce, that would raise combined annual compensation by $1.2 trillion. That’s every year. And that would reverse one third of the increase in inequality that we’ve experienced since 1979. That’s real money. It’s larger than the Pentagon’s 2025 budget, and it would provide an enormous relief to families struggling to afford a decent standard of living. Just as one kind of clear example, the median annual cost of mortgage payment these days is a bit over $18,000. So an additional $7,700 a year, that would cover more than 40% of those mortgage expenses. What’s also important to realize is that this extra $7,700 a year, that’s a permanent increase in income. Tripling union density would provide that income boost year after year. So someone working full time over a 35 year career, that’s conservatively $270,000 a year in today’s dollars, even if they never received any additional pay increases above the rate of inflation. That’s a life-changing increase to a family raising young kids and eventually sending them to college.

5:12 Naomi Walker (EPI)

Great. Thanks so much, Ben. And I just saw a note come into the chat, somebody asking for a fact sheet. We will do that. That is a fantastic idea. So following up on those really eye-popping numbers, Ben, are these increases evenly distributed or would some workers see a little more lift than others?

5:29 Ben Zipperer (EPI)

That’s a very important point. Unions tend to raise pay, like I said, for those at the bottom more than at the top. And so what that means is that workers who have been discriminated against and have fewer opportunities to advance and see pay raises, they often benefit the most from unions at a workplace. In particular, that means that unions tend to boost wages more for Black and Hispanic workers than for white workers. This is a pattern that economic research has consistently found. And it’s why unions for decades have been an important force for racial justice. So were we to triple union membership, like we talk about in the report, that would close racial wage gaps by more than one third. In 2025, the typical Black or Hispanic worker was paid 77 cents for every dollar paid to the median white worker. That’s about a wage gap of 23%. But tripling union density because it would raise wages more for Black and Hispanic workers, it would close that gap by more than one third.

6:36 Naomi Walker (EPI)

Wow. Okay. So, Ben, in addition to the financial boost for workers and the reduction in the racial wage gap, were there any other economic benefits that your research found?

6:50 Ben Zipperer (EPI)

One of the bigger benefits that we looked at is better access to health insurance. So we found that tripling union density would dramatically decrease the number of non-elderly people without medical insurance, causing that number to fall by about 25%. The basic story here is that in addition to raising wages, unions improve access to other forms of compensation like employer provided health insurance. And in the US, Health insurance is one of the most important benefits unions collectively bargain to maintain and to improve. Also, in addition to that, unions are a major advocate for increased public benefits like Medicaid and related state level programs. So unions increase both publicly and privately provided health insurance. Low union density states and areas of the country, they can often have double digit uninsurance rates. For example, in Texas, where union membership is really low. half the national average, it has an uninsurance rate about twice the national average. But in places with higher union density, people are much more likely to have employer provided or publicly provided health insurance. So by tripling union density, we would increase access to health insurance, lowering uninsurance rates significantly in places that currently have low union density.

8:11 Naomi Walker (EPI)

Thanks so much, Ben. I am gonna turn to Jen Sherer to talk, to dig in to what is happening in the states. And I’ve seen some questions in the chat come in on this. So Jen, what did you find in states, with states that have a higher union density?

8:28 Jennifer Sherer (EPI-EARN)

So, in addition to what Ben has covered in terms of wages and health insurance access, this report details that even beyond some of these economic factors, high union density correlates very strongly with many widespread public benefits to workers and communities at large. So in addition, just as a couple of examples, states with high union density tend to have better funded public education systems and more robust social safety nets than states with lower union density. So what does that mean in practical sense? The union density of the state you live in is unavoidably affecting not only your wages and your state’s economy, but also the health well-being and the civic or educational opportunities that are available to you and your family. So workers living in states with higher union density have greater access to health insurance has been covered. In part because those are states that are more likely to have expanded Medicaid, but they also have better track records on things like ensuring that workers actually receive unemployment benefits that they’re eligible for if they’re laid off from a job. States with higher union density spend more per pupil on public education. And maybe most importantly, and I know we’re going to get into this even more deeply in a bit, states with higher union density have a stronger, more robust democracy. This is based on data showing that states with higher union density end up with a more active electorate. And fewer restrictions on the right to vote across the board nationally. So, increasing union membership across all states, and I know we’re getting some questions about this in the chat that I’m sure we’re going to come back to later, especially in states with historically low density, is really critical to transforming economic conditions, but also the health and well-being of workers and communities overall.

10:15 Naomi Walker (EPI)

So this next question is gonna go to Celine, and we just heard from Jen talking about the benefits for communities, and Ben’s talked about the impact on individual workers and the economy. Is that the limit, or are there broader gains to be had from tripling union membership?

10:32 Celine McNicholas (EPI)

Sure. So I’ll pick up where Jen left off. There are absolutely broader gains. And I think one of the main gains that we wanted to highlight in the report, and I think really bears consideration here, is that unions are good for democracy. They’re democratic institutions themselves, so they really serve as schools of democracy. They expose members to activism. Members vote for their leadership. They vote on a contract, they serve on committees and as stewards helping to administer their contracts. And research, as Jen sort of indicated, shows consistently that union members use these skills in their civic lives. And that translates to union members are more likely to vote than the general public. And voter turnout, as Jen mentioned, is consistently higher in states with higher union densities. And I think it’s really important as more and more states, unfortunately, are trying to make it harder for their residents, particularly disproportionately residents of color, to vote. They’re enacting, you know, measures that make it harder and harder to access the franchise. States with higher union density are not following suit. Those are the states that are essentially protecting democracy and protecting the right to vote. So in our current political system, even beyond that, where political influence is really closely tied to money, unions are really the main countervailing force in that system. They bring working people’s voices into policy debates. They help build coalitions that challenge what would otherwise really be a policy agenda that serves, unfortunately, only the wealthy. And I just say in closing here, consider that unions have been critical forces to win each and every minimum wage increase ever passed, whether at the state, local, or federal level. They’ve been instrumental in winning anti-discrimination protections for workers and family medical leave protections for workers. And these are all things that union workers themselves have won as a matter of right in their own contract. So they win it for themselves, and then they work in a larger democracy to win it for all of us. And so it’s hard to sort of overstate the gains to, you know, to really increasing union membership and union density.

12:38 Naomi Walker (EPI)

Thank you, Celine. I love those examples at the end about how unions not only fight for their own members, but for other workers as well. Ben, I want to dig in a little bit on inequality. Inequality has risen dramatically in recent decades. a lot of pressure that people… workers are feeling are the pressure to afford a middle-class lifestyle. So, can you talk us through what happened?

13:07 Ben Zipperer (EPI)

That’s absolutely right. Affording a decent life is difficult in the United States, and the main reason why is that there has been a huge transfer of income away from the middle class towards those at the very top. The typical worker today is almost twice as productive as they were in the late 1970s, but since then, their wages have failed to track that productivity increase. And that differs compared to earlier decades when union density was much higher and when pay came much closer to tracking productivity growth. The consequences for workers and affording a decent standard of living because of that are really staggering. A full-time, full-year worker last year earned about $53,000 a year at the annual median hourly wage, but they would have earned over $76,000 a year if their pay had tracked productivity since 1979. That wage suppression. is directly related to the very successful attacks on unions over the last four to five decades, because by weakening unions, our country has eliminated one of the major sources of worker bargaining power that previously compelled employers to share productivity gains much more broadly, rather than enriching a group of highly paid executives and CEOs. Instead, because you Union density has been low. We’ve been in a situation where a lot of money wasn’t paid to the typical or middle class worker and instead went to the very top. Since 1979, earnings for the bottom 90% of households grew just 44%, but earnings for the top 0.1% grew by 354%. Were we to triple union density? That money would instead be distributed much more widely, reversing about one-third of that rise in inequality. A large enough union presence can be a major force in checking the rise in inequality and ensuring that workers’ wages are not suppressed.

15:09 Naomi Walker (EPI)

Thanks, Ben. Jen, so Ben touched on this a little bit about how unions help reduce income inequality. Can you add a little bit to that and talk about some of the historic comparisons?

15:22 Jennifer Sherer (EPI-EARN)

Yeah, that’s right. And EPI has for a long time been tracking this growing increase in inequality across our economy that, as Ben said, reflects a really massive shift of earnings away from low and middle income workers. And it’s coincided directly with the decades-long assault on workers and their unions. I think the second chart that has maybe been shared in the chat and, is another EPI, graphic that shows two lines. The one in blue shows union membership over time. The red line is the share of national income going to the top 10% of households, so in other words, it’s a measure of how concentrated that, income is just at the top at certain points in history. So, in a nutshell, this chart is just showing that by bringing workers’ collective power to the bargaining table in prior decades, unions were able to win better wages and benefits for working people, which also reduced income inequality overall as a result. And of course, that trend has gone the other direction in more recent decades. So, you know, folks have noted that in the early 50s, when union membership is at that historic high point. Unions are at a point where they’re able to set wage standards for entire industries and occupations, giving workers the power to demand their fair share of corporate profits, and that decreases the overall inequality in our economy. In the second half of the 20th century. that changes. And so I know what we’re going to have the rest of our time focused on is what are some of the, you know, policy choices and opportunities we have today to start making those trend lines go in a different direction in the future.

17:03 Naomi Walker (EPI)

And thanks, Jen. And I think before we start digging in on the policy side, I want to turn it over to Ben. I think we understand that unions raise pay for their members, but can you explain how they raise pay for non-union workers too?

17:19 Ben Zipperer (EPI)

Right. Everyone understands, like you mentioned, that unions raise pay for their members. The ability to collectively bargain at workplace levels the playing field between union members and their employers, and it allows unions to negotiate for better pay at the workplace, among other things. But also, unions boost wages for non-union workers, too, because they change pay standards. An economic research has demonstrated that these wage spillovers for non-union workers from union workers are substantial and they grow the higher union density is. There’s basically kind of three mechanisms that cause wage increases for non-union workers when there is higher union density. First is that When you’re raising pay at a given workplace that’s unionized, unionized firms, they become more attractive places to work relative to non-union firms. And that indirectly through the market pressures non-union firms to raise wages because otherwise they’d face recruitment and retention problems. Secondly, when there is greater union presence in a given industry or a given occupation. And the prospect of a newly unionized workplace is a real possibility. Non-union employers will raise wages to preemptively avoid workers from forming a union at their non-union workplace. Finally, the third thing is that Unions are, as we talked about earlier, unions are a major force in advocating for better public policies, in particular, progressive taxes and social benefits. This indirectly raises the pay of both union and non-union workers, because when taxes on top incomes are higher. Corporate executives have less incentive to redistribute income away from workers and toward themselves, because much of that higher pay for the already rich would be taxed away. So for all of those reasons, unions raise wages for the bulk of the workforce, not just union workers.

19:26 Naomi Walker (EPI)

Thanks so much, Ben. And I’ll just note in the chat, some folks are putting some reading recommendations, including one of our participants, Eric Lotke, who has a novel out that has characters talking about the charts that Ben mentioned. and Jen have mentioned, so I am excited to check that out. So, Celine, you know, tripling union membership would raise pay, strengthen communities, build a more robust democracy, and we all see those benefits as being really clear, and the public overwhelmingly sees those benefits as being really clear. But can you help us understand why union membership has been stuck at such low levels for so long?

20:11 Celine McNicholas (EPI)

Sure. I think, you know, this is a relatively easy question to answer in that there’s really one main reason that more workers in the U.S. do not have a union, and that is really that current policy, current law does not provide a meaningful right to a union and collective bargaining. Workers who win union representation and then go on to successfully win a contract really do so in spite of the law, not because it truly a pathway to those gains. And that’s a huge failing. And corporations have really long exploited the law’s weakness. And it’s given rise really to an entire industry of union avoidance consultants and union avoidance law firms. Here at EPI, we’ve done a lot of research into those industries. And we know that companies spend roughly $1.7 billion billion each year on union avoidance business. So just think about that. Companies spend close to $2 billion each year to suppress workers’ rights to a union and collective bargaining. And the law allows that, really frankly, invites it. It’s certainly not the way it should work. But when you think about all of these gains and what it would mean to a restructuring of the economy, you Essentially, those gains are being spent to avoid, you know, paying workers their fair share. Unions would require that. They really are the best private sector mechanism for workers to, you know, claw back some of those, the productivity gains that they participate in. So unfortunately, it really is a failing of our current policy and current law that I think is the greatest contributing factor to that mismatch of. desire and what actually workers are able to win in their workplace.

21:54 Naomi Walker (EPI)

And so one of the questions that came in early was, is there, can we waive our magic wand? If we had to waive our magic wand, what’s the one policy? What’s the silver bullet? Is there a silver bullet, Celine, and what are the changes, that need to happen in order to get to triple union membership?

22:14 Celine McNicholas (EPI)

Sure. So I wish I could say that this is an easy answer and that there is a silver bullet or a magic wand that can be waved. But as we state in the report, there really is no one policy change that would lead to triple union membership. But there are several key policies, many of which have bipartisan support that would help reform the sort of broken system that I just talked about. So I’ll just highlight a few. The law should give public sector workers the right to collective bargaining. We certainly look at that and the potential impacts in state union membership in the report. And there is a bill in Congress now, the Public Service Freedom to Negotiate Act, which would give public workers that right. And it includes an enforcement structure to ensure that states and localities give them that right. There is a bill that provides really a comprehensive set of reforms that would govern private sector workers. That’s also introduced this Congress and has bipartisan support. That’s the Protecting the Right to Organize, or commonly referred to as the PRO Act. And, you know, I guess I would just sort of say, at core, any and all policies that make it easier for workers to choose a union in their workplace and then bargain with their employer successfully and reach a contract should be on the table, should be considered. And, you know, I think that’s really why we tried to offer some new policy ideas that build on, you know, many of these other, they’re complementary to the policy reforms that we’re talking about here. And they are really aimed at centering collective bargaining as a corrective to, you know, the affordability issues that Ben talked about in his remarks. And I would just sort of say that, you know, we know that where individual bargaining is not working at a firm, when you have a ratio of, you know, CEO pay to typical worker pay that exceeds 101, that individual leverage is not enabling workers to gain their fair share. And so we think, you know, mandating collective bargaining in some instances is really required and would be helpful to correct and also to grow the union movement, which has benefits across so many other aspects, not just wages and working conditions.

24:31 Naomi Walker (EPI)

Thanks, Celine. And Jen, I would like to hear from you. What can state policymakers do to improve union membership?

24:40 Jennifer Sherer (EPI-EARN)

Yeah, so we described earlier that workers are experiencing really different economic and social realities depending on where they live. In a high versus low density state. So, it’s not surprising that these big variations in union density by state are the result of some very big policy differences among states. And so, in the new report, we take a look at the impact of two policies in particular. first anti-union so-called right-to-work laws that are on the books in 27 states, and we look at the impact of limitations on collective bargaining rights that public sector workers face in 24 states. So the fact that states are even able to limit or deny some workers’ union rights reflects some of what Celine was, referring to, you know, the long-standing failure in our federal labor law, and the failure of Congress to, update it and fix many of the weaknesses. So many workers, for example, have never been protected by federal labor law at all due to Jim Crow era exclusions. that left out and carved out people by occupation. Domestic workers, agricultural workers, and public sector workers have never been covered fully under federal law. So that leaves their union rights dependent on states, and means we have these huge, uneven disparities across the country. And then furthermore, Congress in 1947 made big amendments to our federal labor law. Long list of bad things that happened in those amendments, but it included, allowing states to continue passing laws, so-called right-to-work laws, that limit the labor rights of private sector workers. So, workers in the U.S. are experiencing big disparities in how difficult it is, or whether it is even legally a viable pathway for them to form or sustain a union, depending on where they live. what their occupation is. So the new report looks at the impact and models, and I think here’s where I want to have people, you know, try to digest some kind of eye-popping results. that we were able to model the impact of removing just these two barriers to unionization at the state level. So in other words, if we got rid of all right to work laws in 27 states and removed limitations on public sector collective bargaining so that all states had a clear legal pathway for state and local government workers to unionize. That impact alone would increase union density nationally from its current level. To 14.4%. So, an almost 50% increase from where we’re at right now. So for workers in one of the 27 states that have one or both of these anti-union policies in place, we also model the wage impacts. And estimate that the median worker wage would increase by up to $4,900 a year. So states have a lot of important roles to play here, and there are a lot of opportunities to make improvements. Even if we’re not at the point where we have all of the long list of important federal reforms that we need.

27:39 Naomi Walker (EPI)

Yeah, Jen, those numbers are eye-popping, and I wonder if you could dig in a little bit more about why state policy is so important, given the political moment that we’re in right now.

27:52 Jennifer Sherer (EPI-EARN)

Well, I mean, strengthening collective bargaining rights is clearly one of the most powerful policy levers that state elected officials have available to confront the affordability crisis. Reversing anti-union state policies is a really critical first step to righting historical wrongs and addressing persistent racial and gender wage gaps and inequities in our labor market. And the anti-union state policies we focus on in this report particularly, both originate in post-World War II white supremacist backlash and big business backlash against the growth of unions and gains that many Black and women workers had begun to achieve, as unions were growing in strength. So we know that historically these policies were designed to suppress multiracial organizing, limit worker power, and explicitly to try to undermine federal labor law. So it’s really long past time that states remove these restrictions and barriers. It’s also extremely good politics right now for state leaders to prioritize these kinds of reforms at a moment when we know public interest. in and approval for unions is at an all-time high.

28:59 Naomi Walker (EPI)

And so, Jen, you talked about, two big things that states could do, remove right-to-work laws and remove restrictions on, collective bargaining. What else can states do on this?

29:12 Jennifer Sherer (EPI-EARN)

Yeah, and I think it’s maybe been in the chat, but we do all have an entire separate report on listing the many opportunities for states to help enable more workers to unionize and remove some of these barriers. So, a couple of examples, you know, in addition to public sector workers who don’t have, federal labor law coverage, states We have a lot of room in our country for states to extend collective bargaining rights to, domestic workers, in-home childcare providers, home healthcare workers, farm workers, and gig workers who are not currently being afforded federal labor rights. And states are also actively beginning to pass policies that protect workers’ rights to refuse mandatory anti-union captive audience meetings. I think we’re up to 14 states. Obviously, you know, there are a majority of states still on the list who could take that kind of step and remove some of the obstacles workers face to forming new unions. Other states are beginning to more actively look at policies like extending unemployment insurance eligibility to workers on strike. So again, I really encourage people to look at the other report for a long list of opportunities states have to take action.

30:28 Naomi Walker (EPI)

And so, Celine, I’m going to come to you with this question. In January, God willing, there’s going to be a new Congress that hopefully will be more worker-friendly. What should we tell them to focus on?

30:42 Celine McNicholas (EPI)

Great question. And we should just acknowledge that there is so much wrong. So there’s a ton that could be focused on. But I think the main focus for policymakers really must be to prioritize passing labor law reforms. And as we’ve heard, that’s really essential to addressing the affordability problems that we’re facing. But the reality is that Prioritizing labor reforms, reforms aimed at growing unions and collective bargaining will go a long way to helping address many of the other key policy issues we are facing. So attacks on our democracy. We know that unions do a ton to create and protect vibrant, inclusive, participatory democracy. Health care. We know that unions win their members quality health insurance. and are instrumental in protecting and expanding programs like Medicaid that provide those benefits to millions of children, pregnant women, the elderly, retirement security. Unions help workers win a decent retirement, and then they fight to protect programs like Social Security that ensure that all workers can retire with some dignity. So really, again, here, it’s like it’s hard to overstate the benefits that could flow from prioritizing labor law reform. Unfortunately, it has not been previously, you know, prioritized. Realistically, we understand that, you know, that may require expanding what can be considered under reconciliation or potentially lifting the filibuster for consideration of labor law reform. But those process challenges really cannot be used as an excuse to abandon trying for those policies. They’re rules that Congress created, and I would just keep arguing that Congress can change those rules and do at times to prioritize other issues. And I guess it would just also be remiss, Naomi, not to flag that obviously any and all progress on the front of labor law reform, promoting collective bargaining at the federal level will not only require a new Congress, but a new president, because Trump has expressly promised. to veto the measures that I talked about at the beginning, the Public Service Freedom to Negotiate Act and the PRO Act, to say nothing of sort of his own union busting as president. So, you know, hopefully a new Congress can figure out a way to prioritize these reforms, but I do wanna flag that obviously there is an impediment in the White House as well.

33:10 Naomi Walker (EPI)

Absolutely a very, very big impediment. Okay, Celine, one of the things I want to dig in on is that you mentioned there is some measure of bipartisan support, which is so wild to me, because Republicans have, waged a decades-long war on workers’ rights, both at the national level and at the state level. And so I’m really curious about, like, how do you square their attacks with this newfound interest? And do you think it’s genuine, this interest they’re showing

33:42 Celine McNicholas (EPI)

Yeah, it’s a great question, and I think the proof will really be in whether Republicans push these measures that they’ve in some places endorsed or introduced when they can no longer count on Trump really to serve as the ultimate backstop, that obstacle to any real progress. But, you know, really regardless of the genuineness question, like it is clear that there are a group of Republicans, 20 odd Republicans in the House that have joined Democrats to actually bypass Speaker Johnson and pass bills that, you know, would restore collective bargaining rights to federal workers after Trump took those rights from them. Another group of 20 Republicans did the Same thing again, bypassing Speaker Johnson and Republican leadership to help pass a bill that would ensure that workers can actually win a first contract when they win themselves a union. And, you know, on the genuineness question too, it’s politicians, you know, pay attention to polls, as Chen and you have both sort of touched on, Naomi, like unions have record high favorability in polls. especially among young people, those that’s across party lines. And I think in the most recent Gallup polling, Congress had a 10% approval rating and an 86% disapproval rating. In that same Gallup polling, unions had, as you mentioned, nearly a 70% approval rating, and that is for the fifth consecutive year. So it certainly is not a new concept in politics to champion something that polls well. Particularly when you, Congress, is polling abysmally. So, you know, I think that’s obviously part of it. It’s capitalizing off of popularity. But I do want to be careful not to suggest that Democrats and Republicans occupy the same position on unions and collective bargaining. As you mentioned, Naomi, their records are absolutely distinct over the last several decades. Really, Republicans have battled unions, stood in the way of labor law reform, often explicitly including anti-union policies in their party platform. But it’s also true that many Democrats, despite consistently putting forward a far more pro-union set of policies in their platform, have failed to prioritize real reforms in these areas. And at times they’ve stood in the way as well. So it’s a bipartisan moment. It’s a bipartisan problem. And so hopefully, whether genuine or not, those polls continue to demand a response. And you to see these issues prioritized.

36:24 Naomi Walker (EPI)

Thank you, Celine. And I’m gonna give you the last question, but before I do that, we are about to move into questions. And if you’re a participant and you have a question, please for sure put it in the Q&A section. I know there have been some… Questions that have come in the chat, it’s hard for us to see those. So if you put them in the Q&A, it’s easier for us to see. So get your questions ready while we tackle this last question for Celine. And you alluded to some of this, but Celine, what do you think that we need to do to get policymakers to truly support labor?

37:02 Celine McNicholas (EPI)

So really, this is about getting them to support, getting politicians to support labor, not only on the campaign trail, but when they’re actually elected, because we know that they, when they’re running for office, many politicians use rhetoric that is pro-worker, pro-union, even Trump embraced that rhetoric on the campaign trail, and then they sort of abandon when they are in office. And so to me, the real question is, how can we as voters, as activists, as union members or union allies hold elected officials accountable for the promises that they make on the campaign trail. It certainly should not be enough to simply campaign on that rhetoric. But, you know, we have an opportunity in the midterms. We can vote smart. We can push candidates beyond the rhetoric and demand real commitments to vote for the bills that we’ve talked about today. A commitment not to, you know, basically to not let parliamentary procedures stand in the way of an agenda that provides working people with the benefits of collective bargaining, which as we’ve established here, go, you know, far beyond wages and benefits. And lastly, I’ll just say from my personal perspective here, I think we can and should elect more union members to office. That would be one surefire way to help prioritize those issues would be to actually elect people who’ve benefited from it and feel an investment in the system. You’d also, I think, have far more working class voters who are less likely to abandon their principles when then they’re put in office. So I’ll stop there.

38:33 Naomi Walker (EPI)

That was a great way to stop the presentation part of this webinar. We’re going to move into questions. I’m going to give the first question to Jen Sherer, and it’s actually kind of a combination of some of the questions that we’ve seen in the chat. Allison asked, “Can you provide examples of successful campaigns in the state to expand rights to unionize and any analysis on what made them successful?” And I’m kind of gonna combine that with a question that came in. from someone before the webinar started, which was, what is a red state, to do, and are there examples of campaigns that are happening in red states that are illustrative for us? So, Jen, kicking it to you.

39:20 Jennifer Sherer (EPI-EARN)

Yeah, I think even if we just… For now, look at the two, you know, big state policies that we focus on mostly in the report, and think about expansions of public sector collective bargaining. there have been several in the past few years. Now, I want to be clear, none of these policy changes or policy fights at the state level have been easy, and many of them have been incremental rather than comprehensive, and so we could look at, you know, probably maybe the the really, most, highly publicized example from this past year is Virginia. You know, a southern state, that historically has had an outright ban on public sector collective bargaining until a few years ago when they Partially, just partially lifted that ban for, local governments to opt in. But even that incremental step has allowed, we think, an estimated 80,000 workers to now have a union contract just in the matter of 3 or 4 years. who had a barrier there before. And so it’s a combination of workers were already organizing in local cities, school districts, counties, and are continuing to organize, to put the pressure on, the state to make these reforms. Now, people may know this past year, and for two years in a row, there was a much stronger comprehensive bill that the legislature passed twice now, has been vetoed twice now by two different governors, one Republican, one Democrat, to go back to Celine’s point. about this being a bipartisan issue. But people are not going to be giving up on that issue, because the momentum that, workers organizing both in the public and private sectors in Virginia have been building, is going to continue. So, I think there… many other examples like that, but Virginia might be the most profound one at the moment in terms of the public sector. And on the right to work front, similarly, you know, there was a slate of several states that, after 2010, passed right-to-work laws that had never had them before in, you know, during a wave of Republicans coming into government, state government. Michigan is one of the first of those states that has recently reversed its right-to-work law, and there are discussions underway in almost all of those states, similarly about what it’s going to take, now that people have lived through some of those conditions. We… we give some data from Wisconsin as an example of a state that Imposed a right to work law and the right to work law. repealed its formerly robust collective bargaining system in the last 15 years, and what that has done to decimate the state’s union density. It looks like union density in Wisconsin fell by half during that period of time, as compared to nationally. A very small change in union density overall. So people have lived through these conditions, are preparing to reverse some of those bad policies. And again, I would encourage people to look at the report for lots more, the other report on state campaigns to look for lots more examples or to feel free to also follow up with us if you’re interested in a particular locality or state. And red states are, on the, you know, on this list as well. I know, Naomi, you asked me two questions, and I didn’t fully get to the second one, but I think what we’re seeing in a lot of red southern states and midwestern states Is, people working on the local level in tandem with building momentum for state policy change. So I think one of the questions that came in in advance was from Georgia specifically. And, just to give a very concrete example, firefighters in Atlanta have been working on organizing and finding a pathway to a union contract for several years, which they just achieved this year. Again, it’s a state that does not have a clear, robust statewide framework for public sector collective bargaining, but at the local level, groups like the firefighters are finding a pathway there, and again, building a foundation for eventually, leading up to state reform.

43:43 Naomi Walker (EPI)

Thanks so much, Jen. Ben, I am coming to you with a question that came in before the webinar. What percentage of union members are women?

43:55 Ben Zipperer (EPI)

I don’t know the exact number, but it is basically half. So, I think there’s a bit of a… misunderstanding about the current state of the Union, you know, population that they think it is basically white men. And you know, there were times when what that was true, because the workforce mainly reflected white men. But now the workforce and Union membership is much more diverse. So basically, half of Union members are women. It’s something like two-thirds or so of union membership is either female or a person of color. And There actually is some pretty interesting research by scholars about how the unions can sometimes, unions can sometimes play a role in reducing gender wage gaps just like they reduce racial wage gaps. So, for example, when Wisconsin pursued a bunch of anti-union policies and effectively moved away from standardized pay scales in public schools, what that meant was that women no longer, teachers, female teachers no longer saw pay increases, but men did. So the kind of attacks on unions basically increased the gender gap, whereas before, when there was actually a stronger union presence that was able to set pay scales more collectively, gender wage discrimination was much more muted.

45:37 Naomi Walker (EPI)

Thank you so much, Ben. I am going to throw the next question. I think it’s going to go back to Jen. I think she’s the one that can answer this, but Celine, please jump in. This came in earlier. How did Taft-Hartley get passed in the first place?

46:00 Jennifer Sherer (EPI-EARN)

So, Taft-Hartley, to remind folks, is the 1947 amendment to our federal labor law that really changed a lot of the intended framework. I saw somebody else put a question in the Q&A about, you know. How widely does the general public and our, you know, current policymakers understand? That one of the things our federal labor law says is that our policy of our country is to encourage the practice and procedure of collective bargaining. well, Taft-Hartley Amendments 1947 were designed to really curtail, much of the, success that our federal labor law had begun to enable. Worker organizing had soared in the decade following the passage of the labor law, and the way it got passed was you have to really sort of look at it in historical context as a convergence of many factors, including big business backlash. Industry groups had been trying to repeal or get rid of via court challenges or undermine via state policies our federal labor laws since the moment it got passed. We should be clear, they’re still trying to do that today, and they used the opportunity of a convergence, and some really, solid alliances with white supremacist groups. groups and Southern Democrats at the time who wanted to block multiracial union organizing that was taking off in a lot of sectors. And so a wave of Republicans who were elected to Congress in 1946 had a new majority. They joined forces with some Southern Democrats to have a veto-proof majority. Taft-Hartley was not necessarily a political popular prospect even at the time among the electorate. But it was forced through Congress over a presidential veto. And it’s still embedded in our labor law today. We’re still living with the damage of it.

48:02 Naomi Walker (EPI)

Thank you so much, Jen. Celine, I’m sending this next question to you from Steven Knight. Isn’t the day-to-day reality of the retaliation workers face for speaking up, let alone organizing, close to the heart of the problem?

48:17 Celine McNicholas (EPI)

Absolutely. I mean, that is sort of when we talk about the broken system of labor law, it allows for that kind of retaliation for workers when they do try and speak up and form a union. We’ve done a ton of research on that issue at EPI and how prevalent it is that employers try and coerce and retaliate against workers. And they really do that, unfortunately, under current law. without meaningful, there’s really no meaningful penalty. There’s no, you know, there are no monetary penalties at all, really, civil monetary penalties in the NLRA. So they do so with relative impunity. It’s a perverse system in that it sort of incentivizes, because it is so weak, employers to violate workers’ rights pretty routinely. And as I mentioned, we have a whole sort of report that looks at that the charges that workers unfortunately file at the National Labor Relations Board when they’re trying to form a union and employers do everything from firing workers in retaliation for union activity to coercing them. And it’s just they do that and there really is very limited, if any, recourse under existing law, unfortunately. But even in that, I will just say, like last year, we did see, as you mentioned out of the gate, Naomi, an uptick in, you know, union membership. So I just don’t want to ever kind of, as we approach the end here, end on the note that, yes, the system is broken and there’s absolutely retaliation, but there are also success stories where even in the face of that, you know, kind of retaliation, workers really do rise up. That’s part of the, you know, benefit of all acting collectively, you know, and with some solidarity, which is at the heart of the union movement. It is a lot harder for employers to, you know, resist that in a way.

50:08 Naomi Walker (EPI)

Thanks, Celine. I am gonna, this is a toss up question. a question from Tim Newman. I was wondering if the panelists see increased fissuring and subcontracting as a counter-trend that makes expanding union density more challenging, and if so, how do we counteract that? And that’s for any of our, any of our crew, Ben, Celine, or Jed, who wants to take it.

50:42 Ben Zipperer (EPI)

Maybe, Celine, you could say some extra things, but I mean, absolutely, that’s absolutely the case. That is a major impediment to… kind of, any form of solidarity at a workplace. And, that, that, that is why, you know, we’re going to, like Celine said earlier, there’s not actually a silver bullet to solve all these problems, and, you know, one additional policy that would help with that is a better joint employment, employer standard. And, That… that is definitely, a tool that employers, will use on… unless it’s, unless we prevent them from using it or sufficiently penalize them from… When they do use it.

51:33 Naomi Walker (EPI)

Yep. Celine, do you want to add anything to that?

51:38 Naomi Walker (EPI)

Okay, good, thanks. Thanks for taking the jump shot. All right, I don’t even know if I used that the right way, but anyway, we’re gonna move on. All right, so next question up, I’m gonna ask. I’m actually, I don’t think we’re gonna answer this, but Dennis Olson put a really interesting note in the question and answer, and I’m just flagging that for Jen, that Rhode Island recently passed a new bill requiring labor peace agreements and set-asides for worker-owned co-ops. Do you wanna say anything? about that.

52:15 Jennifer Sherer (EPI-EARN)

I don’t know enough about that specific policy to say anything about that, but I’m glad to know more about it and excited to look at it. And yeah, I think it’s a great example of another avenue that many state and local governments are pursuing are forms of labor peace agreements. It’s becoming a… you know, I think there’s some really good model policies, particularly in the growing cannabis industry in some states. So, appreciate you raising that as yet another, good example of opportunities that states have.

52:46 Naomi Walker (EPI)

Great, thank you. All right. And then I think we are we’re going to do one more question and then we are going to wrap it up. One question came in. From, Lewis, I think it is. How do you suggest we connect union density and collective bargaining as a means to addressing the social justice concerns that are on top of mind for families? And that, again, jump shot, probably Celine or Jen, but Ben is welcome to it as well.

53:21 Jennifer Sherer (EPI-EARN)

I’ll just say right out of the gate, and then toss it to Celine, that I think we view this report as a tool that we hope people can use exactly for that purpose, because no matter what your top issue is, if it’s democracy, if it’s reversing poverty, if it’s addressing racial disparities, if it’s reproductive justice, no matter what it is, there is, it’s very hard to see that we have a collective pathway toward permanently transforming our society on any of those, issues without a stronger, organized, collective, base of, workers. And unions are the pathway to that, so I’ll just toss it to Celine for any other…

54:12 Celine McNicholas (EPI)

I’m not even gonna weigh in. Not have said it better than Jen, so that’s, yeah, right. Ditto, plus one.

54:19 Naomi Walker (EPI)

Awesome. Well, I am going to wrap us up. Thank you so much for joining us today. I hope you check out the report, share it with your friends, share it with your family, send it out on social media. We need all the help we can get sharing this message that tripling union membership would really have a transformative impact. on workers, their families, and our communities. And so please do help us lift this up. Thank you for sharing this hour with us. We appreciate your time and we look forward to you joining other sessions. And also if you have any other questions, please drop them in the chat really quickly. A lot of times they’re fodder. for FAQs or blog posts or reports, and so don’t hesitate. If there’s something that you want to raise, don’t hesitate to bring it up right now. So thank you so much. Have a great rest of your day. Take care.

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EPI comment on Postal Service’s proposed rule regarding “Ballot Mail for Federal Elections”

Monique Morrissey — Thu, 02 Jul 2026 17:46:35 +0000

Submitted via email

Director, Product Classification
U.S. Postal Service
475 L’Enfant Plaza S.W., Room 4446
Washington, DC 20260-5015
PCFederalRegister@usps.gov

Re: Proposed Rule: Ballot Mail for Federal Elections

The Economic Policy Institute (EPI) is a nonprofit, nonpartisan think tank that for 40 years has centered working families in economic policy discussions. EPI is submitting these comments in response to the Postal Service’s proposed rule on Ballot Mail for Federal Elections,1 which would have a disparate impact on Americans who face barriers to voting in person, including workers with disabilities, working parents, and workers with long and unpredictable work shifts. For this and other reasons outlined below, we believe that the proposed rule should be abandoned permanently and in its entirety.

The proposed rule follows a March 31, 2026, executive order from President Trump2 that would require the Postal Service to set new standards for the design of ballot envelopes used by state and local jurisdictions to facilitate centralized tracking of ballots to and from individual voters, thus encroaching on the authority to regulate and administer elections that the Constitution assigns to Congress and the states. The proposed rule also directs the Postal Service to compile a national voter list from state voter rolls and to reject ballots addressed to voters who are not on the list or that do not conform to the new envelope standard.

Tellingly, the proposed rule does not instruct the Postal Service to notify voters whose ballots were not delivered so that voters can challenge these decisions and correct errors caused by typos and similar discrepancies, which are vastly more common than deliberate fraud. Discrepancies and gaps in government records are not purely random, but are more likely to affect people with uncommon or hyphenated names (including many foreign-born citizens), married women who changed their names, and elderly and low-income Americans, among others.3

The proposed rule would misuse government data for political purposes.

The proposed rule should be viewed in the larger context of actions taken by this administration to use government data for unauthorized purposes, including voter suppression.

In addition to directing the Postal Service to compile a list of registered voters and use it to restrict mail voting, other provisions of the president’s executive order direct the United States Citizenship and Immigration Services (USCIS) and the Social Security Administration (SSA) to compile lists of voting-age citizens in each state, even though there is no evidence that fraudulent voting by noncitizens is a problem in U.S. elections.4 However, purging voter lists of suspected noncitizens could be used to disenfranchise eligible voters.

A case pending before the U.S. Supreme Court that would weaken the National Voter Registration Act could enable voter purges of suspected noncitizens close to elections when voters have little time to challenge errors that are common in such purges.5 Since some groups are more likely to vote for particular parties, purges can be weaponized for partisan advantage, a problem that would be magnified if done on a national scale.

The executive order adds to previous efforts by this administration to use SSA and other sensitive personal data for purposes beyond their intended use. It also risks another data breach in violation of federal privacy laws similar to an earlier breach of SSA data by a DOGE operative.6

The proposed rule would discourage voting by mail and harm working families who are more likely to face barriers to in-person voting.

Importantly, the harm inflicted by the proposed rule would extend beyond eligible voters who are directly prevented from voting by mail because they do not appear on the Postal Service list of registered voters. By casting doubt on the integrity and impartiality of mail voting, the rule would increase the number of voters dissuaded from voting by mail who later find themselves unable to vote in person.

Thirteen states, along with Puerto Rico and the Virgin Islands, restrict absentee voting to voters who know they will be out of the county on election day, or, in some states, who face barriers related to age, health, disability, work schedules, or other conflicts, such as jury duty.7 In my personal capacity as a volunteer on a voter assistance hotline, I can attest that many, if not most, people who face barriers to in-person voting could not have predicted them in advance. Voters frequently fall sick, face long lines at the polls that threaten to make them late for work, or find themselves with last-minute childcare and transportation problems.

Even voters who face predictable barriers that are valid reasons for absentee voting in their state can find it difficult to determine whether they qualify since specifics are not spelled out or are buried in dense legal language. What counts as a disability? Is documentation required? What if an anticipated work shift, jury duty, or vacation does not happen?

As the Institute for Policy Studies has pointed out, working-class voters are more likely to face barriers to voting in person due to work and family obligations.8 The Shift Project at the Harvard Kennedy School has documented the large number of low-wage workers, disproportionately workers of color, who work long and unpredictable shifts with little input into their schedules.9 In-person voting hours vary by state, but typically span a 12- or 13-hour time period.10 For working parents transporting children to school, workers with long commutes, and workers who face mobility challenges, it can be difficult if not impossible to vote in person within the designated window, especially if lines at the polls are long. Though some white-collar workers face these challenges, low-wage workers are less likely to work from home, have predictable schedules, or be given flexibility by employers to vote.

The Postal Service should scrap the proposed rule.

The above-mentioned constitutional, voting rights, and logistical problems with the proposed rule have been described in lawsuits and in commentary from a wide range of stakeholders and perspectives, including Lawfare,11 the Cato Institute,12 and the American Postal Workers Union.13 Twenty-three states and the District of Columbia successfully sued to temporarily block the executive order on which the proposed rule is based.14 However, the administration has said they will challenge the ruling, and regardless the rule could still take effect after the upcoming November election (the focus of the temporary injunction).

EPI believes that the proposed rule should be abandoned permanently and in its entirety for the following reasons:

It is an unlawful attempt by the executive branch to seize control of elections from states and Congress.15
It would inflict reputational damage on the Postal Service by involving it in decisions about who can and cannot receive ballots and vote by mail.16
It would impose financial and logistical burdens on the Postal Service, which is already stretched to its limit.17
It could jeopardize the timely delivery of all mail ballots, including those that conform to the requirements of the rule.18
In combination with other provisions of the executive order, it could facilitate systematic voter purges for partisan advantage.
It would cast doubt on the integrity and impartiality of mail voting.
It would dissuade eligible voters from voting by mail, many of whom will face barriers to voting in person.

The Postal Service is an independent agency that, by design, is not under the direct control of the president and therefore not subject to his executive order.19 It has impartially delivered mail ballots to voters since the Civil War, when states introduced absentee voting for soldiers, a right later extended to other absentee voters. Some states have also extended vote by mail to voters who face specific barriers to in-person voting, such as people with disabilities. Other states and the District of Columbia have gone much further, mailing ballots to all registered voters. This is by far the fairest solution, but until it is the law of the land, we should work to extend, not restrict or suppress, mail voting.

Respectfully submitted,

Monique Morrissey
Senior Economist

Endnotes

1. “Ballot Mail for Federal Elections: A Proposed Rule by the Postal Service on 06/02/2026,” Federal Register Published Document: 2026-10968 (91FR 32915). https://www.federalregister.gov/documents/2026/06/02/2026-10968/ballot-mail-for-federal-elections

2. Donald J. Trump, “Ensuring citizenship verification and integrity in federal elections,” March 31, 2026. https://www.whitehouse.gov/presidential-actions/2026/03/ensuring-citizenship-verification-and-integrity-in-federal-elections/

3. Monique Morrissey and Daniel Costa, “Cleaning up administrative records or targeting immigrants?” https://www.epi.org/blog/cleaning-up-administrative-records-or-targeting-immigrants/

4. See, for example, Wren Orey, Theresa Cardinal Brown, Feyisayo Oyolola, and Theo Menon, “Four Things to Know about Noncitizen Voting,” Bipartisan Policy Center, February 20, 2026. https://bipartisanpolicy.org/article/four-things-to-know-about-noncitizen-voting; Michael Waldman, “Why the Myth of Noncitizen Voting Persists,” Brennan Center for Justice, August 21, 2024. https://www.brennancenter.org/our-work/analysis-opinion/why-myth-noncitizen-voting-persists. Stephen Richer, “Trump’s Claims About Noncitizens Voting Are False. We Can Prove It.” Cato Institute, February 5, 2026. https://www.cato.org/commentary/trumps-claims-about-noncitizens-voting-are-false-we-can-prove-it

5. Jim Saksa, “Supreme Court will hear Arizona case that could badly weaken key federal law protecting voter registration,” Democracy Docket, June 29, 2026. https://www.democracydocket.com/news-alerts/supreme-court-will-hear-arizona-case-that-could-badly-weaken-key-federal-law-protecting-voter-registration/

6. Stephen Fowler and Jude Joffe-Block, “The Trump administration admits even more ways DOGE accessed sensitive personal data,” Weekend Edition, National Public Radio, January 30, 2026. https://www.npr.org/2026/01/23/nx-s1-5684185/doge-data-social-security-privacy

7. National Council of State Legislatures, Table 2: Excuses to Vote Absentee, website accessed July 2, 2026. https://www.ncsl.org/elections-and-campaigns/table-2-excuses-to-vote-absentee

8. Sarah Anderson, “Attacks on Mail Voting are Attacks on the Working Class,” Institute for Policy Studies, April 6, 2026. https://ips-dc.org/attacks-on-mail-voting-are-attacks-on-the-working-class/

9. Daniel Schneider and Kristen Harknett, “It’s About Time: How Work Schedule Instability Matters for Workers, Families, and Racial Inequality,” October 16, 2019. https://shift.hks.harvard.edu/its-about-time-how-work-schedule-instability-matters-for-workers-families-and-racial-inequality/

10. Ballotpedia, “State Poll Opening and Closing Times (2026),” website accessed July 2, 2026. https://ballotpedia.org/State_Poll_Opening_and_Closing_Times_(2026)

11. Molly Roberts, “What’s up with Trump’s Mail-In Voting Executive Order?” Lawfare, Monday, June 29, 2026. https://www.lawfaremedia.org/article/what-s-up-with-trump-s-mail-in-voting-executive-order

12. Stephen Richer, “USPS Issues Proposed Mail Voting Rules Pursuant to Trump Executive Order,” Cato at Liberty blog, May 29, 2026. https://www.cato.org/blog/usps-issues-proposed-mail-voting-rules-pursuant-trump-executive-order

13. Jonathan Smith, APWU Comments on Proposed Rule: Ballot Mail for Federal Elections, June 29, 2026. https://apwu.org/wp-content/uploads/2026/06/APWU-Comments-VBM-Rulemaking.pdf

14. Dion Nissenbaum, “Federal judge blocks key pillars of Trump executive order restricting mail voting in 2026 election,” VoteBeat, June 25, 2026. https://www.votebeat.org/national/2026/06/25/trump-election-overhaul-mail-voting-executive-order-blocked-talwani-usps-dhs/

15. Molly Roberts, “What’s up with Trump’s Mail-In Voting Executive Order?” Lawfare, Monday, June 29, 2026. https://www.lawfaremedia.org/article/what-s-up-with-trump-s-mail-in-voting-executive-order

16. Smith, op. cit.

17. Ibid.

18. Ibid.

19. Ibid.

EPI comment on DHS’s proposed rule on “Employment Authorization Reform for Asylum Applicants”

Daniel Costa — Fri, 24 Apr 2026 13:11:32 +0000

Submitted via https://www.federalregister.gov/documents/2026/02/23/2026-03595/employment-authorization-reform-for-asylum-applicants

Division of Humanitarian Affairs
Office of Policy and Strategy
U.S. Citizenship and Immigration Services
Department of Homeland Security
5900 Capital Gateway Drive
Camp Springs, MD 20746

Re: DHS Docket No. USCIS-2025-0370, Employment Authorization Reform for Asylum Applicants, Notice of Proposed Rulemaking (Feb. 23, 2026)¹

To whom it may concern:

The Economic Policy Institute (EPI) submits this comment strongly opposing the Department of Homeland Security’s (DHS) Notice of Proposed Rulemaking (NPRM) titled Employment Authorization Reform for Asylum Applicants, published February 23, 2026. and assigned DHS Docket No. USCIS-2025-0370 (i.e. the proposed rule).

About EPI and organizational interest

The Economic Policy Institute (EPI) is a nonprofit, nonpartisan think tank established 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 policies that protect and improve economic conditions and raise labor standards for low- and middle-income workers—regardless of immigration status—and assesses policies with respect to how well they further those goals.

EPI has researched, written, and commented extensively on the U.S. system for labor migration, including on temporary immigration protections and Employment Authorization Documents (EADs), and on labor standards enforcement for both the low-wage and professional workforce. EPI has also provided expert testimony about the U.S. immigration system to both the U.S. Senate and House of Representatives, as well as state legislatures.

Summary of the comment

The proposed rule is designed to force asylum applicants seeking haven in the United States to live in the country without being able to work or support themselves and their families. Among other changes, the proposed rule introduces extreme and potentially indefinite delays to obtain a work permit, as it proposes to extend the waiting period to apply for work authorization from 150 days to 365 days, increase the mandatory processing timelines once an initial work permit application is received from 30 days to 180 days, and pause initial work permit processing completely when average affirmative asylum processing times exceed an average 180 days.1 The proposed rule also imposes many new eligibility barriers for both initial and renewal work permits, and would make approval of both applications completely discretionary, meaning asylum-seekers may be denied employment authorization for no reason at all.2

This proposed rule would be acutely harmful to asylum-seekers, but also to employers, coworkers, and spouses and children who rely on asylum-seekers’ employment and income. From the perspective of worker rights, labor standards, and growth in the overall economy, this NPRM raises at least four significant concerns that should be avoided by withdrawing the proposed rule in full.

First, DHS ignores the true value and impact of work authorization on the workforce, and fails to estimate the negative economic impacts that will result from the NPRM. In addition, the proposed rule would impact many workers already participating in the U.S. workforce, including individuals the NPRM classifies as “initial” asylum applicants who previously held lawful employment authorization through programs such as Temporary Protected Status (TPS), humanitarian parole, or deferred action. By focusing on deterrence of future migration while overlooking these workforce impacts, the NPRM substantially understates both the disruption the rule would cause and the reliance interests at stake.

Second, the NPRM rests on the flawed assumption that employers can easily replace asylum-seeking workers who lose employment authorization, and that such replacement can happen quickly and without disruption to the economy. In reality, sudden workforce losses that result from the NPRM terminating or putting in jeopardy the work authorization of roughly 2 million current workers would disrupt operations across multiple industries, forcing employers to increase mandatory overtime, heightening workplace safety risks, and creating significant operational instability that would impact not only asylum-seekers but also their coworkers. Employers would also lose the experience and job-specific skills that many asylum applicants already possess.

Third, by making it far more difficult for asylum-seekers to obtain or renew work authorization, the proposed rule would eviscerate the workplace rights of millions of current and future workers, pushing many into the informal economy, increasing the risk of wage theft, retaliation, and other forms of worker exploitation. This shift would also undermine labor and employment law enforcement by making workers less likely to report violations or cooperate with investigators, weakening workplace protections and lowering labor standards for all workers. The NPRM fails to acknowledge the scope of these enforcement and labor-standards consequences for U.S.-born citizens and foreign-born workers, half of whom are U.S. citizens.

Fourth, the NPRM fails to consider the substantial reliance interests that workers have developed around a predictable system of asylum-based employment authorization, which the NPRM would upend.

Far from streamlining the regulation of asylum-related employment authorization, the proposed rule would harm workers across the board. For these reasons, DHS should withdraw the proposed rule.

The worker rights of millions are protected by EADs

The role that Employment Authorization Documents (EADs) play when it comes to protecting worker rights and uplifting workplace standards should not be ignored and cannot be overstated. For workers who lack a permanent or more durable immigration status, obtaining a temporary EAD can mean having enforceable workplace rights that an individual would otherwise not have. While all workers have some labor and workplace rights under U.S. law—regardless of immigration status—enforcing them in practice becomes virtually impossible because of the threat of deportation, which prevents workers who lack an immigration status or an EAD from calling out lawbreaking employers and demanding that they comply with the law, or from reporting workplace violations to labor enforcement agencies. But having an asylum-based EAD, or protection from deportation through temporary administrative immigration protections like parole, Temporary Protected Status, deferred action—accompanied by an EAD—means that, in practice, workers can report workplace violations to government officials without fear of retaliation that can lead to deportation. It also means that a worker with an EAD can be employed by just about any U.S. employer and change jobs or employers, unlike, for example, migrant workers employed with temporary visas who can only be employed by the sponsor of their visa.

Altogether, nearly 5.6 million people in the U.S. held a temporary but precarious immigration status in 2024, including over 2 million people who are asylum-seekers. (see Table 1 below).

Table 1

While these statuses and protections are only a band-aid for a flawed immigration system that is deeply in need of reform,3 they have been shown to protect millions of workers from some of the worst forms of employer lawbreaking. Employers also greatly benefit from workers having a protective status and a work permit because it allows them to lawfully employ millions of people who would otherwise not be eligible to work, leading to billions in economic contributions to the U.S. economy and generating demand that stimulates growth.

DHS ignores the positive value and impact of work authorization on the workforce and economy, and the negative impacts of terminating and delaying work authorization

In the NPRM, DHS does not estimate and consider the true value and impact that EADs have on the workforce and economy, not even specifically for asylum-seekers. There are examples of existing research showing the important economic contributions that workers with temporary immigration protections and EADs are able to make thanks to being work-authorized. These estimates are relevant because parole, TPS, and DACA recipients are likely to see similar wage gains associated with having an EAD, due to gaining the ability to work lawfully, which brings with it the practical ability to enforce workplace rights and standards. In addition, may persons with protections like TPS and DACA may also be asylum applicants.

One estimate from the American Immigration Council estimated that when the TPS population was approximately 354,000 in 2021, “TPS holders contributed more than $2.2 billion in taxes, including almost $1 billion to state and local governments,” as well as “held $8 billion in spending power.”4 Another estimate by Moriarty found that TPS-eligible individuals “annually contribute some $31 billion in wages to the national GDP.”5

Research has also quantified some of the contributions made by persons who have an EAD because they qualified for Deferred Action for Childhood Arrivals (DACA). DACA was created by DHS in 2012, and recipients are eligible for protections from deportation and EADs that are valid for two years and renewable. More than 835,000 persons have benefitted from DACA, and more than 500,000 were enrolled as of 2024.6 Svajlenka and Truong found that DACA recipient households “pay $6.2 billion in federal taxes and $3.3 billion in state and local taxes each year,” and “after taxes, these households hold $25.3 billion in spending power,” and that DACA recipient families “own 68,000 homes, making $760 million in mortgage payments and $2.5 billion in rental payments annually.”7

When it comes to measuring the workplace impact and economic benefits of workers being issued an EAD, there are a few examples that are worth citing here. One is an annual survey of DACA recipients that was conducted in 2024 for the ninth time. The most recent survey, conducted by Wong et al. and published by the Center for American Progress, showed that DACA has been an essential tool to improve the economic and educational outcomes of recipients.8 In terms of the impact that deferred action and an EAD have had on the employment of DACA recipients: 59.1% of respondents moved to a job with better pay; 47.3% moved to a job with better working conditions; 47.5% moved to a job that “better fits [their] education and training”; 49.6% moved to a job that “better fits [their] long-term career goals”; 57.3% moved to a job with health insurance or other benefits; and 19.6% of respondents obtained professional licenses.

Wong et al. also measured the impact of EADs on DACA recipients’ wages, finding that “[d]ata from the past nine years show that DACA has had a significant and positive effect on wages: Recipients’ average hourly wage more than doubled from $11.92 to $31.52 per hour—an increase of 164.4 percent—after receiving DACA.” These significant wage increases are no doubt a result of the labor and workplace rights and stability that DACA recipients gain from having an EAD.

Orrenius and Zavodny examined the wage and employment impact of TPS9—which allows those who are eligible to also be granted an EAD. They looked specifically at migrants from El Salvador, finding that having TPS increased employment rates, and that less-educated Salvadoran men who were employed earned 13% more if they had TPS. They note that “As a whole, the results suggest that less-educated Salvadoran men who receive TPS are able to move into better jobs and become more selective about the jobs they hold, increasing their earnings but also their job search and unemployment incidence.”

One other analysis comes from Kallick,10 looking specifically at asylum-seekers in New York and nationwide, assesses the wage impact of being issued an EAD. Relying on previous methodologies for measuring the impact of a lawful immigration status being granted to unauthorized immigrants, Kallick estimates that asylum-seekers who are granted EADs increase their wages by 10%.

While the relative benefits of precarious and temporary immigration protections and EADs to migrant workers and the broader economy are clear, it is important to note here that because of the NPRM’s new provisions and pauses in processing, a significant share of the 2 million EADs held by asylum-seekers are unlikely to be renewed, or at a minimum, will be substantially delayed—and initial applications will not be granted—despite meeting the statutory requirements for issuance. This violates the statute and will leave hundreds of thousands of workers at least, and possibly millions, unemployed and without the ability to feed and house themselves, causing them to rely on homeless shelters and food banks, which are already overstretched given the current state of the economy and the affordability crisis. Thus, DHS through this NPRM will intentionally hurt the economy and eliminate the economic benefits for workers and employers that EADs held by asylum-seekers create—and exacerbate a crisis among social safety net providers—a fact that the NPRM does not grapple with or address.

In the meantime, EADs obtained through the asylum process, like those obtained through TPS, parole, and DACA, can mean the difference between having rights on the job or being extraordinarily vulnerable to the worst abuses by employers. While the current administration has claimed they want to help U.S. workers, actions like the mass detention and deportation of millions of workers and canceling EADs reveal they are willing to degrade conditions and standards for all workers, as well as kill jobs and shrink the economy, in order to carry out their extreme immigration enforcement agenda.11

If the NPRM is not withdrawn, millions of workers will be more easily exploited by their bosses and driven into the informal economy. That, in turn, will reduce their tax contributions that support the social safety net and lower their wages significantly12—ultimately hurting U.S workers in low-wage industries and the U.S. economy writ large by driving down demand for goods and services. It will also leave employers without millions of reliable employees in industries like construction, hospitality, childcare, agriculture, food processing and production, and more.

The NPRM underestimates the economic harm to initial asylum applicants who are already employed in the U.S. workforce

The NPRM rests heavily on the premise that restricting access to asylum-based work authorization will deter future asylum applicants by reducing the perceived “pull factor” of employment opportunities in the United States given the lengthy asylum backlog.13 While briefly referenced above, it is worth highlighting that this premise overlooks that many “initial” asylum employment authorization applicants are workers who are already here, including many who are gainfully employed.

Since January 2025, the federal government has terminated or moved to dismantle legal immigration programs that provided work authorization to hundreds of thousands of individuals, including several countries’ TPS designations, the CBP One parole program, the parole program for Cubans, Haitians, Nicaraguans, and Venezuelans (CHNV), multiple family reunification parole programs, and DACA.14 Many workers whose work permits have been terminated or threatened by these changes—and who are also eligible for asylum—are filing asylum applications and seeking initial employment authorization based on their pending applications.

The NPRM acknowledges this trend in passing,15 but largely sidesteps its implications—namely, that the NPRM’s sweeping restrictions on employment authorization for “initial asylum applicants” will largely fall on individuals who are already integrated into the lawful workforce. These workers are not hypothetical future entrants; they are experienced employees currently working in hospitals, manufacturing facilities, construction sites, hotels, schools, and public services. The NPRM therefore risks removing from the workforce hundreds of thousands of workers who have already been performing essential roles in the U.S. economy.

By focusing on speculative deterrence effects for future migrants while overlooking the proposed rule’s immediate impact on workers already embedded in the U.S. economy, the NPRM fails to accurately assess the scope of the disruption the proposed rule would cause. This flawed premise permeates the NPRM’s analysis and projected impacts and, on its own, warrants withdrawal of the proposed rule.

The NPRM incorrectly assumes that asylum-seekers who lose employment authorization can easily be replaced and ignores the resulting disruption to the economy

The NPRM suggests that asylum-seeking workers who lose employment authorization may be replaced and that the resulting shifts may lead to increased hours or compensation for currently employed workers.16 Although the NPRM acknowledges that restrictions on asylum-based employment authorization may lead employers to rely more heavily on currently employed workers through increased hours or overtime, it largely treats these effects as a potential transfer of compensation rather than as a source of workforce disruption.17 These assumptions simply do not reflect the realities in which many asylum applicants work.

A) The NPRM would shrink the legal workforce, exacerbating staffing issues in key industries

Asylum applicants are employed in a number of key industries, such as construction, transportation, manufacturing, food preparation and service, and building and grounds maintenance.18 Employers in sectors such as health care, long-term care, hospitality, education, and logistics frequently report difficulty recruiting and retaining sufficient numbers of workers.19 In these and other industries, the loss of experienced workers cannot easily be offset by replacement hiring. This is the case, in part, because of the Trump administration’s immigration enforcement policies, which are resulting in stagnant population and workforce growth, leaving fewer available workers to fill positions previously held by asylum-seekers.20

The NPRM as a result will exacerbate staffing issues in key industries, by pausing, terminating, or simply not adjudicating EAD applications. Further, the NPRM provides no empirical analysis demonstrating that employers will be able to replace workers who lose asylum-based employment authorization. Instead, the proposed rule rests on speculative assumptions that are inconsistent with the experience of the industries most affected.

B) The NPRM would increase mandatory overtime and workload pressures on remaining workers

Across unionized industries, abrupt workforce losses rarely produce the seamless labor substitution envisioned in the NPRM. Instead, employers often struggle to recruit qualified replacements, leaving operations understaffed for extended periods. In some cases, employers may scale back operations or lay off additional workers when they can no longer meet production or service demands due to the loss of experienced personnel.21 These dynamics are particularly severe in rural areas and specialized industries where the available labor pool is already limited and recruiting new workers can take months or even years.

When employers cannot quickly replace lost staff, the burden falls on the remaining workforce. Workers may be required to work extended shifts, mandatory overtime, or intensified production schedules to maintain operations. These conditions increase worker fatigue and place significant strain on the remaining workforce.22

C) The NPRM would increase workplace safety risks by disrupting experienced workforces

Staffing shortages and excessive overtime can also create significant safety risks. In many safety-sensitive workplaces, such as construction sites, manufacturing facilities, warehouses, and healthcare settings, the sudden loss of experienced workers can create immediate hazards for the remaining workforce. Short-staffing often forces employees to perform additional tasks or work at faster production speeds, increasing the likelihood of fatigue-related injuries and other workplace incidents. Efforts to rapidly replace experienced workers with new or inexperienced hires can further heighten safety risks for the entire workforce. Unionized workplaces have reported increased injury rates, higher stress levels, and exacerbated turnover and burnout following sudden staffing reductions tied to immigration policy changes.23

D) The NPRM would weaken bargaining power in unions and organizing capacity

Many asylum-seekers and other immigrant workers are union members, and their ability to work lawfully is critical to the stability of union bargaining units. By severely restricting asylum-seekers’ access to employment authorization, the NPRM would harm not only individual workers but also the unions that represent them by disrupting membership, weakening collective representation, and undermining unions’ capacity to maintain stable bargaining relationships with employers.

Labor history and modern labor-market research confirm the central role immigrant workers play in sectors where unions organize and represent workers.24 Immigrant workers are disproportionately employed in high-turnover, demanding industries where unions depend on workforce stability to sustain membership and bargaining strength.25 As immigrant employment has grown, so too has immigrants’ share of union membership, making them an increasingly important source of union participation and organizing.

By sharply curtailing asylum-seekers’ access to employment authorization, the NPRM would destabilize the workforce in industries where unions are building and maintaining collective representation. Denying or delaying work authorization would force many workers out of lawful employment or prevent workers from entering lawful employment relationships and joining unions, weakening existing bargaining units and reducing unions’ membership base. It would also disrupt organizing efforts by removing workers from the workforce before they can participate in union campaigns or collective bargaining.

The NPRM’s restrictions on asylum-seekers’ work authorization would significantly impair unions’ ability to represent and grow their membership.

The NPRM would push workers into the underground economy, increase labor and employment violations, weaken labor standards enforcement, and lower wages in numerous industries

The proposed rule would significantly restrict asylum-seekers’ ability to work legally while their asylum claims—often pending for years—are adjudicated, effectively forcing many asylum-seekers to support themselves and their families for extended periods of time without lawful employment.

The NPRM does not meaningfully analyze how individuals in this situation are expected to sustain themselves during those years, nor how effectively eliminating asylum-seekers’ access to employment authorization will impact the enforcement of labor standards, including wage and hour laws, labor laws, and workplace safety laws. In practice, without work authorization, many people will turn to informal or off-the-books employment arrangements in order to support themselves and their families. And we know from existing research that employees who lack work authorization are more than twice as likely to be victims of wage theft for minimum wage violations than U.S.-born citizens.26 Workers in these circumstances are significantly more vulnerable to exploitation. Employers may take advantage of workers’ immigration status to suppress wages, deny overtime pay, ignore workplace safety standards, or retaliate against workers who attempt to assert their rights.

When workers are pushed into informal employment, the resulting labor violations extend beyond those workers themselves—to all workers—regardless of immigration status or the country where they were born. Employers who exploit vulnerable workers not only depress wages and benefits for authorized workers in the same workplace, but they also gain a competitive advantage over law-abiding employers that comply with labor laws and collective bargaining agreements.27 In this way, the NPRM’s restriction of lawful employment authorization would distort workplace competition by rewarding employers that exploit vulnerable workers while disadvantaging those that comply with labor laws and collective bargaining agreements, thus lowering wages for all workers in the many industries where asylum-seekers are employed.

These consequences would reverberate across workplaces and industries. When employment moves into the informal economy, labor violations become harder to detect and enforce, enabling exploitative employers to undercut law-abiding competitors and driving down wages and working conditions for other workers. The NPRM does not meaningfully analyze these foreseeable effects. By failing to account for the predictable expansion of informal employment created by the proposed rule, the NPRM substantially understates its impact on labor standards and the broader labor market.

The NPRM disregards the significant reliance interests created by the existing system of asylum-based employment authorization

Under the Administrative Procedure Act (APA), agencies must consider the reliance interests that regulated parties have developed under existing policies before adopting regulatory changes that would disrupt those settled expectations.28 The NPRM fails to meaningfully account for the reliance interests that workers and unions have developed around the current system of asylum-based employment authorization.

For years, asylum-seekers and labor organizations have relied on a predictable regulatory framework under which individuals who meet the criteria for employment authorization can obtain a work permit within a defined timeframe. Workers make critical life decisions—including housing, transportation, and family support—based on the expectation that, if they satisfy the applicable requirements, they will be able to work lawfully while their asylum claims are pending. By introducing sweeping delays, additional eligibility barriers, and broad discretionary authority to deny applications, the proposed rule would upend these settled expectations and inject profound uncertainty into a system on which workers have long depended.

These reliance interests are particularly significant because many individuals the NPRM characterizes as “initial” asylum employment authorization applicants are not new entrants to the labor market. As described above, many have already been participating in the lawful workforce through programs such as TPS, humanitarian parole, deferred action, or other programs that allow for employment authorization. When those programs are terminated or curtailed, many workers eligible for asylum turn to the asylum system in order to maintain lawful employment authorization—relying on claims for asylum that are almost certainly valid given the circumstances that allowed them to qualify for temporary protections like TPS and parole—but which they did not assert sooner because of their eligibility for other programs which could be approved more quickly. Closing off this pathway for these current lawful employees in the U.S. labor market who also have valid asylum claims will eliminate the only remaining pathway for them to continue working lawfully in jobs they already hold. Their coworkers, employers, and entire workplaces depend on their continued participation in the labor force.

By imposing new eligibility barriers and expanding the circumstances under which renewal applications may be denied, along with creating unjustified lengthy bureaucratic pauses in adjudication, the proposed rule would significantly slow the renewal process and increase the likelihood that workers will lose lawful employment authorization while their applications remain pending. Given the scale of the existing asylum backlog, these changes threaten to create widespread gaps in work authorization for workers who have already been lawfully employed for years.

The NPRM would bring the asylum-based employment authorization system to a functional standstill. Workers who have relied on timely adjudication of work authorization applications would face prolonged periods without lawful employment authorization, while co-workers who depend on those workers would face sudden and unpredictable staffing disruptions. The NPRM does not meaningfully engage with these reliance interests or the systemic consequences of destabilizing an employment authorization framework on which hundreds of thousands of workers and employers have come to depend.

Because the proposed rule disregards these substantial reliance interests and fails to evaluate the disruptive consequences of overturning longstanding expectations about the availability and timing of employment authorization, the NPRM fails to consider an important aspect of the problem before the agency.

Conclusion and recommended action

The NPRM rests on a chain of flawed assumptions that do not reflect the realities of the modern U.S. labor market. It ignores the positive economic benefits and value of Employment Authorization Documents for asylum-seekers, and fails to estimate the many negative impacts that will result, harming not only asylum-seekers, but also U.S. employers and U.S.-born citizen workers. It mischaracterizes who will be impacted by the proposed rule, failing to recognize that many “initial” asylum applicants who would face the harshest aspects of the proposed rule are already embedded in the workforce. It disregards the substantial reliance interests that workers and employers have developed around a predictable system of asylum-based employment authorization. It ignores the predictable expansion of informal employment that will result from leaving asylum-seekers without lawful means of supporting themselves for years. And it assumes—without evidence—that employers will be able to easily replace workers who lose employment authorization.

In practice, the proposed rule would not streamline the administration of asylum-based employment authorization. Instead, it would destabilize workplaces, disrupt established workforces, weaken labor standards enforcement—leading to lower wages for workers in many industries—and impose significant costs on workers, employers, and the broader labor market.

For these reasons, the Economic Policy Institute urges DHS to withdraw the proposed rule.

Comment submitted by:

Daniel Costa
Director of Immigration Law and Policy Research
Economic Policy Institute

Endnotes

1. See Employment Authorization Reform for Asylum Applicants, 91 Fed. Reg. 8616, 8618–20 (Feb. 23, 2026).

2. See id. at 8618–19.

3. Daniel Costa, Josh Bivens, Ben Zipperer, and Monique Morrissey, The U.S. benefits from immigration but policy reforms needed to maximize gains: Recommendations and a review of key issues to ensure fair wages and labor standards for all workers, Economic Policy Institute, October 4, 2024.

4. American Immigration Council, The Contributions of Temporary Protected Status Holders to the U.S. Economy (fact sheet), September 19, 2023.

5. Andrew Moriarty, “Temporary Protected Status (TPS): 5 Things to Know,” Policy Brief, FWD.US, February 29, 2024.

6. President’s Alliance on Higher Education and Immigration (President’s Alliance), Breakdown of Dreamer Populations—Both with and Without DACA, Updated May 23, 2024.

7. , Nicole Svajlenka and Trinh Q. Truong, “The Demographic and Economic Impacts of DACA Recipients: Fall 2021 Edition,” Center for American Progress, November 24, 2021.

8. Tom Wong, Ignacia Rodriguez Kmec, Diana Pliego, Karen Fierro Ruiz, Silva Mathema, Trinh Q. Truong, and Rosa Barrientos-Ferrer, 2023 Survey of DACA Recipients Highlights Economic Advancement, Continued Uncertainty amid Legal Limbo, Center for American Progress, March 25, 2024.

9. Pia Orrenius and Madeline Zavodny, “The Impact of Temporary Protected Status on Immigrants’ Labor Market Outcomes,” Federal Reserve Bank of Dallas Working Paper no. 1415, December 2014.

10. David Dyssegaard Kallick, “’Let Us Work’: The Wage Gain When Asylum Seekers Gain Work Authorization,” Immigration Research Initiative, September 7, 2023.

11. See for example, Ben Zipperer, Trump’s deportation agenda will destroy millions of jobs: Both immigrants and U.S.-born workers would suffer job losses, particularly in construction and child care, Economic Policy Institute, July 10, 2025.

12. See for example, Carl Davis, Marco Guzman, and Emma Sifre. 2024. Tax Payments by Undocumented Immigrants, Institute on Taxation and Economic Policy, July 30, 2024.

13. This rationale—the validity of which is beyond the scope of this comment—is repeated throughout the NPRM. See, e.g., Employment Authorization Reform for Asylum Applicants, Notice of Proposed Rulemaking, 91 Fed. Reg. 8616, 8620 (Feb. 23, 2026) (“[T]he affirmative asylum application backlog serves as a magnet pulling aliens into the U.S. illegally.”); id. at 8664 (same); id. at 8629 (“filing fraudulent, frivolous, or otherwise meritless asylum cases primarily to access employment authorization” is a “pull factor for illegal immigration,” such that the NPRM “should decrease the number of illegal border crossers”); id. at 8659 (proposing new eligibility bar on asylum-based work permits to “curb the pull-factor of employment authorization for those who have been present in the United States for more than 1 year”); id. at 8660 (“This rule will prioritize the safety and security of the American people by disincentivizing illegal migration and criminal conduct for [sic] aliens who would like to obtain employment authorization.”); id. at 8669 (“tethering (c)(8) EAD application acceptance to asylum processing times . . . will permanently eliminate the possibility that asylum backlogs may serve as a magnet attracting illegal immigration”).

14. See Temporary Protected Status (TPS): Fact Sheet, Forum (Feb. 4, 2026), https://forumtogether.org/article/temporary-protected-status-fact-sheet/ (listing recent TPS termination announcements, including TPS protections for Venezuela, Haiti, Nepal, Honduras, Nicaragua, Syria, Afghanistan, Cameroon, South Sudan, Burma, Ethiopia, Somalia, and Yemen); Dep’t of Homeland Sec., DHS Issues Notices of Termination for the CHNV Parole Program, Encourages Parolees to Self-Deport Immediately (June 12, 2025), https://www.dhs.gov/news/2025/06/12/dhs-issues-notices-termination-chnv-parole-program-encourages-parolees-self-deport; U.S. Citizenship & Immigr. Servs., Termination of Family Reunification Parole Processes for Colombians, Cubans, Ecuadorians, Guatemalans, Haitians, Hondurans, and Salvadorans, 90 Fed. Reg. 58032 (Dec. 15, 2025); Gregory Royal Pratt & Laura Rodríguez Presa, DACA delays lead to lost jobs, less stability and anxiety over potential deportation under Donald Trump, Chicago Tribune (Mar. 15, 2026), https://www.chicagotribune.com/2026/03/15/daca-delays-trump-immigration/.

15. See 91 Fed. Reg. at 8652-53, 8658 (acknowledging former TPS, parole, and DACA holders often apply for asylum).

16. 91 Fed. Reg. at 8620–21, 8664-65.

17. See id. (noting that lost compensation may be transferred to currently employed workers through additional hours or overtime).

18. See, e.g., fwd.us, People seeking asylum are contributing to the workforce (Jan. 31, 2026), https://www.fwd.us/news/people-seeking-asylum-are-contributing-to-the-workforce/.

19. See, e.g., Brief of Amici Curiae AFL-CIO and Ten Affiliated Labor Unions, Lesly Miot v. Trump, No. 26-5050 (D.C. Cir. Feb. 17, 2026) (“AFL-CIO and Affiliated Labor Unions Haiti TPS Brief”), at 16–17.

20. See, e.g., Julia Gelatt, “Trump Restrictions on Legal Immigration Could Sharply Reduce U.S. Population Growth,” Migration Policy Institute (April 2026), https://www.migrationpolicy.org/news/trump-legal-immigration-cuts-us-population-growth; and Chair Jerome Powell, “Transcript of Chair Powell’s Press Conference, March 18, 2026,” Federal Reserve, https://www.federalreserve.gov/mediacenter/files/FOMCpresconf20260318.pdf (March 18, 2026).

21. See, e.g., Brief of Amici Curiae AFL-CIO and Affiliated Labor Unions, Svitlana Doe et al. v. Noem et al., No. 25-1384 (1st Cir. July 7, 2025) (“AFL-CIO and Affiliated Labor Unions Parole Brief”), at 13.

22. See, e.g., id. at 8–17 (discussing the chaos and harmful fallout that union members and employers experienced when DHS abruptly ended work authorization through the CHNV parole program); Andrea Hsu, Factories from GE to Kraft Heinz lose immigrant workers, stressing those who remain, NPR (Aug. 11, 2025), https://www.npr.org/2025/08/11/nx-s1-5496335/trump-immigration-workers-parole-tps.

23. See, e.g., AFL-CIO and Affiliated Labor Unions Haiti TPS Brief at 36 (noting that “[a]s a direct result of DHS’s actions [in terminating TPS for Haiti], nurses and other healthcare workers will feel pressure to work longer hours to attend to more patients, exacerbating the turnover and burnout that is endemic to the industry”).

24. See, e.g., Mae M. Ngai, Impossible Subjects: Illegal Aliens and the Making of Modern America (2004) (discussing historical links between immigrant labor and industrial unionization); Joint Econ. Comm. of the U.S. Cong., Unions Protect Employment and Raise Earnings, Including for Workers Who Are Immigrants (June 14, 2023) (finding unionization increases wages, benefits access, and workplace protections for immigrant workers); Andrea Hsu, Factories from GE to Kraft Heinz lose immigrant workers, stressing those who remain, NPR (Aug. 11, 2025), https://www.npr.org/2025/08/11/nx-s1-5496335/trump-immigration-workers-parole-tps.

25. See, e.g., Kevin Appleby, The Importance of Immigrant Labor to the US Economy, Center for Migration Studies (Sept. 2, 2024), https://cmsny.org/importance-of-immigrant-labor-to-us-economy/ (noting foreign-born workers were mainly employed in service occupations, construction, transportation, and material moving occupations); Dorothy Neufeld, Ranked: Union Membership by Industry in America, Visual Capitalist (Nov. 7, 2024), https://www.visualcapitalist.com/union-membership-by-industry-in-america/ (listing top industries with union membership based on Department of Labor statistics, including construction and transportation); Migration Policy Institute, Immigrants and Union Membership in the United States (2004) (demonstrating rising absolute numbers of immigrant workers in unions despite lower overall union density among foreign-born workers).

26. Annette Bernhardt et al., Broken Laws, Unprotected Workers: Violations of Employment and Labor Laws in America’s Cities, Center for Urban Economic Development, National Employment Law Project, and UCLA Institute for Research on Labor and Employment, 2009.

27. See, e.g., AFL-CIO and Affiliated Labor Unions Parole Brief at 15–16 (when the hotel industry is faced with labor shortages, employers often use temporary labor agencies to supply workers, which not only “undermin[e] the wages and working conditions” for U.S. citizen workers employed by the hotel “by paying substandard wages and benefits,” but also “often violate immigration law by hiring undocumented workers”).

28. See FCC v. Fox Television Studios, Inc., 556 U.S. 502, 515–16 (2009) (noting that an agency must sufficiently explain its decision when it departs from a previous position, which requires a “reasoned explanation” as to why it is “disregarding” any “factual findings . . . which underlay its prior policy” and “contradict” the factual findings underlying its new policy).

1. The proposed rule includes multiple reference numbers, which are listed here out of an abundance of caution: No. 2799-25; DHS Docket No. USCIS-2025-0370; DHS Docket No. 2025-0370; and RIN 1615-AC97.

The Economic Policy Institute’s Family Budget Calculator: Technical Documentation

Elise Gould, Emma Cohn, Zane Mokhiber — Sun, 01 Mar 2026 10:00:30 +0000

This paper presents the methodology and data sources used in the 2026 update of the Economic Policy Institute’s Family Budget Calculator. EPI’s Family Budget Calculator measures the monthly income a family needs in order to attain a modest yet adequate standard of living. The budgets estimate community-specific costs for 10 family types (one or two adults with zero to four children). Compared with the federal poverty line and the Supplemental Poverty Measure, EPI’s family budgets provide a more accurate and complete measure of economic security in America.

The budget calculator draws upon the most recent reliable data, which in many instances is data for 2025. If 2025 data were unavailable, we used data from the latest available year inflated to 2025 dollars with the budget-item-appropriate inflator. The calculator includes data for all 3,143 U.S. counties and county equivalents and for all 613 HUD FMR metropolitan areas.

View the EPI Family Budget Calculator

Definitions of families

The size of a family dramatically affects the budget needed to maintain a modest yet adequate standard of living. We have constructed budgets for 10 different types of families in each area. These families include a single person with no children; a married couple with no children; single-parent families with one, two, three, or four children; and a married couple with one, two, three, or four children.

We make assumptions about each of the 10 family prototypes in order to generate specific cost estimates for each family type’s tax liability, child care expenses, food costs, etc.

Our definition of a single person with no children assumes that they are employed and the head of household for federal income tax purposes. Our definition of a married couple with no children assumes both are employed, live together, and jointly file federal income taxes. Our definition of single-parent families assumes that the head of household is employed, lives with his or her children, and files as the head of household for federal income tax purposes. Our definition of two-parent families assumes that both partners are employed, live together with their children, and jointly file federal income taxes.

Families with one child are assumed to have a 4-year-old. Families with two children are assumed to have a 4-year-old and an 8-year-old. Families with three children are assumed to have a 4-year-old, an 8-year-old, and a 12-year-old. Families with four children are assumed to have a 4-year-old, an 8-year-old, a 12-year-old, and a 16-year-old.

Definition of areas

The EPI Family Budget Calculator presents data for all 3,143 U.S. counties and county equivalents as of 2025 (some locations are not inside any county but are defined as county-equivalents by the federal government for administrative and statistical reasons). We have also constructed cost estimates for all 613 metropolitan areas (“metro areas”) using both metro-level data and aggregations of county data.

Where possible, the family budget metropolitan areas correspond with the metropolitan statistical areas (MSAs) delineated by the Office of Management and Budget (OMB) for application to U.S. Census Bureau data. OMB defines MSAs as having at least one urbanized area of 50,000 or more people, plus adjacent territory that has a high degree of social and economic integration with the core, as measured by commuting ties (OMB 2023).

Our number of metro areas (613) exceeds the nearly 400 official MSAs because our housing costs are calculated using fair market rent (FMR) areas. FMR areas are defined by the U.S. Department of Housing and Urban Development (HUD 2025). These FMR areas are used to help determine the value of rent subsidies offered to families in the nation’s low-income rental assistance programs. FMR areas are divided into metropolitan FMR areas and nonmetropolitan FMR areas. When we refer to “metropolitan areas” or “metro areas,” we are referring collectively to the MSAs and HUD metropolitan FMR areas in our data.

Counties located in metropolitan areas will have cost estimates available at both the county and metropolitan area levels, while nonmetro counties will have cost estimates available only at the county level.

Child care costs and out-of-pocket medical costs depend on whether an area is designated as a metro area or a nonmetro (rural) area.

Components of the EPI family budgets

The EPI family budgets consist of seven individual components: housing, food, transportation, child care, health care, taxes, and “other necessities.” The following sections describe the methodology used to construct a monthly cost for each of these seven components across the 3,143 U.S. counties and 613 metro areas.

Housing

Data for rental costs come from the U.S. Department of Housing and Urban Development’s fiscal year 2025 fair market rents (FMRs) (HUD 2025). HUD releases estimated fair market rents (FMRs) for every fiscal year to establish cost information for certain federal housing assistance programs. For example, FMRs are used to determine landlord reimbursements for accepting rental housing vouchers in over 600 FMR areas, and thus help ensure a sufficient supply of housing for these programs. HUD calculates FMRs for each FMR area using five-year data from the American Community Survey (ACS) and relies on the Office of Management and Budget for definitions of metropolitan areas. All counties that are not in FMR areas are classified as nonmetro counties. Because FMRs within metro areas are calculated at the metropolitan level, counties within the same metro area all have the same FMRs, and nonmetro counties each have their own FMRs.

Fair market rent estimates are provided at the 40th percentile of rental costs—the dollar amount below which 40% of standard-quality rental units are rented.

For each county that crosses into multiple FMR/metro areas, weighted FMR averages are calculated based on the share of the population living in each metro area located in the county’s borders.

Finally, since FMRs within metro areas are provided at the metropolitan level only, counties within the same metro area all have the same FMR value. We adjust these numbers to create county-level variation using county-level ACS median gross rent data (Census ACS 2024). We create a metro-level population-weighted average rent, and then apply the ratio of ACS metro rent to ACS county-within-metro rent to each county FMR that is calculated at the metro level.

HUD makes rental rates available for studio apartments and one-bedroom through four-bedroom apartments. The EPI family budgets assume that a one-adult household occupies a studio and a two-adult household occupies a one-bedroom apartment. Families with one or two children occupy a two-bedroom unit. Families with three or four children occupy a three-bedroom unit. Rental costs include shelter plus all tenant-paid utilities, excluding telephone service, cable or satellite service, and Internet service. Those costs are included in “other necessities” within the family budgets.

Food

Data for food costs are taken from Official USDA Food Plans: Cost of Food at Home at Four Levels, a report published by the Department of Agriculture’s Center for Nutrition Policy and Promotion (USDA 2025). Presented there are the official USDA costs for four types of food plans that serve as national standards for nutritious diets: the “Thrifty Plan,” “Low-Cost Plan,” “Moderate-Cost Plan,” and “Liberal Food Plan.” We use the USDA Low-Cost Plan, which assumes that almost all food is bought at a grocery store and then prepared at home. We use June 2025 data, which represents the 2025 average weekly cost (Carlson, Lino, and Fungwe 2007). We provide county-level food costs by adjusting the national cost estimates from the USDA for county-level food cost variance using a multiplier generated from 2023 data from Feeding America’s Map the Meal Gap project (Feeding America 2023).

Family food costs are constructed from data for the categories child age 4–5 and child age 6–8 and from averages of male and female data at age 12–13, age 14–18, and age 19–50.

For single-adult households, we use an average of the male age 19–50 data and the female age 19–50 data to represent the adult in the household. For married-couple households, we assume one male age 19–50 and one female age 19–50 are the two adults in the household. All costs in the USDA food plans table are for individuals in four-person families; for individuals in families of other sizes, USDA suggests making the following adjustments to account for differences in returns to scale:

One-person family: add 20%

Two-person family: add 10%

Three-person family: add 5%

Five-person family: subtract 5%

Six-person family: subtract 5%

To calculate overall household food costs, we first adjust food costs for each person in the household and then sum the adjusted food costs.

Example: For a one-parent, two-child household (a three-person family):

Food cost = [(average [female age 19–50, male age 19–50]) 1.05] + [child age 4–5 1.05] + [child age 6–8 1.05]

As the USDA notes, the USDA food plans represent a nutritious diet at four different cost levels. The nutritional foundation of the plans is based on the 1997–2005 Dietary Reference Intakes, 2005 Dietary Guidelines for Americans, and 2005 MyPyramid food intake recommendations. In addition to cost, plans vary in terms of the specific foods and quantities of certain foods that make up the “market baskets” (week’s worth of groceries, based on age and gender) in each plan (USDA 2025). According to the USDA, all four food plans are “based on 2001–2002 data and updated to current dollars by using the Consumer Price Index for specific food items” (USDA 2025).

For all U.S. counties and county equivalents, Feeding America’s Map the Meal Gap 2023 report provides average cost estimates for a meal consumed by a 19-to-50-year-old male under the USDA’s Thrifty Food Plan. These county-level meal cost estimates are derived from data provided by Nielsen PLC that measures the costs of Universal Product Code (UPC) barcoded food items in over 65,000 stores across the country. We generate county-level multipliers to gauge the relative cost of food per county by dividing county-level meal costs by average meal costs. These multipliers are then applied to the USDA estimates of average meal costs to generate food costs that are more reflective of local food price variation.

Metro-level food costs are derived by calculating population-weighted averages of the meal costs for the counties that constitute each metro area.

Child care

For the 2026 update of the Family Budget Calculator, we use three data sources to estimate child care costs in all counties. The majority of the child care data comes from the National Database of Childcare Prices (NDCP) which is an initiative of the Women’s Bureau at the Department of Labor (DOL Women’s Bureau 2025). However the NDCP does not provide data for some states so we supplement with data from Child Care Aware of America’s (CCAoA), Child Care Data Center (CCAoA 2022), and CCAoA’s annual “price of care” reports (CCAoA 2025).

DOL

The NDCP provides data on the cost of child care at the county level for nearly all states in the US (excluding New Mexico, Indiana, and the majority of counties in Alaska and Missouri). This data is collected from state Market Rate Surveys over a 14-year time period (2008-2022), and updated to 2025 dollars using the consumer price index (CPI) for day care and preschool for all urban consumers (BLS 2026b, DOL Women’s Bureau 2020).

CCAoA

For the states and counties not covered by the NDCP, we use data from two sources from CCAoA. We turn first to CCAoA’s Child Care Data Center, which provides county level data for six states, including Missouri (CCAoA 2022). We take the county level data where it exists from CCDC but not for NDCP, and adjust to 2025 dollars using the CPI for child care and nursery school for all urban consumers (BLS 2026b).

For the remaining missing counties and states not available in either data source we use the CCAoA “price of care” reports, which report data at the state level for all 50 states and DC. Since there is some variation in quality and recency in certain states, we calculate the average reported state level costs from all of the “price of care” reports from 2014 to 2024. To adjust child care costs to the county level, we create a ratio of the county-level costs of rent for two-, three-, and four-bedroom apartments to the population-weighted state average of the same costs. We then adjust 50 percent of the child care costs using this ratio to estimate the variation in child care costs by county. We find this method to be theoretically sound because rental costs are a significant portion of the cost of running a child care operation (whether center-based or home-based), and variations in rents are also a reasonable proxy for variations in costs of living in general and therefore of wage differences within the state. If a metro area is in multiple states, we use a metro area population-weighted average of the counties within the metro area to come up with a single number for the metro area. All costs are inflated to 2025 dollars using the consumer price index (CPI) for child care and nursery school for all urban consumers (BLS 2026b).

Family Composition

We calculate our child care costs for our family types based on the following assumptions:

One child = cost of 4-year-old care

Two children = cost of 4-year-old care + cost of care for one school-age child

Three children = cost of 4-year-old care + cost of care for one school-age child + cost of full-day summer care for one school-age child

Four children = cost of 4-year-old care + cost of care for one school-age child + cost of full-day summer care for one school-age child

The following subsections explain these assumptions and cost estimates in greater detail.

Center-based care

We use cost estimates for center-based child care for counties that are within metro areas. We use center-based care estimates because center-based care is more regulated than family care and because the costs of center-based care do not fluctuate as much as the costs of family child care.

Family child care

Family child care (also sometimes called “home-based care”) is defined by CCAoA as “child care offered in a caregiver’s own home”; family child care providers “may be licensed or exempt from licensing,” “depending on the state’s licensing regulations” (CCAoA 2020).

We use cost estimates for family child care for the nonmetro counties, operating under the assumption that family child care is more accessible than center-based care for those located in rural areas.

Infant care

The family budget child care costs do not include costs for infant or toddler care because we do not include an infant or toddler as part of any of our family types. It should be noted, however, that center-based infant and toddler care is significantly more expensive than center-based care for 4-year-olds, so the child care component of some families’ budgets may be underestimated.

Four-year-old care

Four-year-old care is full-time, year-round care. To approximate the costs of care in metro areas and nonmetro areas, we use center-based and family child care estimates, respectively, for all 4-year-olds.

School-age child care

In our calculations, we assume that school-age child care for an 8-year-old includes nine months of before- and after-school care and two months of full-time summer care. We assume that school-age child care for a 12-year-old includes only the two months of full-time summer care. For the 16-year-old, we assume child care is not necessary.

The State Child Care Resource and Referral Network survey for school-age care specifically represents the cost of nine months of before- and after-school care; it does not represent full-time care, nor does it include weekend care or full-day summer care. Both the full-time and part-time summer care data in the CCAoA “price of care” data contain many missing values. In order to include summer care costs in the “school-age child care costs” that we use for the 8-year-old child, we impute our own summer care costs by assuming that the cost of full-time summer care for a month is twice the cost of before- and after-school care for one month, and we assume 8-year-olds need two months of full-day summer care. To the extent that parents need their children to be in care for additional time in the summer, we are underestimating the total cost of care.

We assume that 12-year-olds need full-day care during the summer months only; thus, our two months of imputed summer costs are added to families with three and four children. For families with four children, we assume child care is not necessary for the fourth child, who is assumed to be 16 years old.

Transportation

We use data provided by the Center for Neighborhood Technology (CNT) and derived from CNT’s Housing and Transportation Affordability Index (CNT 2023). Transportation costs in the H+T index are estimated by adding up three major components of transportation costs: auto ownership, auto use, and transit use. These components were estimated by CNT using data from the Consumer Expenditure Survey, the 2019 National Transit Database, CNT’s AllTransit database, and the Illinois Department of Natural Resources (CNT 2023).

In the data provided to EPI, CNT modified these costs to account for the different family sizes in the Family Budget Calculator, as well as to account for assumptions made about trip purpose. Adults in all family types are assumed to be working and, for the purposes of CNT’s cost model, are assumed to be commuters. At our request, CNT adjusted the miles traveled component of their equation to only include work and nonsocial trips for the first adult in a household, and only work trips for the second adult (in two-adult households). Using national data from the 2022 National Highway Transportation Survey, this comes to 75% of average total vehicle miles traveled for the first adult, and 42% of average total vehicle miles traveled for the second adult, if applicable.

This 2026 update inflates the transportation data to 2025 dollars using the regional transportation CPI (BLS 2026c).

Health care

Health care expenses have two components: Affordable Care Act (ACA) health insurance exchange premiums and out-of-pocket expenditures. The Family Budget Calculator assumes that families have purchased insurance through the health insurance exchanges created by the ACA.

Premiums

Premium costs are obtained through the Henry J. Kaiser Family Foundation’s 2025 Health Insurance Marketplace Calculator (KFF 2025), compiled from the U.S. Department of Health and Human Services (U.S. Dept. HHS 2025). Premiums are based on the lowest-cost bronze plan in the rating area, adjusted for family size, age of user including children (adjusted using state-specific age curves), and tobacco surcharge (KFF 2025). Under ACA plan rules, there is no additional premium cost for families with more than three children under the age of 21. The Family Budget Calculator assumes all children are 16 or younger, so for families with four children, premium costs are capped after the cost for the three oldest children are calculated. The family budgets assume all adults are 40-year-old nonsmokers.

Out-of-pocket costs

The method for calculating out-of-pocket costs for the current Family Budget Calculator follows the 2018 methodology and both differ slightly from the prior editions of the calculator because those relied on data from HHS’s Medical Expenditure Panel Survey (MEPS), specifically the geocoded restricted-use MEPS files, which are not publicly available after the 2012 data year file. For the current Family Budget Calculator, we calculate out-of-pocket costs using three-year averages from the restricted-use geocoded version of the MEPS “Household Component (Full year Consolidated Files)” for 2019, 2020 and 2021, adjusted to 2021 dollars (U.S. Dept. HHS 2021). The new data were provided by request, according to the specifications listed below, by the Agency for Healthcare Research and Quality onsite data center (AHRQ 2023).

We assume that everyone has private health insurance (defined by the variable PRIV12 in the public-use files). Out-of-pocket medical expenditures are calculated for adults and children separately by region and are differentiated between MSAs and non-MSAs for those covered by private insurance (U.S. Dept. HHS 2021). Costs are estimated as follows:

We use the regional breakdown of costs for both adults and children (with the regions defined as Northeast, Midwest, South, and West).

The data are further divided within each region into MSA data and non-MSA data. For out-of-pocket costs, we use metro area data for counties in metro areas and we use nonmetro data for nonmetro counties (see the above section titled “Definition of areas” for more detail on the distinction).

We classify a child (regardless of family size) as age 17 and under, and an adult as age 18–64 (using the variable AGE12X). We do not break down data for children into smaller age groups or by gender because the resulting sample sizes are too small.

Adult out-of-pocket costs are the average costs (variable TOTSLF12) for adults ages 18–64 with private insurance in the region where the family resides (Northeast, Midwest, South, or West) and for the metropolitan classification of their location within that region.

Child out-of-pocket costs are the mean costs for children ages 0–17 with private insurance for the region and for the metropolitan classification within that region.

We compute total out-of-pocket costs (OOP) in the following way:

[(number of adults) (adult OOP)] + [(number of children) (child OOP)]

The total out-of-pocket costs are adjusted for inflation to 2025 dollars using the regional breakdowns of the Consumer Price Index-All Urban Consumers for Medical Care (CPI-U-MC) from the Bureau of Labor Statistics (BLS 2026d).

When computing the mean, we use a population weight (variable PERWT12F).

Total health care costs

We compute total health care costs in the following way:

[Total premium] + [Total out-of-pocket cost]

EPI’s family budgets do not take into consideration the two types of health insurance subsidies available through the state and federal health insurance exchanges: the premium tax credit and the cost-sharing subsidy. Therefore, the health care budget may be overestimated for some families.

Other necessities

Our calculation of “other necessities” is derived from Bureau of Labor Statistics (BLS) Consumer Expenditure Survey (CEX) data (BLS 2026a). We define “other necessities” as items that do not fall into the aforementioned categories but that are necessary for a modest yet adequate standard of living. We include the following expenditures from the CEX in our “other necessities” calculation: apparel, personal care, household supplies (including furnishings and equipment, household operations, housekeeping supplies, and telephone services), reading materials, and school supplies. In editions of the Family Budget Calculator prior to the 2018 update, we also included the CEX expenditures “entertainment” and “other miscellaneous items” in our total for “other necessities,” but for now we leave these two categories out of our calculations so that we can more narrowly assess what is the bare minimum income required to get by.

We use the CEX data for families in the second fifth from the bottom of the overall income distribution (those in the 20th- to 40th-percentile range). Using the 2023 CEX expenditure table “Quintiles of income before taxes,” we sum the values of the categories mentioned above to create an “other necessities” aggregate number, and then divide this by CEX food and housing costs. In the 2023 data, we determine this proportion to be 33.6%. Therefore, we estimate the cost of other necessities by applying this percent to each respective family budget’s food and housing costs.

Taxes

The family budget components, without taxes, sum to the family’s post-tax income. To calculate the family budget tax component, a pre-tax income level must be estimated using a tax rate and the post-tax income.

We use the National Bureau of Economic Research’s TAXSIM, a microsimulation model of the U.S. federal and state income tax systems accessed online. We use Version 35 to calculate these tax rates; the tax year is 2023 and has not been updated for subsequent years (NBER 2022). The TAXSIM model accepts 32 input variables, including state, marital status, dependent exemptions, wage income, other incomes, rent paid, child care expenses, and capital gains and losses (Feenberg and Coutts 1993). We run the TAXSIM model for each family type across all county and metro areas.

Our input variables are (variables not listed are input as zero):

State

Marital status (“single” for one-adult families, “married” for two-adult families)

Dependent exemptions (one for each child)

Wage and salary income of taxpayer (entire post-tax family budget for one-adult families)

Wage and salary income of spouse (for two-adult families, the post-tax family budget was split evenly between the two adults)

Rent paid (the annual cost of rent for each family budget, which is used to calculate state property tax rebates in certain states)

Child care expenses (the annual cost of child care for each family budget)

Number of dependents under age 17 (one for each child)

The TAXSIM model takes these inputs and calculates three outputs: federal tax liability, state tax liability, and Federal Insurance Contributions Act (FICA) tax liability (for Social Security and Medicare taxes). Additionally, the TAXSIM model calculates FICA liability as the full 15.3 percent tax from both the employer and employee side; we cut this in half to more accurately represent the typical taxpayer’s FICA liability. Local taxes, such as county- or city-level income taxes, are not included in this model. Sales taxes are also not included in the “taxes” category (they are instead wrapped into the costs of taxable expenditures in other categories).

Of course, we cannot simply input the post-tax family budgets as the wage incomes and use the TAXSIM output as the tax rates. The tax rate must be based on the pre-tax income levels. To obtain an accurate tax rate and accurately calculate the income tax liability for each family, we first input the post-tax family budgets and obtain the tax rates and establish these as a lower floor for tax rates. (Because the pre-tax incomes will almost always be higher than these post-tax incomes, these tax rates must be lower than the actual tax rate given our assumptions about sources of income and the income ranges we are considering). We then establish an upper bound of tax rates by taking the post-tax family budgets, multiplying by 1.25, and inputting the resulting amounts into the TAXSIM model.

Once we have the lower and upper bounds of tax rates, we calculate an accurate average of these tax rates using a weighting procedure, described below:

Multiply the lower bound (post-tax family budget) and upper bound (post-tax family budget 1.25) inputs by (1 – calculated tax rate)
Calculate the difference between the actual post-tax family budget and the lower bound calculated in step 1: [post-tax family budget – lower bound]
Calculate the difference between the upper bound and the actual post-tax family budget calculated in step 1: [upper bound – post-tax family budget]
Calculate the difference between the upper bound and the lower bound calculated in step 1: [upper bound – lower bound]
Calculate the weight for the lower bound: upper-bound post-tax budget difference divided by the upper–lower difference:
Calculate the weight for the upper bound, which is equal to [1 – weight for lower bound (calculated in step 5)]
Multiply the lower-bound tax rate from TAXSIM by the lower-bound weight from step 5: lower-bound tax rate
Multiply the upper-bound tax rate from TAXSIM by the upper-bound weight from step 6: upper-bound tax rate [1 – lower weight (calculated in step 5)]
Add these two weights to get the final, weighted tax rate: [step 7 + step 8]

The final tax rate calculated in step 9 is then applied to the post-tax family incomes [post-tax family budget / (1 – final weighted tax rate)], to obtain a pre-tax income. The difference between the pre- and post-tax incomes is the annual tax bill for the family budget unit.

In cases where the post-tax budget exceeds the bounds, we increase the budget multiplier by increments of .05 (1.30, 1.35, 1.40, 1.45, 1.50) until the post-tax budget no longer exceeds the upper bound.

References

Agency for Healthcare Research and Quality (AHRQ). 2023. Medical Expenditure Panel Survey—Restricted Data Files Available at the Data Centers. Accessed December 2023.

Bureau of Labor Statistics (BLS). 2026a. Consumer Expenditure Survey. Current Expenditure Tables. Accessed January 2026.

Bureau of Labor Statistics (BLS). 2026b. Consumer Price Index Program, CPI-All Urban Consumers (Current Series), Series ID CUUR0000SEEB03 [database]. Accessed January 2026.

Bureau of Labor Statistics (BLS). 2026c. Consumer Price Index Program, CPI-All Urban Consumers (Current Series, Series ID CUUR0100SAT – CUUR0400SAT [database]. Accessed January 2026.

Bureau of Labor Statistics (BLS). 2026d. Consumer Price Index Program, CPI-All Urban Consumers (Current Series), Series ID CUUR0000SAM [database]. Accessed January 2026.

Carlson, Andrea, Mark Lino, and Thomas Fungwe. 2007. The Low-Cost, Moderate-Cost, and Liberal Food Plans, 2007. ResearchGate, January 2007.

Census Bureau American Community Survey (Census ACS). 2024. Median Gross Rent by Bedrooms. Accessed January 2026.

Center for Neighborhood Technology (CNT). 2023. H+T Affordability Index. Accessed December 2023.

Child Care Aware of America (CCAoA). 2025. “2024 Price of Care: Child Care Affordability Analysis” (web page). Accessed January 2026.

Child Care Aware of America (CCAoA). 2022. “Child Care Data Center” (web page). Accessed January 2024.

Child Care Aware of America (CCAoA). 2020. Picking Up the Pieces: Building a Better Child Care System Post COVID 19 (report and appendices), September 2020.

Department of Agriculture Center for Nutrition Policy and Promotion (USDA). 2025. “USDA Food Plans: Monthly Cost of Food Reports.” June 2025.

Department of Health and Human Services (U.S. Dept. HHS). 2025. “QHP Landscape PY2026 Individual Medical” (dataset on data.healthcare.gov).

Department of Health and Human Services (U.S. Dept. HHS). 2021. Medical Expenditure Panel Survey HC-216 2021 Full Year Consolidated Data File [microdata].

Department of Housing and Urban Development (HUD). 2025. Fair Market Rents [county-level data file]. Accessed January 2026.

Department of Labor, Women’s Bureau (DOL Women’s Bureau). 2025. “National Database of Childcare Prices” (web page). Accessed January 2025.

Department of Labor, Women’s Bureau (DOL Women’s Bureau). 2020. National Database of Childcare Prices: Final Report.

Feeding America. 2023. “Food Insecurity in the United States” (interactive map), Map the Meal Gap project. (interactive map), Map the Meal Gap project.

Feenberg, Daniel, and Elizabeth Coutts. 1993. “An Introduction to the TAXSIM Model.” Journal of Policy Analysis and Management vol. 12, no. 1, 189–194.

Henry J. Kaiser Family Foundation (KFF). 2024. 2025 Health Insurance Marketplace Calculator.

National Bureau of Economic Research (NBER). 2022. Internet TAXSIM Version 35. Accessed January 2025.

Office of Management and Budget (OMB). 2023. OMB Bulletin No. 23-01.

Building worker power in the states when federal labor laws are under attack

Celine McNicholas, Jennifer Sherer — Thu, 19 Feb 2026 20:00:59 +0000

The Trump administration continues to brazenly attack workers and their unions, undermining federal labor laws and emboldening corporate union busters. Amid this escalating worker rights crisis, states across the country are stepping up to strengthen threatened labor standards, level the playing field for unionizing workers, and expand pathways to collective bargaining.

Originally held Thursday, February 19, 2026

Webinar links, notes and discussion

Timestamped themes, discussion, and resources mentioned in the webinar

Open

1:49 Introduction

Economic Analysis and Research Network (EARN) website
EARN network directory of partners in your state

Holding the Line: State solutions to the U.S. workers’ rights crisis

Unemployment insurance

Union rights

Wage payment

5:34 EPI tracking Trump administration attacks on working people and unions

Celine McNicholas, EPI Direct of Policy and Government Affairs

Latest EPI analysis of the annual union membership data, Workers’ resolve drives unionization in 2025

Federal Policy Watch

Unions aren’t just good for workers—they also benefit communities and democracy

Trump is the biggest union-buster in U.S. history

Find all of EPI’s work on Unions and Labor Standards

22:30 Collective bargaining rights in Virginia

Levi Goren, Director of Research and Education Policy, The Commonwealth Institute.
Levi/they leads TCI’s analysis and advocacy work on education, safety net programs, and macroeconomic conditions in Virginia, making sure the strongest analysis is brought to bear on key issues facing communities of color and low-income families. Outside of paid work, Levi has worked on grassroots social and economic justice campaigns.

Angel Pye, Executive Board member, SEIU Local 512 Home Care Chapter.
A former mental health professional who transitioned to full-time caregiving for her late son, Angel now uses her experience to fight for collective bargaining rights to ensure all home care workers receive the dignity, respect, and living wages they deserve.

Stronger collective bargaining laws will benefit all Virginians

34:24 Fighting wage theft and defending state labor standards in Ohio

Ali Smith, Senior Project Coordinator, Policy Matters Ohio.
Ali Smith leads the Work & Wages team at Policy Matters Ohio. She was born and raised in Ohio, in a family supported and empowered by union steelwork, and previously spent eight years as a childcare provider — experience that continues to shape her approach to worker justice and to drive her research. Ali guides organizational campaigns and strategy, driving major initiatives and advocacy efforts to advance policy goals for workers across Ohio. Ali also serves as president of the Central Ohio Worker Center’s board of directors.

Isbel Alvarado, Case Manager and Community Organizer, Central Ohio Worker Center.
Isbel has worked with immigrants and low-wage workers on employment rights violations including wage theft and related issues that particularly affect low-wage and immigrant workers. Isbel has strengthened partnerships with government agencies and community organizations, trained thousands of workers on their rights in the workplace and was instrumental in the successful campaign that led to Ohio passing the Paystub Protection Act in 2025, requiring all employers to provide paystubs to their employees.

45:39 Washington state fighting for collective bargaining rights for farmworkers

Kaitie Dong, Senior Policy Analyst, Washington State Budget and Policy Center.
Kaitie (she/her) leads the Budget and Policy Center’s immigrant justice policy analysis and advocacy. As a lifelong Washingtonian and granddaughter of Chinese immigrants, Kaitie is inspired by her family and community to advance immigrant rights and racial justice. Kaitie is passionate about relationship building and education and her work has included building leadership of immigrant youth in WA state and advancing policy campaigns focused on keeping immigrant families together, tenants’ rights, language access in K-12 schools, and early learning.

Edgar Franks, Political Director for the independent union of farm workers, Familias Unidos por la Justicia.
Edgar keeps members informed of legislation and laws affecting rural people and immigrants. His past work has included supporting organizing efforts of fruit processing workers and helping farmworkers win 2021 legislation (Senate Bill 5172) to extend overtime pay to all agricultural workers. And he represents the union in other national and international alliances. He also serves on the Agricultural and Seasonal Workforce Services Advisory Committee to provide oversight on the H2A program in Washington State and recommendations to state agencies.

MORE ABOUT THE HOLDING THE LINE SERIES

Federal worker protections are under attack

Long-standing U.S. worker rights and protections are under acute threat. These include attempts to roll back standards that set a national floor for minimum wages, health and safety, nondiscrimination, unemployment insurance, and other rights and protections long taken for granted in most U.S. workplaces.

The crisis calls for urgent action. At a minimum, states must be equipped to maintain and enforce basic protections should at-risk federal standards disappear. The crisis also presents opportunities for states to do much more to:

remedy longstanding gaps and exclusions in weak or outdated labor and employment laws;
advance new policies that address the pressing challenges of eroding worker power, growing income inequality, persistent racial and gender wage gaps, and declining job quality; and
position states over the long term to assume more expansive, effective roles in enacting and enforcing key protections that form the bedrock of an economy that works for all.

Holding the Line: State solutions for the workers’ rights crisis provides a roadmap to defending and strengthening protections at the state and local level.

Go to the series →

This is permitted under a non-commercial use Creative Commons license CC BY-NC-SA 4.0.

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What’s missing from the affordability debate

Heidi Shierholz, Josh Bivens, Samantha Sanders, Valerie Wilson — Thu, 22 Jan 2026 20:00:22 +0000

Everyone is talking about affordability — and making the same mistake.

Enjoy this conversation with Economic Policy Institute President, Heidi Shierholz; Director of the Program on Race, Ethnicity and the Economy, Valerie Wilson; and Chief Economist, Josh Bivens; moderated by Samantha Sanders, about what’s missing from the current debate!

Originally held Thursday, January 22, 2026.

Webinar links, notes and discussion

Timestamped themes, discussion, and resources mentioned in the webinar

Open

Other affordability resources

The missing piece in the affordability debate: Higher paychecks

The free market won’t solve our nationwide housing affordability problem: Equity-focused policy is the solution

The federal minimum wage is officially a poverty wage in 2025

Holding the Line: Minimum wage state solutions to the U.S workers rights crisis

Raising taxes on the ultrarich: A necessary first step to restore faith in American democracy and the public sector

The impact of the Raise the Wage Act of 2025 factsheet

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EPI comment on DHS Interim Final Rule eliminating automatic extensions of Employment Authorization Documents

Daniel Costa — Mon, 01 Dec 2025 20:00:24 +0000

Submitted via https://www.federalregister.gov/documents/2025/10/30/2025-19702/removal-of-the-automatic-extension-of-employment-authorization-documents

December 1, 2025

Paul Buono
Chief, Business and Foreign Workers Division
Office of Policy and Strategy
U.S. Citizenship and Immigration Services
Department of Homeland Security
5900 Capital Gateway Drive
Camp Springs, MD 20746

Re: Removal of the Automatic Extension of Employment Authorization Documents, CIS No. 2826-25; DHS Docket No. USCIS-2025-0271, RIN 1615-AD05 (October 30, 2025)

Chief Buono:

The Economic Policy Institute (EPI) submits this comment strongly opposing the October 30, 2025 Interim Final Rule (IFR) eliminating automatic extensions of Employment Authorization Documents (EADs). The 2025 IFR unlawfully reverses DHS’s nearly decade-long policy choice of providing automatic EAD extensions; ignores ongoing adjudication delays and economic evidence; disregards reliance interests that DHS itself recognized less than a year ago; rejects feasible alternatives; and relies solely on an unsupported security rationale all while unlawfully bypassing notice-and-comment procedures as required by the Administrative Procedure Act (APA). The result is a rule that will strip employees of their workplace rights, destabilize the workforce, disrupt employer operations by creating gaps in employment authorization with unknown durations, and inflict severe harm on workers and their ability to provide for their families solely due to the government’s bureaucratic processing delays. We urge DHS to withdraw the IFR in full.

EPI fully supports and endorses the written comments and recommendations submitted by the Asylum Seeker Advocacy Project (ASAP), which includes a number of examples of the IFR’s impact on ASAP members.

About EPI and organizational interest

EPI has researched, written, and commented extensively on the U.S. system for labor migration, including on temporary immigration protections and EADs, and on labor standards enforcement for both the low-wage and professional workforce. EPI has also provided expert testimony about the U.S. immigration system to both the U.S. Senate and House of Representatives, as well as state legislatures.

The worker rights of millions are protected by EADs

For workers who lack a permanent or more durable immigration status, obtaining a temporary EAD can mean having enforceable workplace rights that an individual would otherwise not have. While all workers have some labor and workplace rights under U.S. law—regardless of immigration status—enforcing them in practice becomes virtually impossible because of the threat of deportation, which prevents workers who lack an immigration status or an EAD from calling out lawbreaking employers and demanding that they comply with the law, or from reporting workplace violations to labor enforcement agencies. But having protection from deportation through temporary administrative immigration protections like parole, Temporary Protected Status, deferred action—accompanied by an EAD—means that, in practice, workers can report workplace violations to government officials without fear of retaliation that can lead to deportation. It also means that a worker with an EAD can be employed by just about any employer and change jobs or employers, unlike migrant workers employed with temporary visas who can only be employed by the sponsor of their visa.

Altogether, nearly 5.6 million people in the U.S. held a temporary but precarious immigration status in 2024, including over 2 million people who are asylum-seekers. (see Table 1 below).

Table 1

While these statuses and protections are only a band-aid for a flawed immigration system that is deeply in need of reform,1 they have been shown to protect millions of workers from some of the worst forms of employer lawbreaking. Employers also greatly benefit from workers having a protective status and a work permit because it allows them to lawfully employ millions of people who would otherwise not be eligible to work, leading to billions in economic contributions to the U.S. economy and generating demand that stimulates growth.

While comprehensive data are limited, we know, for example, that in 2017 the top five industries for TPS beneficiaries from El Salvador, Honduras, and Haiti were construction, restaurants and food services, landscaping, child day care services, and grocery stores.2 Employers in these industries and many others are in danger of losing their current workforce and will be prohibited from legally recruiting millions of other workers. Just one example is the GE Appliance Park in Louisville, Kentucky, a unionized plant where nearly 200 employees received a letter from the administration terminating their status and work authorization.3 Overnight, GE lost 200 employees.

DHS ignores the value and impact of work authorization on the workforce

In the IFR, DHS does not estimate and consider the value and impact that EADs have on the workforce and economy. There are examples of existing research showing the important economic contributions that hundreds of thousands of migrants with temporary protections and EADs are able to make thanks to being work-authorized. For example, when the TPS population was approximately 354,000 in 2021, the American Immigration Council estimated that “TPS holders contributed more than $2.2 billion in taxes, including almost $1 billion to state and local governments,” as well as “held $8 billion in spending power.”4 Another estimate by Moriarty found that TPS-eligible individuals “annually contribute some $31 billion in wages to the national GDP.”5

Research has also quantified some of the contributions made by persons who have qualified for Deferred Action for Childhood Arrivals (DACA). DACA was created by DHS in 2012, and recipients are eligible for protections from deportation and EADs that are valid for two years and renewable. More than 835,000 persons have benefitted from DACA, and more than 500,000 were enrolled as of 2024.6 Svajlenka and Truong found that DACA recipient households “pay $6.2 billion in federal taxes and $3.3 billion in state and local taxes each year,” and “after taxes, these households hold $25.3 billion in spending power,” and that DACA recipient families “own 68,000 homes, making $760 million in mortgage payments and $2.5 billion in rental payments annually.”7

When it comes to measuring the workplace impact and economic benefits of being issued an EAD for the workers themselves, there are limited examples, but three are worth citing here. One is an annual survey of DACA recipients that was conducted in 2024 for the ninth time. The most recent survey, conducted by Wong et al. and published by the Center for American Progress, showed that DACA has been an essential tool to improve the economic and educational outcomes of recipients.8 In terms of the impact that deferred action and an EAD have had on the employment of DACA recipients: 59.1% of respondents moved to a job with better pay; 47.3% moved to a job with better working conditions; 47.5% moved to a job that “better fits [their] education and training”; 49.6% moved to a job that “better fits [their] long-term career goals”; 57.3% moved to a job with health insurance or other benefits; and 19.6% of respondents obtained professional licenses.

Wong et al. also measured the impact of DACA and EADs on wages, finding that “[d]ata from the past nine years show that DACA has had a significant and positive effect on wages: Recipients’ average hourly wage more than doubled from $11.92 to $31.52 per hour—an increase of 164.4 percent—after receiving DACA.” These significant wage increases are no doubt a result of the labor and workplace rights and stability that DACA recipients gain from having an EAD.

One other analysis that assesses the wage impact of being issued an EAD comes from Kallick, which looks specifically at asylum seekers in New York and nationwide.10 Relying on previous methodologies for measuring the impact of a lawful immigration status being granted to unauthorized immigrants, Kallick estimates that asylum seekers who are granted EADs increase their wages by 10%.

While the relative benefits of precarious and temporary immigration protections and EADs to migrant workers and the broader economy are clear, it is important to note here that the protections and EADs are only temporary and will end if renewals are not approved, or if renewals are delayed. Thus, DHS through this IFR will intentionally hurt the economy and eliminate the economic benefits for workers and employers that EADs create, a fact that the IFR does not grapple with or address.

An alternative to the path that DHS has chosen of terminating temporary statuses and EADs would be if Congress provided these workers with a permanent immigration status like a green card—and the rights that accompany it—allowing them to have full, equal, and permanent workplace rights and to exercise them in practice. That, in turn, would lead to even higher wages and improved labor standards for all workers,11 not just those who newly obtain green cards. However, the current administration so far has shown no appetite for supporting Congress in the creation of even one new green card.

But in the meantime, EADs through tools like TPS, parole, and DACA can mean the difference between having rights on the job or being extraordinarily vulnerable to the worst abuses by employers. While the current administration has claimed they want to help U.S. workers, actions like the mass detention and deportation of millions of workers and canceling protections like TPS and parole, reveal they are willing to degrade conditions and standards for all workers, as well as kill jobs and shrink the economy, in order to carry out their extreme immigration enforcement agenda.12

If the IFR is not withdrawn, millions of workers will be more easily exploited by their bosses and driven into the informal economy. That, in turn, will reduce their tax contributions that support the social safety net and lower their wages significantly13—ultimately hurting U.S workers in low-wage industries and the U.S. economy writ large by driving down demand for goods and services. It will also leave employers without millions of reliable employees in industries like construction, hospitality, childcare, agriculture, food processing and production, and more.

DHS ignores significant reliance interests

The 2025 IFR also disregards the significant reliance interests that DHS itself reaffirmed less than a year ago when it issued a permanent 540-day automatic extension, and which have existed since the agency’s issuance of the 2016 Final Rule. For nearly a decade, USCIS has automatically provided an extension of some length to some groups of workers with expiring EADs.14 In the 2024 Final Rule, DHS invited stakeholders to rely on a permanent 540-day extension and explicitly sought comment on making the extension permanent to provide regulatory certainty and workforce stability.15 Employers and workers reasonably structured hiring, staffing, payroll planning, and employee retention around that assurance.

Additionally, the only reliance interests DHS barely acknowledges—but does not meaningfully consider—are those of migrants and their employers. Yet, DHS entirely failed to consider the reliance interests of other stakeholders who rely on regulatory stability preventing immigrant communities from suffering government-caused lapses in employment authorization. These other stakeholders include state, city, and local governments; entire regional economies; educational institutions; healthcare providers; legal and social service providers; and the broader public, among others.

DHS cannot now abruptly withdraw the permanent 540-day automatic extension without addressing these significant reliance interests. Doing so violates core administrative law principles.16 In short, DHS invited workers, employers, families, schools, service providers, and communities to rely on regulatory stability, then pulled the rug out from under them without explanation. DHS failed to properly consider these significant reliance interests when issuing the 2025 IFR.

DHS fails to consider feasible alternatives as required by the APA

DHS fails to meaningfully consider feasible, less disruptive alternatives, in violation of the APA.

Consecutive EADs. For instance, DHS claims that “proper planning” by renewal applicants could ensure no lapses in work authorization, yet this fails to recognize that DHS does not issue consecutive EADs. When individuals file well in advance of expiration, USCIS routinely issues overlapping validity periods rather than tacking the new approval onto the end of the existing authorization. As a result, early filers lose usable work-authorization time, forcing them into an ever-accelerating renewal cycle where they must apply earlier and earlier at significant personal and financial cost merely to maintain continuous work authorization. Filing fees, legal fees, time off work to prepare filings, and the emotional and economic strain of constant renewal planning make this approach untenable. If DHS truly believed early filing was the solution, it was required to consider—and explain why it rejected—the obvious alternative of issuing consecutive EAD validity periods so that applicants could file early without losing work authorization time and money. This straightforward fix would allow individuals to apply far in advance, provide USCIS a longer adjudication window, and preserve the full period of authorized employment. DHS’s failure even to address this option underscores the inadequacy of its “proper planning” rationale and confirms that the agency did not meaningfully consider reasonable, less disruptive alternatives.

Concurrent vetting. Nor does DHS explain why it cannot simply continue to conduct vetting during the renewal process and deny renewal of employment authorization if “potential hits of derogatory information” arise—a process it already uses.17 With or without the automatic extension, the individual remains in the United States; the only question is whether they are forced out of lawful employment while being vetted. In other words, DHS already has a system that protects security while letting people keep working, and it has not explained why it cannot keep using it.

Secure paper. DHS’s concern that its own receipt notices are printed on “non-secure” or “plain” paper ignores an obvious solution: printing the extension notices on secure paper.18 Rejecting straightforward, commonsense solutions in favor of a rule that causes sweeping economic harm and predictable worker displacement is the definition of arbitrary and capricious decision-making.

DHS’s use of an Interim Final Rule violates APA requirements

DHS made the 2025 IFR effective immediately, without providing the notice or opportunity to comment required by the APA. Thus the agency’s use of an interim final rule was unlawful.

First, DHS has not satisfied the “meticulous and demanding” standard for invoking the APA’s “good cause” exception.19 That narrow exception allows an agency to bypass notice and comment only where it “for good cause finds . . . that notice and public procedure thereon are impracticable, unnecessary, or contrary to the public interest.”20 While DHS claims that notice and comment would be impracticable and contrary to the public interest, it relies almost entirely on the unsupported security rationale discussed above, along with stating it is “self-evident” that more workers would “rush” to apply for EAD renewals before the rule took effect.21 Again, DHS has not provided evidence of any security risks caused by automatic extensions.22 DHS therefore cannot satisfy the good cause exception to avoid notice-and-comment rulemaking.

Second, the 2025 IFR improperly relies on the exception for normal rulemaking involving the “foreign affairs function of the United States.”23 This exception, too, comes with a “high bar.”24 In particular, courts have warned against “[t]he dangers of an expansive reading of the foreign affairs exception” in the immigration context, where inevitable “incidental foreign affairs effects” would “eliminate[] public participation in this entire area of administrative law.”25 DHS cannot meet that high bar here, as the potential effects on international relations that it puts forward are all speculative, tenuous, or otherwise reliant on unsupported claims of security risks.26

Conclusion and recommended action

For all of these reasons, DHS should withdraw the 2025 IFR in its entirety and reinstate the permanent 540-day automatic extension. The IFR contradicts DHS’s statutory mandate, its own 2016 and 2024 Final Rules, and the factual and economic record. It rests on speculation, ignores constitutional concerns, and will cause predictable, major harm to worker rights and workers themselves, as well as families, employers, and the broader economy—all due to bureaucratic processing delays caused by the government alone.

Comment submitted by:

Daniel Costa|
Director of Immigration Law and Policy Research
Economic Policy Institute

Endnotes

1. Daniel Costa, Josh Bivens, Ben Zipperer, and Monique Morrissey, The U.S. benefits from immigration but policy reforms needed to maximize gains: Recommendations and a review of key issues to ensure fair wages and labor standards for all workers, Economic Policy Institute, October 4, 2024.

2. Robert Warren and Donald Kerwin, A Statistical and Demographic Profile of the US Temporary Protected Status Populations from El Salvador, Honduras, and Haiti, Center for Migration Studies, 2017

3. Keely Doll, “Letters warn nearly 200 GE Appliances workers to leave U.S. as immigration program ends,” Louisville Courier Journal, April 4, 2025.

4. American Immigration Council, The Contributions of Temporary Protected Status Holders to the U.S. Economy (fact sheet), September 19, 2023.

5. Andrew Moriarty, “Temporary Protected Status (TPS): 5 Things to Know,” Policy Brief, FWD.US, February 29, 2024.

6. President’s Alliance on Higher Education and Immigration (President’s Alliance), Breakdown of Dreamer Populations—Both with and Without DACA, Updated May 23, 2024.

7. , Nicole Svajlenka and Trinh Q. Truong, “The Demographic and Economic Impacts of DACA Recipients: Fall 2021 Edition,” Center for American Progress, November 24, 2021.

9. Pia Orrenius and Madeline Zavodny, “The Impact of Temporary Protected Status on Immigrants’ Labor Market Outcomes,” Federal Reserve Bank of Dallas Working Paper no. 1415, December 2014.

10. David Dyssegaard Kallick, “’Let Us Work’: The Wage Gain When Asylum Seekers Gain Work Authorization,” Immigration Research Initiative, September 7, 2023.

11. Daniel Costa, Josh Bivens, Ben Zipperer, and Monique Morrissey, The U.S. benefits from immigration but policy reforms needed to maximize gains: Recommendations and a review of key issues to ensure fair wages and labor standards for all workers, Economic Policy Institute, October 4, 2024.

12. See for example, Ben Zipperer, Trump’s deportation agenda will destroy millions of jobs: Both immigrants and U.S.-born workers would suffer job losses, particularly in construction and child care, Economic Policy Institute, July 10, 2025.

13. See for example, Carl Davis, Marco Guzman, and Emma Sifre. 2024. Tax Payments by Undocumented Immigrants, Institute on Taxation and Economic Policy, July 30, 2024.

14. See 2016 Final Rule, 81 Fed. Reg. at 82,455.

15. 2024 Final Rule, 89 Fed. Reg. at 101,230.

16. Dep’t of Homeland Sec. v. Regents of the Univ. of Cal., 591 U.S. 1, 30 (2020) (agency must meaningfully consider reliance interests when abandoning prior policy).

17. 2025 IFR, 90 Fed. Reg. at 48,804 (“If the application is denied, the automatically extended employment authorization and/or EAD generally is terminated on the day of the denial.”); id. at 48,806, 48,808–10 (citing concerns about “potential hits of derogatory information”).

18. See 2025 IFR, 90 Fed. Reg. at 48,809–10, 48,817 (concerns about automatic extension being memorialized on “non-secure” paper).

19. Sorenson Commc’ns Inc. v. FCC, 755 F.3d 702, 706 (D.C. Cir. 2014) (citation omitted).

20. 5 U.S.C. § 553(b)(3)(B).

21. 2025 IFR, 90 Fed. Reg. at 48,813.

22. Cap. Area Immigrants’ Rts. Coal. v. Trump, 471 F. Supp. 3d 25, 46 (D.D.C. 2020) (good cause exception not satisfied where agencies only provided a single example of potential adverse consequences and “offer[ed] no other data or information that persuasively supports their prediction of a surge” in border crossings before rule took effect).

23. 5 U.S.C. § 553(a)(1).

24. Cap. Area Immigrants’ Rts. Coal. v. Trump, 471 F. Supp. 3d 25, 55 (D.D.C. 2020).

25. City of New York v. Permanent Mission of India to United Nations, 618 F.3d 172, 202 (2d Cir. 2010).

26. 2025 IFR, 90 Fed. Reg. at 48,814.

Good news and bad news about U.S. labor force participation: Many headwinds from the 2010s are gone, but we’re not investing enough in the future

Elise Gould, Hilary Wething, Josh Bivens, Sarah Jane Glynn — Thu, 25 Sep 2025 09:00:12 +0000

Key takeaways

The last decade marks a shift in the prime-age labor force participation rate (LFPR). It moved away from a long-term decline toward rebounded participation in the wake of strong labor markets. Current prime-age LFPR is now back to its 2001 level, erasing much of those losses. Key conclusions from this: Full-employment labor markets are needed to keep LFPRs strong, and long-term structural determinants of LFPR growth cannot be accurately diagnosed during times of cyclical labor market weakness.
Since 1979, key drivers of the decline in men’s labor force participation included the following:
- extended periods of excess unemployment rates
- the labor market scarring effect of mass incarceration
- the decline of historical sources of employment for noncollege men like the manufacturing and military sectors
- increased opioid usage
During the strong labor market in the late 2010s and following the tremendous recovery from the pandemic recession, noncollege men and Black men have seen substantial increases in labor force participation.
Women, by contrast, experienced historical gains in labor force participation throughout the 1980s and 1990s but then their participation stalled out in the early 2000s —and began falling behind relative to peers in OECD countries. In the U.S., insufficient support for balancing paid work and family responsibilities has been a limiting factor in further increases in women’s labor force participation. However, increases in workplace flexibility, with the rise of hybrid or remote work following the pandemic, may have boosted labor force participation, particularly for women with caregiving responsibilities.

Policy recommendations for maintaining and improving gains in labor force participation:

In addition to policies that prioritize tight labor markets, policies should target the following for adults:
- reductions in opioid use
- reductions in incarceration rates
- improvements in policies that support parents and caregivers
- substantial improvements in the pay and working conditions of jobs of the future (like caregiving jobs) to attract and retain workers
Investments in today’s children are crucial for boosting the labor force participation of future generations, such as safety net policies that promote long-term health and educational investments. The future labor market benefits of investing in children are so strong in the long run that they may even be fiscally self-financing.

Key takeaways:

The last decade marks a shift in the prime-age labor force participation rate (LFPR). It moved away from a long-term decline toward rebounded participation in the wake of strong labor markets. Current prime-age LFPR is now back to its 2001 level, erasing much of those losses. Key conclusions from this: Full-employment labor markets are needed to keep LFPRs strong, and long-term structural determinants of LFPR growth cannot be accurately diagnosed during times of cyclical labor market weakness.
Since 1979, key drivers of the decline in men’s labor force participation included the following:
- extended periods of excess unemployment rates
- the labor market scarring effect of mass incarceration
- the decline of historical sources of employment for noncollege men like the manufacturing and military sectors
- increased opioid usage
During the strong labor market in the late 2010s and following the tremendous recovery from the pandemic recession, noncollege men and Black men have seen substantial increases in labor force participation.

Women, by contrast, experienced historical gains in labor force participation throughout the 1980s and 1990s but then their participation stalled out in the early 2000s —and began falling behind relative to peers in OECD countries. In the U.S., insufficient support for balancing paid work and family responsibilities has been a limiting factor in further increases in women’s labor force participation. However, increases in workplace flexibility, with the rise of hybrid or remote work following the pandemic, may have boosted labor force participation, particularly for women with caregiving responsibilities.

Policy recommendations for maintaining and improving gains in labor force participation:

In addition to policies that prioritize tight labor markets, policies should target the following for adults:
- reductions in opioid use
- reductions in incarceration rates
- improvements in policies that support parents and caregivers
- substantial improvements in the pay and working conditions of jobs of the future (like caregiving jobs) to attract and retain workers
Investments in today’s children are crucial for boosting the labor force participation of future generations, such as safety net policies that promote long-term health and educational investments. The future labor market benefits of investing in children are so strong in the long run that they may even be fiscally self-financing.

Executive summary

Labor force participation is both a key input and a consequence of strong economic growth. While there are many reasons some do not participate in the formal labor market—school, family caregiving responsibilities, retirement, work-limiting disabilities—a strong labor market with high employer demand for workers is a necessity to give as many willing workers as possible a chance for employment.

In an aging population in which college attendance is far more common than it used to be, demographic trends have a strong influence on the overall labor force participation rate. Few people think that it’s a problem that many older Americans choose to enjoy retirement or that many younger adults are enrolled in school rather than searching for work. What is, however, a potential problem is many prime-age workers—those between 25 and 54—are dropping out of the job search and work. To assess the extent of this problem, this report focuses primarily on prime-age labor force participation, the share of the population between 25 and 54 that is working or looking for work. This measure rose sharply from the mid-1970s to the mid-1990s. After that, it was flat for a period, then fell during the mid-2010s, most notably following the Great Recession. Over the last 10 years, participation has rebounded strongly and is now back to its 2001 level, erasing much of those post-2000 losses.

The rise in participation before 2000 was primarily driven by women as they increased their education, delayed family formation, and chose to participate in the paid labor market, driven in part by greater opportunities to access higher-paying previously male-dominated professions. The rise in participation over the last decade improved outcomes for both men and women, as strong employer demand led to workers entering or returning to the labor market. By 2024, women’s participation hit an all-time high, and men’s participation rate is back to its 2010 level.

Changes in labor force participation over the last nearly five decades varied by gender, but also across various demographic groups. While changes within demographic groups were the most important drivers of overall trends, there were notable differences between groups. For instance, those without a college degree—particularly men—experienced steeper declines in participation. And education upgrading (increasing the share of the population with a college degree) over the long term did little to offset that weakness. Loss of jobs in areas that traditionally were large-scale employers of noncollege men, such as manufacturing and the military, is undoubtedly related to reduced opportunity and participation in the labor force for those without a four-year college degree.

Black men, in particular, experienced notable declines in participation before the strong labor market over the last 10 years returned their participation to its 2000 level. The quadrupling of incarceration rates through the 1980s and 1990s disproportionately impacted Black men, making it harder for them to secure employment because of both the labor market scarring effects of incarceration as well as labor market discrimination.

Across peer countries in the OECD, prime-age labor force participation didn’t fall off to the same extent for men as it did in the U.S. and continued to rise for women over time. Insufficient support for balancing paid work and family responsibilities in the U.S. has been a limiting factor, particularly for women’s labor force participation. A body of international evidence indicates that larger investments in those areas—such as child care and paid leave—have the potential to help boost participation. Recent increases in work flexibility following the pandemic, such as hybrid or remote work, may have aided the entry or reentry of workers with caregiving responsibilities.

Policy choices–both of commission and omission—can affect the future growth of labor force participation, but outside of immigration, the effects will be comparatively modest relative to historical swings in labor force participation. Strengthened public care can increase labor supply, particularly for women. Poor health, pain, and opioid use have been linked to lower participation, so improving population health and the provision of health care could increase labor force participation. Further, investments in today’s children, through programs that provide health care, early education, and food security, can also pay dividends in terms of future labor force participation.

A strong economy and high-quality jobs are strongly related to labor force participation. When the labor market is tight, workers come back in search of better opportunities. Even with the pandemic job losses, the tight labor market over the last decade has all but erased the declines in the 2000s when excess unemployment and slow job growth kept would-be workers on the sidelines.

Other briefs, reports, and analysis from this series

The U.S.-Born labor force will shrink over the next decade Achieving historically ‘normal’ GDP growth rates will be impossible, unless immigration flows are sustained

Better things come to those who wait The importance of patience in diagnosing labor force participation rates and prescribing policy solutions

Job quality is a policy decision Better jobs can spur higher labor force participation for both men and women

Assessing the strength of the labor market Preliminary downward revisions do not necessarily signal a weaker 2024 labor market, but there are warning signs for 2025

Introduction

The rate at which people participate in the U.S. labor force—which includes people who are working, as well as those who are unemployed but actively looking for work—has enormous implications for the economy and can serve as a barometer for its overall health.

There is no ideal labor force participation rate, and a society in which 100% of the population is in the labor force is not only unrealistic, but also undesirable. For example, high labor force participation could reflect a strong economy, or it could reflect a lack of access to social safety nets that force the very old and people with work-limiting disabilities into the workforce in order to survive. Falling labor force participation rates could be the result of a recession or other negative event like a global pandemic or could be caused by an aging population with many retired people or increased educational opportunities that delay entry into the labor force among younger cohorts.

Because there is no obvious ideal labor force participation rate, policymakers should think less about particular targets to hit for this rate and should instead aim at removing barriers that stand in the way of willing workers and their ability to search for and secure a decent job. While there are good reasons to not participate, such as gaining education or skills, harmful barriers could include macroeconomic slack in labor markets or more structural barriers like discrimination or insufficient societal investment in workers’ health and skills or insufficient support for balancing paid work and family responsibilities.

Labor force participation that is high due to few barriers between willing workers and the ability to find decent jobs is a key ingredient to a healthy, stable economy. This relationship moves in both directions: A healthy economy is one that sees few barriers to willing workers finding jobs, and growing labor force participation is also a key component of economic growth. When the number of people in the labor force increases, it boosts production and leads to higher consumption.

The overall labor force participation rate in the United States is lower now than at its peak in 2000, largely because the population is aging and members of the baby-boom generation have retired. Participation among younger people has declined over time, raising concerns among some economists and policymakers. But the direction of these trends has not been consistently negative, and there is evidence from the last decade that earlier patterns were less durable than predicted.

This report provides an overview of prime-age labor force participation over the last 45 years, summarizes prior research on possible drivers behind the changes over time, and highlights when and how patterns have shifted over the last decade, concluding with policy recommendations that the data suggest could be most helpful to support a continued upward trajectory.

Overall trends in labor force participation

The prime-age labor force participation rate is the share of the civilian noninstitutional population between ages 25 and 54 that is working or looking for work. We focus on this measure to remove those who may be more likely to be in school or retired. As educational attainment has increased over time, a larger share of the population may be out of the labor force for longer (primarily affecting the population younger than 25). At the same time, the population has aged, and a growing share of the population has moved into retirement. Removing those under 25 and over 54 from our analysis removes those mostly demographic changes in labor force participation. Unless otherwise stated, all analysis in this report will include only the U.S. population 25 to 54 years old and will, therefore, be referred to as the labor force or the labor force participation rate (LFPR).

In this report, our primary data set is the basic monthly Current Population Survey. For most analysis, we have a consistent series from 1976 to 2024 and use that entire period, when possible, to display trends. For consistency when decomposing changes over periods of time, we start with 1979 because it is the first business cycle peak in our data, and we don’t want to capture any cyclical trends that may have impacted the data from 1976. Using endpoints for analyses that are at different points of the business cycles can cloud conclusions on structural changes in the labor market. This is what happened with much of the research on labor force participation rates from the mid-2010s when the economy was still suffering employment losses in the aftermath of the Great Recession.

Prime-age labor force participation increased year over year throughout most of the post-World War II era for which we have data. Between 1976 and 2024, the prime-age labor force participation rate rose 8.8 percentage points from 74.8% to 83.6%. As Figure A demonstrates, there was a sharp rise in labor force participation from 1976 to the mid-1990s when it stabilized somewhat, then fell until the mid-2010s. With the notable exception of the pandemic recession, labor force participation has been on the rise for the last 10 years.

Figure A

Labor force participation rates by gender

The overall trends in prime-age labor force participation are valuable in understanding the overall story of the labor market, but they mask some stark differences between participation rates for men and women. Figure B shows that men’s labor force participation is consistently higher than women’s throughout the entire period. What’s most striking is the rise in participation overall through the 1990s was entirely driven by women. There are a number of cultural and socioeconomic factors behind that rise in women’s participation as women increased their college attendance and graduation rates while narrowing the gender gap in college majors, delayed marriage and childbirth, and acquired more market-relevant skills. Combined, these shifts led to greater opportunities for women to enter previously highly male-dominated occupations and earn higher wages (Goldin 2006). Both men and women experienced declines in participation from around 2000 to the mid-2010s, and then both groups experienced a rise since then, though stronger for women.

Figure B

Labor force participation rates move with overall labor market strength

Labor force participation rates tend to decline under weak economic conditions, like recessionary periods. But when the 2008 recession began, prime-age participation had still not fully recovered losses from the early 2000s, and LFP continued to fall for both men and women after the recession ended and the economy started expanding again. The majority of the decline in prime-age labor force participation occurred in the years after the 2008 recession, when prime-age LFP fell by 2.2 percentage points over the course of six years.

A significant body of research was released in the mid-2010s that highlighted the long-term fall in labor force participation, particularly among men, but the last 10 years have shown us a notable reversal in trend as participation for both men and women have been on the rise. While prime-age women are now experiencing their highest labor force participation rates on record, men’s have stopped their downward movement and risen 1.1 percentage points since their low point in 2014 (except in the pandemic recession).

The strength of the labor market over the last 10 years has meant more and better opportunities for potential labor market entrants. There have been two distinct periods over the last 45 years in which a growing economy has led to more broadly shared prosperity: the late 1990s and the last 10 years. Table 1 maps changes in labor force participation in those particular time periods against unemployment rates. Then, we summarize those two periods of time into two categories. The stronger labor market is defined by 1995–2000 and 2014–2024, while the weaker labor market is defined by the remaining 30 years since 1979.

In the good times, the unemployment rate averaged 4.7%, and labor force participation increased 0.3 and 0.1 percentage points per year, on average for women and men, respectively. In the bad times, women’s labor force participation continued to rise, but was largely driven by the structural increases in opportunities in education and reduced barriers to entry for higher-paying professions that characterized the 1979–1995 period. Men’s participation fell 0.2 percentage points in these times of weaker opportunities and lower wage growth when the overall unemployment rate averaged 6.7% (Gould 2020). Since 2000, periods of high unemployment have been associated with declines in both male and female labor force participation.

Table 1

Periods of higher unemployment for much of the last 45 years appear to be related to lower participation rates, particularly among men. But, as the women’s labor force participation rate stabilized in 2000, the trends have been similar for both men and women. The weaker labor market between 2000 and 2014 meant losses in participation, as workers saw fewer opportunities for themselves in the labor market. Though delayed, the labor market expansion in the lead-up to the business cycle peak in 2019, and in the strong bounceback of the last four years, has coincided with greater labor market participation for new or returning workers.

Mechanically, when workers see fewer opportunities and leave the labor force, the unemployment rate will fall as people who may have been classified as unemployed are now out of the labor force and, therefore, not counted. To the extent this is happening, even the higher unemployment rates in the bad times may be overstating labor market strength or undercounting weakness.

Since men’s and women’s labor force participation rates differ greatly in terms of their absolute levels across the entire period in question, we will conduct separate analyses for women and men. We caution readers to note the change in scale between figures for women and men when comparing trends. Women’s low participation in the 1970s requires a wider range; when men’s are narrowed to the range of interest, it can appear to amplify changes. While there were large losses over the entire period for men, they may appear larger than they are when compared with women’s wider labor force experiences.

Labor force participation rose for all racial/ethnic groups among women, while white and Black men experienced the largest declines

Figure C illustrates prime-age labor force participation rates for women (on the left) and men (on the right) for four groups: Hispanic of any race, white non-Hispanic (white), Black non-Hispanic (Black), and other (non-Hispanic). Other (non-Hispanic) is mostly Asian and Pacific Islander women and men; however, a series for this group doesn’t date as far back as 1976. Among women, Hispanic women have the lowest participation rates, while white and Black women have the highest. White women experienced the sharpest rise in participation through the 1970s, 1980s, and 1990s, and all groups experienced a lack of progress or a softening in participation in the early 2000s. Except for the dip in the pandemic recession, all groups experienced a resurgence in participation over much of the last decade.

Figure C

Over the entire period, Black men had the lowest labor force participation rates, and their declines were the sharpest for much of the last 45 years, never recovering fully in each recovery until the most recent period. With the exception of losses in the pandemic recession, Black men experienced a significant increase in participation over the last decade. Now, their labor force participation rate is the highest it has been in nearly 25 years. White men also experienced declines until the mid-2010s, but their participation rate stabilized and remains just shy of their pre-pandemic levels. Hispanic men experienced milder declines over the entire period and an uptick since the pandemic recession.

Though we do not show a figure for labor force participation rates by nativity (and the data only go back to 1994), it’s worth noting that among women, the participation rate of noncitizens is much lower than that of native or naturalized women (See Appendix Table 1). Among men, the largest fall in participation occurred among the native-born though 2014 but then rose over much of the last 10 years, except during the deep pandemic recession. Non-native men, either naturalized or noncitizens, did not experience large declines in participation, but their presence in the U.S. is often tied to the availability of work so their denominator—the population of each of these groups—also ebbs and flows with the strength of the labor market.

Over the last nearly five decades, the prime-age population has shifted from over 80% to about 55% white non-Hispanic, a drop of about 28 percentage points (EPI 2025a). While the Black share of the prime-age population rose about 4 percentage points, the largest gains were among the Hispanic share, increasing about 16 percentage points between 1979 and 2024 (EPI 2025a).

Given differences in labor force levels by race and ethnicity and the changing composition of the population by race and ethnicity over time, it is useful to decompose the overall change in the labor force into its component parts: the change in population share (or the between effect) and the change in labor force participation within groups (the within effect). Figure D shows these two effects, on the left for women and on the right for men.

Figure D

Compared with the changes due to the changing composition of the workforce, the changes within groups loom much larger. For women, the changing composition pulls down participation in part because Hispanic women were a growing share of the population with lower participation rates, compared with the falling share and higher participation rates of white non-Hispanic women. The rise is due to within-group increases in participation over the entire period.

Among men, the changing composition of the workforce played a small role, though likely driven by a falling population share of white men with higher participation rates in general. The drop in participation rates within each race/ethnic group played a much larger role over the 45-year period.

Labor force participation rate fell sharply for men with less than a four-year college degree, while participation for women with a college degree is at its highest ever

Labor force participation rates for different groups by educational attainment vary but follow the same general pattern for men and women, respectively. Both men and women with lower levels of educational attainment, shown in Figure E as noncollege—less than a four-year bachelor’s degree—exhibit lower levels of labor force participation throughout the last 45 years. For women, the noncollege participation tracked college participation, though their rates notably continued rising into 2000, while college participation peaked in 1997 (before the current period). Then, noncollege women’s participation dropped off in the 2000s and rose only mildly over the last 10 years. After softening for several years, labor force participation for women with a college degree is now at an all-time high.

Figure E

The labor force participation rate for men with and without college degrees has declined over time, but unevenly. Men without a four-year college degree experienced large declines between 1979 and 2014, a fall of 8.2 percentage points. They experienced some gains in the expansion of the late 2010s but were harmed more in the pandemic recession. While their participation rate is now back to their 2019 level, the increase hasn’t put a huge dent in the losses they suffered in the 35 years following 1979.

The reduction in labor force participation for noncollege men over time has been considerably greater than for men with a four-year degree. Technology has reduced employment for some types of workers, especially in manufacturing and jobs made up of routine tasks, while boosting employment for other kinds of work, and there is evidence that middle-skilled or middle-wage occupations have declined and have been replaced with a combination of low- and high-skilled jobs (CEA 2016).1

The decline in jobs that are available to workers with lower levels of formal education—or perhaps more accurately, the decline in the types of jobs these men have traditionally had access to, such as those in manufacturing—may make men more likely to leave the labor force. The decline in routine manual-labor jobs—skilled and semi-skilled jobs in production, maintenance, and material moving occupations, which are concentrated in manufacturing but are common in many other industries as well—has been significant and was accelerated by the 2008 recession.

From 2000 to 2017, routine manual-labor jobs as a share of all nonfarm employment fell by nearly 5 percentage points (Valletta and Barlow 2018). There is a correlation between routine manual-labor jobs and prime-age labor force participation, and in states where the drop was larger, there tended to be corresponding larger declines in participation. Controlling for other state-level economic conditions does not alter the relationship, indicating that the share of routine manual-labor jobs is not a proxy for other broad changes such as changes to the unemployment rate. The reduction in the routine manual employment share from 2000 to 2017 is estimated to have reduced the prime-age participation rate by approximately 1.3 percentage points, slightly more than half of the actual 2.3 percentage point decline in prime-age LFP (Valletta and Barlow 2018).

More specifically, the share of men’s employment in the manufacturing sector has fallen to less than half of what it was in 1979. As shown in Appendix Table 3, men’s share of employment in combined durable and nondurable goods manufacturing was 28.5% in 1979, but by 2024, these shares were reduced to 12.8%. To be clear, women’s participation in manufacturing jobs also declined substantially over the period, dropping from 17.9% to 6.3% of women’s employment; however, given that these jobs made up a smaller share of women’s overall employment composition, the loss was felt less by women than by men.

Additionally, the debate over falling male labor force participation often does not mention an important and heavily male economic sector that has shrunk enormously in terms of the opportunities it provided for those who might otherwise have lower-than-average participation rates: the military.

Figure F shows the overall decline in men’s labor force participation alongside the decline in total military employment scaled to the male noninstitutional prime-age population. To be clear, these are not true shares because our measure of the prime-age population is limited to the noninstitutional population, which excludes those in military service. However, the decline in military employment has meant that millions of noncollege men who might have lower-than-average opportunities in the civilian economy can no longer find work in the military. Throughout the mid-1960s through the 1990s, the share of prime-age men in the military dramatically decreased, from a high of 14% in 1967 leveling out at just under 4% of the prime-age male population in the 2000s.

Figure F

Educational upgrading played a small role compared with within-group changes in labor force participation

As with the composition of the population by race and ethnicity, there were large shifts in the educational attainment of men and particularly women between 1979 and 2024. As shown in Appendix Table 2, the share of women with a college degree rose 30.3 percentage points, while the share of men with a college degree rose 14.3 percentage points. Even though women started out with a smaller share of college graduates, today they are more likely to have a four-year degree relative to men. Given that overall labor force participation is far higher for college degree holders, all else equal, we would expect participation rates to have climbed over the 45-year period. While not the same as the labor force participation rate, prime-age women’s increased educational attainment is estimated to have contributed 2.7 percentage points to their employment rate between 2000 and 2023 (Arnon et al. 2023).

There is evidence that pursuing postsecondary education may be delaying labor force entry, at least for some populations. While most college students are younger than prime age, about one-third of students enrolled at Title IV institutions in the fall of 2023 were age 25 or older, and one-quarter were ages 25 to 39 (NCES 2024). Research comparing prime-age men between millennial and baby-boomer generational cohorts found that school attendance explains a roughly a third of millennial men under 30s’ lower labor force participation, but that this effect has virtually no impact by age 40 (Bengali, Duzhak, and Zhao 2023). And when millennial men are separated by education, labor force participation for those with a high school diploma or less is relatively flat from age 25 to 40, while it increases with age for those with a college degree or more, suggesting that additional educational attainment may play a role in delaying eventual entry into the labor market.

In Figure G, we examine the role that changing education composition played in the changes in labor force participation. As the shift in educational attainment was twice as large among women, it’s not surprising that it played a large role in lifting women’s participation rates overall. But the increases in participation within education groups were even more important since 1979. For men, the declines in participation within each group played an outsized role in explaining declines in labor force participation. As we saw in Figure E, these losses were more acute among noncollege men.

Figure G

Labor force participation among married women rose quickly, as unmarried women saw little change

Participation rates for men and women by marital status display a strikingly different pattern, as shown in Figure H. Married men are more likely to work than unmarried men, while unmarried women are more likely to work than married women. Unmarried women always exhibit relatively high levels of labor force participation, and that has changed little over much of the last few decades, except for mild rising and falling in business cycles. Married women, however, experienced a sharp rise in participation from just over a half (52.3%) to three-quarters (75.8%), currently at their highest level of participation on record.

On average, married men are about 9 percentage points more likely to participate in the labor force than unmarried men. That gap has been relatively consistent over the last 45 years, though unmarried men are more subject to swings in the labor market.

Figure H

Over the last nearly five decades, marriage rates have declined for both men and women, falling by about a quarter overall (see Appendix Table 2). All else equal, the decrease in marriage rates for women would pull up overall labor force participation for women. Figure I illustrates this decomposition. The shift toward unmarried status pulled up women’s participation but depressed men’s, as unmarried women are more likely to work than unmarried men, but unmarried men are less likely to work than married men. Rising participation, especially among married women, was a major factor in the rise of participation among women. Men’s falling labor force participation over the 1979–2024 period is explained by both falling participation among married and unmarried men and falling married rates.

Figure I

Labor force participation among women with young children rose, while men’s labor force remained tied to aggregate labor market conditions

While a small percentage of prime-age workers overall report they are not in the labor force due to family and care responsibilities, family structure and caregiving have strikingly disparate impacts on men’s and women’s participation. Care for children is a significant driver of this difference, as mothers are more likely than fathers to be primary caregivers. Mothers have lower participation rates than similarly aged women without children, even after controlling for demographics and education (Kahn, García-Manglano, and Bianchi 2014).

Participation rates for women with young children tend to lag participation rates for women overall and have not grown at the same rate (see Appendix Table 1). Women with children under age 3 have lower participation rates than women with children under 5, although the gap between these two groups has closed slightly since the early 2000s. Women experience a significant and sharp decline in labor force participation after having their first child. Compared with one year prior to having their first child, mothers are 18 percentage points less likely to be in the labor force in the quarter they give birth, and it takes an estimated two years after the birth of their last child for LFP to recover to roughly the same rate as pre-motherhood (Sandler and Szembrot 2019).

Some of this is likely due to personal preferences and cultural norms around caregiving, but there is also evidence that suggests high prices for child care contribute significantly to lower maternal labor force participation. Previous studies have found a positive relationship between access to child care and the mother’s LFP, although the size of the effect varies across studies (Morrissey 2017). More recent data suggest a close to a 1-to-1 relationship between the price of care and employment; as child care prices increase by 1 percentage point, a mother’s probability of employment declines by 0.9 percentage points, and the relationship is even stronger in states with traditional gender norms (Collins et al. 2021).

Factors thought to have influenced prime-age labor force participation between 2000 and the mid-2010s

The majority of the decline in prime-age labor force participation occurred in the years immediately after the 2008 recession, when the participation rate fell by 2.2 percentage points over the course of six years. This prompted a wave of research and subsequent news coverage aimed at understanding the drivers behind this shift. Labor force participation rates tend to decline under weak economic conditions like recessionary periods. But when the recession began, the prime-age LFP had still not fully recovered losses from the early 2000s, and it continued to fall for several years for both men and women after the recession ended and the economy started expanding again.

The longer-term trends indicated that there were factors exerting downward pressure on prime-age participation beyond the business cycle. Estimates on how much of the change in LFP was caused by cyclical factors vary, ranging from one-sixth to about two-thirds (Shierholz 2012; CEA 2016). But while point estimates varied, there was widespread agreement that structural factors contributed significantly to falling labor force participation after 2007.

Many of the factors identified, such as declining opportunities for men without four-year college degrees and stalled parental and child care policies, have already been discussed. A wide range of other potential causes has also been hypothesized to be behind the reduction in prime-age participation, with an overall focus on the experience of men, given their steeper declines.

Poor health, pain, and the opioid epidemic

The number of prime-age adults who report they are not in the labor force due to poor health or disability has increased over time and is the primary reason for nonparticipation reported by men (Tüzeman and Tran 2019). Prime-age women overall report their health as better and their well-being as higher compared with men, and women’s self-reported health does not vary significantly by labor force status. In contrast, prime-age men who are not in the labor force report worse health indicators compared with working men (Graham and Pinto 2021).

Racial and ethnic disparities in health are well documented (NASEM 2017), but in contrast to decades of findings that people of color experience disproportionate health challenges, white men, among prime-age men not in the labor force from 2010 to 2016, reported worse health, lower well-being, and more pain than men of other racial groups. Among these white men, overall low scores were driven by those with lower educational attainment and those at the older end of the prime-age range, especially those ages 45 to 54. Because their health was so much worse than similar men who are working, this suggests that poor health may be the cause of their nonparticipation rather than its effect (Graham and Pinto 2021).

The opioid epidemic has also been linked to declining labor force participation, although it is difficult to assign causation or separate cause from effect due to a lack of reliable data. Opioid prescriptions increased significantly beginning in the late 1990s and peaked in 2012 (Chai et al. 2018) with 17.8 billion opioid analgesic pills dispensed that year alone (Woods et al. 2021). While the overall decline in prime-age labor force participation predates the opioid epidemic, there is evidence opioid use may have contributed to the trend.

A number of studies show that increases in the use of opioids are associated with negative labor market outcomes, including lower labor force participation, although effect sizes vary (Maclean et al. 2020). One widely cited report found that labor force participation fell more in counties with higher opioid prescription rates. After controlling for race, marital status, age, education, manufacturing jobs, and census region, increased opioid prescriptions are estimated to account for as much as 0.6 percentage points of the decline in prime-age male LFP and 0.8 percentage points of the decline for women—or roughly 20% of the total decline from 1999 to 2015 (Krueger 2017). Subsequent research found an opposite pattern by gender, estimating that a 10% increase in the local opioid prescription rate is associated with a 0.53 percentage point decline in prime-age participation for men and a 0.10 percentage point decline for prime-age women (Aliprantis, Fee, and Schweitzer 2023).

Social Security Disability Insurance

Along with increased self-reported poor health, pain, and opioid use, growing incidence of disability benefits has also been proposed as a cause of falling prime-age labor force participation in the 2000s and 2010s. Social Security Disability Insurance (SSDI) has been an important component of the social safety net since benefits began in 1957. Reforms were made to the disability screening process in the 1980s, and researchers have posited that, coupled with an increase in the real value of benefits, this led to the subsequent large increase in enrollment, with the number of workers receiving SSDI benefits tripling from 1980 to 2013. Some went so far as to suggest that many of the applicants may be making fraudulent claims (Autor and Duggan 2006). Although SSDI benefits replace only a fraction of a disabled worker’s prior earnings and disabled beneficiaries are more than twice as likely to live below the poverty line (CBPP 2025), some researchers hypothesized that SSDI benefits would reduce the incentive for people with some remaining work capacity to stay in the labor force.

Estimates on how much increased SSDI receipt has contributed to declining labor force participation for prime-age men vary but generally account for very little of the total change (CEA 2016). SSDI is suggested to have a particularly chilling effect on LFP for men with lower levels of education since benefit receipt has grown more for prime-age adults without a college degree, a group that has also seen larger declines in participation (Burk and Montes 2018). But research comparing data on SSDI and participation rates between 1975–1984 and 2008–2017 found that increases in disability benefits explain almost none of the decline in LFP for men with less than a high school education and only very small shares of the drop in LFP for prime-age men with only a high school diploma—0.01 percentage points of the decline for men ages 25–34 and 35–44, and 0.3 percentage points for those ages 45–54 (Binder and Bound 2019).

Incarceration rates

The number of people incarcerated in the U.S. quadrupled from 1978 to 1998 (BJS n.d.), and young Black men are disproportionately likely to be impacted. The rise in incarceration has cross-cutting effects on measured labor force participation. Because the surveys that estimate participation do not include the incarcerated population, if those currently incarcerated would be likely to have lower-than-average labor force participation rates in the noninstitutional labor market, a rise in incarceration can actually boost measured participation by removing this population from the denominator.

However, if a spell of incarceration causally reduces the probability of labor force participation because it makes an individual’s connections to the labor force more tenuous (being in an institution categorically means one is not in the labor force) or because skills and work experience can depreciate over time, then a growing stock of people in the market with a spell of incarceration in their history could lower overall participation through these scarring effects. Further, people with a history of incarceration are more likely to experience labor market discrimination (Burk and Montes 2018).

Spells of incarceration are estimated to have accounted for at least a quarter of the decline in LFP among all Black men between 1979 and 2000, and over one-half of the decline in participation rates among Black men ages 25–34 without a high school diploma (Holzer, Offner, and Sorenson 2005). More recently published research found that having received a criminal charge in their youth significantly increased the number of weeks prime-age men spent out of the labor force up to 26 years later. However, the data used in this research may be overestimating effects since it cannot account for reasons why someone is not in the labor force, including school attendance or because of later incarceration (Ellsworth 2017).

While not specifically measuring effects on prime-age labor force participation, additional research quantifies the way prior convictions—which may or may not result in incarceration—impact future employment. Having been convicted of a felony is estimated to have reduced the employment rate for all men in 2008 by 1.5 to 1.7 percentage points, and by 6.1 to 6.9 percentage points for men without a high school diploma (Schmitt and Warner 2011). Later research using state-level modeling estimated that every 1 percentage point increase in the share of the adult population with a felony conviction is associated with a 0.3 percentage point increase in the rate of nonemployment—including unemployment and being out of the labor force—for adults aged 18 to 54 (Larson et al. 2022).

Leisure activities

As previously discussed, prime age women are much more likely to leave the labor force to undertake family responsibilities, and men rarely report this as the reason for their nonparticipation. But regardless of the reason for their nonparticipation, there is also no evidence that men ultimately use the time they may have otherwise used for labor market activities on household work. Time-use data show that prime-age men not in the labor force spend twice as much time on leisure activities compared with other men, but only slightly more time on housework and caring for children (Krause and Sawhill 2017).

From 2000 to 2015, total market hours worked fell more for younger men ages 21 to 30 than for men ages 31 to 55, and younger men’s detachment from the labor market increased. Computer and video game technology advanced over this same period, which increased the appeal of this leisure time, and younger men significantly increased their time spent gaming. While recognizing other factors such as declining demand for younger men’s labor, researchers have hypothesized that video and computer games are a potential factor that contributed to the reduction in the labor supply of younger men, estimating that increased gaming technology was responsible for up 38% to 79% of the differential in work hours reduction between younger and middle-aged men (Aguiar et al. 2017).

Subsequent research confirms that time spent playing video games increased among men in the 2000s (Krueger 2017; Gray 2019). The increase in time spent gaming was concentrated among men under 30, and nonworking young adult men spent more time playing computer and video games than their working peers did. However, total electronics leisure time was flat over this period because time spent on gaming was generally offset by decreased time watching television or movies, not by reduced job search or labor market activity. And while young men who had recently exited the labor force spent more time gaming than employed men did, they spent less time compared with men who had been out of the labor force longer, undercutting the hypothesis that gaming was the reason for their exit (rather than a consequence of it). Overall, the data suggest that shifting cultural norms have made it more socially acceptable for slightly older and non-employed men to spend time playing video games, not that young men were leaving the labor force in order to devote more time to gaming (Gray 2019).

Real and relative wages

Real hourly wages (adjusted for inflation) for prime-age men without a college degree were meaningfully lower in 2015 compared with the early 1970s, while real wages for men with degrees increased over the same time—although the decline is not consistent throughout the entire period, and real wages for all educational groups did increase in the late 1990s (Binder and Bound 2019).

While an individual’s personal level of pay is important to labor market decisions, there is also evidence that men’s relationship to other men’s wages may have a meaningful impact on their beliefs about the financial returns on the time and effort invested in work and subsequent labor supply. Data from 1980 to 2019 show that noncollege prime-age men are more likely to leave the labor force when their earnings decline relative to other prime-age men. Increases in real earnings may not be enough to offset the effect of inequality; it’s the comparison to what other similar-ages men are paid that seems to matter most. The relationship with women’s wages is weaker, and white non-Hispanic men are driving the relationship, indicating that the LFP of historically privileged groups may be more sensitive to changes in relative economic standing. This decline in relative earnings for noncollege prime-age men is estimated to have contributed to 44% of the decline in labor force participation over this period (Wu 2022).

Additional recent research comparing wages in men’s birth states found a positive relationship between the wages paid to other men starting in an individual’s boyhood and their eventual labor force participation when they reach prime age, even after controlling for labor market conditions and demographic variation. The study found that a $0.33 increase in the average experienced aggregate lifetime hourly wage of men raised the probability of prime-age labor force participation by 10 percentage points. The effects persisted even when men moved states, and were stronger within racial categories with an effect twice as strong for Black men compared with white men. Racial decompositions found that white men were most influenced by the wages of other white men, while Black men were influenced by both Black and white wage trajectories (Levin and Vidart 2025). The data suggest that lifetime wage experiences, and what men see other similar men being paid throughout the life course, may shape beliefs about the returns on work, which in turn, influence labor force participation. This may help explain why men’s LFP continued to decline in the 1990s when real wages rose.

More recent changes to the economy

The research outlined above was largely conducted using data from the years immediately after the 2008 recession, often with endpoints before prime-age labor force participation started recovering in the late 2010s. Labor force participation declined dramatically in 2020 but rebounded faster than predicted, continuing the upward trend in place before the pandemic. Between 2020 and 2024, the prime-age labor force grew about two-and-a-half times faster than the prime-age population (EPI 2025b). And as of 2024, prime-age men’s participation had regained its 2010 level, while women’s hit a historic high.

Research on the drivers of the rapid recovery and longer-term prime-age LFP increases is ongoing, but there are indicators that the single most important factor might simply be the state of macroeconomic slack. The 2010s saw prolonged and large output gaps that persisted for almost a decade after the business cycle peak in 2007. The more recent post-pandemic recovery was far faster, with output gaps essentially erased 18 months after the previous peak.

Since 2015, when prime-age participation started to recover, researchers have found a consistent procyclical relationship between changes in state unemployment rates and prime-age LFP, a relationship that is not present for business cycles between 1990 and 2014. The wage gains experienced by low-wage workers have been larger during the recent economic expansions compared with earlier periods, and since this groups tends to be more responsive to changes in labor market conditions, it is possible that higher wages for workers at the lower end of the wage spectrum drove labor force participation rates up (Prabhakar and Valletta 2024). However, as wage growth has slowed, this procyclical rise has likely cooled for now.

Prime-age women’s labor force participation fell more than men’s in the early months of the pandemic, declining by 3.4 percentage points compared with men’s decline of 2.8 percentage points, although women’s LFP recovered earlier and more consistently than men’s in 2023 (EPI n.d.). Maternal employment and labor force participation were also deeply impacted by the closure of in-person schooling and child care, more so than for fathers and women without children (Landivar et al. 2023). As a result, in contrast to studies done in the 2010s, much of the post-pandemic research has focused on the labor market experiences of women and mothers.

Labor force participation for mothers whose youngest child was under age 5 hit a record high of 71% in September 2023 (Aron-Dine, Bauer, and Powell 2025). There are a number of factors that could have influenced this outcome, including increased access to telework, as mothers with preschool-aged children are the most likely group of prime-age workers to telework, or this could be the result of the procyclical factors previously discussed.

Earlier analysis found that prime-age women contributed the most to the rebound of the overall labor force participation rate post-pandemic, and among all prime-age women, it was mothers with children under 5 who increased their participation the most from 2019 to 2023. However, this seems to be largely because their participation rate, which was already lower than the rate for all prime-age women and mothers of older children, declined the least among mothers in the labor market collapse period (April–May 2019 to April–May 2020). During the recovery period (April–May 2020 to April–May 2023) prime-age women without minor children had a larger impact on the net change in the labor force participation rate, holding population constant. (Bauer and Wang 2023).

Analysis by the Council of Economic Advisers on the impact of the Biden-Harris administration’s $24 billion in child care stabilization funds, which were issued as subsidies to child care providers, estimates a 2–3 percentage point increase in the labor force participation rate for mothers of children under 6 as a result of the funds (CEA 2023). Labor force participation rates stabilized around the time the funds expired, and after that point, growth in LFP for mothers of young children followed the same patterns as those of other women, lending support to the hypothesis that increased child care funding was driving earlier increases. However, these estimates only control for the expanded child tax credit and state unemployment rates, with no control for increases in telework. Telework increases have also been hypothesized to affect all groups of women similarly, but that finding differs by data source. Analysis using Current Population Survey data shows prime-age parents are more likely to telework than workers without children (Aron-Dine, Bauer, and Powell 2025), while others using Census Pulse Survey data found non-mothers were more likely to telework in the first half of 2023 (Bauer and Wang 2023).

Prospects for labor force participation going forward and how policy can affect them

There are many reasons for comparative optimism about prime-age labor force participation going forward, driven by a partial reversal of a number of pressing social challenges. For one, the low points of the 2010s seem to have been significantly driven simply by excess macroeconomic slack. To the degree such prolonged periods of slack can be avoided going forward, labor force participation rates should avoid similar large slumps. For another, the incarcerated population in the United States has fallen significantly in the past 2 decades. To the degree that the future will see fewer workers scarred by a spell of incarceration, this should boost labor force participation. Further, the high point of the opioid epidemic seems to have passed, and rates of addiction are falling, removing another key headwind to labor force participation.

All of these potential tailwinds to labor force participation are obviously contingent on policy decisions—both economic and social. Further, a number of other margins that will affect labor force participation also will be largely driven by policy. Below, we highlight a number of determinants of labor force participation in coming years and assess how policy can increase or reduce their effect.

Efforts to reduce opioid use further may increase labor force participation

Although the exact effects are challenging to measure due to a lack of comprehensive data, there is some evidence suggesting that the increased use of opioids contributed to declining labor force participation in the late 2000s through mid-2010s (Aliprantis, Fee, and Scheitzer 2023). Since that time, a number of laws at the state and national levels have been enacted in response to the opioid crisis. Federally, the Comprehensive Addiction and Recovery Act of 2016, the 21st Century Cures Act, and the Substance Use Disorder Prevention that Promotes Opioid Recovery and Treatment for Patients and Communities Act are intended to lessen the demand and supply of opioids while reducing the harms of opioid use disorder (CBO 2022). These efforts are multifaceted but include strategies such as providing funding to states to invest in prescription drug monitoring programs, increasing budgets for public health services to prevent and treat substance use disorders, and developing treatment alternatives to incarceration.

Tracing the impact of these laws is difficult, in part due to the effects of the pandemic, which contributed to increased opioid use, misuse, and deaths in 2020 (CBO 2022). However, post-2020 some measures have markedly improved. The overall rate of opioid dispensing has declined by roughly 20% since 2019, and opioid deaths involving prescription drugs have declined since their peak in 2017 (CDC 2024; NIDA 2024b). Emergency room visits for suspected nonfatal overdoses related to all opioids also declined over this time period (CDC 2024). At the same time, overdose deaths from any drug and those involving any opioid (not just prescription drugs) continued to increase through 2022 before declining in 2023, although they remain elevated by historical standards (NIDA 2024a).

It is too early to know if these measures will continue to trend downward, but there does not seem to be a simple, straightforward, ongoing connection between opioid misuse and labor force participation. Overdose rates are not a perfect proxy for misuse, but deaths from synthetic opioids increased dramatically after 2014 and remain very high, largely caused by illicitly manufactured fentanyl (NIDA 2024c). This occurred at the same time that prime-age labor force participation has also been increasing. It is possible that there are more complex relationships developing between opioid misuse and LFP, particularly as the opioid crisis changes over time.

Reducing the labor market scarring of incarceration

For Black men in particular, incarceration presents a uniquely challenging obstacle to gaining employment and rejoining the labor force (Pager 2003; Williams, Wilson, and Bergeson 2019; Holzer, Offner, and Sorenson 2005; Ellsworth 2017). At least 1 in 5 Black men will experience incarceration at some point in their lives (Robey, Massoglia, and Light 2023). These results suggest that any successful policy effort to reduce incarceration and recidivism rates would be highly supportive of labor force participation. While recent ban-the-box policies (such as those that do not require job applicants to disclose their criminal history for most jobs) have had mixed results in their ability to promote overall employment (Rose 2021), Bailey et al. (2024) found that children in households that received food stamps had a reduced likelihood of being incarcerated as adults later in life by 0.5 percentage points, suggesting that meeting families’ basic needs can do more than just improve health.

More promising than the ban-the-box policies is California’s 2011 policy to redistribute the costs of sending an adult to prison to the governing locality that makes the decision to incarcerate. This policy is associated with a reduction in the prison population of 50,000 between 2009 and 2019, suggesting that public financing policy can play a surprisingly effective role in supporting labor force participation (Pfaff 2024). The law, AB 109 or colloquially referred to as realignment,” mandated that nonviolent, nonsexual, and nonserious offenders were required to serve sentences under county supervision. Prior to the law, prosecutors, who are paid by the county, were incentivized to prosecute offenses to their highest conviction to get offenders sent to prison, which was paid for exclusively by the state. This redistribution of costs significantly curtailed prosecutors’ incentives to seek higher sentences for less serious offenses and as a result, reduced incarceration rates in California substantially.

Job quality matters to attract workers into the labor market, particularly into some of the fastest-growing occupations

A key headwind for men’s labor force participation in the past few decades has been a slowdown in job growth in sectors like manufacturing and mining that traditionally provided relatively high wages for workers without a college degree. Much of the change in the composition of employment is largely outside the purview of policymakers—but policy can have some effect on the margins of this employment composition. More importantly, how changing employment composition translates into changes in wages or perceived opportunities for different population groups is highly contingent on policy.

Occupational segregation is the tendency for one gender to more likely work in certain occupations than another. For instance, men are more likely to work in manufacturing and construction, while women are more likely to work in education and health care (industrial sectors are provided in Appendix Table 3, but the same phenomenon exists in occupations). Gender stereotypes, such as the idea that women are better suited to caregiving or that men are naturally better at physically demanding tasks, can constrain people’s options and make them more or less likely to pursue traditionally gendered jobs (Palffy, Lehnert, and Backes-Gellner 2023).

Occupational segregation is driven by social and cultural forces that compel women into caring professions (Schieder and Gould 2016). While many people do have choices about which jobs to apply for, accept, or reject, these decisions are made within the context of larger social and cultural influences. Occupational choices are shaped by a lifetime of experiences, including the expectations children are raised with, educational experiences, hiring practices, and norms and beliefs about family roles and the division of household labor held by employers, co-workers, and society. These norms and expectations impact women’s as well as men’s occupational “choice.” As we’ve shown above, the loss of both manufacturing and military jobs in the U.S. came at a cost to men in particular. On the flip side, the growth in jobs in health care will disproportionately benefit those more likely to work in health care, in this case, women.

Figure J illustrates the occupations expected to gain the most jobs, in percent terms, between 2024 and 2034 (BLS 2025a), as well as the share of women in those four occupations in 2024. The industries shown are expected to grow at least twice as fast as the average rate of 4%.

Three of the four fastest-growing occupation groups are dominated by women. The fastest-growing occupation group over the next 10 years—health care support occupations—is expected to grow by 12.4% and is comprised of jobs that pay lower-than-average wages. The median wage in health care support occupations is about three-fourths the median wage overall ($37,000 versus $49,000). Currently women make up about 84% of workers in health care support occupations. Low pay is both a cause and effect of occupational segregation. Jobs in which women are overrepresented tend to provide lower pay and fewer benefits than male-dominated occupations do, and wages tend to fall in occupations as the share of women increases (Levanon, England, and Allison 2009).

Figure J

For workers of any gender to enter those faster-growing occupations, those jobs need to be better. That means better pay, better working conditions, and better benefits. Stronger labor standards, such as a higher minimum wage and overtime protections, can improve those jobs and make them more appealing to a broader range of workers. Increased unionization can also improve pay in those jobs. On average, workers in unionized jobs are paid about 12.8% more than workers in nonunion jobs (EPI 2025c) A key reason jobs in manufacturing could support a middle-class lifestyle was the high unionization rates. There’s no reason currently low-paid health care support occupations couldn’t enjoy such conditions. The number and share of unionized workers in health care support jobs has recently increased, and their wages are higher than those of their nonunion counterparts (BLS 2025b; BLS 2025c).

Labor force participation is more resilient in peer countries

Figure K compares the United States with the OECD average prime-age labor force participation, 1976–2024, women on the left and men on the right. While they display similar overall trends at the endpoints—upward for women and downward for men—there are some notable differences. In the OECD countries, men’s participation also fell between 1976 to the early 2000s, but the losses tapered off quickly, and today, participation remains around its 2000 level. In the United States, men’s participation continued to drop, most notably during the Great Recession and prolonged recovery before starting its upward climb as the economy expanded.

While it is the case that many of our peer countries in the OECD also experienced downturns, particularly in the Great Recession, their labor force participation rates did not fall as far, largely due to different policy responses. Policies such as work sharing and time banking that provide support for workers to stay on the payroll helped blunt the impact of the Great Recession in places like Germany, which saw its unemployment rate tick down at the same time the rate in the U.S. more than doubled (Baker 2018).

Figure K

Women’s labor force participation never stopped its upward rise in the OECD average, even while it softened in the United States following 2000. The steep gains in participation in the U.S. tapered off significantly, while it continued to rise in the OECD until today. The policy environment around work for women is quite different, particularly in Western European countries, which have stronger family leave and child care supports.

There is meaningful evidence that the lack of work-family policies and relatively sparse care infrastructure in the U.S. depresses women’s labor force participation. In 1990, out of 22 OECD countries, the U.S. ranked 6th for women’s prime-age labor force participation, but by 2010 had fallen to 17th place. The lack of family-supportive policies in the U.S., such as paid parental leave and publicly provided child care, can explain 29% of the decline in the U.S.’s ranking of female LFP relative to other OECD countries (Blau and Kahn 2013).

In the subsequent 15 years, the gaps between policies in other OECD countries and the U.S. have typically widened. Compared with other high-income OECD countries, the U.S. is now even more of an outlier on nearly every workplace policy that could help boost labor force participation among workers with family responsibilities.

Since 2010 the total amount of paid parental leave available to two parents in OECD countries has increased from an average of 58.1 weeks to 64.6 weeks (OECD 2024). Yet the United States remains an extreme outlier and is one of the only countries in the world that does not guarantee workers the right to any form of paid parental leave. Across the other 37 OECD countries, mothers are eligible for an average of more than one year (53.5 weeks), and fathers are eligible for more than three months (13 weeks) of paid leave.

Families in the United States also pay more on average for child care than families in other OECD countries. In the U.S., a single parent paid the average wage would need to spend 40% of their wages to pay for center-based care for two toddlers—about 5 times the cost burden (8%) for the OECD, on average (OECD n.d.). And while net costs increased for U.S. families, they declined in most other OECD countries, with the overall OECD average dropping from 15% to 8% between 2004 and 2023.

The cost burden is much greater in the U.S. compared with other countries where child care fees are similarly high or higher because the U.S. does not provide meaningful benefits like child care allowances or fee rebates to help families reduce their financial costs. While there are tax credits that allow some working parents to write off child care expenses, not all families qualify, and the overall impact on net costs is minimal.

The share of GDP the United States spends on early childhood education and care has declined since 2010, while the OECD average has increased (OECD Social Expenditure Database n.d.). In 2021, the last year with complete data on all 38 OECD countries, U.S. spending (0.3% of GDP) was less than half the OECD average (0.7%).

Policies related to remote work and workplace flexibility—such as the ability of workers to alter their start and stop times—were not part of the original analysis conducted by Blau and Kahn (2013). However, flexibility and remote or telework options have been identified as important policies to support labor force participation, particularly among mothers post-2020. As of April 2024, 25 of the 38 OECD countries had laws in place allowing workers to request flexible schedules, remote work, or both (World Bank 2024).

The 2019 Work-Life Balance Directive2 created a right for workers in the European Union to request flexible work arrangements, including remote work, to better coordinate work with family caregiving responsibilities. The law does not guarantee that employers will grant approval to every request, but they are required to seriously consider requests for flexibility and must provide reasons for refusing requests. In the United Kingdom, workers’ rights to request flexible work arrangements were expanded through the Employment Relations (Flexible Working) Act 20233. Workers in the U.K. now have a legal right to request flexibility starting from their first day of employment rather than having to wait 26 weeks before making the request as they did previously.

In the United States, workers do not have an explicit legal right to request remote work or workplace flexibility, and employers are not required to consider such requests when they are made. Although the data are not conclusive, there are indications that increased access to telework during and after the pandemic enabled greater labor force participation, including among mothers of young children. Broadening access to flexibility and remote work would likely further increase entry or reentry into the labor force among workers with caregiving responsibilities, as well as supporting continued participation for current workers.

Investing in children is a long-run strategy to increase labor force participation in the future

Previous sections noted the sharp increase in college attainment among the U.S. population in recent decades and also noted that college graduates saw much slower rates of declines in labor force participation than noncollege workers did. The public sector has supplied the majority of financing for higher education in the United States for the entire post-World War II period. In short, the boost to labor force participation (and economic growth generally) supplied by higher education was a policy choice.

Policy choices about how prepared future generations will be to participate in the labor force are not just confined to education spending (though that is obviously important as well). Investing in children by supporting their basic needs such as food, medical care and child care has been shown to have demonstrable long-term effects on health and economic sufficiency. These, in turn, support attachment to the labor market. Early childhood is a sensitive period, and investments in children tend to have large benefits as they age (Cunha and Heckman 2007; Heckman 2008). Additionally, a stronger welfare state raises the income and resources of a child’s family (Ruhm and Waldfogel 2012). Importantly, these benefits tend to outweigh the costs of the program or any potential impacts on the parents (Aizer, Hoynes, and Lleras-Muney 2022).

Long-term studies have tracked children in households with access to food stamps (SNAP), early childhood education, and Medicaid to assess the impact of these programs on these children as adults. With respect to food stamps, Hoynes, Schanzenbach, and Almond (2016) found that access to food stamps for households with children led to statistically significant improvements in measures of metabolic health when they were adults. Moreover, researchers found positive impacts of receiving food stamps on economic sufficiency (high school completion, use of food stamps, and earnings), with statistically significant increases among adult women who receive food stamps. Bailey et al. (2024) linked the 2000 Census and 2001–2013 American Community Survey to information from Social Security to examine how SNAP program rollouts from 1961–1975 impacted children as adults. They found that children with access to food stamps before age 5 have better outcomes as adults in the form of increased economic self-sufficiency (3% standard deviation increase), human capital (6% SD increase), quality of neighborhood residence (8% SD increase), and a 1.2-year increase in life expectancy.

Several studies have also documented the long-run impact of Medicaid with implications for labor market participation. Miller and Wherry (2019) studied infants who gained access to Medicaid in utero via their mother’s prenatal coverage. They find that infants with prenatal coverage had lower rates of chronic health conditions as adults, fewer hospitalizations, and increased high school graduation rates. Thompson (2017) examined the long-term impact of Medicaid access and found that each additional year of Medicaid eligibility during childhood improved overall adult health (self-score evaluations) and reduced chronic conditions and asthma prevalence as adults. Given that disability and chronic health conditions are some of the main reasons that individuals stay out of the labor force, these studies show that access to Medicaid as a child can promote the conditions that would lead to labor force attachment.

Finally, Brown, Kowalski, and Lurie (2020) use tax data to estimate the long-term impact of Medicaid eligibility in childhood on a variety of outcomes measured at ages in early adult life. They find that eligibility for Medicaid during childhood increased college enrollment rates, delayed fertility, reduced mortality, and reduced dependence on EITC benefits, and led to higher tax payments among adults, suggesting that access to Medicaid has the long-term benefit of improved economic self-sufficiency and employment.

While the U.S. doesn’t have a national pre-K early-childhood program, studies of individual programs show promising results. Chicago’s Child-Parent Center Education Program preschool was linked to higher educational attainment and socioeconomic status, a higher likelihood of health insurance coverage, and lower rates of justice-system involvement and substance abuse (Reynolds et al. 2011). Michigan’s HighScope Perry Preschool program was linked to fewer arrests, higher earnings, and higher educational achievement and attainment (Schweinhart 2005), and careful cost- benefit analysis estimated that every dollar invested at age 4 yields a return of $60–$300 by age 65 (Heckman et al. 2010). Additionally, studies of state-introduced universal kindergarten programs in the 1960s and 1970s found that this additional early childhood education increased both educational attainment for some groups of students (Cascio 2009, 2010; Dhuey 2011); and labor market outcomes in the form of weeks worked and wages (Dhuey, 2011), suggesting that early childhood education interventions can support labor market attachment.

Studies in Europe have documented the impact of pre-K and early childhood care on long-term outcomes. In Denmark, researchers found that early increased preschool density was positively associated with completed schooling, particularly for daughters of less educated mothers, and later adult earnings (Bingley and Westergaard-Nielsen, forthcoming). In France, researchers found that the large-scale universal preschool program increased test scores, high school graduation rates, and adult wages, with larger effects for children from disadvantaged backgrounds (Dumas and LeFranc 2010). In Norway, an expansion of subsidized child care led to increased educational attainment (more years of schooling, higher rates of college attendance) and labor market participation (Havnes and Mogstad 2011).

The role labor force participation rates play in the economic future of the U.S.

Labor force growth is a key element of economic growth more generally. At the most basic level, growth in overall gross domestic product (GDP) over brief periods of time can be proxied as the sum of the growth rates of the labor force and of labor productivity—with productivity defined as the amount of output generated in an average hour of work in the economy. Given this, every percentage point rise or fall in the growth rate of the labor force translates one for one into a corresponding change in overall GDP growth.

In coming decades, the question that matters more than any other for projecting labor force growth for the U.S. economy is the pace of net immigration. For example, the Congressional Budget Office projects that the U.S. labor force will grow by just under 7% from 2025 to 2035 (CBO 2025a). But if the influence of immigration flows is removed, this growth will fall to just 0.5% over the entire next 10 years.4

There is no realistic scope at all for changes within U.S.-born labor force participation rates to fundamentally change this and lead to significant increases in the labor force over the next decade. Most importantly, the U.S.-born population is aging fast. Over the next 10 years the share of the U.S. adult population over the age of 65 will rise by another 4 percentage points (to over 27%). Given the gap in labor force participation rates for workers aged 65–74 and those under the age of 65, this translates into a reduction in the overall labor force participation by roughly a full percentage point over the decade—a powerful headwind to growth.5

In theory, the CBO has taken some account of the fact that major headwinds to growth in prime-age participation rates over the past decade or so should likely reverse (or at least, dial down) in the next 10 years. These headwinds include excess labor market slack, the stock of prime-age adults with some spell of incarceration in their past, the prevalence of opioid addiction, and the steady shrinkage of military employment scaled against the civilian workforce. If none of these past headwinds to labor force participation were taken into account in CBO projections, their reversal could conceivably add 1–2 percentage points to prime-age labor force participation rates over the next 10 years. But, again, this doesn’t come close to rivalling the potential effects of changes in net immigration, and CBO has likely accounted for a number of these influences in their projections, at least in part.6

If one of the more ambitious long-run strategies for boosting future labor force participation highlighted in the previous section was undertaken (large investments in child health, nutrition, and education for example), these effects could conceivably add another percentage point to labor force participation rates, but only at a quite long time horizon (well over 10 years).7

One upshot of the dominance of immigration flows in conditioning future labor force growth and the continued downward pressure on labor force growth imposed by the aging of the U.S.-born population is that anybody promising large increases in GDP growth in coming years without calling for higher rates of immigration will have a very hard time fulfilling this. Again, every percentage point decline in the growth rate of the labor force subtracts a percentage point from GDP growth, and changes in labor force growth in the coming decade will be driven near entirely by immigration inflows.

Of course, GDP growth is (roughly) the sum of growth in the labor force plus the growth of productivity. In theory, a slower growth rate of the labor force could be overcome by a surge in productivity growth, and overall GDP growth could still rise. However, productivity growth over the past century in the U.S. economy has fluctuated with a relatively narrow band—essentially between 1% and 2% annually. Since the 1960s, spells of productivity growth over 2% have been rare—just the late 1990s and early 2000s. It is theoretically possible that we are in a stage currently where technological change will accelerate and productivity growth will surge to the higher bands of its historical experience, but this is very hard to bank on. Promises of future growth surges from other technological changes (like robotization in the 2010s) yielded real, but quite modest, productivity growth.

But while productivity growth is unlikely to generate historically fast GDP growth in coming decades, it is the most relevant part of the growth equation to focus on. A higher GDP driven by a larger labor force does not necessarily raise living standards. It is productivity growth alone that makes a country richer over time in the most relevant sense—providing the potential for higher living standards per person.

By far the most substantive way that differing rates of labor force growth can affect Americans’ economic future is through the tax and transfer system. The federal government in the U.S. has historically taken on the role of ensuring adequate income in retirement for all citizens by running social insurance programs—Social Security and Medicare—through the nation’s fiscal system. Very roughly speaking, current workers are taxed to provide benefits to current retirees. As the share of the population that is retired rises relative to the stock of current workers, this means a higher share of workers’ output needs to be devoted to providing income for retirees.

This need not imply any pronounced economic pressure. Productivity growth means that even if a rising share of workers’ incomes is devoted to social insurance for current retirees that workers’ net-of-tax income levels can still rise steadily over time. But this demographic angle of the large social insurance programs run by the federal government does pose potential political challenges. These political challenges could well be lessened by policy decisions that keep the ratio of current workers to current retirees higher than it otherwise would have been—and here is where issues of labor force participation could matter.

Conclusion

Labor force participation is both an input and a consequence of a healthy economy. While there is no ideal labor force participation rate that policymakers should target, they should target any barriers that are keeping willing workers from being able to actively search for work. These barriers include too-slack labor markets stemming from macroeconomic policy failures; labor market discrimination; insufficient investment in workers’ health, skills, and credentials; and a failure to make investments needed to enable parents with young children to also participate meaningfully in the labor market.

Outside of immigration, however, the changes to labor force participation that can be leveraged by even quite ambitious policy changes will be relatively small and will not meaningfully change the trajectory of the U.S. macroeconomy over a decade or so. This does not mean they are not worth doing, instead it means that policymakers should be realistic when claiming that future economic growth can be boosted by increasing growth in the U.S. labor force.

Appendix

Appendix Table 1

Appendix Table 2

Appendix Table 3

Acknowledgments

The authors thank Katie deCourcy and Stevie Marvin for research assistance and Grace Park for editing. This project was made possible by financial support from the Peter G. Peterson Foundation.

Notes

1. We should note that this change in employment shares by skill- or credential-grouping does not predict at all accurately any related change in wages. In short, one can believe that changing employment shares by occupation—even those driven by technological changes—fail to move relative wages or inequality in any significant way, and that non-relationship between employment and wage changes by occupation is validated in the data (see Mishel, Schmitt, and Shierholz 2013).

2. Council Directive 2019/1158, 2019 O.J. (L 188), 79–93.

3. The Employment Relations (Flexible Working) Act 2023, c. 24 (UK), https://www.legislation.gov.uk/uksi/2024/438/made.

4. Authors’ analysis is based on information in CBO 2025a, b. The size of the over-19 labor force over the next decade is provided directly in CBO 2025b. This data also provide the share of growth in the over-19 population that is accounted for by immigration. To obtain the counterfactual growth, we just removed the portion of growth associated with immigration each year and recalculated the level of the labor force for each year in the next decade.

5. Numbers in this paragraph are based on authors’ analysis of data in CBO 2025a, b. CBO 2025b reports that the share of the over-64 population will rise as a share of the total adult population by almost exactly 3 percentage points between 2025 and 2035. Currently, the LFPR for workers between the ages of 65 to 69 is almost exactly 30 percentage points lower than for workers between the ages of 55 to 64. Multiplying these together (which gives 0.9%) should give a very rough sense of the downward pressure on labor supply stemming from aging.

6. Schmitt and Warner (2011) estimated that the scarring effect of incarceration could reduce the employment-to-population ratio of men by between 0.6 to 2.6 percentage points by 2008. Given that the stock of incarcerated men has fallen by roughly 20% since its highest point (and a bit more than this as a share of the population), this penalty going forward could have been reduced by 0.15 to 0.6 percentage points. In regard to opioids, given estimates that rising opioid use throughout the 2000s could have reduced labor force participation rates by as much as 1 percentage point, any leveling off of this could remove a powerful headwind to labor force growth, and any affirmative reduction in the incidence of opioid addiction should, in theory, potentially boost labor force growth.

7. Most estimates of the effect of early childhood investments—whether it be early education, health, or nutritional investments—report the effect on earnings of exposed children when they become adults. Assuming a package of investments in today’s children were able to boost their earnings by 5% when they became adults (which seems plausible given that early childhood educational investments alone have been estimated to increase annual earnings of exposed children by over 20%, and the share of today’s children not currently receiving high-quality early childhood education is estimated to be over half of all children (see Lynch and Vaughul 2015)). If increased labor force participation accounted for a fifth of this total earnings effect (as opposed to lower unemployment rates, higher hours worked during a year, and higher hourly wages), then a range of estimates would indicate that these investments could boost the adult labor force participation rates of today’s children by roughly a percentage point. It seems plausible that increased labor force participation could, by itself, explain a fifth of projected future earnings. For example, annual earnings of workers with a college degree are roughly 60% higher than with only a high school degree. This 60% difference can be very roughly expressed as the sum of differences in labor force participation, unemployment rates, hours worked per year, and average hourly earnings. Labor force participation rates for workers with a bachelor’s degree or greater are roughly 12% higher than for workers with only a high school diploma , which is roughly a fifth of the total difference in annual earnings.

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Trump’s deportation agenda will destroy millions of jobs: Both immigrants and U.S.-born workers would suffer job losses, particularly in construction and child care

Ben Zipperer — Thu, 10 Jul 2025 09:00:55 +0000

Immigrant workers make up a substantial part of the workforce in the United States: 1 in 5 workers is an immigrant, and about half of immigrants are noncitizens. Because of their sizable presence in the workforce, large-scale attempts to remove them will lead to extensive employment losses for foreign-born workers. What is less apparent, however, is the impact that arrests, detentions, and deportations of immigrants will have on millions of U.S.-born workers who will lose their jobs. The widespread job losses for both immigrants and U.S.-born workers will undercut the narrative that abruptly removing immigrants will somehow magically increase employment opportunities for U.S.-born workers.

Although the economic consequences of reduced or increased immigration flows are often contested, recent research clearly demonstrates that immigration enforcement that increases deportations will also cause job losses for both foreign-born and U.S.-born workers. This report uses that research to estimate the employment consequences for all workers if the Trump administration succeeds in carrying out its goal of 1 million deportations annually over the next four years.

Deportations will lead to employment losses

How deportations reduce jobs for immigrants and U.S.-born workers

Deportations sharply reduce the supply of labor, threatening the ability of employers to generate revenue and pay for business expenses like rent, machinery, and even the labor of any remaining workers. Immigrant labor supply will fall because immigrants tend to have high employment rates, so arresting, detaining, and removing immigrants from the country removes people from the workforce. Also, others who are not formally deported may need to leave the country to accompany their deported family or community members. In addition, deportations raise the risks of arrest and removal for remaining immigrants and cause them to curtail activities with the potential for interaction with the government, like labor market participation.

These chilling effects can even extend to citizens who are by law not subject to deportation but are nevertheless connected to communities at risk. For example, Alsan and Yang (2024) examined the effects of “Secure Communities,” a large interior immigration enforcement program in the United States that began in 2008. This program linked state and local government databases to federal immigration enforcement in order to detect immigrants who are deportable and led to increased detentions and deportations.1 Alsan and Yang (2024) found that Hispanic citizen-headed households reduced their participation in federal safety programs in response to Secure Communities enforcement actions, perhaps out of concern for other family members and close contacts.

Regardless of the exact mechanisms, deportations can cause a sharp and abrupt enough fall in labor supply that some employers will respond by shutting down operations entirely. For example, Ali, Brown, and Herbst (2024) found that Secure Communities, which led to increased immigration-related arrests and deportations, reduced the number of child care facilities, harming both immigrant and U.S.-born employment in the child care sector.

Deportations also reduce labor market leverage that immigrants have with employers. The rising threat of arrest or deportation makes it harder for immigrants to find new employment opportunities that do not risk their ability to stay in the U.S., compelling them to stay with a bad or lawbreaking employer. With shrinking alternative job options, immigrants are forced to settle for lower wages and worse working conditions. These deteriorating conditions for immigrant workers will negatively affect all workers who compete with immigrants in the same labor markets since lower wages and bad conditions for one group will drag down wages and conditions for all workers. Employment will decline for U.S.-born workers, as they are less likely to work at jobs with falling wage rates.

As working conditions deteriorate, so does the willingness of workers (either immigrant or U.S.-born) to report on degraded conditions. For example, Grittner and Johnson (2024) found that the rollout of Secure Communities increased workplace injuries and reduced worker safety complaints at workplaces with higher shares of Hispanic workers. In addition, Grittner and Johnson found that this increased immigration enforcement caused minimum wage violations to increase among Hispanic workers and non-Hispanic workers. Deportations limited the alternative job options of those workers most at risk of expanded immigration enforcement, lowering their labor market leverage, which, in turn, reduced the bargaining power of all workers competing in those same labor markets.

Because jobs held by U.S.-born and immigrant workers are often complementary and economically linked, the shrinking supply of immigrant labor can adversely affect employer demand for jobs held by both groups of workers. As Howard, Wang, and Zhang (2024) observe, when there are fewer immigrant roofers and framers to build the basic structure of homes, there will be less work available for U.S.-born electricians and plumbers. If there are fewer dishwashers and cooks, restaurants may limit their hours or shift their operations toward takeout, reducing the overall employment of waitstaff and managers.

Complementary immigrant and U.S.-born employment can also cut across sectors. East and Velásquez (2024) found that the Secure Communities enforcement program reduced the hours of immigrant child care workers and cleaners, and U.S.-born mothers of young children worked less in response, presumably due to increased care responsibilities at home.

Finally, the reduction in the immigrant population and their public activities is a reduction in consumers and business owners, negatively affecting consumer demand and investment on top of falling local demand due to reduced immigrant and U.S.-born employment. As immigrant employment and earnings fall, so will consumption of goods and services. Removing immigrants will also slow business creation and weaken employment demand, as immigrants are more likely than U.S.-born workers to start businesses (Azoulay et al. 2022).2 A large mass deportation program could also in principle generate very broad chilling effects on consumption. For example, declining numbers of international travelers to the United States will negatively affect the tourism industry. In general, purchases by nonresidents, including foreign students, are a major U.S. export, but that spending may drop precipitously when noncitizens face higher risks of detention and deportation.3

For all these reasons, increased immigration enforcement through arrests, detentions and deportations can reduce employment opportunities for noncitizens, immigrant citizens, and U.S.-born workers.

Recent studies on the employment effects of deportations

Recent empirical research finds that heightened immigration enforcement reduces employment, often causing job losses for both foreign- and U.S.-born workers.

Several studies show that Secure Communities led to large job losses as the program was rolled out across counties beginning in 2008. Secure Communities increased fingerprint and other information sharing between U.S. Immigrations and Customs Enforcement (ICE), the Federal Bureau of Investigation (FBI), and state and local law enforcement. The program allowed local law enforcement to hold those arrested, who may otherwise have been released, for up to 48 hours so that ICE could facilitate removal proceedings. As intended, Secure Communities led to a rapid increase in detentions and deportations. East et al. (2023) calculated that between 2008 and 2014, the program resulted in the deportations of more than 454,000 people.4

East et al. (2023) found that the Secure Communities rollout between 2008 and 2014 led to large overall employment losses for both immigrants and U.S.-born workers. Howard, Wang, and Zhang (2024) found that Secure Communities reduced the size of the construction sector, reducing immigrant and U.S.-born employment and delaying residential homebuilding. Ali, Brown, and Herbst (2024) found that the program reduced immigrant and U.S.-born employment in the child care sector, leading to a significant drop in the number of child care centers. Relatedly, East and Velásquez (2024) found that in response to Secure Communities, mothers of young children were less likely to be employed and worked fewer hours.

These studies demonstrate that increases in immigration-related arrests, detentions, and deportations harm the broader labor market, with particularly large negative consequences for certain sectors.5 The construction industry will be disproportionately harmed because of its large immigrant workforce, and child care centers also face staffing challenges even in the absence of increased immigration enforcement (Fee 2024).

How Trump’s escalating deportations will reduce employment

The scale of Trump’s deportations

The Trump administration plans to increase the number of deportations to unprecedented levels. For the purpose of estimating the employment effects of this policy, this report assumes that the deportation rate could reach 1 million people per year, totaling 4 million deportations over four years, a rate consistent with public and private statements by policymakers. Sacchetti and Bogage (2025) reported that internally the Trump administration has focused on deporting 1 million immigrants in one year. The Department of Homeland Security (DHS) Immigration and Customs Enforcement congressional budget justification for fiscal year 2026 requests funding increases “to support the Administration’s strategy of 1,000,000 removals per year” (DHS 2025b), and in a press release, the White House (2025) quoted the House Judiciary Committee as stating the 2025 Republican-led budget reconciliation bill “provides funding for at least 1 million annual removals.”6 An increase to 1 million deportations is similar to an annual scenario considered by the American Immigration Council (2024) in their report on the costs of mass deportation.

Figure A shows that, typically, the U.S. deports about 300,000 people per year. Deportation rates just exceeded that during the 2014–2019 period but dropped during the onset of the pandemic, primarily due to immigration restrictions that expelled migrants more immediately at the border.7 In fiscal year 2024, the U.S. deported about 330,000 people.

Figure A

Given these data, I assume that the United States baseline or “business as usual” rate of deportations is 330,000 annually. By aiming for 1 million deportations annually, the Trump administration intends to triple the baseline rate, increasing annual deportations by 670,000, for a four-year total increase of 2,680,000. Below, when I estimate the employment effects of the Trump administration’s increase in deportations to 4 million over four years, I use the 2,680,000 increase in deportations as the magnitude of the intensity of the Trump administration’s policies. On the one hand, this will underestimate job losses stemming from deportations generally if the annual rate of deportations prior to the Trump administration was already causing large employment reductions. On the other hand, the estimates will reflect the actual policy change made by the Trump administration; this method is also consistent with how the original research estimated the employment effects of an increase in police-based immigration enforcement due to the Secure Communities program, over and above the baseline immigration enforcement policy.8

Overall employment effects

To estimate the national employment effect of increased deportations, I extrapolate the employment effect estimates of the rollout of the Secure Communities immigration enforcement from East et al. (2023); Howard, Wang, and Zhang (2024); and Ali, Brown, and Herbst (2024). As described above, Secure Communities increased immigration-related arrests, detentions, and deportations across the United States.

East et al. (2023) found that the rollout of the Secure Communities immigration enforcement program reduced foreign-born employment in the United States by an average of 670,000 people over their study period.9 During that period, Secure Communities deported 454,000 people, suggesting that one deportation resulted in 1.47 fewer employed immigrants. Alternatively, a more conservative assumption is that one additional deportation by the Trump administration results in one fewer employed immigrant; this assumption is similar to the initial labor force shock modeled by McKibbin, Hogan, and Noland (2024).

This report takes the average of these two possibilities and assumes that one additional deportation results in about 1.24 immigrant job losses. If the Trump administration deports 4 million people over four years (increasing total deportations above baseline by 2,680,000), immigrant employment will fall by about 3.3 million (see Table 1).

Table 1

As discussed above, reductions in immigrant employment can also lead to U.S.-born employment losses. East et al. (2023) found that the Secure Communities program reduced the number of employed U.S.-born people, where the magnitude of U.S.-born employment losses was about 77.5% of the size of foreign-born employment losses.10 Therefore, I assume that one deportation, leading to 1.24 immigrant job losses, also results in 0.96 U.S.-born job losses. As Table 1 shows, 4 million deportations by the Trump administration will, therefore, cause the number of U.S.-born workers with jobs to fall by 2.6 million. Total job losses due to an increase in Trump administration deportations would be about 5.9 million, with job losses among the U.S.-born population accounting for about 44% of the total employment reduction.

Job losses in the construction and child care sectors resulting from Trump’s deportations

The increase in deportations will cause large declines in construction employment, likely due to large numbers of immigrants working in this sector and the high degree of complementarity among construction jobs held by immigrants and U.S.-born workers. Howard, Wang, and Zhang (2024) found that the increase in immigration enforcement associated with the Secure Communities program had large negative effects on immigrant and U.S.-born construction employment.

Specifically, their estimates imply immigrant and U.S.-born construction employment losses that are, respectively, 42.3% and 33.5% the size of immigrant and U.S.-born overall employment losses estimated by East et al. (2023).11 I then use these ratios to scale the overall job losses per deportation used above, yielding construction employment reductions of 0.52 immigrants and 0.32 U.S.-born workers per deportation.

Table 1 shows that, assuming 4 million total deportations over four years, about 1.4 million fewer immigrants and 861,000 fewer U.S.-born workers will be employed in construction. Some of these workers will no longer be employed, some will work fewer hours, and others may move to other sectors. In total, however, the construction sector will shrink precipitously, losing 18.8% percent of its workforce relative to 2024 employment levels.

Research also shows the child care sector will experience large employment declines after increases in deportations. As Ali, Brown, and Herbst (2024) observe, child care centers may face a particularly intense labor supply shock due to rising fear among immigrants who will increasingly try to avoid governmental authorities. Child care centers have relatively frequent interactions with the government because of regular, unannounced inspections; workers’ personal and earnings information is also often reported to authorities for licensing purposes. In addition, child care centers have high worker turnover and strict staffing ratios, so difficulties in recruiting and retaining staff could quickly lead to shutdowns. In particular, Ali, Brown, and Herbst (2024) found that the number of child care establishments shrank after the rollout of the Secure Communities program.

To estimate child care employment reductions, I use the employment-to-population ratios Ali, Brown, and Herbst (2024) provide for women in the child care sector, as well as separate population-level estimates, and then I divide the implied employment level changes by the deportation counts used in East et al. (2023).12 Table 1 shows the implied employment effects if the Trump administration deports 4 million people over four years. About 104,000 fewer immigrants and 444,000 fewer U.S.-born workers will be employed in the child care sector. Trump’s deportations will cause the total child care sector to shrink by 15.1%, a shock with potentially much broader labor market consequences when working parents are already having significant trouble finding care for their children. As East and Velásquez (2024) show, the broad expansion of immigration enforcement created by Secure Communities also led to a drop in the number of employed U.S.-born mothers who could not continue working without child care.

Trump’s deportations will cause job losses in every state

Because immigrants live throughout the entire country, deportations will cause job losses in every state. To create state-level estimates, I first distribute the additional number of national deportations by each state’s share of the national noncitizen population, under the assumption that states with higher (or lower) shares of noncitizens are more (or less) likely to experience deportations. For example, about 1 out of every 5 noncitizens in the United States lives in California, so I assume about 1 out of every 5 additional national deportations will occur in that state. Then I multiply these additional state-level deportations by the national multipliers of foreign-born (1.24) and U.S.-born (0.96) job losses per deportation. This is equivalent to allocating national job losses by each state’s share of national noncitizen employment; by construction, the sum of all job losses across states equals the national total.

Figure B shows that for a scenario of 4 million national deportations, the job loss levels across states vary widely. California’s 775,000 deportations imply total job losses of 1.1 million, equal to 6.2% of total employment in the state. Other states with very large predicted employment losses in percentage terms include Texas (5.8%), Florida (5.1%), New Jersey (5.1%), Nevada (4.7%), and New York (4.6%).

Figure B

Figure B also shows state-level construction job losses using the national construction deportation multipliers. To account for the fact that some states may have relatively more (or fewer) noncitizen workers in the construction sector, I allocate the national job losses by each state’s share of national noncitizen construction employment.13

Predicted estimates of construction job loss, therefore, vary across states due to the size of their noncitizen construction workforce. Figure B shows that some states, like Alabama, will experience smaller job losses than the average state because their construction sector is small, and fewer noncitizens work in it. Others like Texas (32.1%), Nevada (26.3%), California (25.5%), and North Carolina (25.5%) will see the largest percent reductions; construction job losses for these states will be about 40% of the national construction job loss estimate of 2.3 million workers. (The appendix to this report also shows detailed overall and construction-sector estimates for each state.)

Broader economic effects of the overall employment shock

The total employment effects after four years of deportations would be a historically large and persistent drop in employment, unprecedented outside of the worst recessions in U.S. history. In March, Congressional Budget Office (2025) projected that total civilian employment would grow by 4.2 million people between 2025 and 2029. In contrast, this analysis suggests that employment would actually fall in absolute terms by 2029, given the estimated job loss of about 5.9 million due to four years of Trump’s deportations.

A widespread reduction of immigrants will also likely raise the prices of goods and services throughout the economy. Immigrants are a somewhat deflationary force in the sense that they boost output more than they do demand—mainly because immigrants immigrants are younger and therefore more likely to work than U.S.-born residents, and because some of the immigrants’ income is not spent in the United States but is instead sent as remittances to other countries (Costa et al. 2024). As a result, the removal of immigrants will raise inflationary pressures.

In addition, because aggressive immigration enforcement will lead to a reduction in the number of workers and a subsequent drop in production, some businesses will charge higher prices if they continue to have consumers. For example, Howard, Wang, and Zhang (2024) found the rollout of the Secure Communities immigration enforcement program led to a construction slowdown that increased home prices.

What will happen to wages in the face of these shocks is somewhat unclear. In some cases, employers may try to raise wages to attract new workers, but in other cases, labor demand may fall, or some employers may choose to operate at lower levels of employment and wages.

The evidence in East et al. (2023) suggests that, overall, wages tend to decline in the face of increased deportations, particularly for U.S.-born workers. Howard, Wang, and Zhang (2024) presented some evidence that in the second year after a Secure Communities rollout, hourly wage rates in construction might have increased, perhaps for U.S.-born workers, but as the authors describe it, most of the relative change in construction wages is to keep them flat in the face of declining overall wages.14 Ali, Brown, and Herbst (2024) found that wage rates fell for both U.S.-born and immigrant women who are child care workers in response to increased immigration enforcement, but East and Velásquez (2024) found rising wages for low-educated women in household services.

All told, the existing evidence suggests that Trump’s deportations will not improve the hourly wage rates of the overall workforce or even U.S.-born workers in many instances.

Conclusion

The consequences of immigration on the labor market are often a matter for heated debate. While some studies have findings at odds with others, a fair assessment of the evidence suggests that reduced immigration generally will not lead to increased job opportunities for U.S.-born workers. A comprehensive empirical review by the National Academies (2017) found that “most studies find little effect of immigration on the employment of natives.” However, it is important to understand that the labor market consequences to the United States of increased deportations are likely to be far worse than the effects of gradually changing the size of the immigrant population through reduced immigration flows into the United States.

For immigrants and U.S.-born workers remaining in the United States, the main similarity between reduced immigration and increased deportations is a drop in the supply of immigrant workers. The reduced supply of labor can reduce competition for jobs and make it easier for some remaining immigrant and U.S.-born workers to find work. On the other hand, fewer immigrants lead to a general reduction in aggregate demand and a reduction in employer demand for complementary jobs. A priori, the net employment effect of reduced immigration on remaining workers is ambiguous and may indeed vary, depending on the specific group of workers under consideration.15

Deportations trigger some of the same mechanisms for affecting employment as reduced immigration flows, but there are two additional reasons deportations depress the employment of remaining immigrants and U.S.-born workers. First, unlike a gradual, longer-term reduction in the supply of labor, the sudden removal of the actual and potential workforce can cause employers to rapidly scale back operations and sometimes shut down entirely. Second, deportations greatly weaken the labor market leverage of any remaining immigrant workers, negatively affecting everyone competing in the same labor markets. Increased arrests and removals make immigrants’ employment situation vastly more precarious, reducing their alternative job options, and U.S.-born workers will, in turn, be working alongside ever more precarious employees who cannot reasonably complain about poor conditions and pay or join a union, making it more difficult for those U.S.-born workers to bargain for better conditions and pay as well. As a result, employers can pay lower wages and profitably operate with lower employment so that employment falls for both immigrant and U.S.-born workers.

These additional labor market effects may be why many studies on increased immigration enforcement more clearly signal negative employment effects for both immigrant and U.S.-born workers. Extrapolating from this evidence suggests the Trump administration’s deportation goals will cause a major blow to the U.S. labor market, squandering the full employment that the Trump administration inherited from the Biden administration and also causing immense pain to the millions of U.S.-born and immigrant workers who may lose their jobs.

Appendix

Appendix Table 1

Appendix Table 2

Notes

1. For more background on Secure Communities, see Waslin 2011.

2. See also the outsized immigrant ownership share in retail, restaurants, and neighborhood services described by Kallick 2015.

3. Annual purchases by nonresidents in 2024 were $218 billion, nearly three-quarters of the U.S. annual trade surplus in services (see BEA 2025, Tables 1.1 and 2.4.5U.)

4. See Alsan and Yang 2024 for a description of Secure Communities.

5. For other analysis related to removing immigrants from the United States, see Lee, Peri, and Yasunov 2022, which found that increased repatriations to Mexico between 1929 and 1934 reduced the employment of U.S.-born workers. Clemens, Lewis, and Postel 2018 estimated that the removal of Mexican bracero farmworkers during the 1960s did not increase the employment for U.S.-born farmworkers. The model developed by Chassamboulli and Peri 2015 predicts that deportations will reduce both U.S.-born and immigrant employment. In a review of related research, Lynch and Ettlinger 2024 argue that “deportation of unauthorized immigrants would shrink the economy, cause American workers to lose jobs, likely reduce the wages of U.S. citizens, lose the taxes paid by deported unauthorized immigrants and worsen the finances of federal, state and local governments.”

6. The legislation triples funding for ICE and quadruples the annual funding for immigrant prisons (Costa 2025).

7. Technically, the deportations shown in Figure A are “removals,” based on a formal order of removal and typically carried out by ICE but also sometimes by Customs and Border Protection. In addition to removals, there have been tens to hundreds of thousands of other “returns” of migrants, typically occurring at the border. The figure also omits the pandemic-based Title 42 expulsions used to immediately expel border crossers during 2020–2023. See DHS 2025a.

8. In fiscal year 2007, just before the rollout of the Secure Communities program, the United States deported about 319,000 people (see Table 39 of DHS 2022).

9. The estimate of -0.387 from Table 3, panel B, specification 1 of East et al (2023) divided by 100 and then multiplied by their baseline population of 173 million yields a low-education foreign-born employment loss of 670,000. In extrapolating this estimate to all immigrants, I assume that there are no high-education foreign-born employment losses.

10. East et al. 2023 report an effect size of -0.387 for the low-education foreign-born population in Table 3, panel B, specification 1, and an effect size of -0.300 for the U.S.-born population in Table 4, panel B, specification 1.

11. Based on the estimates in text and what is plotted in Figure 4 of Howard, Wang, and Zhang 2024, I assume the average construction employment change over three years per 100 people is about -0.164 for lower-education foreign-born workers and about -0.100 for U.S.-born workers. The analogous estimates from East et al. 2023 are, respectively, -0.387 and -0.300.

12. Table 6 of Ali, Brown, and Herbst 2024 reports child care employment-to-population ratio changes for females ages 20–55 of -0.0025, -0.0012, -0.0011, and -0.0014 for, respectively, the low-education foreign-born, high-education foreign-born, low-education U.S.-born, and high-education U.S.-born population. From the basic monthly Current Population Survey, I calculate the population levels for these groups during 2005–2007 to obtain foreign-born employment reductions of 17,700 and U.S.-born employment reductions of 75,140. Dividing these by the 454,000 deportations reported in East et al. 2023 implies about -0.04 foreign-born and -0.17 U.S.-born employment reductions per deportation.

13. Again, this is mechanically the same as allocating the national number of additional deportations by shares of noncitizen construction employment and multiplying these new state-level deportations by the same national employment reductions of 0.52 foreign-born construction jobs and 0.32 U.S.-born construction jobs per deportation.

14. The top left panel of Figure 11 of Howard, Wang, and Zhang 2024 shows a marginally statistically significant increase in construction wages after two years. The bottom two panels show that relative to wages in all industries, the wages of lower-educated foreign-born construction workers may have stayed flat, whereas the wages of U.S.-born construction workers may have increased.

15. To the extent that reduced or increased immigration causes some negative labor market effects, Costa et al. 2024 argue that policymakers can keep unemployment low by ensuring tight labor markets with stimulative fiscal and monetary policies.

References

Ali, Umair, Jessica H. Brown, and Chris M. Herbst. 2024. “Secure Communities as Immigration Enforcement: How Secure Is the Child Care Market?” Journal of Public Economics 233 (May).

Alsan, Marcella, and Crystal S. Yang. 2024. “Fear and the Safety Net: Evidence from Secure Communities.” Review of Economics and Statistics 106, no. 6: 1427–1441.

American Immigration Council. 2024. Mass Deportation: Devastating Costs to America, Its Budget and Economy, Special Report, October 2, 2024.

Azoulay, Pierre, Benjamin F. Jones, J. Daniel Kim, and Javier Miranda. 2022. “Immigration and Entrepreneurship in the United States.” American Economic Review: Insights 4, no. 1 (March 2022): 71–88.

Bureau of Economic Analysis (BEA). 2025. National Income and Product Accounts. Accessed June 1, 2025.

Chassamboulli, Andri, and Giovanni Peri. 2015. “The Labor Market Effects of Reducing the Number of Illegal Immigrants.” Review of Economic Dynamics 18, no. 4 (October 2015): 792–821.

Congressional Budget Office. 2025. Data Supplement to The Long-Term Budget Outlook: 2025 to 2055. Accessed June 23, 2023.

Clemens, Michael A., Ethan G. Lewis, and Hannah M. Postel. 2018. “Immigration Restrictions as Active Labor Market Policy: Evidence from the Mexican Bracero Exclusion.” American Economic Review 108, no. 6 (June 2018): 1468–1487.

Costa, Daniel. 2025. “House Republican Budget Bill Gives Trump $185 Billion to Carry Out His Mass Deportation Agenda—While Doing Nothing for Workers: Immigration Enforcement Would Have 80 Times More Funding Than Labor Standards Enforcement.” Working Economics Blog (Economic Policy Institute), June 5, 2025.

Costa, Daniel, Josh Bivens, Ben Zipperer, and Monique Morrissey. 2024. The U.S. Benefits from Immigration but Policy Reforms Needed to Maximize Gains. Economic Policy Institute, October 4, 2024.

Department of Homeland Security (DHS). 2022. 2022 Yearbook of Immigration Statistics. Office of Homeland Security Statistics. Accessed May 29, 2025.

Department of Homeland Security (DHS). 2025a. Immigration Enforcement and Legal Processes Monthly Tables. Office of Homeland Security Statistics. Accessed May 29, 2025.

Department of Homeland Security (DHS). 2025b. U.S. Immigration and Customs Enforcement Budget Overview, Fiscal Year 2026 Congressional Justification. Accessed May 29, 2025.

East, Chloe N., Annie L. Hines, Philip Luck, Hani Mansour, and Andrea Velásquez. 2023. “The Labor Market Effects of Immigration Enforcement.” Journal of Labor Economics 41, no. 4: 957–996.

East, Chloe N., and Andrea Velásquez. 2024. “Unintended Consequences of Immigration Enforcement: Household Services and High‐Educated Mothers’ Work.” Journal of Human Resources 59, no. 5: 1458–1502.

Economic Policy Institute (EPI). 2025. Current Population Survey Extracts, Version 2025.6.11.

Fee, Kyle D. 2024. Using Worker Flows to Assess the Stability of the Early Childcare and Education Workforce, 2010–2022. Federal Reserve Bank of Cleveland, Community Development Report, January 19, 2024.

Grittner, Amanda, and Matthew S. Johnson. 2024. “Complaint-Driven Regulation and Working Conditions: Evidence from Immigration Enforcement.” Working Paper, March 29, 2024.

Howard, Troup, Mengqi Wang, and Dayin Zhang. 2024. “Cracking Down, Pricing Up: Housing Supply in the Wake of Mass Deportation.” Working Paper, October 2024.

Kallick, David Dyssegaard. 2015. Bringing Vitality to Main Street: How Immigrant Small Businesses Help Local Economies Grow, Fiscal Policy Institute and Americas Society/Council of The Americas, January 2015.

Lee, Jongkwan, Giovanni Peri, and Vasil Yasenov. 2022. “The Labor Market Effects of Mexican Repatriations: Longitudinal Evidence from the 1930s.” Journal of Public Economics 205 (January 2022): 104558.

Lynch, Robert G., and Michael Ettlinger. 2024. “Literature Review on the Economic Consequences of the Deportation of Unauthorized Immigrants.” Working Paper, July 2024.

McKibbin, Warwick J., Megan Hogan, and Marcus Noland. 2024. “The International Economic Implications of a Second Trump Presidency.” Peterson Institute for International Economics Working Paper 24-20, September 2024.

National Academies of Sciences, Engineering, and Medicine (National Academies). 2017. The Economic and Fiscal Consequences of Immigration. Washington, D.C.: The National Academies Press.

Sacchetti, Maria, and Jacob Bogage. 2025. “‘One Million.’ The Private Goal Driving Trump’s Push for Mass Deportations.” Washington Post, April 12, 2025.

Waslin, Michele. 2011. The Secure Communities Program: Unanswered Questions and Continuing Concerns. American Immigration Council Immigration Policy Center, November 2011.

The White House. 2025. “The One Big Beautiful Bill Will Crack Down On Illegal Immigration” (press release). May 17, 2025.

How banning state regulation of AI harms workers

Samantha Sanders, Sara Steffens — Thu, 26 Jun 2025 16:00:24 +0000

This fact sheet is a joint publication, originally published by the Congressional Progressive Caucus Center on June 26, 2025.

The ban on state regulation of artificial intelligence (AI) contained in both the House and Senate versions of the Republican megabill is overly broad, dangerous to workers, and out of step with public interest. This provision – a ten-year blanket ban on state and local governments’ ability to protect their residents from the harms of AI – is a reckless giveaway to Big Tech that will have far-reaching consequences for economic fairness, worker power, and public trust.

Both the Senate and House versions of the provision use an extremely broad definition of AI—including automated decision-making systems – tying the hands of state lawmakers from taking any meaningful role in how AI technologies are being rapidly rolled out in many sectors of society. The Senate version ties the moratorium on regulating AI to federal funding for broadband internet infrastructure – a program on which all 50 states and territories rely to make critical progress to improve connectivity.

The provision is opposed by a broad, bipartisan coalition – including unions, civil rights groups, state attorneys general, members of Congress across the political spectrum, and the public, who understand it as a rash giveaway to big tech. Banning state regulation of AI gives even more power to a handful of billionaires, while reducing the power of working people and communities.

Congress can still act to remove this harmful provision and ensure that AI can expand in ways that are responsible, innovative, and grounded in public trust—while protecting the rights of workers, consumers, and communities.

Congress has a responsibility to develop and adopt federal standards that ensure new technologies lead to positive economic outcomes – and to ensure that workers have the power to control how AI and related digital tools are used in their workplaces, ideally through collective bargaining agreements.

However, in the absence of federal action, it is critical that states be permitted to step in and act – and those lessons can hopefully inform federal policymaking. All 50 states have been working to regulate uses of AI that harm communities and society. This ban would stop all of that progress in its tracks, blocking commonsense AI laws in development or already on the books.

Here are a few key ways this unprecedented ban on state action to protect workers and consumers could harm workers and erode public trust:

Make it easier for employers to discriminate

The right to equal opportunity at work is already under threat from the Trump administration’s attacks on federal anti-discrimination protections and enforcement. Unregulated AI systems could speed up and cement discrimination even further.

Major employers increasingly rely on predictive AI software and algorithmic analysis to choose who they interview, hire, promote, discipline, or dismiss. We know these untested tools for “automated decision making” can fuel discriminatory outcomes, such as a preference for resumes with white- and male-associated names.

With no federal guardrails in place, and with federal enforcement on anti-discrimination weakened, banning state action would allow discrimination to flourish unchecked. States must be able to step in to address algorithmic bias and enforce anti-discrimination protections so that everyone has a fair shot at a good job.

Make it easier for employers to drive down wages

With a low federal minimum wage, rampant misclassification of contract workers, and no guardrails on how employers use AI and algorithms to make decisions about pay, the race to the bottom already experienced by gig workers could become the norm in all industries.

Employers already use algorithms and automatic decision systems to dynamically determine the lowest possible pay for each task, location and individual, with little transparency for workers. If states are blocked from even investigating wage suppression by algorithm, these exploitative practices will spread across all industries.

Increase retaliation, union-busting, and surveillance

Automated surveillance systems and AI-powered monitoring can track everything from workers’ keystrokes and voices to their precise location in their workplace. These tools can be weaponized against workers who organize, speak up about unsafe conditions, or simply take too long in the bathroom. Workers already are vulnerable to unfair – and sometimes illegal – retaliatory discipline and firing. If workers don’t even know the extent to which they are being surveilled, they will struggle to exercise their legal rights or defend themselves from wrongful termination – especially the majority of workers who lack the protections of a collective bargaining agreement.

As one school bus driver told researchers from UC Berkeley Labor Center:

“The bus cameras are the worst— they were originally installed to protect the kids, but now three cameras are pointed directly at us and recording at all times, even when no kids are on the bus. We know now that they use this footage in personnel matters, they listen to us through the bus cameras, and that they use the cameras to read our text messages when we are parked and using our phones while the children are off the bus and we are on breaks from work.”

Preventing states from regulating this kind of surveillance will leave workers more vulnerable to unlawful retaliation and to employer wrongdoing, unsafe conditions, and unfair wages.

Worsen worker privacy

A decade of unregulated AI will allow the aggregation and sale of vast amounts of highly specific data on individual workers in ways that can never be truly erased. For instance: With the aid of AI, data collected from GPS systems and wearable technology could be used to identify an employee’s private medical conditions, even before the worker has the chance to invoke the protections of the ADA or FMLA. If this data is sold to other hiring managers or the open market without any regulations, that same individual will find it difficult to secure future employment.

Workers and consumers need transparency and tools to control how AI-powered systems use their personal data – not a decade-long ban on state oversight.

Steal creative work

Artists, writers, musicians, and performers are already seeing their work scraped and reused by AI systems without consent or compensation. The ban would make it more difficult for creative workers to protect their work, including their own images and voices. Those whose work is stolen without compensation to fuel large language models may have no recourse, even as big tech companies continue to profit.

Harm public safety and public services

In critical sectors like healthcare, education, and transportation, AI systems are already being used to override expert human judgment. The ban would restrict the ability of workers and their advocates to respond. For example, in healthcare, nurses are fighting to protect patients and provide the care they know is best – even when an algorithm advises otherwise. This is equally true in education, childcare, public safety and transportation – all fields with vulnerable lives and worker safety at risk.

A better alternative is possible

Corporations do not need a blank check and a deregulated landscape to succeed in creating and selling artificial intelligence, automated decision systems, and related technologies. The balance of power already tilts too far in favor of employers. Congress should remove this dangerous 10-year preemption of state action from the budget megabill, which already poses serious harm to low-income people in this country. Instead, policymakers should consider responsible AI policy frameworks through the normal legislative process, where these critical issues can be debated and assessed fairly.