Key takeaways:

• Affordability is not just about prices; it’s the outcome of a race between income growth and price inflation. When income growth is slower than price inflation, affordability worsens. When income growth is faster, affordability improves.
• Focusing just on prices is bad for understanding how the economy works and how it has performed in the recent past, and it leads to an overly restrictive policy menu for improving families’ affordability.
• Policy can more reliably address income growth for typical families. This growth has been stunted for decades by the rise of inequality. Closing this gap by ensuring more equitable distribution of future growth is the strongest tool we have for improving affordability.

Affordability has been the policy buzzword of recent years. Much of the affordability discourse—both among policymakers and the public—has focused near-exclusively on prices as the big affordability problem. But affordability is not a problem of high prices, instead it’s the outcome of a race between incomes and prices. And the reason typical families have faced an affordability crunch in recent decades is not because prices have grown exceptionally fast, it’s because incomes for the vast majority have grown too slowly. This income growth has been suppressed mostly by rising inequality that has put a growing wedge between overall economic growth and the income growth of typical families.

Getting the drivers of affordability right is important—it’s not just quibbling. If you only examine price growth and try to infer what has happened to affordability over periods of economic history, you’ll usually get the story wrong. And if policymakers only look at how to change the trajectory of prices while ignoring what they can do to change the trajectory of incomes, they will be far less effective in providing useful relief to U.S. families. There are far more ways to use policy to raise incomes in a targeted and effective way than there are to suppress price growth.

Below, we provide some more background on why analyses of affordability need to include incomes, why policymakers have much more scope to raise incomes in a useful way as opposed to pushing down prices, and why focusing just on prices can obscure whether affordability has improved or worsened.

Why do prices dominate today’s affordability debates?

In modern capitalist economies, prices rise essentially every year (though at quite different rates), but so do incomes. Determining what has happened to families’ ability to afford a decent and secure life requires looking at measures that take into account both sides of the affordability equation, such as real (inflation-adjusted) income growth. Nobody really disputes this. After all, Americans could buy a new car for $600 in the 1930s, but nobody thinks society was generally richer back then.

The narrow focus on prices in assessing one’s own economic struggles likely stems from several factors.

First, inflation was very fast in the early 2020s. Americans hadn’t experienced inflation rates that high in decades, and they didn’t like them, so prices remain front of mind for many.

Second, it is true that price changes can dominate what happens to real incomes over very short time periods (say a year or less). This recognition is why we can be so sure that the oil price shock inflicted by the U.S. bombing of Iran is going to be so damaging to U.S. families. The rise in oil prices so far this year has likely baked in at least a 1.5% increase in inflation over the next 6–12 months. In 2025, real wage growth for the large majority of workers was slower than 1.5% (which was the outcome of roughly 4% nominal wage growth minus 2.5% inflation). Given this, a sharp and unexpected 1.5% jump in prices will likely erase any prospective real wage gains for workers in 2026.

Finally, it has been noted that many Americans see wage gains as something they accomplished themselves through hard work, while prices are out of their immediate control. Inflation is hence seen as damage done to them and something they need relief from. But this is mostly wrong—policy choices impact wage growth at least as much as inflation, and the most effective policy relief for living standards will come through measures that raise wages, not restrain prices.

Policy can target incomes more effectively and precisely than prices

One person’s income is another person’s cost, which means prices are a bundle of different stakeholders’ incomes. The bill you pay at the grocery store must cover payments the store makes to its shareholders, the salary of the CEO and managers, the wages of cashiers, and the cost of buying food from producers. We don’t want all these incomes to be forced down. Given extreme levels of inequality in the U.S., we would likely be fine with lower CEO pay and payments to shareholders, but we would want wages of cashiers and many in the food production supply chain to rise. Efforts to simply clamp down on this price will have uncertain effects on incomes.

In the jargon of economists, focusing on prices is sector-based policy but to genuinely improve affordability we need factor-based policies, where factors of production like capital, rank-and-file workers, and corporate management can be specifically targeted by policies that aim to raise or restrain their incomes.

Fortunately, there are many good policy options for targeted affordability policy specifically toward low- and middle-income families. Incomes for these families—and for anybody without dynastic wealth—are dominated by wages and public benefits. We talk about each of these in turn below.

Boosting public benefits is affordability policy

Public benefits are entirely under policymakers’ control. If policymakers really cared about the affordability of groceries or health care or energy, they could boost benefits for food stamps, Medicaid, and the low-income heating energy assistance program. These programs currently deliver needed assistance to tens of millions of families to make life more affordable—and they do this with vanishingly small administrative costs, meaning they are highly efficient. Yet all of these programs are slated for steep cuts in the coming decade due to the Republican tax and spending megabill passed in 2025. This bill will inflict large damage to the most vulnerable families’ ability to afford decent and secure lives.

Further, Congress and the Trump administration chose to not extend the Biden administration’s more-generous subsidies for people to buy health insurance through the marketplace exchanges of the Affordable Care Act. The failure to extend these subsidies—even after a full federal government shutdown engineered by congressional Democrats aimed at prioritizing this issue—means that average out-of-pocket costs will double for those buying insurance in the exchanges.

Besides just reversing these cuts, making the U.S. welfare state more robust could also greatly boost the affordability of a decent life. Things like making health coverage more universal with lower out-of-pocket costs, reforming unemployment insurance to make it more protective, and providing all families with children a generous universal child allowance could dramatically improve affordability.

Policy can boost affordability through higher wages as well

The link between policy changes and wage growth is slightly less direct than for public benefits, but it remains very strong. Capitalist labor markets are inherently tilted toward employers and against workers. The only periods of history that have seen strong and equal rates of wage growth across the workforce have been periods where policy supported institutions that boosted workers’ leverage with employers.

The 30 years after World War II saw the creation of policies and institutions that successfully spread the gains from rising productivity equitably among workers up and down the wage distribution, with low- and middle-wage workers seeing growth rates as fast as high-wage workers. This equitable distribution of wage growth was a crucial way that income growth more broadly was kept equitable in this period.

Since 1979, however, these institutions have been steadily attacked and weakened with no new institutions being stood up to take their place in ensuring an equitable distribution of economic growth. The result has been that wages and incomes of typical families have lagged far behind average income and wage growth (or productivity). The wedge between income growth experienced by the vast majority of families and average growth is simply income being generated in the economy that is not helping typical families’ affordability struggles. Instead, it is income being funneled reliably away to the top.

There’s no reason that the institutions that equalized wage growth cannot be built back up and modernized.

The federal minimum wage is the most obvious policy institution for raising wages at the low end of the labor market. Raising the federal minimum wage from its current shamefully low $7.25 would directly boost affordability for tens of millions of workers. In the middle of the wage distribution, unions have proven to be the institution that has historically counteracted employer power and given typical workers increased leverage. However, unions are in a far weaker position today relative to their high points because of intentional policy choices—specifically because policymakers failed to act to curb employers’ growing hostility (and often their illegal activities) toward union organizing. If stronger policy boosted union density, unions would raise wages for both members and non-members alike.

Low- and middle-wage workers also benefit enormously from a determined effort to keep unemployment low for extended periods of time. In recent decades, policymakers have tolerated excess unemployment to keep inflation in check, but this is far too costly a strategy to keep potential inflation in check. Besides locking out millions of willing workers from job opportunities, long periods of excess unemployment were periods when real (inflation-adjusted) wage growth became literally stagnant.

Policymakers often seem skeptical of the effectiveness of these wage-boosting policies, arguing that the effects are too indirect and will take too long to provide benefits to workers. It’s true that efforts to boost unionization and sustain full employment will take some time to push up wages. But they will do this reliably. Further, many policies advanced in the name of reducing prices would also take a long time to come to fruition. For example, calls to tighten antitrust restrictions against corporate mergers and to break up established monopolies often have lots of merit. However, they are not policies that happen instantly and have purely predictable effects.

Focusing too hard on prices can obscure when affordability is actually improving

Finally, one key reason to broaden the affordability debate beyond prices is simply to make sure the public and policymakers can correctly identify periods of improvement or degradation of affordability. As an example of how focusing only on prices can lead to an incorrect diagnosis of affordability trends, take the example of two five-year stretches in recent economic history, both measured from a business cycle peak and going five years forward from there: In the years between 2007 and 2012, annual inflation averaged 1.8% and peaked at 5.5%, while between 2019 and 2024, inflation averaged 4.2% and peaked at 9%. Based on price growth alone, one would expect affordability to have eroded more rapidly in that second period, and indeed the popular narrative is that the early 2020s inflation was particularly destructive for affordability.

But between 2007 and 2012, the nation’s unemployment rate averaged 8.3%, while it averaged less than 5% between 2019 and 2024. After 2007, it took 93 months to re-attain the pre-recession unemployment rate, while it took just 29 months after the 2019 business cycle peak. In short, the labor market was far stronger in the second period.

And when it comes to real (inflation-adjusted) wage growth, the second period—largely because of its lower unemployment—saw far better outcomes than the first. In the 2019–2024 period, inflation-adjusted wages for low-wage workers (those at the 10th percentile) and the median worker rose by a cumulative 15.3% and 5.8%, respectively. In short, contrary to most conventional wisdom, affordability improved in this time. Between 2007 and 2012, real wages outright fell for both low-wage and median workers. Even with very slow inflation, affordability was demonstrably worse in that earlier period.

Figure A

More recently, inflation averaged slightly lower in 2025 (2.5%) than 2024 (2.9%). Yet for many workers—and particularly low-wage workers—2025 saw weaker (or even negative) real wage growth. This is largely due to some slight cooling in the labor market as unemployment rose from 4.0% to 4.4% over the course of 2025. Hence, even as inflation decelerated, the cooling labor market led to an even faster deceleration in nominal wages, which meant that affordability worsened for many workers.

Figure B

Reducing inequality is the key to improving affordability

Because many policymakers believe that affordability concerns are a new problem caused by inflation of recent years, they are now on a frenzied search for new and creative solutions to this price problem. But because the real affordability problem for U.S. families did not emerge in the past few years (remember, affordability was improving in the five years before 2025) and because the genuine long-run problem of affordability was about the inequality of income and wage growth, not excess inflation, most of these new and creative solutions just won’t hit the mark.

It’s understandable why many policymakers seem frustrated with being reminded of the long-diagnosed problem of inequality and the proven remedies—such as sustained full employment, higher wage standards like minimum wages, protecting workers’ fundamental rights to organize unions and bargain collectively, and a more robust welfare state.

Some, of course, just don’t believe in some of these solutions, while many who do would argue that these proven remedies are politically unrealistic in the current moment. But because the real affordability problem is an inequality problem that requires those at the top of the income and wealth scales having to accept less growth going forward (less than the stratospheric gains they’ve gotten used to, it should be said), any genuine solution is going to seem impossible in today’s political system that is dominated by the wealthiest families and corporations. Any policy—whether old and well-tested or new and creative—that actually aims to redistribute income, wealth, and power away from where it sits today will face a wall of opposition that must be politically overcome one way or the other. There’s no “one weird trick” where you can develop a policy creative and neat enough that it will somehow fool the rich and powerful about what its end result will be. And if the end result of the new and creative policy does not threaten the prerogatives of the rich, it’s not a real solution.

Today’s affordability concerns are indeed rooted in objective facts about the material circumstances of middle- and working-class families in the United States. Precisely because of this, they deserve more serious analysis and policy responses than they have been getting. This means focusing more on incomes than prices, and it means being clear-eyed that it has been the upward redistribution of income to the top—abetted by policy decisions—that is the drag on typical families’ affordability. Until solutions address that, they’re mostly just noise.

Originally held Thursday, April 9, 2026.

Webinar links, notes and discussion

Timestamped themes, discussion, and resources mentioned in the webinar

Listen on The State of Working America Podcast

If you are an academic, student, non-profit researcher or advocate, or a journalist, you may view and use the content of this webinar and its related materials without requesting any further permission.

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

If you are a commercial enterprise looking to this information or data in any product that will be sold or as part of services and data you provide to paying customers, request commercial use by contacting EPI.

Find out about upcoming webinars first! Subscribe to EPI newsletters.

The American Rescue Plan Act (ARPA) was enacted on March 11, 2021. Among other provisions, ARPA allocated $350 billion for State and Local Fiscal Recovery Funds (SLFRF). SLFRF was a recognition of the stark reality that the COVID-19 pandemic had wreaked havoc on state and local government finances (McNicholas, Bivens, and Shierholz 2020). SLFRF was also a reflection of lessons that policymakers learned from recent history. In the years following the Great Recession, inadequate fiscal support to state and local governments resulted in massive budget cuts, public-sector job losses, and reduced spending that dragged on the economy, delaying economic recovery by years (Shierholz and Bivens 2013). With the prospect of potentially devastating COVID-19-induced state and local budget shortfalls, Congress and the Biden administration made the decision to spend at the scale of the problem by making sure SLFRF was large enough to meet its recipients’ needs.

Of the $350 billion in fiscal recovery funds, $195.3 billion went to state governments, $65.1 billion to counties, $45.6 million to cities, $20 billion to tribal governments, $4.5 billion to territories, and $19.5 to small units of local government, mostly towns and villages. They could use the funds for five purposes: responding to the public health emergency caused by COVID-19; responding to the negative economic impacts of COVID-19; providing premium pay to “essential” workers; improving water, sewer, and broadband infrastructure; and replacing public-sector revenue lost by the economic downturn that accompanied COVID-19. Recipient governments had until December 31, 2024, to obligate those funds and until December 31, 2026, to spend them.

By any objective assessment, SLFRF was a transformative success. It averted a potential crisis. It empowered state and local leaders to address long-standing community needs. It helped millions of working families. It saved lives during the COVID-19 pandemic. The design and implementation of SLFRF offer many important lessons to future policymakers.

This report will highlight the smart design of SLFRF, which made it well positioned to address the needs of state and local governments in 2021 and beyond. The report will also note ways in which future policymakers could improve upon SLFRF’s design. The report will describe how SLFRF funds were deployed, showcasing the breadth and variety of uses to which they were put. State and local fiscal recovery funds were a vital part of the U.S. economic recovery post-2020. They provide a shining example of what government can achieve when it has adequate resources, and when the needs of communities and families are the main drivers of investment decisions.

SLFRF played a vital role in preventing a second Great Recession

The pandemic recession that began so suddenly in March 2020 was the biggest economic shock the country has seen since the Great Recession that started in 2008. Comparing the distinctly different policy responses to those two crises demonstrates how important SLFRF was to speeding the economic recovery and to preventing a second Great Recession.

First, SLFRF was vital in preserving and rebuilding the public-sector workforce. In the wake of the Great Recession, state and local governments faced devastating budget cuts that resulted in significant reductions in staffing and services. All faced fiscal crises because of sharp revenue declines caused by the Great Recession, but public services were further strained in many states by deliberate policy decisions, predominantly by Republican-controlled state governments, to cut taxes and slash public services (Cooper, Gable, and Austin 2012). State and local government employment peaked in July 2008, then fell for five straight years. It took a total of 11 years to reach July 2008 levels again (Cooper 2020). By contrast, the peak in state and local governments jobs before the pandemic was in February 2020. By October 2023—just three years and eight months later—state and local public sector employment had fully recovered to pre-pandemic levels.

In the first year following the passage of ARPA, there is evidence that the pace of a state’s SLFRF spending was positively correlated to the recovery of its public workforce:

Table 1

After that, the direct correlation between SLFRF spending and public-sector jobs faded, but that is hardly surprising, given all the other variables that impact job markets.

Second, this rapid recovery mirrored the recovery of the overall job market. The typical U.S. state needed 77 months after the start of the Great Recession for its job numbers to recover; it only took 29 months after the beginning of the COVID-19 pandemic for the same level of recovery. Of course, SLFRF was hardly the biggest factor in the overall economic recovery, but Cooper (2020) has shown that disinvestment in the public sector drags on growth in the private sector as well, and on economic growth overall. SLFRF supported conditions that made the private-sector economic recovery possible.

Third, SLFRF allowed states and localities to enact programs of social insurance and income support that directly responded to immediate community needs. In just the first two years of SLFRF’s operation alone, more than 4.5 million households received mortgage, rent, or utility assistance. Emergency programs offered housing to people who had been displaced by the pandemic and direct government assistance to food pantries and other programs that helped people facing food insecurity. These programs were valuable tools for helping working families in need.

Fourth, SLFRF has helped state and local governments and communities become more resilient against future downturns. Many states upgraded their unemployment insurance (UI) systems to make it easier to cope with an influx of claimants in the future. Some local governments created greater tenant protections and used recovery funds to give tenants facing eviction the right to free legal counsel. Several cities invested in pre-apprenticeship programs to help people in underserved communities gain access to high-quality infrastructure and climate jobs. These investments and others like them will help state and local governments to quickly distribute social insurance benefits when the next crisis hits and provide additional safety for working families put in jeopardy through job loss, illnesses, or natural disasters. (Kamper 2025).

SLFRF’s innovative program design meant funds could be used where they did the most good

The SLFRF program had two unusual characteristics that helped make it successful.

First, unlike previous iterations of state and local aid, SLFRF funds went directly to individual state and local governments. While payments to smaller cities were distributed first to states and then passed on to those cities, states were prohibited from imposing conditions on that distribution and could not hold back the payments; their role was purely administrative.

On previous occasions when federal money was allocated to local governments, it was much more common for the state government to hold federal aid on behalf of local governments. This was, for example, the mechanism behind the COVID-19-era financial assistance to school districts: the Elementary and Secondary Schools Emergency Relief Fund (ESSER, which had three iterations in 2020 and 2021, called ESSER I, ESSER II, and ESSER III respectively). A state’s department of education held ESSER funds and only parceled them out to school districts after the district had made a qualifying expenditure. The districts were not free to spend ESSER funds on their own. With SLFRF, however, recipients received funds before they needed to make expenditures and had complete control over how to use them.

This leads to a second important characteristic of SLFRF: Recipients were given broad latitude in how to use their funds. Under the legislation and the rules put out by the U.S. Department of the Treasury, SLFRF could be used for:

1. responding to the public health emergency caused by COVID-19
2. responding to the negative economic impacts of COVID-19
3. providing premium pay to “essential” workers
4. improving water, sewer, and broadband infrastructure
5. replacing public-sector revenue lost by the economic downturn that accompanied COVID-19

In 2023, the eligible uses for local governments were broadened to include government-built (or renovated) housing, surface transportation projects, and natural disaster relief, though in the end only a small share of recovery funds was used for those purposes.

Treasury rules also made the process simpler for smaller local governments by allowing up to $10 million to be used as public-sector revenue replacement without having to account for specific losses of funding—the SLFRF equivalent of the standard deduction on one’s taxes. Those rules also made clear that “negative economic impacts” could include existing inequities that predated the pandemic, such as long-standing racial employment and wage gaps (Economic Policy Institute 2025).

The combination of these two characteristics—state and local governments had the money within their control before making spending decisions, and great latitude in how to use it—meant that recipients could tailor the focus and pace of SLFRF spending to meet particular local needs. Given the extremely fluid state of the pandemic and the economy when ARPA was passed, this was the right decision to meet the pressing needs of the COVID-19 crisis. Overly prescriptive rules or additional bureaucratic hurdles to accessing and disbursing funds would have made it much harder for state and local recipients to respond rapidly to their specific needs.1

Lessons to apply for future policy design

Despite the great freedom given to recipients to use SLFRF in ways that best met their needs, of the roughly 31,000 local government recipients, almost 600 local government recipients did not report using their fiscal recovery funds at all and a further 600 reported using less than 99%. Another 220 local governments failed to file a single report on their use of fiscal recovery funds, and 1,089 more have been delinquent in filing for at least a year.

At least part of the explanation is that while ARPA guidance allowed for fiscal recovery funds to be used for myriad reasons, recipients (especially smaller local governments) with little experience in receiving money directly from the federal government often struggled to understand Treasury rules on allowed uses of funds. Unlike state governments with experienced personnel deeply versed in Treasury’s complex rules and how to navigate them, many local governments had no such in-house expertise. Advocacy organizations reported, again and again, that even in 2024, as the deadline to obligate ARPA funds was approaching, many local policymakers were still raising questions about how funds could be used and what was allowed (Rochford, Bauer, and Wallace 2024).

Relatedly, Treasury officials who talked with EPI noted that many of the smallest local governments did not have a website or internal email system. Because all SLFRF reporting was supposed to be done electronically, some of these recipients struggled to properly report their expenditures. Sometimes the departure of a single municipal official created significant problems because that person was the only one who knew the electronic passwords.

An abundance of reports from across the country make clear recipients struggled to choose from among many appealing options, creating a kind of paralysis of choice. This is completely understandable; the needs communities were facing at this time were myriad and diverse, and prior to SLFRF, most local government officials had likely never had access to such flexible resources before then.

These challenges were exacerbated because the Treasury Department made a conscious decision not to offer specific technical assistance regarding recipient governments’ possible uses of fiscal recovery funds. When local government officials reached out to Treasury to seek guidance on whether a particular idea was within the scope of the law, Treasury rarely offered definitive answers. This was understandable given that more than 31,000 governmental units received their own fiscal recovery funds; Treasury could not possibly handle detailed queries from more than a fraction of them. What this meant, though, is that many opportunities to use fiscal recovery funds in innovative and imaginative ways were missed. Many local governments chose caution over ambition, out of fear that particular uses of the funds would not be permitted and the funds rescinded.

To prevent a similar situation in the future, policy designers might do well to study Colorado’s Regional Grant Navigator program. Colorado chose 13 community and nonprofit organizations across the state to help local governments find ways to best access funds from the 2021 Infrastructure, Investment and Jobs Act and the 2022 Inflation Reduction Act. These navigators helped local governments understand the complex regulations around the laws, helped them design proposals to apply for funding, and offered advice on which programs might be best suited to the needs of those communities (Colorado n.d.). A similar model might allow local governments to get unbiased and timely assistance from organizations committed to helping them make the most of their funds.

A final challenge of the SLFRF policy design was the lack of clear definition of what “obligating” the funds meant. As advocates, policymakers, and others reported throughout 2022, 2023, and 2024, many local governments understood “obligation” to mean something similar to “budgeting” or “allocating”—making a formal decision as to how to use the funds (Kamper 2024). Recipients unfamiliar with the language used by Treasury could and did make that mistake. It was not until May of 2024 that Treasury explicitly stated in a webinar that “obligating” funds is not the same thing as budgeting (Treasury 2024). “Obligation” required not just a budgetary decision, but concrete steps to implement the decision, such as signing a contract with a vendor or an interagency agreement to send the funds to a particular department. Future fiscal recovery efforts should be more conscious of the need to clearly define terms, especially when plain-language definitions may not match Treasury’s technical definition.

How were fiscal recovery funds used?

General spending trends

The primary use of fiscal recovery funds—approximately 50% of state allocations and 60% of local government allocations—was revenue replacement, (replacing state and local funds that were lost because the economic shock of COVID-19 reduced tax and fee revenues). Revenue replacement had not been an allowed use of previous iterations of COVID-19 fiscal relief funds. Most notably the CARES Act, the first COVID-19 relief measure passed in 2020, did not allow use of Coronavirus Relief Funds for revenue replacement.

State and local governments face considerable constraints on their ability to raise revenues. Measures like Colorado’s Taxpayer Bill of Rights and California’s Proposition 13 often prohibit states from raising taxes or require legislative supermajorities to do so (Jefferson 2025). Local governments face even more constraints, with few policy levers available to raise revenues. As such, any shock to state and local government revenues can take a long time to reverse, a lesson we learned in the aftermath of the Great Recession. By allowing revenue replacement, SLFRF made it much easier for state and local governments to maintain adequate levels of funding, even as the pandemic recession lowered income from taxes. Revenue replacement was an important innovation in ARPA that should be replicated in the future.

Although the interim rules for ARPA put out by Treasury soon after the law was enacted required complex accounting of lost revenue, the final Treasury rule made the process much easier. For amounts less than $10 million, recipients did not need to calculate lost revenue. They could simply designate funds as revenue replacement and use them as needed. The appeal of this rule to local governments is evident in data summarizing subsequent uses of SLFRF; the smaller a recipient government, the more likely they were to use their fiscal recovery funds for revenue replacement.

Table 2

After revenue replacement, the next most popular use of SLFRF was addressing negative economic impacts of the pandemic. Once again, the flexibility given to recipients under this category was almost certainly a key factor encouraging use of funds for such purposes.

Table 3

Infrastructure was the third-largest use of fiscal recovery funds, and here there is a notable regional variation—state and local governments in the South allocated a far greater share of their funds to infrastructure than those in the rest of the country. In particular, 82% of all state funds obligated for broadband were in Southern states (not shown in Figure A).

Figure A

Not only is water and sewer infrastructure essential for people’s health, these investments are vital to a well-functioning economy. As EPI has extensively documented in its Rooted in Racism series, Southern states have long underinvested in in basic physical infrastructure (Childers 2023–2025). These spending choices likely reflect, at least in part, a need to address the long-standing underinvestment in the region—underinvestment driven by Southern lawmakers’ antipathy toward raising adequate revenue.

Aside from infrastructure spending in the South, there are no clear regional trends in how fiscal recovery funds were used. This is not surprising, given the flexibility of the funding (a feature EPI has long supported) (Bivens 2020). When ARPA was enacted in early 2021, there was simply no way for the federal government, or state and local governments, to know what their needs would be. ARPA’s flexibility was the right decision. The ability of recipient governments to immediately fill unanticipated budget holes via revenue replacement meant hundreds of thousands of state and local jobs were preserved, vital public programs were maintained, and a deeper economic crisis averted. The most notable success of ARPA SLFRF lies in what did not happen: a collapse in basic public services, massive long-term unemployment, and an extended economic depression.

Innovative SLFRF investments supported working families

In all, SLFRF funded more than 159,000 different projects across the country. Some were gigantic, like a $787 million program in New Jersey to provide rental assistance to low- and moderate-income tenants, and some were very small, like the $28 that St. Clair County, Michigan, provided to help renovate the Port Huron Township Museum.

There are many examples of state and local governments using fiscal recovery funds to make transformative investments to build an economy that supports working families. Several types of uses deserve special attention: fighting the COVID-19 pandemic, investing in public health, and addressing problems with food access and nutrition.

First, ARPA SLFRF went a long way to address the health emergency the country faced in 2021. States, cities, and counties were on the front lines of keeping people safe, providing access to new vaccines once they became available, and saving lives throughout the COVID-19 pandemic.

Over $1.8 billion in SLFRF was used to test, trace, and vaccinate people against COVID-19. Much of this money was used to deal with the practical and logistical challenges of testing and vaccination. Cities and counties, especially, bought personal protective equipment for government employees, especially first responders. Scores of governments purchased testing kits and lab equipment and worked to engage the public to encourage vaccination and tracing outbreaks. For example, Milan, Illinois, rented a meeting hall in town for $43,200 to host their vaccine clinic. Jefferson County, Missouri, hired a nurse for every public school district to oversee a contact-tracing program to track COVID-19’s progress through schools. Monroe County, Indiana, was one of many governments that instituted wastewater monitoring to check for COVID-19 surges While any individual expenditure may seem minor, together these measures did much to reduce COVID-19 infections and deaths.

Second, SLFRF allowed recipient governments to make long-term upgrades to infrastructure that both mitigated COVID-19 threats and made public spaces permanently safer, healthier, and more accessible. Almost $4.3 billion was obligated to upgrade the air quality and safety of public and private facilities. At least 550 projects upgraded HVAC systems in schools, nursing homes, public buildings, and correctional facilities. Governments invested in digital communications tools to reduce the need for in-person meetings. Typical examples include Peoria, Arizona, which allocated $124,996 to install touchless drinking fountains in public buildings, and Stafford County, Virginia, which spent $115,255 to add a glass partition to the entrance of the Commissioner of Revenue’s office so that the administrative staff could be protected from visitors’ virus transmission.

The freedom given to local governments to innovate was particularly evident in the way multiple localities sought to address problems related to food access and nutrition—an issue that has received tremendous public attention resulting from New York City Mayor Zohran Mamdani’s plan to establish municipally operated grocery stores. While one commentator claimed such a project would resemble “the old Soviet Union” (McArdle 2025), the fact is that many SLFRF recipients used public funds to increase access to food for low-income communities, including by opening their own stores.

For example:

• Sioux Falls, South Dakota, set up a mobile grocery market that would operate in underserved parts of the city.
• The small town of Cutler, Illinois, set up a Community Commissary to make it easier to buy food without having to travel a long way.
• Branson, Colorado (population 74 in the 2010 census), constructed a community greenhouse to grow and sell fresh fruits and vegetables for the town and school.
• Charleston, West Virginia, opened a community grocery store that would provide access to fresh groceries for 14,000 residents, and the city of Austin, Texas, did something similar.

There were, in addition, scores of grants to food pantries and other nonprofits that help people find the food they need. The proposal for New York City fits well with how these communities used SLFRF to address food access.

Above are just a handful of the tens of thousands of useful projects made possible by fiscal recovery funds. Some uses were more effective than others, however. For example, although modernizing state unemployment insurance systems was a useful endeavor (see above), more than $22 billion was also spent replenishing state unemployment insurance trust funds, which was unnecessary. UI trust funds hold UI taxes paid by businesses, to make sure funds are available to pay UI claims during spikes in unemployment. While those funds had, indeed, been depleted by the pandemic recession, state UI trust funds are designed to be self-correcting.2 They have automatic mechanisms to raise employer payroll taxes when the trust fund has been drawn down, to rebuild the funds and be prepared for future downturns. It was wholly unnecessary to use fiscal recovery funds to refill trust funds that would have returned to full strength on their own. Spending SLFRF to refill trust funds was a missed opportunity to support economic growth and strengthened public services (Banerjee, Martinez Hickey, and Sawo 2021). Future fiscal recovery projects should not make refilling UI trust funds an allowed use, though they should continue to support modernization of and upgrades to UI systems.

SLFRF accomplished its goals without driving inflation

Finally, it is worth noting that, despite politically motivated claims to the contrary, there is little evidence that SLFRF, or indeed the entire $1.9 trillion American Rescue Plan, was a significant contributor to inflation. As Bivens, Banerjee, and Dzholos (2022) show, the rise in inflation starting in 2022 was a global phenomenon, one that impacted countries, regardless of whether they provided fiscal relief to their economies during COVID-19. Nor was inflation correlated with the rapid decrease in unemployment the U.S. saw, thanks in part to ARPA. Rather, inflation was primarily driven by the dramatic supply shocks to various sectors of the economy caused by COVID-19, and then exacerbated by the Russian invasion of Ukraine in early 2022. Given the scale of the crisis policymakers were confronted with in early 2021, they were right to spend at the scale of the problem, and critiques blaming that spending for inflation are not backed up by the data. Moreover, policy measures that prioritized lowering inflation would have led to either lower employment or lower real wage growth, as there was no policy option that would have lowered inflation, increased wage gains, and supported the strong job growth of 2021–2024 (Bivens 2024).

Conclusion

ARPA’s State and Local Fiscal Recovery Fund was a great success. By spending at the scale of the problem, the federal government aided the economic recovery, supported the maintenance of public services, and gave myriad governments the chance to make innovative choices that have improved the well-being of their communities. A smaller SLFRF would have slowed our economic recovery and made governments more cautious about enacting bold policies to protect working families.

By giving recipient governments so much flexibility in using the funds, the Biden administration allowed every state, county, city, territory, and tribal government to fashion the response most appropriate to their particular needs. When faced with a crisis that had so much unpredictability, this was the right decision.

We don’t know when the next economic downturn, global pandemic, or climate disaster will hit. Whenever it does, federal policymakers should seek to emulate the model set by ARPA.

Notes

1. The devastating Flint, Michigan, water crisis of the 2010s is a prime example of a situation in which too many bureaucratic hurdles worsened a disaster. Flint was facing a serious fiscal crisis and therefore lacked the internal capacity to apply for federal funding (which they would have received) that might have prevented lead contamination of the water supply. See GAO 2015 for more details.

2. At least they should be, provided policymakers have set adequate UI tax base rates. See Perez 2025 for more information.

References

Banerjee, Asha, Sebastian Martinez Hickey, and Marokey Sawo. 2021. “States Are Choosing Employers over Workers by Using COVID Relief Funds to Pay Off Unemployment Insurance Debt: Policymakers Shouldn’t Be Afraid to Increase Taxes on Employers to Improve Unemployment Insurance.” Working Economics Blog (Economic Policy Institute), November 19, 2021.

Bivens, Josh. 2020. “Getting Serious About the Economic Response to COVID-19.” Working Economics Blog (Economic Policy Institute), March 9, 2020.

Bivens, Josh. 2024. “The Post-Pandemic Recovery Is an Economic Policy Success Story: Policymakers Took the Best Way Through a Rocky Path.” Working Economics Blog (Economic Policy Institute), October 1, 2024.

Bivens, Josh, Asha Banerjee, and Mariia Dzholos. 2022. “Rising Inflation Is a Global Problem: U.S. Policy Choices Are Not to Blame.” Working Economics Blog (Economic Policy Institute), August 4, 2022.

Callaghan, Peter. 2021. “The Minnesota Legislature Approved $250 Million for Pandemic Worker Bonuses. Should the State Give Away More Than That?” Minnpost, August 12, 2021.

Callaghan, Peter. 2022. “How the Legislature’s Deal on Pandemic Worker Bonuses and Unemployment Insurance Got Done.” Minnpost, May 4, 2022.

Childers, Chandra. 2023–2025. Rooted in Racism and Economic Exploitation (report series). Economic Policy Institute, October 2023–June 2025.

Colorado, State of. n.d. “Regional Grant Navigators” (web page). Accessed December 3, 2025.

Cooper, David. 2020. “Without Federal Aid, Many State and Local Governments Could Make the Same Budget Cuts That Hampered the Last Economic Recovery.” Working Economics Blog (Economic Policy Institute), May 27, 2020.

Cooper, David, Mary Gable, and Algernon Austin. 2012. The Public-Sector Jobs Crisis: Women and African Americans Hit Hardest by Job Losses in State and Local Governments. Economic Policy Institute, May 2012.

Economic Policy Institute. 2025. Racial and Ethnic Disparities in the United States: An Interactive Chartbook. Economic Policy Institute. October 2025.

Jefferson, Rita. 2025. Anti-Tax Revolts Backfire: What We’ve Learned from 50 Years of Property Tax Limits. Institute on Taxation and Economic Policy, July 2025.

Kamper, Dave. 2025. “Some States and Localities Will Be Better Prepared to Fight a Possible Recession Because of How They Used ARPA Fiscal Recovery Funds.” Working Economics Blog (Economic Policy Institute), April 30, 2025.

Kamper, Dave, and Emma Cohn. 2024. “Time Is Running out for State and Local Governments to Obligate American Rescue Plan Funds.” Working Economics Blog (Economic Policy Institute), October 17, 2024.

McArdle, Megan. 2025. “Zohran Mamdani Has a Seriously Bad Idea—for Grocery Stores.” Washington Post, July 1, 2025.

McNicholas, Celine, Josh Bivens, and Heidi Shierholz. 2020. “The Next Coronavirus Relief Package Should Provide Aid to State and Local Governments, Protect Employed and Unemployed Workers, and Invest in Our Democracy.” Working Economics Blog (Economic Policy Institute), April 27, 2020.

Perez, Daniel. 2025. Holding the Line: Unemployment Insurance. Economic Policy Institute, September 29, 2025.

Rochford, Patrick, Julia Bauer, and Michael Wallace. 2024. “Obligate It or Lose It! Preparing for the Upcoming ARPA SLFRF Obligation Deadline.” National League of Cities, October 1, 2024.

Shierholz, Heidi, and Josh Bivens. 2013. “Four Years into Recovery, Austerity’s Toll Is at Least 3 Million Jobs.” Working Economics Blog (Economic Policy Institute), July 3, 2013.

U.S. Department of the Treasury (Treasury). 2024. “State and Local Fiscal Recovery Funds: New Obligation FAQs Webinar” (web page). Accessed December 3, 2025.

U.S. Department of the Treasury (Treasury). 2025. “Public Data: State and Local Fiscal Recovery Funds” (web page). Accessed December 11, 2025.

U.S. Government Accountability Office (GAO). 2015. Municipalities in Fiscal Crisis: Federal Agencies Monitored Grants and Assisted Grantees, but More Could Be Done to Share Lessons Learned. Publication number 15-222, March 2015.

Wakeley, Dev. 2021. “Alabama Is Making a Costly Mistake on COVID-19 Recovery Funds. Here’s a Better Path Forward.” Working Economics Blog (Economic Policy Institute), November 8, 2021.

AI-related spending is providing much of the growth in the U.S. economy today. Business investments in structures and equipment (capex) that are driven by AI firms have accelerated noticeably in the past year. How much of this investment consists of imports rather than U.S.-based production is an open and important question. Even more important is the wealth effect on consumption from the AI stock boom, which seems to have firmly entered bubble territory. Combined, the capex spending and the consumption spending spurred by the stock market bubble are adding over a percentage point to GDP growth.

Worse, both types of spending seem fragile as medium-term sources of growth. The stock market bubble could deflate at any time, and when it does, it will almost certainly pull down much of the capex spending as well. After all, the entire reason for the frenzied capex build-out is the expectation of future profits. If these expectations radically change, the capex spending will evaporate.

If AI spending growth slows and the economy falls into a recession, policymakers should follow the typical recession-fighting playbook and use monetary and fiscal policy to boost the demand that was erased. The Federal Reserve should cut interest rates, and Congress and the president should direct fiscal aid to struggling families.

I then point to a couple of long-run observations about AI and its effect on labor markets, mostly echoing our arguments made in this report. One key finding: Despite widespread concern that AI will be strongly capital-biased, the profit share in the non-financial corporate sector has actually declined markedly since 2022.

For those interested, the PowerPoint and notes from the briefing are below.

PowerPoint presentation

Briefing notes

President Donald Trump has said some strikingly out-of-touch things about affordability: that it’s a “hoax,” he’s “solved it” and he’s “won affordability.” In his State of the Union address, he even said “prices are plummeting downward.” U.S. families know this is nonsense. But to see how much Trump’s policies will erode affordability in the coming years, you must understand that affordability isn’t just about prices. 

Affordability is the outcome of a race between incomes and prices. And for typical families, the Trump agenda is near-guaranteed to harm their incomes far more than it can possibly reduce their prices. 

Even judged by the movement of prices alone, Trump’s record on affordability is poor. Inflation fell from 8.0% to 3.0% in the final two years of the Biden administration. This rapid downward movement slowed to a crawl in the first year of Trump’s second term, with inflation falling from 3.0% to just over 2.6%.

There are clear policy reasons why progress in reducing inflation has slowed. Electricity prices have surged as the Trump administration has ended subsidies for renewable generation passed during the Biden administration. The Trump tax cuts passed in the president’s first term were part of a law that gouged loopholes in the tax code, including inviting pharmaceutical companies to offshore their production and import back into the United States. Last year the Trump administration put tariffs on these offshored pharmaceuticals, pushing up their costs. When the administration failed to extend Obamacare subsidies for people buying health insurance through the exchanges, healthier enrollees who could afford to began opting out, driving up prices for everybody left in the Affordable Care Act marketplace.  

And these are not the only ways that Trump administration policies have intensified affordability issues for ordinary Americans.

Read the full piece here. 

Key takeaways

The Trump administration’s unwise policy agenda has the potential to do great damage to U.S. families—and this is true even if it does not lead to recession or spiking inflation in the near term. While this agenda has heightened the risk of recession in coming years, the greatest future damage will come from slowing growth in the economy’s supply side and raising inequality. Trump’s economic policies will cause incomes and wages for typical families to grow more slowly, and this will lead to a less affordable life for many.  

How will Trump administration policies harm income growth for typical families? 

• The Trump administration inherited a fundamentally strong economy from the Biden administration. Yet the Trump administration’s policy agenda has raised the risk of a near-term recession by slowing growth in spending by households, businesses, and governments (aggregate demand).  

• • Federal workforce cuts, deportations and a slowdown in immigration, and chaos in trade policy and the administration’s approach to the Federal Reserve have all weighed on demand growth. 

• • The deportation agenda and cutbacks to the federal workforce will deeply damage the economy’s supply side as well. Further, deficit-financed tax cuts will also put headwinds in front of growth in the economy’s supply side in coming years. These growth reductions will be small in any given year but will accumulate quickly and lead to future incomes being significantly lower than they would have been under a different policy regime.  

• Finally, the 2025 Republican-led tax cuts favor the rich, while the spending cuts included in the same Republican megabill will sharply lower incomes for the bottom half of U.S. households (ranked by income) in coming years. This combination will lead to a very large spike in inequality.  

• • The Trump administration’s assaults on typical workers’ bargaining power and leverage, and its support for corporations with significant market power, will increase pre-tax inequality.  

Policy choices that fostered excess unemployment, slow growth of the economy’s supply side, and rising inequality have all contributed to making recent decades extremely difficult for typical families. The policies of the Trump administration double down on the worst policy decisions of this period and will make typical families reliably poorer in the future, even if an outright recession or spiking inflation does not happen.  

In the first months of the second Trump administration, the question that popped up frequently about its economic policy agenda was, “Will it cause a recession?” After a year and no clear signs of a recession (at least not yet), many looking to formulate an organized critique of the Trump agenda argue that it is making affordability for American families worse.

Both the concerns of heightened recession risks and deteriorating affordability are valid. Trump policies really are making a recession more likely and even if a recession does not occur, these policies will harm typical families’ ability to afford what they need. This affordability crunch will happen for two reasons: Trump policies will hamstring the economy’s ability to supply goods and services, and these policies aim to increase inequality by transferring income from the bottom and middle toward the top. Sometimes this affordability crunch will manifest as higher prices or faster inflation, but it is more likely to appear as slower wage growth and the rollback of public supports for households. But its root is always and everywhere poor economic choices, including prioritizing the interests of the rich and corporations over the concerns of typical American families.

This report provides an explanation and overview of how Trump policies will impact overall U.S. economic performance and the living standards and economic security of typical families.

• In the short run, Trump policies raise the risk of recession.
  • The U.S. economy might avoid a recession over the next year, but the Trump agenda has made a recession far more likely than it would have been without these policy choices.
    • The short-run danger from Trump policies stems from the chaotic implementation of tariff policies, the administration’s cuts to social spending in the 2025 Republican budget megabill, their rapid and random downsizing of the federal workforce, and the chilling effects their mass deportation aspirations have on spending.
• In the long run, the Trump policy agenda will significantly reduce the U.S. economy’s ability to supply goods and services without high and rising inflation.
  • The administration’s deportation agenda is slowing the size of the future U.S. labor force and has maybe even shrunk it.
  • Trump has backed mostly deficit-financed tax cuts for the rich, which will slow the size of the future U.S. capital stock.
  • His administration is attacking key federal agencies and has shown a lack of strategy in tariff policies, which are slowing the size of the future U.S. technology stock.
• In both the short and the long run, the Trump policy agenda is guaranteed to cause greater inequality.
  • In the short run, the huge tax cuts tilted mostly toward the rich and the spending cuts falling mostly on the bottom 40% will lead to an enormous rise in inequality.
  • A possible recession will damage the labor market and likely lead to rising inequality over any subsequent recovery as unemployment remains elevated.
  • Further, the Trump administration’s attacks on the leverage and bargaining power of typical workers and the administration’s toleration of monopolization and abusive financial practices will see income in the business sector reliably funneled away from typical workers and toward the already-rich owners and managers of large companies.
  • The Trump administration has hamstrung or downsized the key functions of the federal civilian workforce that work to level playing fields between the rich and corporations on one hand and typical workers and consumers on the other.
• Finally, many of the Trump administration’s policy choices will inflict significant damage on U.S. families that is not reflected in contemporaneous measures of GDP or income. Just because this damage is not reflected in real-time GDP or income data does not mean it is unimportant or cannot be measured well.
  • For example, regulations enforced by the federal government lead to greater air and water quality, and voluminous research indicates these save lives and many Americans highly value them. If the attack on the federal workforce and the Trump administration’s generally anti-regulatory stance lead to rollbacks in air and water quality, people will suffer, even as most of this suffering is not well captured in GDP.

In what follows, we provide the economic basis for these conclusions, focusing on Trump policy effects on aggregate demand, potential output (supply), and income distribution and how these drive real-world outcomes for typical families. Families will feel the bad outcomes from all three dimensions of macroeconomic performance as a deterioration in affordability.

Three key dimensions of macroeconomic performance: Demand, supply, and distribution

A quick overview of some important macroeconomic concepts can help organize thoughts about how the Trump policy agenda will tangibly affect U.S. families. The most important tasks policymakers must get right to offer typical families’ economic security are as follows: managing aggregate demand, fostering potential output (supply) growth, and ensuring equitable distribution of income.

Managing aggregate demand just means making sure unemployment and inflation stay low most of the time and are quickly returned to low levels when shocks push them higher for some stretch of time. The key to successful aggregate demand management is ensuring that spending by households, governments, and businesses is high enough to fully employ all resources in the economy—especially labor, but not so high as to generate ongoing inflation. This means ensuring that aggregate demand matches potential output.

Fostering growth in potential output (supply) involves making sure the economy’s productive capacity grows rapidly over the long run. Key elements include fostering growth in the labor force and productivity (a measure of how much output and income is generated in an average hour of work in the economy). Growth in productivity depends on the educational attainment and quality of the labor force, the size of the capital stock that workers can use to aid production, and the state of technology in the economy.

Ensuring an equitable distribution of growth means making sure the overall income growth generated in the economy is shared at least proportionally throughout the income distribution. Even better would be growth biased more toward households in the bottom half of the income distribution. This would help reverse some of the large increases in inequality that occurred over the past few generations of economic life in the U.S. Fostering an equitable distribution of growth matters for typical families for an obvious reason: If average living standards rise rapidly, but living standards for the large majority lag far behind as households at the very top see extreme above-average gains, it is hard to declare this an economic success for broad-based economic security. Without an equitable distribution of growth, too many people would be unable to afford daily life.

Trump policies will drag on aggregate demand and raise recession risks

Recessions happen and unemployment rises when spending by households, businesses, and governments (demand) lags behind potential output (supply). Because supply tends to change slowly and predictably, it is sharp cutbacks in demand that lead to recessions and rising unemployment.[1]

When demand falls short of supply, this means that there is more capacity in the economy to produce goods and services than demand to buy them. To illustrate, let’s take the example of a restaurant. It will not hire staff to cover every table and cook meals for a full house, unless there are paying customers at each table. If demand (or the number of customers) falls, then the restaurant will cut back staff and food purchases by roughly the same amount.

Figure A shows estimates of potential output and actual gross domestic product (GDP) over time. When actual GDP falls short of potential output, it can be inferred that GDP is demand-constrained (more could be produced if economic actors simply spent more). The shortfalls of actual GDP relative to potential may look small on the graph, but they correspond to significant economic distress. The growing gap between 2007 to 2009 was associated with the unemployment rate rising from 4.4% to just under 10%—meaning that roughly 9 million people lost their jobs during this time period. Others dropped out of the labor force, and wage growth even for those workers who kept their jobs was significantly damaged as well, as their main source of leverage to gain wage increases (the threat of—or ability to—leave their current job to find a higher-paying one) lost power in a labor market with huge pools of unemployed workers. Over the 2007–2017 period, excess unemployment translated into roughly 47 million years of avoidable unemployment for U.S. workers, and this period of soft labor markets kept wage growth firmly suppressed.[2]

Figure A

Throughout 2025, many have raised concerns that Trump administration policies could lead to a recession. It should be noted how surprising this development would be, considering the context. The economy handed over by the outgoing Biden administration in January 2025 was extremely strong, and there were no obvious macroeconomic threats moving forward that would have led one to forecast a recession in the next few years.[3]

For a recession to happen in the next year or two, there would need to be some short-run shock or drag on aggregate demand that forces it below the economy’s potential output. Despite the strength of the economy the Trump administration inherited, their subsequent policy agenda since his inauguration in 2025 contains plenty of reasons to worry about such drags.

For one, the Trump administration’s assault on the federal workforce directly destroys employment and incomes. Between January and December 2025, 290,000 federal workers have lost their jobs. While this is not enough by itself to drag an otherwise healthy national economy into recession (as it constitutes less than 0.2% of total employment), it certainly puts downward pressure on aggregate demand.

On top of this, the spending cuts in the 2025 Republican budget megabill (which the White House has referred to as the OBBB) will reduce aggregate demand in coming years. [4] For example, the Republican megabill will cut SNAP and Medicaid benefits by a combined $100 billion per year on average over the next decade. Households receiving Medicaid and SNAP benefits will cut back spending sharply when these benefits are reduced. Further, the megabill rolled back a set of Biden administration policies that sharply reduced student loan payments. In coming years, households will have to pay substantially higher student loan payments to the federal government.

Finally, another fiscal change that was not an explicit part of the megabill but was notable in its absence is the expiration of enhanced subsidies to buy health insurance in the marketplace exchanges established by the Affordable Care Act (ACA). The rollback of these enhanced subsidies—also passed during the Biden administration—will double out-of-pocket payments for the premiums of the 20 million Americans enrolled in these exchanges, increasing costs by more than $30 billion annually in coming years.[5]

The tax cuts in the Republican megabill are unlikely to do much to spur demand for two reasons. First, they are tilted toward high-income households whose spending is not constrained by their current incomes. Second, the tax cuts are small relative to a “current policy” baseline, meaning that they leave tax burdens unchanged, not appreciably lower, relative to 2025.[6]

The mass deportation agenda of the Trump administration will have its most predictably negative effects on the economy’s supply side, as millions of immigrant workers are forced out of the country.[7] But immigrants are not just workers; they are consumers as well. Further, immigrant workers are key complements to U.S.-born workers in many industries. Deporting these consumers and complementary workers and making it harder and more dangerous for those who remain to conduct the normal business of their lives will clearly have depressing effects on aggregate demand as well.

Most importantly, the radical uncertainty and chaotic implementation of Trump policies—particularly the trade policies—seem almost designed to freeze new business investment. Who would set up a new manufacturing facility if they had no idea what the competitive landscape of the sector was going to look like in coming years? Will tariffs protect domestic production? Will tariffs make imported inputs into the factory more expensive? Will protective tariffs vanish overnight when a foreign government meets the president’s demands of the day? Will future profits be reduced because the Trump administration arbitrarily demands ownership stakes in companies? Business investment is by far the most volatile component of aggregate demand, and it is the one that generally leads to recessions. It seems highly plausible that the Trump administration’s policies could cause business investment to seize up and slow growth.

Early in Trump’s second term, the administration’s “Liberation Day” tariffs led to most forecasters sharply raising the risk of a recession happening over the next year.[8] The sharp reversal of these historically high and broad tariffs to levels “only” half as high on average led to this risk receding a bit, yet still remaining sharply higher than it was in January 2025. So far, most of the “hard” economic data (that measure actual economic transactions like wages, employment, incomes, or gross domestic product) have yet to signal that a recession is coming.

Part of the relative robustness of macroeconomic measures likely owes to the fortuitous timing of a boom in AI-related spending, which largely began in mid-2023.[9] The valuation of stock markets has reached the second-highest levels in history—trailing only the stock market bubble of 2000–2001 (also driven by a boom in tech stocks). Much of these stock market gains have been driven by AI-related firms. A significant amount of consumption spending out of these wealth gains has likely contributed nontrivially to growth over the past year.

Further, capital expenditures related to the AI-boom have also been contributing to growth. Starting in 2023, year-over-year real growth (adjusted for inflation) in data centers, for example, has consistently exceeded 35%, peaking at just under 77% in late 2024 and remaining above 30% throughout most of 2025. While this AI-related spending has helped keep the U.S. economy well clear from recession through the third quarter of 2025, it is the kind of spending that would likely evaporate relatively quickly if business sentiment about the future use and profitability of AI investments dims.

If this happened, the depressing effect on wider business investment stemming from the uncertainty mentioned above might well dominate and lead to quick decelerations in growth. Evidence of this depressing effect seems already clear, as investment in components not related to the AI boom looks notably weak over the past year.

Figure B

The danger of a slowdown in aggregate demand highlights how much discussions about affordability need to go beyond prices.[10] Much of the discourse about affordability recently was driven by the outbreak of very high inflation in the early 2020s, following the COVID-19 pandemic. But absent very rare and sharp increases in inflation like that (and which tend to be driven by external events like pandemics and wars, not policy missteps), the main damage to affordability over time does not stem from fast inflation, but from slow growth in wages and incomes. A recession would return inflation in the U.S. to very low levels. The recession of 2008–2009, for example, led to inflation averaging below 2% for the following decade. And yet this low inflation provided next to no relief for affordability because the high unemployment of that period—which was the source of disinflation—sapped workers’ leverage and bargaining power in labor markets and led to slow wage growth.[11]

A recession in the next year would solve the price side of affordability in that it would lead to a sharp slowdown in inflation, but it would force wage growth down even faster, and hence, would exacerbate, not help, the ongoing problem of affordability properly defined.

All in all, it seems safe to say that the Trump administration’s policies have significantly elevated the risk of a recession over the next year. Their trade policy retreat has been sharp enough that a recession might well be avoided. But this hinges largely on the administration’s being able to resist whipsawing trade policy chaotically again—and this seems far from certain. But we may well navigate the next year without a recession—largely stemming from the momentum of the strong economy the current administration inherited and the lucky timing of much AI-related spending remaining strong through 2025.

Trump polices will quickly erode the economy’s ability to supply goods and services without inflation—this damages affordability for typical families

However, the avoidance of a recession would not mean the economic policy decisions of this administration were wise. If the only question on the table regarding the impact of Trump policies was “Will there be a recession?” the future of the U.S. economy would be much less bleak. Instead, the more predictable and larger amount of damage that the Trump administration’s policies will inflict will not come through downward pressure on aggregate demand but through the rapid erosion of the economy’s potential output and the upward redistribution of income instead. These influences will be experienced by typical families as wages, incomes, and public supports failing to outpace prices by sufficient margins over time, thereby damaging affordability.

In the previous section, we noted the sharp economic damage done by the aggregate demand shortfall of the early 2010s. The most obvious and acute damage stemming from this shortfall was the elevated unemployment rate of that time, along with the attendant damage to wage growth.

However, the worst lingering damage from that long period of deficient aggregate demand likely came from its spillover effect in destroying potential output. When employers see that customers are scarce and workers are cheap and plentiful, their imperative to invest in worker training or newer capital or innovative technological processes to economize on labor costs and boost productivity is blunted. And when jobless workers see elevated unemployment rates and the low probability of being hired, job seekers can get discouraged, and labor force participation can falter.[12]

Over time these dynamics lead to a lower-quality workforce and smaller capital stock, which reduce productivity growth and potential output. Figure A showed actual GDP and successive estimates of potential output over time. Between 2007 and 2019, these potential output estimates continually fall as the demand shortfall bends down potential output, as productive investment is blunted. By 2019, potential output was $2.2 trillion below where its 2007 trend would have left it in that year. This translates into $6,500 less income for every adult and child in the United States in 2019 (or $26,000 less income for a family of four). In short, over a 5–10-year period, even small bends in the growth of potential output have huge real-world consequences.

Supply destruction leads directly to unaffordability

This discussion of potential output growth likely sounds abstract to noneconomists. But it has profound effects on typical families’ economic security, and the way this slowing down of potential output translates into observable real-world effects is by making affordability worse for these families. For example, in the paragraph above, we said that the slowdown of potential output growth after 2007 translated by 2019 to $6,500 less in inflation-adjusted income for every person in the United States (or $26,000 less income for a family of four). The way this happens is by wages and incomes failing to outpace growth prices by satisfactory amounts—even during times (like the 2010s) when inflation was extremely low.

And, of course, the gap in the race between wages and prices differs depending on the specific goods and services examined. In the 2010s, the output that was produced less and less, relative to historic norms, was housing.[13] This reduced output of housing translated directly into higher relative prices for rents.

While there is a lot about this collapse in housing production and rise in rental prices that is housing-specific, the root of all of this pressure on affordability stems from macroeconomic choices. If potential output growth slows for the overall economy, then the production of something will lag, and its price is likely to rise. If we had somehow kept housing construction constant in the face of a fall in overall potential output, the biggest affordability problem would have shown up someplace else, but one surely would have emerged.

How Trump policies will slow potential output and exacerbate affordability concerns

In the current moment with unemployment that is still relatively low by historical standards and so-far adequate aggregate demand, the imminent threat to the economy’s supply side today is not an extended recession, but simply the direct effect of many Trump policies. When (not if, but when) potential output growth falters in coming years, it will again represent a sharp break from the economy the Trump administration inherited, an economy that saw rapid productivity growth in the years following the pandemic.

Figure C

The potential supply destruction stemming from Trump administration policies comes along many margins.

Loosening immigration restrictions and unleashing mass deportations

The most obvious blow to the economy’s potential output would be Trump’s mass deportation policy. If the U.S. relied solely on growth in U.S.-born workers, labor force growth would shrink rapidly over the next decade (see Bivens 2025c). Successful mass deportations—besides causing great and unnecessary human misery—would actually push labor force growth in the U.S. economy into negative territory in coming years.

Further, immigrant and U.S.-born labor supply are often complementary (Zipperer 2025). One obvious example is that child care centers are disproportionately staffed with foreign-born workers. If mass deportations cause significant closures of these centers, U.S.-born parents will often be forced into stopping work in order to care for children.

Cutting back federal spending and the workforce

We noted the cutbacks to federal workforce and spending previously as short-run threats to aggregate demand. But the federal government is not just a source of short-run demand; it also provides absolutely crucial inputs needed for robust private-sector growth.[14] Recent decades have seen sharp cuts in the size of the federal workforce and the investments in the functions it provides. By January 2025, the size of the federal workforce and the spending to support it were at historically low levels relative to the broader economy. In short, it seems clear that this workforce and the state capacity of the federal government were already significantly degraded even before the Trump administration took power. Since then, the administration has unleashed an unrelenting attack on this state capacity.

Perhaps the clearest way reduced federal spending will translate into slower potential output growth in coming years comes from cutbacks to science and research. Fieldhouse and Mertens (2025), for example, have estimated that nearly a third of total factor productivity (TFP) growth stems from federally financed research and development spending.

Further, the Trump administration has significantly cut back federal spending on universities. A key driver of productivity growth over time is a more educated and skilled workforce. Today’s higher education cuts are guaranteed to slow the growth of labor quality in the U.S. workforce in coming decades.

Other federal agencies collect, analyze, clean, and provide access to free, publicly available, high-quality data on the nation’s economy and demographics. These services provide enormous monetary value to private-sector actors (see Hughes-Cromwick and Coronado 2019).

Other agencies provide crucial monitoring services that help the nation avoid financial, epidemiological, or weather disasters. These investments provide a huge rate of return relative to the (likely too small) federal spending done on them. Even monitoring and surveillance that directly aim to constrain and manage private-sector decision-making can often actually lead to better private-sector outcomes. Hirtle, Kovner, and Plosser (2019), for example, examine the outcome of banks when they receive more or less regulatory scrutiny from federal banking supervisors. The authors find that “…banks that receive more supervisory attention hold less risky loan portfolios, are less volatile, and are less sensitive to industry downturns, but do not have slower growth or profitability.”

By far the biggest long-run threat to the U.S. and global economies’ ability to produce goods and services without inflation is the effect of climate change. Climate change can be thought of as an ongoing erosion of the economy’s productive capacity. For example, key swathes of land will become less valuable as flooding and disaster exposure rise, buildings and factories will be threatened by extreme weather, and the productivity of work that must be performed outside will suffer due to either extreme weather or needed spending to mitigate the effects of it on workers. Investments that mitigate greenhouse gas emissions (GHG) and reduce the effects of climate change are incredibly valuable in the long run for maintaining the economy’s supply side. By far the biggest and most effective investments in this type of mitigation ever made by the United States were the subsidies for clean energy and its adoption in the Inflation Reduction Act (IRA) of 2022. The Republican budget megabill, however, rolled back the majority of these IRA subsidies and will hence lead to far fewer reductions in GHG emissions in coming years. Essentially these rollbacks will accelerate the destruction to the economy’s supply side that is ongoing due to climate change.

Many federal agencies are responsible for providing and enforcing transparent rules for markets that channel economic competition into productivity improvements, instead of zero-sum opportunism. For example, the Securities and Exchange Commission and the Consumer Financial Protection Bureau provide protection to investors by enforcing rules against fraud or misappropriation of their funds from companies they invest in. This promotes trust and allows more liquid capital markets that are able to provide finance for more prospective and ongoing businesses. The Federal Trade Commission and the Antitrust Division at the Department of Justice aim to keep firms’ monopoly power from distorting markets. The Occupational Health and Safety Administration and the Wage and Hour Division at the Department of Labor protect employees from abusive workplaces, allowing them to choose among prospective employers without having to factor in whether there will be unsafe or exploitative working conditions with these employers.

Another key federal agency priority that has had profoundly beneficial effects on the U.S. economy’s supply side in recent decades is enforcement of anti-discrimination laws. The Equal Employment Opportunity Commission, for example, was established in 1965. Hsieh et al. (2019) have noted that since then, there has been an enormous increase in the share of high-wage, high-skill occupational employment that is accounted for by women and Black men. In turn, the authors estimate that this more efficient allocation of workers to occupations based on talent and merit accounted for up to 40% of all growth in the U.S. economy since 1960. Much of this better allocation of talent has stemmed directly from enforcement of anti-discrimination laws. Going forward from today, there is ample scope for ongoing and/or improved enforcement of anti-discrimination laws to support future growth. If instead, the enforcement of these laws withers, and there is a reduction in the efficient allocation of talent to occupation, this could be an outright headwind to growth going forward.

Haphazardly implementing poorly designed and chaotic tariff policy

The chaotic implementation of the administration’s tariff policy is surely a short-run drag on aggregate demand. But, if the end result of the policy is to leave the United States with historically high and broad tariff rates (which is where the tariff policy has landed as of December 2025, even with the sharp reversal of many of the highest tariffs), without any obvious corresponding benefit from well-designed industrial policy considerations, then this will also slow potential output growth.[15]

Tariffs are essentially a way to block the lowest-cost method of delivering goods to U.S. households and businesses, if this lowest-cost method involves imports. Sometimes this kind of blockage is fully justified by other policy concerns besides what is the cheapest production at the moment. For example, if foreign governments subsidize their producers in a specific sector, and if the U.S. deems it imperative to have productive capacity in that sector, then tariffs can help keep domestic producers from being forced out of business by the decisions of foreign governments.

Further, if the sectors that domestic producers are being forced out of looked poised to drive productivity gains in coming decades, there might be a strategic benefit to using tariffs to protect domestic production. The case of electric vehicles (EVs) is one potential example. There is clearly going to be a large global shift toward EVs in the coming decades. EV manufacturing will scale rapidly, and often this kind of scale produces huge leaps in productivity. If today’s constellation of EV production facilities and foreign countries’ subsidies of their own EV makers threaten to shove U.S. producers entirely out of the race for EV market share, it seems like industrial policy efforts to support domestic production of EVs would make a lot of sense—and this was indeed a priority of the Biden administration.

Similarly, if some or all of the cost advantage of imports in a sector stems from objectionable practices of producers in other countries—say, blatant disregard of fundamental labor rights—tariffs can protect U.S. producers from being forced out of business by these objectionable practices.

But the historically broad and high tariffs of the Trump administration are not being calibrated in any kind of strategic or careful way. Instead, they are blocking the lowest-cost means of delivering goods to U.S. households and businesses randomly. This essentially is the equivalent of a negative technology shock. Businesses (both foreign and domestic in the U.S.) that supply goods have been forced out of the most efficient way to produce goods, and without any countervailing benefit from smartly designed industrial policy considerations.

Finally, the chaotic implementation does not only affect aggregate demand. If ever-shifting tariff levels change the patterns of production that lead to the lowest-cost ways of producing goods in random ways, this makes it impossible to set up efficient supply chains, hence stunting potential output growth.

Financing tax cuts for the rich and corporations with higher debt

In 2000, the ratio of U.S. public debt to gross domestic product (GDP) stood at less than 35%. In 2024, the debt ratio nearly tripled, rising to almost 96%.[16] A large part of this increase was due to the two historically large economic crises experienced in those years: the financial crisis and Great Recession of 2008–2009, and the COVID-19 recession.

More worryingly, even in 2024—a year in which the unemployment rate averaged 4%, the Fed’s short-term interest rates stood at over 5%, and inflation was above the Federal Reserve’s target—the federal budget deficit was 6.2% of GDP. This is too large a deficit for an economy that is at roughly full employment and not in need of fiscal support.[17]

The 2024 deficit can essentially be entirely explained by the successive rounds of tax cuts engineered by Republican administrations since 2000. In 2009, the Congressional Budget Office (CBO) projected what federal revenue as a share of GDP would be if the tax cuts signed into law by George W. Bush in 2001 and 2003 were allowed to lapse (see CBO 2009). They projected that revenue would be 20.2% of GDP by 2019. However, in 2019—after the vast majority of the Bush-era tax cuts were maintained and President Trump signed the 2017 Tax Cuts and Jobs Act (TCJA)—federal revenue came in at just 16.1% of GDP.  If revenue had remained at 2000 levels going forward, even with the extra debt incurred by economic crises, budget deficits by 2024 would’ve been effectively zero.

In the decade after the onset of the Great Recession in 2008 and during the early stages of the 2020–2021 pandemic, large deficits were not harming the economy. In fact, they were usefully propping up aggregate demand even as private sources of demand were plummeting. This chronic shortfall of aggregate demand (sometimes labelled “secular stagnation”) kept spending weak and interest rates and inflation historically low (short-term interest rates stood at essentially zero in all these years).[18] And so long as interest rates were low, no damage was being done by higher deficits.

But in the post-pandemic recovery, aggregate demand (aided by a robust fiscal response to the crisis) has been stronger, and interest rates and inflation have moved decisively off their historic lows. In this environment—when the economy is no longer demand-constrained—further increases in federal debt now compete with private-sector borrowers to find available savings. This, in turn, pushes up interest rates and threatens to crowd out private sector investments in new factories, plants, and equipment. This slowdown in the growth of the nation’s capital stock, in turn, leaves U.S. workers with less capital to aid them in doing their jobs and hence slows the pace of productivity growth.

This potted history of fiscal policy debates in recent decades tells us that after a decade and a half of warnings about the crowding-out effect of higher deficits on investment not ever coming to pass, there is now strong evidence to suggest this might be an important influence on growth going forward. Figure D shows the “real debt service ratio,” a measure of how sharply the government’s borrowing costs are rising. After a long stretch of being under 1%, this measure has recently surpassed its historic high.

Figure D

This historic high was surpassed even before the passage of the 2025 Republican budget megabill—a bill that will add nearly $4 trillion to the federal debt over the next 10 years. Borrowing costs are guaranteed to spike further going forward from now in any time period when the economy sits near full employment.

If the worried-about recession comes to pass in the next year or so, the collapse in private spending will reduce competition for available savings and interest rates will fall and the supply destruction effect of higher interest rates will be muted. But so long as the underlying fiscal structure of the U.S. sees large budget deficits even when the economy is at full employment, this means that interest rates will be high during these full employment periods and investment will be suppressed, leading to slower future productivity growth.

A key aggravating factor of the supply-destroying effects of higher deficits in coming years is what they were used for: simply to give much higher disposable incomes to rich households in the United States.          

One could imagine a counterfactual in which instead of using debt to finance higher disposable incomes for the rich, the federal government used this debt to make significant investments to mitigate emissions of greenhouse gases. This would leave the country with a higher stock of “green” capital (capital used to mitigate greenhouse gas emissions) and a smaller stock of conventional capital. This would be an affirmatively good thing. It would effectively be leaving future generations with slightly lower productivity in producing conventional goods and services, but a more livable and viable climate. Consistent economic growth essentially guarantees that future generations will be significantly richer than the current one in their ability to buy conventional goods and services. Trading off a bit of this advantage for a livable planet would be welcomed by this future generation—and it’s a trade-off they won’t be able to make. Only their ancestors can make it for them.

Alternatively, one could imagine a world in which the federal government took on additional deficits of the size generated by the 2025 Republican megabill to radically increase investments in children: providing federal financing of universal, high-quality pre-kindergarten; boosting aid to K–12 public school systems; and providing a universal Child Allowance to end child poverty. This would not only raise human welfare much more than tax cuts to rich people would; it would also see some of the deficit costs defrayed in coming decades as today’s children grew up healthier and better educated and worked more and earned higher wages in the decades to come. Some of these offsets could be considerable.[19]

There are no such happy offsets that stem from running larger deficits simply to give tax cuts that are radically tilted toward households that don’t need them—the ones at the very top of the income distribution. These deficits are supply destruction for the sake of intentionally increasing inequality.

Threatening a political takeover of Federal Reserve policy decisions

The Trump administration has been far more forceful than previous ones in pressuring the Federal Reserve to fall in line with the administration’s economic goals. They have demanded that the Federal Reserve set interest rate policy to meet the administration’s short-term economic goals and have constantly demanded lower interest rates, even as conditions do not warrant cuts in interest rates (inflation remains above the Fed’s long-run target, and unemployment remains generally low).

If decision-makers throughout the economy—households, businesses, and state and local governments—begin to think that the Federal Reserve’s interest rate decisions will be managed entirely by the executive branch, they might well raise their expectations of inflation in the future. This, in turn, would likely require any future Federal Reserve that committed to reducing inflation (and inflation expectations) to raise interest rates higher than they would otherwise have to be. These higher long-run interest rates would, in turn, reduce investment and slow productivity growth (much like too-large deficits run during times of full employment).

How much will supply destruction slow growth in coming years?

It is very hard to provide any convincingly precise estimates as to how much supply destruction will result from this portfolio of Trump administration policies. What determines the ebb and flow of productivity growth in advanced economies is one of the most debated topics in economics, and one in which no consensus exists. Yet we can give some very rough bounds for how important each element of this potential supply destruction might be over the next decade. The sum of these negative effects would be highly significant for future living standards growth—or affordability.

We start with the Congressional Budget Office’s (2025b) forecasts of potential output growth for the next decade. Currently they forecast that annual growth will average 2.0% between 2025 and 2034.

About 30% of the 2.0% that CBO forecasts (or 0.6% of this growth) stems from their estimate of how much the labor force will grow in those years. However, if one accounts for the Trump administration’s meeting their mass deportation goal of removing 1 million immigrants each year from the United States, this would imply that the labor force will barely grow at all in those years, translating into a 0.4% slowdown of growth in potential output.[20]

More than half of the projected growth in potential output comes from CBO’s forecast of growth in total factor productivity—a measure of how much extra output can be obtained holding inputs constant. TFP growth is often interpreted as a measure of pure technological advance—using new processes and production techniques to get more output out of a given stock of inputs. However, as we noted before, Fieldhouse and Mertens (2025) have estimated that fully one-third of TFP growth in recent decades can be accounted for by direct federal spending on research and development. The Fieldhouse and Mertens (2025) results would imply that a 20% cut in federal research and development spending would reduce projected productivity growth in the U.S. over the next decade by 0.2% annually.[21] This, in turn, would reduce potential output enough by roughly $2,500 for every adult and child in the United States by 2035.[22]

Importantly, their estimates do not include the effect of federal support for institutions of higher education, and this support has been large and critical for these centers of scientific research—likely as important as the direct federal research and development spending. This could easily double the effects from direct federal research and development spending, especially if one accounts for the long-run loss in the labor supply of trained scientists and researchers capable of undertaking research and development that will occur as higher education funding erodes.

CBO (2025b) has estimated that the 2025 Republican megabill will add roughly 7.1 percentage points to the ratio of public debt to GDP by 2034. Using earlier estimates from CBO (2025e) to translate the effect of a higher debt ratio on economic growth, this level of debt increase (assuming no recession intervenes) would slow growth by 0.1%–0.2% by 2034 through its effect on interest rates and investment. Given that Figure D previously showed that higher interest rates really have emerged in recent years, this effect seems possible.[23]

Estimates of the growth effects of the Trump administration’s trade policy are more uncertain. The Yale Budget Lab indicates a long-run effect on the level of GDP of 0.4%. However, it is hard not to make a comparison between the strategy-free actions of the Trump administration and a similar lack of planning that went into the United Kingdom’s exit from the European free trade area (Brexit). Estimates of the effect of Brexit are substantially larger than 0.4%—on the order of 2%–3% of GDP over 10 years (Bloom et al. 2025). If we think that Brexit is a suitable potential model for the fallout from the Trump trade policy—similarly chaotic and unplanned—this would imply a reduction in productivity growth of around 0.25% over the next year.

The long-run growth effect of eroding the federal government’s state capacity through budget cuts and downsizing is harder to estimate. One suggestive paper on this is Klein Martins (2025), who looks at episodes of sharp permanent spending cutbacks in advanced countries over the past 30 years. He estimates highly persistent negative effects on GDP growth of these cutbacks, over timespans well longer (15 years) than could be explained simply by the effect of these spending reductions adding to demand shortfalls. Klein Martins finds that each 1% of GDP in public spending reductions leads to GDP that is 2% smaller 15 years later. Say that half of these effects were driven by the erosion to state capacity stemming from these cuts. The cuts to the federal workforce in 2025 will result in a reduction of federal government spending of roughly 0.1% of U.S. GDP, which would imply (using half of Klein Martins’ estimates) a reduction in GDP of about 0.1%.

Tedeschi (2024) estimates how much higher interest rates driven by political events (like the capture of Fed policymaking by the executive branch) could reduce growth in coming years.[24] He finds that if the political events just moved the “country risk premium” of the United States to look more like the United Kingdom, this could reduce growth by 0.1% annually. If instead, this country risk premium deteriorated enough to look more like other rich, stable economies like Spain, the damage could be closer to 0.3% annually.

Adding up supply destruction from Trump policies

The Trump deportation goals could reduce labor supply growth by 0.4% over the next decade. The cuts to direct public research and development spending and this spending supported by institutions of higher education could each slow productivity growth by 0.2% over this period. Financing the Trump administration’s tax cuts for the rich with debt could reduce capital investment and hence productivity by 0.2%. If Brexit is the best model for the administration’s strategy-free trade policy, this could also reduce productivity growth by 0.2%. If the Trump-led attacks on the Fed led to steep concerns in international financial markets that raise the U.S. country risk premium and other interest rates significantly, this could slow growth by up to 0.3% in coming years. The administration’s attacks on the state capacity of the federal government could reduce growth by 0.1%. Their capture of Federal Reserve policy—leading to rising interest rates—could slow growth by between 0.1%–-0.3%. Adding these up, this means growth could slow by just under 2% on average over the next decade, with productivity growth slowing by well over 1%.

Somewhat ironically, the optimistic projections of how much advances in AI could boost U.S. productivity growth over the next decade tend to cluster around 1% annually.[25] The damage being done by the Trump administration to the economy’s supply side over the next decade is hence potentially as large as the most optimistic projections for how much a new burst of technology could boost it. If this came to pass, it would constitute just the latest episode of poor policy decisions squandering the potential benefits of economic growth and technological advance. The typical U.S. household today is not poorer in absolute terms compared with decades ago. But they are shockingly poorer relative to the potential growth they could have enjoyed with smarter policy that prioritized their economic security over showering the rich with even more perks.

Trump policies will raise inequality—the worst blow to families’ affordability

As we noted before, affordability is determined simply by the race between families’ economic resources (wages, incomes, and publicly provided subsidies and benefits) and prices. When affordability is strained, it is overwhelmingly because something—a recession or slowing of potential output growth, for example—has dragged on growth in families’ economic resources. Moreover, even when the aggregate economy seems strong—free of recession or inflation and with adequate growth in potential output—affordability for the vast majority of families can be squeezed if growth in these families’ resources lags far behind average growth. This mismatch between growth in typical families’ resources and average growth is driven by strongly above-average growth at the top of the income scale—the precise problem that has afflicted the U.S. economy in recent decades and the true root of nearly all U.S. families’ concerns about affordability.

Figure E

The Trump policy agenda will push income away from low- and moderate-income families and toward the top along many different margins. Even if (as expected) inflation rates return to normal during the second Trump term, this will be unlikely to boost the inflation-adjusted resources available to most families because the policies of the administration will actively claw resources—or the market power to claim these resources—away from typical families.

In the short run, the Trump budget megabill will cause an enormous jump in inequality

The signature legislative achievement of the second Trump administration is the 2025 Republican megabill, a budget reconciliation package that continues the individual provisions (and some business provisions) of the 2017 Tax Cuts and Jobs Act. The megabill also enacts steep cuts to health care and nutrition programs (Medicaid and the Supplemental Nutrition Assistance Program, abbreviated as SNAP). On top of this, the megabill also failed to either roll back or otherwise modify the corporate income tax cuts of the 2017 TCJA, but also fails to extend the supplements to subsidies for purchasing health insurance in the marketplace exchanges established by the Affordable Care Act that were passed as part of the Biden-era American Rescue Plan.

To give a sense of scale of the bill’s impact, we compare the one-year change that will result directly from the 2025 megabill policy with the entire upward redistribution of income that happened between 1979–2019, a period widely recognized as one during which U.S. inequality exploded. The share of total income claimed by the top 10% of households over that period rose by roughly 10 percentage points over a period of 40 years (or about 0.25 percentage points per year). But the Republican megabill alone will in one year raise the share of income claimed by these top 10% of households by 1 full percentage point. The 40 years between 1979 and 2019 saw the top 10% gain an average of 0.25 percentage points in the share of income they claim. This means the Republican megabill will see the rate of inequality growth quadruple in its first year, and it will essentially accomplish 10% of the entire post-1979 rise in inequality in a single year.

In the longer run, Trump policies empower the rich and disempower everybody else

Besides these large fiscal changes, other policy priorities of the second Trump administration include stripping workers of the effective right to organize unions and bargain collectively, deregulating some of the most abusive parts of the financial sector, and shrinking the federal workforce. All of these will lead to rising inequality.[26]

Trump policies continue the conservative assault on labor and workers’ rights

The Trump administration has continued to move forward with parts of its first-term priorities like the assault on labor and the bargaining power of typical workers. Two obvious high-profile indications of this were the stripping of collective bargaining rights of more than a million federal workers (including terminating the collective bargaining agreement of the Transportation Security Administration and firing National Labor Relations Board (NLRB) Member Gwynne Wilcox for “unduly disfavoring the interests of employers.” Further, the Trump administration nominated a partner at the very law firm that is currently challenging the constitutionality of the NLRB to be the NLRB’s general counsel. [27]

The assaults on labor and the bargaining leverage of typical workers continue a long-term conservative effort that has been highly successful in suppressing wage growth for low- and middle-wage workers and which has been a primary contributor to the long-run rise of inequality in the U.S. economy. [28]

Normalizing the most abusive parts of the financial system

The rise of the financial sector’s power has played a large role in the upward redistribution of income in the U.S. economy in recent decades. Finance is possibly the economic sector that has most benefitted from the federal government’s intentional industrial policy support. Between deposit insurance, the day-to-day liquidity provisions of the Federal Reserve (like the discount window that provides overnight reserves at the Fed), and the regular occurrences of extraordinary support provided in financial crises, the financial sector is obviously far larger in capitalist economies than it would be without this public support.

Significant public support of the financial sector is warranted—finance provides needed services to the rest of the economy, and without public backing, market failures would prevent these necessary services from being continually available. But this public support also justifies a robust regulatory and supervisory framework surrounding the financial sector.

The history of finance in the United States is one of accepting public support (especially during bad times for finance) while constantly trying to escape regulation and supervision that constrain profits during good times. The period from the late 1970s to 2007 saw regulation and supervision atrophy. This resulted in exploding profits and incomes in the financial sector with very little obvious benefit to the rest of the economy and the spectacular crash of 2008 that demanded even more public support for the sector. In short, the industrial policy support that the financial sector has received is a case study for how complementary policies (regulation and supervision in this case) are needed to ensure public support for a specific sector is not siphoned off into the incomes of economic players with substantial market power.[29]

In the financial regulation space, the Trump administration has continued conservative efforts to keep public supports for finance strong while expanding the scope of what the sector can do to seek profits.[30] The administration has directed the Consumer Financial Protection Bureau to shrink its scope and cede regulatory oversight to state agencies and has supported congressional efforts to slash funding for the bureau. The administration has also stopped U.S. movements toward harmonizing regulations with the Basel III recommendations—essentially meaning that large banks are no longer required to hold as large a set of capital buffers to protect against financial market stress. These capital buffers are there to prevent the public sector from having to bail out large parts of the financial sector during these periods.

The administration has also endeavored to bring cryptocurrency into the realm of traditional financial institutions, but under a loose regulatory regime. This approach would essentially allow some parts of the crypto ecosystem to put the public sector on the hook for bailouts needed due to instability in the sector, but would also allow many of the worst abuses of the crypto ecosystem—its use in illegal transactions and its speculative excesses—to continue unregulated. The approach to crypto represents the worst of all possible worlds. It gives the public sector heavier responsibilities to ensure that crypto crashes are managed but robs them of the tools needed to supervise the sector.

Attacks on the federal workforce

Between January and December 2025, federal payroll employment fell by roughly 290,000 due to the cuts started by the so-called Department of Government Efficiency. We noted previously that these cuts would sharply hurt growth in potential output in coming years. They will also lead to a less equal economy.[31]

Besides providing key inputs to public-sector production that markets generally fail to provide, the activities of federal workers often involve providing a countervailing force against unchecked corporate power. The Federal Trade Commission and the Antitrust Division at the Department of Justice ensure that markets remain competitive and block firms from exercising monopoly power. The Centers for Medicaid and Medicare Services must set reimbursement rates for the health care delivered by private-sector providers but paid for by the federal government. Private-sector health providers have seen a wave of consolidation in recent years and often can exercise pricing power against patients and other payers—the price-setting decisions of the federal government are a key bulwark against this pricing power. The Occupational Safety and Health Administration and the Food and Drug Administration have workplace inspectors to ensure that firms do not try to maximize profits by underinvesting in basic protections for worker or consumer safety.

Further, in a country where the federal tax system remains at least moderately progressive (with richer households facing higher tax rates than low- and moderate-income households), effective administration of the nation’s tax laws is equality enhancing. The vast majority of unpaid taxes are owed by the very rich. As such, attacks on the capacity of the Internal Revenue Service to administer this tax law are intentionally designed to lighten the tax burden of the privileged without passing new legislation.

Measures of GDP and income understate harms of Trump policies

Most of the discussion above concerns economic forces that affect measured GDP and incomes. But the economic security and happiness of U.S. families cannot be captured entirely based on these measures. For example, many Americans report feeling overworked and wish they had more leisure time. Increases in leisure time do not show up as greater GDP or incomes, yet clearly are valuable to families.

A number of policy choices made by the Trump administration will have profoundly damaging effects on families’ welfare that are not captured by GDP or data on incomes. For example, much of the damage done by climate change will not be well captured in these statistics. At the starkest level, climate change is forecast to lead to worse health outcomes and more premature deaths. The famous Stern review of climate change (2021) noted that accounting for these non-GDP influences likely at least doubles the true economic cost of climate change.

Similarly, the cutbacks to health insurance coverage signed into law by the Trump administration will cause poorer health and excess deaths in the coming decade if they stand. These deaths will not directly affect GDP, but obviously they need to be accounted for when assessing the impact of these policy changes.

Some of the outcomes of public policy raise GDP but actually reduce welfare. As climate change makes people spend more money on air conditioning, for example, this shows up as an increase in GDP yet makes peoples’ lives worse. Similarly, an increase in health spending driven by maladies related to climate change will raise GDP yet reduce welfare.

Further, some government spending provides outputs that GDP does not measure well at all. The value of less air and water pollution, for example, is immense but not captured in contemporaneous GDP. Much of its value will implicitly show up in future GDP numbers, as less pollution will lead to a healthier and more productive workforce in the future, but in real time, the benefits are not precisely measured. A similar finding concerns investments in children generally. Some of the benefits might occur in the moment (say, child care subsidies that allow parents to work more and earn higher incomes), but most accrue over time as children grow up healthier and become more productive and higher-earning adults.

Just because the benefits of much public spending do not mechanically show up in contemporaneous GDP measures do not mean they cannot be measured. When they are measured, there is ample evidence that families value this spending and the output it produces immensely. Often the estimated value of such spending is on the order of $1.50 for each $1.00 spent, with most of the benefit coming from welfare gains not captured in GDP. Welfare gains this large from public spending are strong suggestive evidence that public spending is already extremely under-provided, and further cuts will make it far worse.

Conclusion

It is essentially a guarantee that the policy path charted by the second Trump administration will leave the U.S. economy poorer and less equal. But much of this damage will be subtle and hard to see in month-to-month or even year-to-year changes in economic statistics. The Trump administration’s inability to implement a policy agenda without rank chaos might lead to a short-run recession that will temporarily expose much of the damage being done. But even if the recession does not come and even when it passes, there will be a steady hollowing out of the U.S. economy’s simple ability to produce the goods and services families need, and the inadequate growth that does get generated will flow disproportionately to the richest households.

In short, the macroeconomic consequences of the second Trump administration are profound. They will leave the vast majority of American families poorer over the next decade, and if Trump’s successors continue in this vein, they will leave the current generation’s children far poorer.

Notes

[1] The obvious historical counterexample to the rule that supply tends to grow slowly and predictably occurred during and immediately after the COVID-19 pandemic and Russian invasion of Ukraine, when these shocks broke global supply chains and led to sharp supply disruptions that restored themselves only with lots of volatility. This was, however, an unprecedented behavior of supply in advanced economies over the past century and is highly unlikely to repeat in the future.

[2] For this calculation, assume a counterfactual in which the unemployment rate stood at 4.0% over the 2007–2017 period and multiply by the size of the labor force in each year. Then, subtract this level of unemployment from the actual rate and sum over the years. For evidence of the damage this excess unemployment did to wage growth, particularly for lower-wage workers, see Gould et al. 2025.

[3] For details on the strength of the economy the Trump administration inherited, see Bivens 2025a.

[4] Numbers in this paragraph about cuts in the 2025 Republican budget megabill are taken from CBO 2025b, c.

[5] See Lo et al. 2025.

[6] This current policy baseline is a wrong and dishonest one to use when grading a law’s fiscal impact in coming years, but it’s the right one to use when figuring out whether growth will accelerate or decelerate in coming years due to policy changes.

[7] See Zipperer 2025 for estimates of the employment impact of the Trump administration’s mass deportation goals.

[8] For a wide range of views on the “Liberation Day” tariffs, resulting pullback and recession risks, see Nathan, Grimberg, and Rhodes 2025.

[9] Numbers in this paragraph can largely be found in Bivens (forthcoming).

[10] See Shierholz 2025 for this broader argument.

[11] Stark evidence that it is the race between wages and prices (and not just prices) that determines affordability can be found in Gould et al. 2025. They show that inflation-adjusted wage growth for low- and middle-wage workers was extremely strong from 2019 to 2024 but was actually negative over the five years following the previous business peak (from 2007 to 2012), even as this 2007–2012 period saw much lower rates of inflation. The strength of the labor market dwarfed changes in inflation in these periods, for good and bad.

[12] See Bivens 2017 for evidence that healthy labor markets support faster productivity growth.

[13] For example, according to the National Income and Product Accounts (NIPA) Table 1.1.10, between 1979 and 2007 residential investment was about 4.7% of overall GDP, whereas between 2007 and 2019 it was just 3.3%.

[14] See Bivens 2025b for an overview of the short- and long-run effects of steep cutbacks in the federal workforce.

[15] See the Yale Budget Lab’s State of U.S. Tariffs feature for a real-time assessment of trade policy under the second Trump administration.

[16] Numbers in this section are taken from CBO 2025b.

[17] Bivens 2019 estimates that a budget deficit of 2.5% or lower is likely consistent with a roughly stable debt ratio when the economy is near full employment.

[18] See Banerjee and Bivens 2022 for an overview of secular stagnation and how it intersects with fiscal policy debates.

[19] See Lynch and Vaygul 2015 for an accounting of the costs and benefits of investments in early childhood education.

[20] Bivens 2025c looks at a scenario in which net immigration between 2025–2034 was halved relative to CBO projections made in January 2025. The goal of deporting 1 million immigrants would yield reductions in immigrant labor supply very close to that “halving net immigration scenario” in that report.

[21] Marr and Cureton 2025 note that the administration’s proposed budget calls for cuts larger than 20% in federal research and development spending.

[22] For this calculation, we compare a scenario in which the $204 billion spent on government research and development in 2024 is cut by 20% going forward and compare it with a scenario in which (as has been largely the norm) this spending was instead held constant as a share of GDP. By 2035 this implies a funding shortfall of nearly $80 billion. We multiply this funding shortfall by the high end of estimated returns to this kind of spending from Fieldhouse and Mertens to ascertain the total cumulative reduction in GDP by 2035, which is 2% of projected GDP in that year. We then divide this by 10 to get the average effect on productivity growth over that time.

[23] In CBO 2025e, they present the effect of GDP on two different scenarios regarding growth in the debt ratio over time. Using this, one could back out the implicit effect on GDP of a given increment of increase in the debt ratio. If this incremental effect holds for the increase in the debt ratio caused by the 2025 Republican budget megabill, one can hence get an estimate of its growth effects.

[24] While Tedeschi 2024 is not just writing about the takeover of the Fed, he absolutely mentions this as one thing that could threaten the very low current “country risk premium” enjoyed by the U.S. The country risk premium is essentially how much lower a return that international investors are willing to take on investments in the U.S. due to the perceived safety and stability of U.S. investments from political manipulation.

[25] See Bivens (forthcoming) for a quick discussion of these estimates.

[26] For a comprehensive assessment of policies undertaken by the Trump administration and their likely effect on typical working families, see Economic Policy Institute 2025–2026.

[27] For a comprehensive overview of actions taken by the Trump administration (including those mentioned in this paragraph) that harm workers’ leverage in labor markets, see McNicholas, Poydock, and Bivens 2026.

[28] See Farber et al. 2021 for the link between unionization and inequality throughout U.S. history.

[29] See Epstein 2018 for a good overview on how powerful economic actors in finance are able to claim a larger share of society’s incomes and resources than their economic contribution justifies.

[30] Much of this section relies on Gensler et al. 2025.

[31] Much of this discussion relies on Bivens 2025b.

References

Banerjee, Asha, and Josh Bivens. 2022. Will Secular Stagnation Return? The Stakes for Current Economic Debates and Fiscal Policy. Economic Policy Institute Report. August 4, 2022.

Bivens, Josh. 2017. A ‘High-Pressure’ Economy Can Help Boost Productivity and Provide Even More ‘Room to Run’ for the Recovery. Economic Policy Institute, March 2017.

Bivens, Josh. 2019. Thinking Seriously About What ‘Fiscal Responsibility’ Should Mean: Full Employment and Reduced Inequality Are the Most Important Targets of Fiscal Policy. Economic Policy Institute, September 2019.

Bivens, Josh. 2025a. “President-Elect Trump Is Inheriting a Historically Strong Economy.” Working Economics Blog (Economic Policy Institute), January 17, 2025.

Bivens, Josh. 2025b. “The Economic Effects of Rapid Federal Downsizing” in Gensler, Gary, Simon Johnson, Ugo Panizza, and Beatrice Weder di Mauro (eds), The Economic Consequences of the Second Trump Administration: A Preliminary Assessment. Centre for Economic Policy Research Press, December 2025.

Bivens, Josh. 2025c. 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. Economic Policy Institute, October 2025.

Bivens, Josh. Forthcoming. “How Are AI Investments Affecting the U.S. Economy?” Working Economics Blog (Economic Policy Institute).

Bloom, Nicholas, Philip Bunn, Paul Mizen, Pawel Smietanka, and Gregory Thwaites. 2025. “The Economic Impact of Brexit.” National Bureau of Economic Research (NBER) Working Paper no. 34459, November 2025.

Bureau of Economic Analysis (BEA). 2025. “National Income and Product Accounts (NIPA)” (web page). Accessed December 2025.

Bureau of Labor Statistics (BLS). 2025. “Major Sector Productivity and Costs Database” (web page). Accessed December 2025.

Congressional Budget Office. 2009. The Budget and Economic Outlook: 2009 to 2019. January 7, 2009.

Congressional Budget Office. 2024. The Distribution of Household Income in 2021. September 11, 2024.

Congressional Budget Office. 2025a. “Estimated Budgetary Effects of Public Law 119-21 to Provide for Reconciliation Pursuant to Title II of H. Con. Res. 14, Relative to CBO’s January 2025 Baseline” [Excel files]. Published July 21, 2025.

Congressional Budget Office. 2025b. Key Budget and Economic Data.

Congressional Budget Office. 2025c. The Budget and Economic Outlook: 2025 to 2035. January 17, 2025.

Congressional Budget Office. 2025d. The Estimated Effects of Enacting Selected Health Coverage Policies on the Federal Budget and on the Number of People with Health Insurance. September 18, 2025.

Congressional Budget Office. 2025e. The Long-Term Budget Outlook Under Alternative Scenarios for the Economy and the Budget. May 2025.

Economic Policy Institute (EPI). 2025–2026. Federal Policy Watch (Blog post series).

Epstein, Gerald. 2018. “On the Social Efficiency of Finance.” Development and Change 49, no. 2: 330–352. March 2018.

Farber, Henry S., Daniel Herbst, Ilyana Kuziemko, and Suresh Naidu. “Unions and Inequality over the Twentieth Century: New Evidence from Survey Data.” Quarterly Journal of Economics  136, no. 3: 1325–1385. August 2021.

Fieldhouse, Andrew J., and Karel Mertens. 2025. “The Returns to Government R&D: Evidence from U.S. Appropriations Shocks.” Society for Economic Dynamics Annual Meeting Working Paper, June 26, 2025.

Gensler, Gary, Simon Johnson, Ugo Panizza, and Beatrice Weder di Mauro, eds. 2025. The Economic Consequences of the Second Trump Administration: A Preliminary Assessment. Centre for Economic Policy Research, December 2025.

Gould, Elise, Katherine deCourcy, Joe Fast, and Ben Zipperer. 2025. Strong Wage Growth for Low-Wage Workers Bucks the Historic Trend. Economic Policy Institute, March 2025.

Hirtle, Beverly, Anna Kovner, and Matthew Plosser. 2019. “The Impact of Supervision on Bank Performance.” Federal Reserve Bank of New York Working Paper no. 768. May 2019.

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

Hughes-Cromwick, Ellen, and Julia Coronado. 2019. “The Value of U.S. Government Data to U.S. Business Decisions.” Journal of Economic Perspectives 33, no. 1: 131–146.

Klein Martins, Guilherme. 2025. “Long-Run Effects of Austerity: An Analysis of Size Dependence and Persistence in Fiscal Multipliers.” Oxford Bulletin of Economics and Statistics 87, no. 2: 330–356.

Lo, Justin, Larry Levitt, Jared Ortaliza, and Cynthia Cox. 2025. ACA Marketplace Premium Payments Would More Than Double on Average Next Year If Enhanced Premium Tax Credits Expire. KFF, September 30, 2025.

Lynch, Robert, and Kavya Vaghul. 2015. The Benefits and Costs of Investing in Early Childhood Education. Washington Center for Equitable Growth, December 2015.

Marr, Chuck, and Josephine Cureton. 2025. Administration’s Proposed Cuts to Non-Defense R&D Pose Long-Term Risk to Rising Living Standards. Center on Budget and Policy Priorities, October 2025.

McNicholas, Celine, Margaret Poydock, and Josh Bivens. 2026. 47 Ways Trump Has Made Life Less Affordable in the Last Year. Economic Policy Institute, January 2026.

Nathan, Allison, Jenny Grimberg, and Ashley Rhodes. 2025. Top of Mind: Tariff-Induced Recession Risk. Issue 138. Goldman Sachs Research, April 2025.

Shierholz, Heidi. 2025. “Everyone Is Talking About Affordability—and Making the Same Mistake: Focusing on Just Prices Misses the Bigger Picture.” MS NOW, November 29, 2025.

Stern, Nicholas. 2021. “15 Years on from the Stern Review: The Economics of Climate Change, Innovation, and Growth” (slide presentation). London School of Economics and Political Science and Grantham Research Institute on Climate Change and the Environment, October 26, 2021.

Tedeschi, Ernie. 2024. Political Risks to the U.S. Safe Harbor Premium. The Budget Lab at Yale, May 2024.

The Budget Lab at Yale 2025. The State of U.S. Tariffs: November 17, 2025. November 17, 2025.

Yellen, Janet. 2016. Macroeconomic Research After the Crisis. A speech at ‘‘The Elusive ‘Great’ Recovery: Causes and Implications for Future Business Cycle Dynamics.’’ 60th Annual Economic Conference sponsored by the Federal Reserve Bank of Boston, Boston, Massachusetts, October 14, 2016. No. 915. Board of Governors of the Federal Reserve System.

Zipperer, Ben. 2025. 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 2025.

Federal statistical agencies (FSAs) produce the gold standard economic data that employers, investors, job seekers, workers, and policymakers rely on to assess the health of the U.S. economy. Today, FSAs face historically unprecedented threats to their capacity and even their independence. This raises the specter of a future where FSA data cannot be relied upon to honestly report whether the U.S. economy is experiencing dysfunction.

This dashboard displays a range of data not collected or disseminated by FSAs to shed some light on the economy during the pause in government data collection during the shutdown and—even more importantly—to provide an accountability check against efforts to manipulate FSA data in the future.

This set of “next-best” data sources is clearly inferior to the datasets that have historically been collected and analyzed by the nonpartisan, expert professionals who staff FSAs. Among many other relative weaknesses, these next-best data offer no insights on how the economy is affecting U.S. households differently by race, gender, or ethnicity.

Data Accountability Dashboard

Indeed job postings vs. BLS JOLTS

    

Indeed job postings correlate strongly with total job openings from the Bureau of Labor Statistics’ Job Openings and Labor Turnover Survey (JOLTS). JOLTS job openings tend to fall in recessions and rise in expansionary periods.

The Indeed Hiring Lab, the research arm of job search website Indeed.com, publishes a job postings data index that aggregates a complete count of all job postings on the Indeed website. This includes a measure of new job postings, which only counts job postings the first time they are visible. The data—available starting in February 2020—are collected daily and reported as a seven-day average. For this comparison, we take monthly averages of the seasonally adjusted daily data.

In the figure, we show that Indeed new job postings track closely with job openings from JOLTS. The correlation between these measures between February 2020 and August 2025 is quite high (0.95).

While Indeed data are only available for the last five years, JOLTS data go back to 2000 and show a clear relationship between job openings and business cycles. Job openings tend to fall in recessions and rise in expansionary periods. That relationship is clearest in the 2001 and 2007 recessions and expansions, where a fall in job openings preceded the start of the recession.

In the wake of the government shutdown, the Indeed new job postings can give use some information on the state of new positions needed by employers. Moving forward, a strong and sustained divergence of trends between the Indeed and BLS measures could provide a worrying signal of degraded data quality or integrity in BLS reports.

Data Accountability Dashboard

ADP employment vs. BLS private-sector payrolls

    

Monthly changes in ADP employment levels tend to track changes in private-sector payroll employment from the BLS Current Employment Statistics, and both measures show that private-sector employment growth falls in recessions and rises in expansionary periods.

The ADP National Employment Report is a monthly measure of the private-sector labor market based on aggregated payroll data of more than 26 million U.S. workers. ADP Research, a research arm of the ADP payroll processing firm, releases the report monthly. While the report provides much detail of employment by firm characteristics, the topline number in the report is private-sector employment changes, available since January 2010.

ADP employment changes track closely with the Bureau of Labor Statistics (BLS) measure of private-sector payroll employment in the Current Employment Statistics survey, data that is published every month as part of the Employment Situation Summary, also known as jobs day. In the figure, we compare seasonally adjusted monthly changes in employment for each measure smoothed to three-month moving averages. These smoothed changes are highly correlated (0.76).

While ADP data are only available as of 2010, BLS private-sector employment data goes back to 1938 and shows a clear relationship between the number of jobs and business cycles. Employment falls in recessions and rises in expansionary periods. The close relationship between these measures allows us to track any notable and sustained divergence, which would indicate a concern about the quality of government data.

Data Accountability Dashboard

Revelio vs. BLS employment data

    

Revelio Labs generates monthly U.S. employment estimates by counting social networking profiles on sites like LinkedIn. Total nonfarm employment changes from Revelio generally track BLS-based estimates.

Seasonally adjusted and nonseasonally adjusted estimates from Revelio are released monthly by industry, occupation, and geographic region. National data are available as of 2021. The data are normally published the day before the BLS employment report is released. Historically, Revelio’s monthly change usually falls below the BLS estimate, but over relatively short periods of time, the data series do tend to rise and fall together.

Data Accountability Dashboard

Challenger, Gray & Christmas vs. BLS unemployment rate

    

The Challenger job cut report data are somewhat noisy on a month-to-month basis, but spike noticeably during recessions.

Challenger, Gray & Christmas collects its job cut data by tracking public announcements made by U.S. companies in both the private and public sectors. The job cuts can include cuts in multinational plants (i.e., outside the United States). The report has been published monthly since 1994 and is typically released at the end of every month or the first week of the following month. The figure shows that large increases in announced job cuts occur in recessions (and when the unemployment rate spikes).

Of note, the spike in layoffs in spring 2025 was partially driven by announced layoffs in the federal government.

Data Accountability Dashboard

State-level UI claims vs. BLS unemployment rate

    

Monthly changes in unemployment insurance claims track the unemployment rate and provide a useful indication of recessionary periods.

While the U.S. Department of Labor (DOL) aggregates unemployment insurance (UI) claims data and is the source of the national data, it relies on administrative data processed at the state level that are generally posted on state government websites, potentially allowing a real-time accuracy check if concerns are raised about the accuracy of data released through the DOL portal. During the shutdown, the number of initial and continued claims has been updated weekly on the 539 report, a DOL-compiled dataset based on information submitted by state unemployment insurance offices. Right now, the data are only available on a nonseasonally adjusted basis because of the shutdown. The figure displays continued (or insured) UI claims and the unemployment rate, both as 12-month moving averages to remove some volatility and seasonality.

Continued UI claims closely track the unemployment rate: They spike during recessions and fall during economic recoveries. The close relationship between UI claims and the unemployment rate allows us to track any notable and sustained divergence, which could indicate a concern about the quality of government data. More information on the UI claims data, including initial claims, federal claims, and state-specific data, is updated weekly on EPI’s UI claims page.

Data Accountability Dashboard

Google Trends vs. BLS unemployment measures

    

Google Trends provides real-time data on the relative frequency of search terms for a given keyword, category of keywords, or a topic. With the right search terms, we can construct an index that tracks the overall unemployment rate

Google Trends is a publicly available database maintained by Google that provides Search Volume Indices. Search Volume Indices are a measure from 0–100 of the relative search intensity (number of searches for a given keyword divided by total searches) by geographic location and period. The data are updated in real time and are available from 2004 onward.

Google Trends data can be benchmarked to several different economic indicators. In fact, academics have used Google Trends data to “nowcast” GDP, private consumption, unemployment, recessions, and health outcomes. The figure shows the monthly average of select labor market-related search terms and the unemployment rate. The Google Trends relative search frequency for these terms tracks the unemployment rate and spikes during recessions. The close relationship between these measures allows us to track any notable and sustained divergence. Any prolonged increase in the search frequency of these select search terms could indicate a recessionary period.

Data Accountability Dashboard

Economic policy uncertainty vs. recession indicators

    

The economic policy uncertainty (EPU) index clearly responds to business cycle downturns—spiking sharply during the recessions of the early 1990s, early 2000s, late 2000s, and the COVID-19 pandemic.

The EPU index is calculated by Baker, Bloom, and Davis, and their full methodology can be found here. The index aggregates information from three basic components: search results from 10 large national newspapers measuring the volume of news articles discussing economic policy uncertainty; the number of federal tax code provisions set to expire over the next year; and the degree of disagreement among economic forecasters about future levels of key economic variables.

While the EPU is clearly cyclical, it does rise during some non-recessionary periods, most notably in the early 2000s and from 2011–-2013. The early 2000s increase is almost surely driven by the Iraq War. From 2011–2013, a rolling series of economic crises in the Eurozone, as well as short-term extensions of expiring provisions from the tax cuts passed in the first George W. Bush administration explain the spikes. The very large spike in early 2025 was related to the “Liberation Day” tariff announcements.

Data Accountability Dashboard

University of Michigan consumer sentiment data vs. recession indicators

    

Sharp falls in consumer sentiment are often followed shortly by recessions.

The University of Michigan consumer sentiment index has been calculated since 1960 (and has been calculated monthly since 1978). The index is derived from answers to five survey questions that have categorical answers (that is, their questions provide survey respondents with two to three possible responses to choose from, for example, “Would you say that your (and your family) are better off, or worse off financially than you were a year ago?”).

For each question, the University of Michigan researchers calculate a relative score for answers that subtracts the unfavorable responses from favorable responses. The sum of responses is then compared with a base value from 1966.

The index reached lows in 2022 that were comparable with most recessionary periods, despite a very strong economy. The clear explanation for that was the sharp inflation spike in late 2021 through mid-2022. Early 2025 saw similarly low measures, likely driven by concerns over the potential effects of tariffs.

Because the 1966 base year was a long time ago, it seems fair to ask if there are structural changes that might reliably change the level of consumer sentiment over time. For example, if rising inequality (or anything else) made U.S. households consistently less happy about their relative economic situation over time, they might generally have a lower “baseline” level of favorable sentiment.

To assess this, and to evaluate whether the University of Michigan consumer sentiment index might be useful for assessing the broader health of the economy, the figure below shows changes in the level of consumer sentiment and changes in inflation-adjusted personal consumption expenditures (the broadest level of household spending). The theory is that consumers’ sentiment about the economy should correlate positively with their actual spending patterns. The pattern is clear: Changes in consumer sentiment do indeed coincide tightly with changes in consumer spending.

Data Accountability Dashboard

Data Accountability Dashboard

Chicago FED's flow consistent unemployment rate (FCR) vs. BLS unemployment

    

The Chicago Federal Reserve flow-consistent unemployment rate (FCR) combines several sources of labor market data to predict monthly unemployment rates. The Chicago Fed FCR closely predicts the official unemployment rate published by the Bureau of Labor Statistics (BLS).

Twice a month, the Chicago Federal Reserve publishes the Real-Time Unemployment Rate Forecast, which predicts the BLS unemployment rate in advance of its official release. The key ingredient in this prediction is the Chicago Fed’s flow-consistent unemployment rate, which is in turn a prediction of Current Population Survey job finding and separation rates using real-time data like UI claims; Google Trends index for unemployment; Bloomberg consensus unemployment rate forecasts; Indeed and Lightcast job openings; ADP employment levels; weekly Morning Consult unemployment and job search activity; Conference Board labor market differentials; and JOLTS layoffs, discharges, and hiring rates. As a result, the Chicago Fed labor market indicators are partially based on U.S. government data, but they can be extended even in the absence of government data releases.

A recent EPI report surveyed trends in labor force participation in the United States in recent decades. Besides presenting basic facts, the report also reviewed the research literature on the determinants of these trends, and the effects of policy changes. This policy brief focuses on one theme from the report: the need for patience when crafting a response to labor force participation trends. This need for patience applies to two main aspects of crafting policy:

Patience in diagnosing determinants of labor force participation trends

A previous wave of research in labor force participation in the mid-2010s came to erroneous and overly pessimistic conclusions simply because it examined a period when the economy was still cyclically depressed. The labor market still had excess slack from the collapse in aggregate demand that caused the Great Recession of 2008–2009. Once this slack was mostly wrung out of the labor market by the late 2010s (and the mid-2020s), many key measures of labor force participation began improving (with a substantial lag). An analogy to the mistake of trying to diagnose structural trends in the economy when it was still plagued by cyclical weakness would be trying to assess how effectively a marathon runner had been training for the past year by timing a race run when they were still recovering from a bad flu.

Patience in allowing for reasonable lags between the implementation of policies and positive results from those policies

As noted above, labor force participation rates are some of the last macroeconomic variables to recover fully from a cyclical downturn—responding with a considerable lag even to short-run changes in the macroeconomy. Further, because labor force participation is positively linked to workers’ skills and credentials, durably boosting economywide participation rates requires a broad and long-lived investment in these skills and credentials. This obviously takes time. In fact, the most promising interventions to raise labor force participation in the long run are likely significant investments in the health and education of today’s children. The payoff to this investment (even in narrow labor force participation terms) is significant and large but will obviously take a substantial amount of time to fully realize—even decades—as childen grow to adulthood and participate in the labor force.

Patience in diagnosis

Economic researchers are often interested in disentangling structural from cyclical effects on various outcomes. For example, in 2000 the unemployment rate averaged 4%, and in 2010 it averaged 9.6%. Researchers might want to know how much of the higher unemployment rate in 2010 was driven simply by the economy being in a different phase of the business cycle in 2010 versus how much was driven by long-running structural forces on the labor market that were unrelated to the business cycle. In theory, drivers of long-running structural trends might include changes in technology that displaced workers or changes in the age structure or educational attainment of the population.1 In regard to 2000 and 2010, however, all of the difference in unemployment rates between those years can be accounted for by cyclical factors: In 2000 the economy was booming with strong aggregate demand, and in 2010 the labor market was in recession and economywide spending was extremely weak. 2

In practice, the easiest way to disentangle structural from cyclical factors in driving trends in economic variables is to look at changes in these variables from business cycle peak to business cycle peak, essentially measuring outcomes only when something close to full employment had been reattained. In the 2010s, many researchers made premature declarations about structural trends about U.S. labor force participation because they did not wait until a business cycle peak was reached to compare with past peaks. This led to misleading conclusions.

The long tail of the Great Recession and why it led to pessimistic forecasts of labor force participation

In 2008, the United States entered what was then its worst economic crisis since the Great Depression—often referred to as the “Great Recession.” The unemployment rate rose to 10% in 2009 and remained above its 2007 average for the next decade. Despite clear evidence that economic growth remained demand-constrained and that the labor market was characterized by substantial slack even as late as 2015, a number of studies were published in the 2010s, aiming to assess structural trends in labor force participation. When these studies included post-2008 data points and assumed these data points were indicative of long-run structural trends, a notably pessimistic picture of labor force participation emerged.

This pessimism was driven by two large considerations, one true and one overstated. The true consideration was that the U.S. population is aging steadily over time, and demographic pressures were always going to see a rising ratio of retirees to active labor force participants. The overstated consideration concerned likely future labor force participation declines among prime-age workers (adults between the ages of 25 and 54). Recent decades had seen a long-running decline in prime-age male labor force participation, a recent stagnation of prime-age female labor force participation since 2000, and a sharp drop in both after 2007.

The confluence of these trends led many of the studies from the 2010s to project a future with a substantially smaller labor force. For example, one of the most influential of these mid-2010s papers (Aaronson et al. 2014) forecast that the overall labor force participation rate in 2019 would be 61.8%, and that in 2022, it would be 61%. In fact, 2019 saw an overall labor force participation rate of 63.1%, and in 2024 it was 62.6%. These are significant differences: Every 1 percentage point increase in labor force participation implies roughly 2.75 million more adults in the workforce, so these projections essentially lowballed the size of the labor force in recent years by close to 4 million workers.

It is certainly true that demographics—particularly population aging—are putting steady and predictable downward pressure on overall labor force participation rates. But the degree to which prime-age labor force participation was on a steep downward trend after 2007 was overestimated. And a large part of this overestimation was simply due to trying to infer structural determinants of labor force participation in the 2010s when the economy remained cyclically depressed. For example, Hall (2014) began his comments on the Aaronson et al. (2014) paper with the following (emphasis added):

The substantial decline in labor-force participation in recent years has raised the important question: How much of this decline is the result of the slack labor market from the Great Recession, and how much comes from other, structural forces? As the unemployment rate has returned to normal, a concern has developed that some of the people now classified as out of the labor force are, effectively, unemployed, but they are not included in the standard unemployment count because they do not satisfy its fairly exacting standards for classifying people as unemployed.

But the unemployment rate in 2014 had decisively not “returned to normal.” It averaged 6.2% over the year compared with the 4.6% average for 2007 (which, itself, was not particularly low). The Aaronson et al. (2014) paper included a figure (Figure 13 in their paper) that also showed what their projections for future labor force participation would have been if they had simply ignored the post-2008 data. These projections were far closer to what actually occurred in the period after their paper was written.

In short, by incorporating the 2010s data that was infected with cyclical weakness when they were trying to estimate a structural trend, their projections were too pessimistic. As Figure A shows, in 2016—a year that saw the overall unemployment rate dip below 5% for the first time in 8 years—prime-age labor force participation began rapidly recovering and continued recovering as overall unemployment rates fell further. By 2024, after years of extremely strong post-pandemic labor markets, labor force participation rates had actually regained the levels of the late 1990s. The evidence here is that there was little in the way of structural downward pressure on labor force participation; it was all driven by excess unemployment.

The best course of action for those who want to use the most timely data and do not want to have structural trend estimation marred by cyclical effects is simply to wait until a full business cycle has run its course and measure from peak to peak. This does not fully neutralize all cyclical effects (some business cycles end even before the economy has reached full employment), but this degree of patience would help a lot in correctly diagnosing trends.

The misdiagnosis in the mid-2010s about the likely trend of future labor force participation could have had serious repercussions. The state of labor force participation is a key variable when trying to assess what the level of potential gross domestic product (GDP) is. If one estimates this potential GDP as being too low relative to its true level, policymakers will stop aiming to boost aggregate demand and will settle for a level of actual GDP that is quite a bit below its true potential. This, in turn, will keep many potential workers from ever finding jobs, and the resulting too-slack labor market will fail to generate acceptable levels of wage growth. In turn, the federal budget deficit will be too high as tax collections hover below what could have been achieved if genuine full employment had been reached.

Patience in waiting for prescriptions to have an effect

In 2024, the biggest observable correlate with labor force participation is educational attainment. Labor force participation rates of workers with a college degree, for example, are 15.6 percentage points higher than for workers with a high school diploma.

Figure B

To the degree that a significant portion of this educational gradient in labor force participation reflects the causal influence of greater educational attainment in improving participation rates, this implies that measures that raise educational attainment would lead to higher labor force participation. This educational gap in labor force participation is often underrated as a source of economic inequality, and hence, also underrated as a possible margin along which educational investments might boost living standards.

For example, it is well known by now that greater educational attainment leads to higher annual (and lifetime) earnings. What is often underestimated is how often this premium is calculated conditional on working. But labor force participation for college graduates is 14.4 percentage points greater (or roughly 25% higher) for workers with a college degree, relative to those with a high school diploma. The National Center on Education Statistics (NCES 2024) reports that workers with a bachelor’s degree have annual earnings that are 59% higher than those with a high school diploma. But if we account for nonparticipation of college and high school workers (essentially assigning zero earnings to the share of each group not participating in the labor force), this would raise the annual earnings gap to roughly 105%, and almost a quarter of it would be accounted for simply by the higher labor force participation rates of college graduates. 3

Investing in children has large beneficial effects but will take decades to realize

The need for patience stems from the obvious fact that investments to boost educational attainment of the labor force will take considerable time: Colleges (including community colleges) and other forms of workforce development require mobilizing resources, and those being trained and educated need time to absorb new skills.

Further, the biggest payoffs to upfront investments in the name of boosting economywide labor force participation will come from investing in children—and particularly in early childhood. Investments in high-quality pre-kindergarten, for example, have very high social rates of return in large part because the children receiving these investments grow up to have higher earnings and stronger labor force attachment than other children do. But these benefits take considerable time to develop. For example, Lynch and Vaughul (2015) document that the annual payoff from a large investment in high-quality pre-kindergarten in year 1 of the investment is roughly 2% as high as the payoff in year 20. This is true even after accounting for the some considerable “real-time” effects of investing in early childhood education—like the boost to parents’ labor force participation when affordable, high-quality child care options are available.

Other research shows that investments in children’s health (including their nutritional health) also have high payoffs in terms of greater labor market success when they become adults. For example, Hoynes, Schanzenbach, and Almond (2016) found that children’s access to food stamps (or Supplemental Nutrition Assistance Program (SNAP) benefits) led to higher rates of high school completion and higher labor market earnings. Bailey et al. (2024) similarly found that access to SNAP increased their measured human capital as adults. Miller and Wherry (2019) found that infants who gained access to Medicaid in utero via their mothers’ prenatal coverage also had increased high school graduation rates. Brown, Kowalski, and Lurie (2020) found that eligibility for Medicaid during childhood increased college enrollment rates and taxes paid as adults.

The earnings effects of exposure to both Medicaid and high-quality early childhood education (ECE) are large. Brown, Kowalski, and Lurie (2020) find that each year that a child is covered by Medicaid adds 0.5% to their earnings as adults. This implies Medicaid coverage over an entire childhood would raise future earnings by as much as 9%. Lynch and Vaghul (2015) find that exposure to high-quality ECE can raise earnings of affected children by 25%–40%. If the total earnings effects of a large investment in children today were earnings that were 40% higher decades from now for children exposed to these greater investments, this necessarily implies a large effect on labor force participation. For example, if a quarter of these earnings effects were driven by higher labor force participation rates and just a tenth of U.S. children were exposed to these higher investments, this would imply a boost in labor force participation for this cohort’s lifetime of over a percentage point. The earnings effects of these interventions would provide a very substantial offset to their upfront fiscal costs. 4

Finally, a common finding across this literature is that effects are largest when they begin when children are young—even in utero. This implies that policymakers hoping for a payoff in labor force attachment from raising investments will need to display a lot of patience. The payoff might only begin in 10–20 years, and the full payoff could well take over 50 years. Patience is not a widely recognized virtue in U.S. policymaking, but it is one that could pay off greatly, should it be practiced in the form of investing today in children’s improved health, nutrition, and education.

Acknowledgments

The author thanks Joe Fast for research assistance and Grace Park for editing. This project was made possible by financial support from the Peter G. Peterson Foundation.

Notes

1. For example, if higher educational attainment causally increases labor force participation rates (something discussed in section two of this brief), then an increasing share of workers having college degrees should boost labor force participation over time. Another example going in the other direction concerns the potential negative causal effect on labor force participation of a spell of incarceration—if such a spell leads to lower labor force participation after re-entry, the large rise in the number of Americans with a spell of incarceration in their past would lower labor force participation rates overall.

2. Evidence of this can be seen in the fact that unemployment rates by 2018 and 2019 were actually lower than they were in the late 1990s and 2000s. Evidently there was no permanent structural shift keeping unemployment from falling back to these levels.

3. We can calculate the average relative earnings per member of the population (rather than per worker) by multiplying the 1.59 relative earnings advantage of those with a college degree by 1.28—which is the ratio of the prime-age employment-to-population ratio of workers with at least a college degree relative to the rest of the workforce. This gives 2.05, for a 105% relative earnings advantage. Since we know that 28% of this advantage is due to the higher employment-to-population ratio, we know that this is over a quarter of the advantage. Finally, if we do the same exercise but use the ratio of prime-age labor force participation rather than employment-to-population ratio, this gives us a relative earnings measure of 2.00—which indicates that 2.00/2.05 of the total effect of higher relative employment is driven by higher labor force participation of college workers rather than by lower rates of unemployment—still over a quarter of the entire advantage.

4. Lynch and Vaghul (2015) find this for early childhood education, and a Congressional Budget Office (CBO) working paper (Ash et al. 2023) finds that allowing Medicaid to offer “continuous eligibility” to children—allowing children to remain on Medicaid for 3 years, even after they may no longer quality for it based on current income tests—could boost future earnings enough that higher taxes could finance between 49% and 197% of the upfront cost of this policy change.

References

Aaronson, Stephanie, Tomaz Cajner, Bruce Fallick, Felix Galbis-Reig, Christopher Smith, and William Wascher. 2014. Labor Force Participation: Recent Developments and Prospects. Brookings Papers on Economic Activity. The Brookings Institution, Fall 2014.

Ash, Elizabeth, William Carrington, Rebecca Heller, and Grace Hwang. 2023. “Exploring the Effects of Medicaid During Childhood on the Economy and the Budget.” Congressional Budget Office Working Paper 2023-07, November 1, 2023.

Bailey, Martha J., Hilary Hoynes, Maya Rossin-Slater, and Reed Walker. 2024. “Is the Social Safety Net a Long-Term Investment? Large-Scale Evidence from the Food Stamps Program.” Review of Economic Studies 91, no.3: 1291–1330. https://doi.org/10.1093/restud/rdad063.

Brown, David W., Amanda E. Kowalski, and Ithai Z. Lurie. 2020. “Long-Term Impacts of Childhood Medicaid Expansions on Outcomes in Adulthood.” Review of Economic Studies 87, no. 2: 792–821. https://doi.org/10.1093/restud/rdz039.

Bureau of Labor Statistics (BLS). 2025. Online Data Retrieval Tool from the Current Population Survey Database–Labor Force Participation Rates for Workers Between the Ages of 25 and 54, Overall and by Educational Attainment. Accessed September 2025.

Economic Policy Institute (EPI). 2025. “Number of Labor Force Participants.” [web], State of Working America Data Library. Published 2025.

Gould, Elise, Sarah Jane Glynn, Hilary Wething, and Josh Bivens. 2025. 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. Economic Policy Institute, September 2025.

Hall, Robert. 2014. Comments on Stephanie Aaronson, Tomaz Cajner, Bruce Fallick, Felix Galbis-Reig, Christopher Smith, and William Wascher. 2014. Labor Force Participation: Recent Developments and Prospects. Brookings Papers on Economic Activity. The Brookings Institution, Fall 2014.

Hoynes, Hilary, Diane Whitmore Schanzenbach, and Douglas Almond. 2016. “Long-Run Impacts of Childhood Access to the Safety Net.” American Economic Review 106, no. 4 (April 2016): 903–934.

Lynch, Robert and Kavya Vaghul. 2015. The Benefits and Costs of Investing in Early Childhood Education: The Fiscal, Economic, and Societal Gains of a Universal Prekindergarten Program in the United States, 2016–2050. Washington Center for Equitable Growth, December 2, 2015.

Miller, Sarah, and Laura R. Wherry. 2019. “The Long-Term Effects of Early Life Medicaid Coverage.” Journal of Human Resources 54, no.3: 785–824. https://doi.org/10.3368/jhr.54.3.0816.8173R1.

National Center on Education Statistics (NCES). 2024. Annual Earnings by Educational Attainment. Condition of Education. U.S. Department of Education, Institute of Education Sciences. May 2024.

Established in the wake of the Great Depression through the Social Security Act of 1935, unemployment insurance (UI) is a critical safety net program that provides a partial replacement of wages to workers who have separated from employment. UI helps workers and their families afford their basic needs during spells of unemployment. It also helps stabilize the macroeconomy by keeping dollars flowing to local economies where layoffs and job losses could otherwise result in harmful drops in aggregate demand. UI is a forward-funded reserve, accumulating tax dollars during periods of economic stability to support workers during economic downturns.

Federal law establishes UI as federal-state partnership. Under the existing framework, the federal government sets baseline program parameters and raises revenue through Federal Unemployment Tax Act taxes to cover state administrative costs (e.g., processing claims or maintaining state unemployment trust funds), provide technical assistance, and conduct performance monitoring. States are responsible for paying worker benefits, although the federal government typically covers at least half of the cost of “extended benefits” during recessions. States have significant discretion to determine key features of their UI programs, such as eligibility criteria, benefit amounts and durations, and financing mechanisms.

What are the threats to state UI programs?

Unemployment insurance programs face mounting threats—some that are new, some from long-standing structural weaknesses that have left many state UI programs chronically underfunded and ill-prepared for economic downturns. In particular:

1. The Trump administration aims to weaponize UI systems to advance its mass deportation agenda: All workers in the U.S. with legal status (regardless of citizenship or nationality) are eligible for UI benefits, though immigrants who lack work authorization are not. Despite this distinction, in April 2025, Secretary of Labor Lori Chavez-DeRemer issued letters warning state governors against granting UI benefits to noncitizen workers, including those legally authorized to work. The letters threatened to withhold federal funds and directed states to verify the immigration status of UI applicants. Further, the U.S. Department of Labor recently proposed a rule change around UI data collection that poses risks to applicant privacy and could expand the risk of UI data being used for immigration enforcement.
2. The Trump administration’s rollback of merit staffing opens the door to UI privatization: Project 2025 calls for states to “innovate” with their UI programs by approving “non-public” organizations to administer benefits. This would dismantle long-standing merit staffing guidelines that require benefits to be administered by impartial career civil servants. Weakening merit staffing risks putting UI administration in the hands of actors who may not be impartial or accountable to the public. Although privatization of UI is explicitly prohibited by the Social Security Act, this backdoor approach erodes the public nature of UI administration. Research shows that introducing a profit motive for vital public services often results in reduced service quality, little cost savings, and less transparency, oversight, and accountability.
3. UI programs suffer from long-standing weaknesses that undermine their effectiveness as a safety net and economic stabilizer: Although unemployment insurance is a critical lifeline for unemployed workers, benefit levels replace less than 40% of wages on average, leaving many workers unable to meet their basic needs and disproportionately discouraging UI take-up among women and workers of color in low-wage jobs. Many states have also shortened benefit durations below the historical standard of 26 weeks, despite research showing such cuts reduce recipiency without improving employment rates or program solvency. At the same time, taxable wage bases and employer tax rates have eroded, starving trust funds. Most states now fail to meet federal solvency standards. Many states also rely on outmoded technology and understaffed state agencies to administer UI benefits and federal funding to modernize state UI systems was recently rescinded by the Trump administration. Finally, restrictive eligibility rules exclude large swaths of the workforce, including part-time and low-wage workers, women, Black and brown workers, misclassified workers, independent contractors, undocumented workers, and the self-employed. These weaknesses leave UI programs chronically underfunded, inaccessible to millions, and ill-equipped to protect workers or stabilize the economy during downturns.
4. Project 2025 seeks to weaken UI eligibility criteria by circumventing suitable work standards: Under federal law, workers can remain eligible for UI if they decline job offers that don’t meet a reasonable standard of suitability. Suitability definitions can vary by state but often consider factors such as health and safety conditions, wages, skills match, commuting distance, or other job characteristics when determining suitability. Some states’ suitable work requirements weaken the longer a worker is unemployed. Despite evidence that continued UI eligibility leads to better job matches and job quality, Project 2025 proposes providing states with waivers to suitable work requirements. Should waivers to this critical UI standard be adopted, workers could be disqualified from UI for turning down any job offer, no matter how unsafe, low-paid, or ill-suited to their experience. This would fundamentally weaken UI’s ability to facilitate good job matching, while putting workers in a precarious financial position following a job separation.

State lawmakers must act now to strengthen UI programs ahead of the next crisis

States lawmakers have broad authority over UI benefits, eligibility, and the financing of their states’ unemployment insurance trust fund, meaning they wield substantial power to ensure programs’ solvency and effectiveness when an economic crisis materializes. In light of the Trump administration’s anti-growth, inflationary economic policy and a softening labor market, policymakers must act with urgency to fortify UI programs.

Step I: Update state funding mechanisms to solidify trust funds and set basic minimum benefit standards

In recent decades, lawmakers in many states have sought to replenish unemployment trust funds by paring back benefits and restricting eligibility criteria. These efforts have largely failed to restore fund solvency or improve employment rates and have instead caused considerable harm to workers. State policymakers have the authority and tools to modernize their programs in ways that protect solvency without undercutting protections for workers. Policymakers should:

• Raise and index the taxable wage base to reflect the typical worker’s income: States have broad discretion in setting their taxable wage base (TWB), provided it meets or exceeds the exceptionally low federal minimum of $7,000. (As of 2025, the median state TWB is only $14,000.) States should link or index their TWBs to typical wages in their state. Currently, 18 states index their TWBs to the state’s average weekly wage, including Oregon (TWB of $54,300), Hawaii ($62,000), and Washington ($72,800). This ensures UI revenues keep pace with growth in the state economy, while creating a more equitable tax base and strengthening trust fund solvency. Adjusting taxable wage bases also allows states to generate more revenue at lower State Unemployment Tax Act (SUTA) rates. For instance, applying a 5.7% rate to a $7,000 tax base generates $400 in revenue per worker, while a much lower rate of 3.8% applied to a $21,000 tax base generates $800—twice the revenue. 
• Guarantee a minimum of 26 weeks of potential benefit duration: An extensive body of research finds that longer UI benefits do not meaningfully discourage work and any resulting increase in unemployment duration is offset by improved job matching, as workers find jobs with higher pay or that better match their skills. Prior to the Great Recession, all states offered at least 26 weeks of potential benefit duration (PBD) to eligible workers. Policymakers should ensure UI programs guarantee a minimum of 26 weeks of PBD.
• Raise benefit levels to afford workers a minimum standard of living: Low benefit levels mean low-wage workers—should they even qualify for benefits—often receive benefits that are unlivable. As a stepping stone to more ambitious and meaningful benefit level increases, lawmakers should set minimum benefit levels that working families can survive on: a benefit amount of at least 30% of the state’s average weekly wage or $300 per week (indexed to median wage growth), whichever is greater.

Step II: Improve program access and benefits to levels that make UI fulfill its core objectives

Unemployment insurance is one of the most important tools for reducing the harmful, reverberating effects of unemployment and one of the most effective programs for combatting recessions. Providing adequate benefits to unemployed workers leads to better reemployment outcomes, keeps dollars flowing in local economies, and ultimately lends itself to a more productive and dynamic economy. To this end, state policymakers should:

• Strengthen program administration and remove barriers to UI access: Applying for UI benefits is often a complex process and serves as a barrier to entry to workers who are navigating job loss. Underfunding and inadequate staffing of state and local UI administrative offices can compound these problems. Lawmakers should ensure that state agencies and UI offices have adequate resources to help applicants navigate the process and quickly process claims. In addition, the Century Foundation and Philadelphia Legal Assistance provide a comprehensive set of recommendations for state policymakers and agencies seeking to modernize UI systems and reduce barriers to access.
• Automatically extend UI benefits in difficult economic conditions to strengthen the program’s role as a macroeconomic stabilizer: When UI programs do not scale with market conditions, this deepens the damage caused by recessions. To better leverage UI’s stabilizing potential, states should utilize the optional Total Unemployment Rate (TUR)-based extended benefit program to guarantee workers can receive up to 20 weeks of extended benefits during severe economic crises. As of 2023, only 27 states and territories utilize the optional TUR-based trigger. Although optional state extended benefit programs carry some budgetary costs, they can help mitigate the long-lasting scarring effects of an economic contraction. 
• Set benefit levels that offer real protection for workers: State laws governing wage replacement and benefit maximums vary widely, but some states have adopted benefit formulas that provide much stronger protection. For instance, in 2024, Hawaii’s program provided an average weekly benefit of $653 (57% of worker wages), Washington’s average weekly benefit was $722 (51% of wages), and Massachusetts’s was $704 (48% of wages.) The National Employment Law Project’s policy brief describes optimal formulas for computing benefits.
• Establish a dependent allowance to allow parents and caregivers to fulfill their obligations: Households with children are much more likely to face food and housing insecurity when a job is lost. Dependent allowances, already enacted in 13 states, can help mitigate these harms by recognizing the added burdens that caregivers face. Policymakers should adopt similar measures and define dependents broadly to reflect the diversity of family structures and care responsibilities.
• Make short-term compensation (“work-sharing”) more appealing for employers and workers: During economic downturns, employers often resort to layoffs to reduce costs, harming workers financially and businesses in lost skilled labor. Under a short-time compensation (STC) (or “work-sharing” arrangement), firms can reduce employee hours instead eliminating jobs, while UI benefits partially offset lost wages for workers. Currently 33 states have STC programs in place, but utilization remains uneven and low relative to comparable programs in OECD nations. States can strengthen STC programs by making firms of all sizes eligible, removing experience rating penalties, allowing employers to certify reductions in hours on behalf of workers, and ensuring earnings from other jobs are not counted against workers’ STC benefits. The Washington Center for Equitable Growth provides additional recommendations for reducing administrative barriers and engaging in employer outreach and education.

Step III: Modernize unemployment insurance to reflect the needs of a 21st century economy

The unemployment insurance system, designed in the 1930s, no longer reflects the realities of today’s workforce. It excludes many gig, part-time, and irregular workers, and inherits frameworks that are rooted in racism and sexism. Lawmakers should adopt more expansive frameworks for UI eligibility and accessibility by taking action to:

• Set progressive benefit levels that truly alleviate economic hardship: Policymakers can ensure UI systems truly alleviate economic hardship and strengthen worker bargaining power, while targeting those workers most in need, by progressively structuring benefits. A smart approach would replace at least 85% of wages for the lowest earners, gradually scaling down to 50% for high earners, and 30% for very high earners.
• Increase benefits duration to ensure workers have sufficient runway and better prospects when reentering the workforce: Evidence shows that when workers have a longer benefit runway, they have better reemployment outcomes, find jobs that better match their skills, earn higher wages, and are more likely to remain on the job. States should guarantee a minimum of 30 weeks of potential regular UI benefit duration.
• Raise or remove the ceiling on the taxable wage base: Policymakers can truly address solvency concerns by dynamically increasing or eliminating caps on taxable wage bases. States should set the TWB to at least half of the Social Security taxable wage limit ($176,100 as of 2025). Several states have successfully increased their TWBs by indexing to a high proportion of the average worker’s wage. Whether by raising the cap, indexing it to wages, or relinking it to the Social Security base, modernizing the taxable wage base would strengthen trust fund solvency and create fairer contributions across employers of low- and high-wage workers.
• Reform experience rating to eliminate harmful incentives to fight legitimate UI claims: Federal law requires states to adopt rules such that employers with higher rates of separations pay higher UI taxes. This approach, known as “experience rating” encourages workforce stability and helps ensure equity among employers by charging more of those who draw more heavily against unemployment trust funds. However, these rules create the perverse incentive for employers to block legitimate claims by encouraging workers to not file, challenging claims, or structuring their workforce to minimize the number of employees eligible for UI, such as relying on part-time or contract labor. States can remove these harmful incentives by experience rating employers based on changes in the number of hours worked by their employees or the number of workers they employ. Alaska, for example, implemented a “payroll decline quotient” method which ties tax rates to changes in payroll over time instead of the number of claims made by workers. Further, since some firms are indifferent to additional layoffs because of a capped experience rating tax, states can impose penalties on firms that persistently remain at the cap.
• Expand eligibility to all workers with demonstrated attachment to the labor force: State monetary eligibility rules should be reformed to guarantee coverage for all workers who demonstrate clear labor force participation. Rather than relying solely on workers meeting specific earnings thresholds, states should also allow workers to qualify based on hours worked. Specifically, any individual who works at least 300 hours during two quarters of a base period should qualify. This means a worker who performed 15 hours of work per week for 20 weeks across two quarters would be eligible for UI. Hours from all work arrangements should be counted toward the 300-hour minimum, given that low-paid workers often hold multiple jobs across different employers. States should also extend the base period for determining eligibility to six quarters of work, to prevent low-paid, seasonal, and temporary workers from falling through the cracks. Oregon is currently the only state with a hybrid model allowing workers to qualify based on either earnings or hours.
• Reform work-search requirements to account for issues that workers commonly face: Overly onerous work-search requirements increase benefit denials while failing to save money for UI programs. States should ensure work-search requirements are not so burdensome that active jobseekers lose UI benefits before finding a new and suitable job. For instance, states should allow workers to continue receiving benefits if they have good cause for missing an appointment or work-search verification. If a worker falls short of work-search requirements, they should lose benefits only for that week, instead of being permanently removed from the program. States should also allow workers engaged in education or training programs that may boost their employment prospects to continue receiving UI benefits. Further, they should ensure continuing eligibility for workers available for part-time work, not just those seeking full-time work.
• Enact strong suitable work requirements to boost worker reentry prospects: A core function of UI is to promote stable, quality reemployment; workers should remain eligible for UI if they decline a job that is a poor match for their skills or of substandard quality. The National Employment Law Project provides recommendations that states can adopt to ensure strong suitable work criteria, including: 1) comparing the wage offered by a new job to the occupation’s prevailing wage and factoring in the worker’s expertise, training, and experience; 2) maintaining standards of suitable work that do not weaken based on the length of unemployment; and 3) reviewing offers for temporary employment under a lens of prevailing labor market conditions.
• Expand eligibility criteria to cover workers compelled to leave their jobs for valid reasons: Historically, the UI program has failed to account for many of the reasons that might compel a worker to leave their job. States should adopt stronger good-cause quits provisions that include reasons such as leaving due to unsafe conditions, caregiving responsibilities, or harassment, while exploring broader eligibility criteria that provide benefits to workers who quit.
• Extend UI eligibility to striking workers: Allow workers engaged in labor disputes to access UI benefits under the same rules as other unemployed workers. While some states impose extra waiting periods for striking workers, policymakers should adopt no or minimal additional delays.
• Establish joblessness protections for independent contractors, self-employed, and undocumented workers: To function as a true safety net UI should cover all labor force participants, including self-employed workers, independent contractors, and undocumented workers who lose work. In recent years, California, Colorado, and New York have pioneered successful initiatives for covering contractors, self-employed, and undocumented workers. States should explore options for establishing similar programs to ensure workers excluded from traditional UI have access to similar safety net protections.
• Adopt clear legal standards to combat worker misclassification: When workers are wrongfully classified as independent contractors, they lose the labor protections of W-2 employees, including UI eligibility. Misclassification imposes heavy costs on both workers and state trust funds. Policymakers can address this by adopting Pennsylvania’s model, which presumes that any worker performing services is an employee unless the employer proves that 1) the worker is free from the employer’s control or direction in performing work and 2) the worker is customarily engaged in an independently established trade or business.
• Design programs to protect workers’ privacy: While some states have expanded wage records to include details such as occupation, industry, or work hours to better evaluate job quality and improve services, UI programs should ensure workers can apply for benefits without risking retaliation or exposure of sensitive personal data. The Century Foundation and Immigration Research Initiative recommend limiting data collection to what is necessary, prohibiting disclosure for nonprogram purposes, and requiring data safeguards, while allowing applicants to self-attest wherever possible. To ensure accountability, violations of privacy rules should carry clear penalties. This year, Maryland lawmakers introduced legislation to protect state databases from unauthorized sharing and immigration inquiries, offering model language for policymakers seeking to protect state data more broadly.

Additional recommended resources

• National Employment Law Project (NELP)’s State Unemployment Insurance Policy Hub;
• Reforming Unemployment Insurance: Stabilizing a System in Crisis and Laying the Foundation for Equity—a joint report of the Center for American Progress, Center for Popular Democracy, Economic Policy Institute, Groundwork Collaborative, National Employment Law Project, National Women’s Law Center, and Washington Center for Equitable Growth;
• The Century Foundation’s Unemployment Insurance Data Dashboard. 

Editor’s note: This piece was revised on October 8, 2025, to add an “Additional recommended resources” section and clarify the need to increase UI funding both to strengthen benefits and ensure effective UI program administration.

Further, this move radically undermines what Trump says his own goal is: lowering U.S. interest rates to spur faster economic growth. Instead, it will likely raise interest rates over the long term and lead to higher costs for working people.

Why will this happen? The interest rates that truly influence economic growth are long-term rates generally set in financial markets. These longer-term rates are usually strongly influenced by the Fed’s decisions over the shorter-term rates it controls directly—but that’s only because the Fed has, until now, been seen as a non-political, evidence-based institution. If the Fed instead becomes politicized, its influence will falter, and changes it makes to short-term rates will have far less effect on the long-term rates that influence economic growth.

Presidential capture of the Fed would signal to decision-makers throughout the economy that interest rates will no longer be set on the basis of sound data or economic conditions—but instead on the whims of the president. Confidence that the Fed will respond wisely to future periods of macroeconomic stress—either excess inflation or unemployment—will evaporate. As a result, investors will demand higher premiums to hold on to U.S. Treasury bonds (and other long-term bonds), because without faith that the Federal Reserve will tamp down inflationary pressures when they appear, they will need reassurance—in the form of higher long-term interest rates—to hold on to these investments.

These higher long-term rates will ripple through the economy—making mortgages, auto loans, and credit card payments higher for working people—and require that rates be held higher for longer to tamp down any future outbreak of inflation. In the first hours after Trump’s announcement, all of these worries seemed to be coming to pass.

The source of the allegation of mortgage fraud against Governor Cook is also extremely concerning: a public announcement by the head of the Federal Housing Financing Authority (FHFA), the agency that oversees Fannie Mae and Freddie Mac. The FHFA has access to mortgage information for tens of millions of U.S. households—access that could be abused by a politically-motivated agency looking to harm perceived political opponents of the president. This seems clearly to be what is happening in the Cook case. Under an honest and well-run administration, any potential impropriety identified by FHFA staff in the normal course of their activities would have been referred (without public notice) to the Department of Justice, which would have conducted an investigation without any public comment. Only if the allegations rose to the level of an indictment would a public announcement be made. That the FHFA has been weaponized to find damaging allegations against a perceived political opponent of the president is deeply worrying.

EPI urges the courts to act quickly to overturn this unlawful dismissal and to reaffirm the independence of the Federal Reserve, which is critical to the health of our economy and our democracy.