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.

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.

Who are low-income families of color?

Families in which the household head identifies as

• Black
• Hispanic
• American Indian or Alaska Native (AIAN)
• Asian American or Pacific Islander (AAPI)

With at least one child under the age of 18 living at home

With a total family income below 200% of the federal poverty line (below $64,300 in 2025 for a family of two adults and two children)

Introduction

Low-income families of color live in a permanent cycle of economic insecurity and uncertainty. These families make up a disproportionate share of the nearly 10 million families with children (9.7 million) who are either poor or vulnerable to poverty. As a result of their economic precarity, these families are among the first to experience the painful consequences of a recession. This was evident during the last two business cycle downturns: the Great Recession and the pandemic recession. We find that these two economic contractions dealt a mighty blow to the employment security of these families, triggering a rise in poverty and housing insecurity.

Given the weak policy response to the Great Recession, it took economically vulnerable families of color nearly a decade to recover in nearly all the economic domains we examine, including employment, poverty status, and housing insecurity. While the bold response to the pandemic recession led to a relatively faster rebound in employment, economically vulnerable families of color remain disproportionately burdened by poverty and housing insecurity.

Instead of easing the pain of economically vulnerable families, the Trump-Vance administration and congressional Republicans have been on the attack in the first half of 2025. They have gone after the agencies, laws, and programs that help protect these families from joblessness, discrimination, poverty, hunger, and premature death. In just its first 100 days, the administration deliberately cut the wages of workers, rolled back protections against bias in employment, and hacked away at staffing at agencies that support the well-being of low-income families (like the Department of Education and the Department of Health and Human Services). As if this weren’t enough, the administration and congressional Republicans prioritized dealing a historic blow to Medicaid and Supplemental Nutrition Assistance Program (SNAP). They cut spending on programs that provide desperately needed health care and nutritional support to families by more than $1 trillion (CBO 2025b).

The chaos and uncertainty ushered in by the economic mismanagement of the Trump-Vance administration even led to the first quarterly contraction in economic growth since 2022. With the prospects of another recession rising, the administration has done everything in its power to leave low-income families even more vulnerable to the pain ahead. As we illustrate in this report, economic downturns hit these families the hardest, and while we’ve learned a great deal since 2007 about how to protect them, the administration has chosen not to build upon those lessons. Instead of protecting the strong labor market they inherited, empowering workers to bargain for better pay and working conditions, and strengthening basic needs programs, the Trump-Vance administration is fighting for an economic agenda centered on austerity for the economically vulnerable and subsidies for the rich.

In just a short period of time, the Trump-Vance administration has left low-income families more economically insecure and vulnerable to pain as recession risks continue to rise

Since taking office, the Trump-Vance administration has worked to dismantle the basic protections that help shelter low-income families from even deeper economic insecurity and hardship. This attack on families has taken the form of executive actions undermining civil and workers’ rights. While some of President Trump’s executive orders have been challenged in court, their introduction has altered the policy discourse and the lived experience of low-income families of color throughout the U.S. with an explicitly racist and xenophobic agenda. Beyond executive actions, the Trump-Vance administration and congressional Republicans also passed one of the most sweeping cuts to the U.S. social safety net in recent history, gutting basic needs programs and making Medicaid and SNAP benefits much more difficult for families in need to access (Shierholz 2025). All of this was done to help offset the cost of tax cuts that disproportionately benefit rich households and corporations (The Budget Lab 2025).

Few policy issues have received as much priority in the Trump-Vance administration as their attack on economic justice and initiatives promoting diversity, equity, and inclusion (DEI). In just his first day in office, President Trump rolled back numerous executive actions expressing the federal government’s commitment to racial justice for Black, Hispanic, Native American, and Asian American, Native Hawaiian, and Pacific Islanders (EPI 2025d). President Trump later also rescinded executive actions that identified systemic barriers impeding Black Americans’ opportunity to fully participate in American society on a level playing field (EPI 2025e). Equity in the classroom is also under attack. This was evident when President Trump rescinded an executive order stating that all students should be guaranteed an educational environment free from discrimination, including discrimination in the form of sexual harassment, sexual violence, and on the basis of sexual orientation or gender identity (EPI 2025c). These efforts form part of more than a dozen executive actions signed by President Trump in his first 100 days to roll back years of progress on racial and economic justice (McNicholas et al. 2025).

The Trump-Vance administration is also working to roll back anti-discrimination protections by weakening the Equal Employment Opportunity Commission (EEOC) (Maye and Wilson 2025). Just days into his second term, President Trump dismissed two EEOC commissioners and the agency’s general counsel, years before the expiration of their appointment (Olson and Savage 2025; EPI 2025b). As a result of these dismissals, the commission lost the quorum needed to perform key functions. Trump has also redirected the EEOC’s priorities to focus more on investigating so-called DEI-motivated race and sex discrimination and anti-American national origin bias and discrimination (EEOC 2025; DOJ 2025). Because wages are the primary source of income for low-income families, weaker enforcement of anti-discrimination laws leaves families of color more vulnerable to employment and pay discrimination in the labor market.

The EEOC is not the only federal body that the Trump-Vance administration has weakened to the detriment of low-income families. In March 2025, President Trump signed an executive order that would effectively eliminate the U.S. Department of Education (ED). The U.S. Supreme Court later lifted a lower court decision that had blocked the administration from firing more than 1,300 employees at ED (Sherman 2025). While the merits of the case before the Supreme Court have yet to be decided, the gutting of ED will disproportionately harm children from low-income families of color that benefit from federal funding for under-resourced schools and programs aimed at closing learning and achievement gaps (Dianis 2025; EPI 2025a; Santhanam 2025).

More broadly, ED serves an essential role in helping enforce Title VI of the Civil Rights Act, which prohibits discrimination based on race, color, or national origin in programs or activities that receive federal financial assistance (ED n.d.). Even the U.S. public health infrastructure is now under attack, as the Trump administration is committed to carrying out layoffs at federal health agencies focused on reducing premature and preventable deaths associated with pervasive racial health disparities (Moore 2025).

President Trump’s attacks on federal agencies that are vital to the provision of public goods and services for families are part of a larger war his administration has waged on workers. In his first 100 days, Trump replaced the leadership of the National Labor Relations Board (NLRB)—the federal agency tasked with protecting the most fundamental U.S. labor rights—with members more likely to carry out his agenda to erode workers’ union and collective bargaining rights (McNicholas et al. 2025). This will hurt the ability of workers to form and join unions at work. Unions are vital to working families, as union workers enjoy better wages and working conditions than their nonunion peers (Banerjee et al. 2021).

Beyond executive actions, the main legislative priority of the Trump-Vance administration imposed more than $1 trillion in cuts to basic needs programs in exchange for continuing a tax regime that overwhelmingly favors rich households and corporations (CBO 2025b; Shierholz 2025). Extending the 2017 tax cuts that President Trump enacted in his first term will not just favor the rich disproportionately. On its own, this extension can even suppress economic growth over the long run and leave policymakers with significantly less room to respond to another recession (Bivens 2025b). To help offset the cost of these large tax cuts to the rich, the Republican-led budget reconciliation bill that Trump signed into law adds more stringent work requirements to Medicaid and SNAP on top of historic cuts.

This combination will leave more than 22 million families at risk of losing some or all of their SNAP benefits and strip away health coverage for more than 11 million people (CBO 2025a; Wheaton et al. 2025). These cruel and misguided efforts will disproportionately hurt low-income families of color and children who are more likely than their peers to rely on Medicaid and Children’s Health Insurance Program (CHIP) for health insurance, and SNAP and other nutritional assistance programs to avoid going hungry in the face of growing food insecurity (Cid-Martinez, Moore, and Maye 2025; Cid-Martinez 2025).

In its totality, the policy positions President Trump has advanced in his first 100 days via executive orders and legislative priorities will leave low-income families of color and children much more vulnerable to hardship. In the face of a recession, which is no longer a hypothetical scenario, the consequences would be devastating. The Bureau of Economic Analysis (BEA) reported the first quarterly contraction of economic growth since 2022, and while growth climbed again in the second quarter, the U.S. economy is now growing significantly slower in the first half of 2025 than in the previous year (BEA 2025). And the chaotic economic climate that the current administration has generated with its trade, immigration, and macroeconomic policy management has increased the prospects of a recession (Bivens 2025a).

The fear of an approaching recession increased with the downward revision of employment gains that defined the weak jobs report published in August 2025 (EPI Staff 2025). What we see in the first half of 2025 is an economy being held back by anemic growth and a deteriorating labor market.

The upheaval that this administration has produced leaves low-income families of color exposed to future hardship. Without a bold policy response to recessions and the support of a strong welfare state, these families are hit hardest by economic downturns and sluggish economic recoveries (Bivens et al. 2025). This report sheds light on this reality by examining how the last two recessions impacted the well-being of low-income families, as captured by their employment situation, poverty status, and housing insecurity.

Low-income families of color with children and the last two recessions

What do we mean by low-income families of color with children?

The sample of families included in this analysis are those in which the household head has at least one child of their own, under age 18, living at home. Within these households, there may also be other members who have children under 18. Families of color are broadly defined as those whose household head identifies as Black, Hispanic, American Indian or Alaska Native (AIAN), or Asian American or Pacific Islander (AAPI).[1]

We further restrict this sample to a subset of economically vulnerable, or low-income, families, defined as having total family income below 200% of the federal poverty threshold.[2] To place the poverty threshold in context, the federal poverty line (FPL) for a single individual in the 48 contiguous states (excluding Alaska and Hawaii), and Washington, D.C., is $15,560 in 2025. While the FPL increases by $5,500 for each additional family member, a year-round worker earning the federal minimum wage ($7.25 an hour) can’t afford to keep their family out of poverty in 2025 (Hickey and Cid-Martinez 2025). For the remainder of this report, we will use families (of color) to refer to families (of color) with children, and the terms “economically vulnerable” and “low income” will be used interchangeably.

Drawing a demographic portrait of economically vulnerable families

While our main economic analysis is focused exclusively on Black and Hispanic families due to data limitations associated with the sample size of other groups, this section provides a demographic picture of low-income families of color more broadly. Table 1 shows low-income families by race and ethnicity, using data from the 2023 American Community Survey (ACS). As depicted in Table 1, families of color are generally overrepresented among the 9.7 million families with children that are economically vulnerable. While Black, Hispanic, AIAN, and AAPI families collectively account for 44.4% of all families with children, they represent 61.1% of economically vulnerable families with children. Although white families make up a larger share of low-income families than any other single racial or ethnic group, they are underrepresented among low-income families (38.9%) relative to their share of all families (55.6%).

More than 3 in 10 (32.6%) low-income families are Hispanic and more than 1 in 5 (21.5%) are Black. Together, Black and Hispanic families represent more than half (54.1%) of all low-income families with children, but just over one-third (35.1%) of all families with children. While less than 1.5% of all families are AIAN, they too are slightly overrepresented (1.8%) among the economically vulnerable. AAPI families account for 7.9% of all families and 5.2% of economically vulnerable families; however, the aggregate socioeconomic status of AAPI families hides important differences that become evident when we separate groups by country of origin (Cid-Martinez and Marvin 2023).

Immigrant families also make up a disproportionate share of low-income families and are especially prevalent among low-income Hispanic and AAPI families. Foreign-born families made up 23.6% of all families in 2023, but a higher share (30.5%) of low-income families were immigrant families. Slightly more than 8 in 10 (81.1%) economically vulnerable AAPI families are foreign-born, as are more than 6 in 10 (61.9%) comparable Hispanic families.

Beyond economic insecurity, these families face ongoing threats under Trump’s draconian mass deportation agenda, which the administration and congressional Republicans bolstered with new financing in the budget reconciliation bill that Trump signed into law (Costa 2025; NIJC 2025). These attacks on immigrant families and the immigrant workforce will also have ripple effects on the labor market, costing the U.S. economy nearly 6 million jobs, particularly in construction and child care (Zipperer 2025). All of this will also put upward pressure on food and housing prices (McNicholas et al. 2025).

In terms of family structure, low-income families are generally more likely to be headed by women or a non-married household head.[3] However, one finds noticeable variations in these patterns across racial and ethnic groups. For example, Black and AIAN families are most likely to be headed by women, 78.7% and 69.5% respectively, compared with less than half (43.3%) of low-income AAPI families. There are also differences in marital status. Low-income AAPI families are significantly more likely to be led by a married couple (76.2%), compared with about half of white (50.5%) and Hispanic (51.6%) families. More than one-third of low-income AIAN families and one-quarter of low-income Black families are led by married couples. Apart from Black families, less than 1% of low-income families report having a partner or spouse of the same sex in 2023. Because most low-income Black families are headed by women, attacks on women’s reproductive rights, along with efforts to undermine nondiscrimination enforcement for racial and ethnic minorities, women, and LGBTQ+ individuals, impose additional disadvantages for these families.

Economically vulnerable families are also more likely to have more than one child (under age 18): 67% of low-income families have two or more children, compared with 58.7% of all families. However, among low-income families, there is little variation in the number of children across racial and ethnic groups. For example, about two-thirds of all low-income families has two or more children, and only 12.6% have four or more children.

The share of low-income families with either a disabled child or parent of a child shows considerable variation across race and ethnicity. AIAN families stand out as having the highest prevalence of disability. About 1 in 3 (33.7%) AIAN households has a parent or child with a disability. Similarly, more than one-quarter of white families, and more than 1 in 5 Black and Hispanic households have a parent or child with a disability. AAPI households had the smallest share (16.2%) of households with a disabled parent or child.

The share of low-income families that is a part of intergenerational households varies significantly by race and ethnicity group. More than 1 in 8 (13.1%) AAPI households are multigenerational or intergenerational, followed by 7.8% of Hispanic households and 5.9% of AIAN households. Economically vulnerable white families are the least likely to be intergenerational, as less than 4% have a grandparent in the household.

Table 1

The Great Recession and the pandemic recession: Differences and similarities

As this report contrasts the economic experience of families during two different recessions, it is important to first understand the severity and duration of these events.

By official accounts, the Great Recession began in December 2007 and ended in June 2009, representing the longest economic downturn to impact the U.S. economy in the postwar period (NBER 2010). We assess the severity of the Great Recession by examining the impact that it had on the labor market via the employment situation of workers of color (EPI 2025g). These workers are among the first to lose a job during a downturn of the business cycle. Between 2007 and 2010, for example, the unemployment rate for Hispanic workers more than doubled, rising from 5.6% to 12.5%. Similarly, the unemployment rate for Black workers shot up from 8.3% in 2007 to 15.9% in 2010. While the recession had been declared officially over by 2009, it took nearly a decade for the unemployment rate of workers of color to fully recover. This prolonged suffering was largely due to the anemic policy response that followed the Great Recession, largely characterized by austerity measures at both the federal and state levels (Bivens 2019; Bivens 2011). 

Compared with the Great Recession, the pandemic recession was considerably shorter. Officially, the pandemic recession only lasted two months, from February 2020 to April 2020, making it the shortest economic contraction in U.S. history (NBER 2021). But this doesn’t mean that the impact on workers was less severe. Just between February 2020 and April 2020, the unemployment rate for Hispanic workers more than tripled, and that of Black workers more than doubled.

Unlike previous contractions, the economic impact on women was particularly pronounced (Alon et al. 2021).[4] By April 2020, more than 1 in 5 (20.3%) Latina workers were out of a job and seeking employment, as the unemployment rate of these workers quadrupled between February and April of that year.[5] Similarly, the unemployment rate of Black women more than tripled during this period, rising from 5% in February 2020 to 16.4% in April 2020.[6] The nature of the economic shock explains much of the disproportionate impact on these workers, as the public health crisis and mitigation efforts fell most heavily on low-wage industries and occupations in which women of color are overrepresented due in large part to occupational segregation (Wilson 2020).

Despite the sharp rise in joblessness caused by the pandemic recession, the economic suffering didn’t last as long as during the Great Recession. Within two years, the unemployment rate for Black and Hispanic workers had fully recovered to 6.2% and 4.3% respectively, reaching historical lows (EPI 2025g). Black women and Latinas experienced similar rebounds; by 2022, the unemployment rate for Black women and Latinas (at 6.2% and 4.4% respectively) was among their lowest in recorded history (EPI 2025g). This swift and atypically even rebound was not just a function of a much shorter recession. As we detail later in this report, the swift and bold policy response to the pandemic and the economic contraction that followed was qualitatively different from that of previous recessions in the United States. Rather than the austerity and conditional support provided during the Great Recession, policymakers responded to the pandemic crisis with more generous cash transfers and extended support for unemployed workers and families with children.

Weathering crises: How did the last two recessions impact the employment security, poverty status, and housing insecurity of economically vulnerable families?

In this section, we examine how the Great Recession and the pandemic recession impacted the well-being of low-income families in three domains: their employment security, poverty status, and housing insecurity.

Employment security: Labor market attachment of families and employment rate of parents

One way of assessing the impact that business cycle downturns have on the economic well-being of families is by examining the impact that these events have on their employment security and attachment to the labor market. Since earnings represent the primary source of income for most families, involuntary separation from the labor market is likely to magnify the economic hardship experienced by these households. In this section, we examine changes in the labor market attachment of economically vulnerable families by looking at the share of families with at least one full-time earner and by capturing shifts in the employment rate of parents between the ages of 25 and 54.

Labor market attachment

Given the importance of work for low-income families, the prevalence of full-time employment in the household provides a measure of their attachment to the labor market. On average, more than two-thirds of low-income families had at least one full-time earner before the Great Recession. However, as can be seen in Figure A, differences in attachment existed by race and ethnicity even before the crisis. In 2007, 63.6% of Black families had at least one full-time earner, compared with more than 67.7% of white families and 77.7% of Hispanic families.

The Great Recession, and the weak policy response that followed, left a major dent in the labor market attachment of families. By 2010, the attachment gap between white and Black families had widened, as only 56% of Black families had at least one full-time earner that year, compared with 63.1% of their white counterparts. The share of low-income Hispanic households with at least one full-time earner also fell by nearly 10 percentage points, from 77.7% in 2007 to 68.1% in 2010. Comparatively, the rate of attachment for white families dropped by less than five percentage points during this period. While Hispanic families were more likely to report a stronger attachment to the labor market than their white peers, this advantage declined during the crisis and its aftermath. Overall, Black and Hispanic families took nearly a decade to recover, as their attachment to the labor market remained below the pre-crisis level in 2016. 

Leading to the COVID-19 pandemic and the recession, families of color regained a significant measure of the employment they had lost during the Great Recession. By 2018, for example, 64.4% and 76.6% of Black and Hispanic families respectively had at least one full-time earner. Largely due to the much shorter duration of the contraction and the robust policy response that followed, the pandemic recession had a much more muted impact on the labor market attachment of these families. Between 2018 and 2020, the share of economically vulnerable families of color with at least one full-time earner in the household declined only marginally, by about three percentage points for Black and Hispanic families.

By 2022, the share of Black families with a full-time earner had rebounded to 68.1%. This figure was nearly identical to the attachment rate for white families in the same year, and it represented the highest rate for Black families since 2007. While that number declined in 2023, it was still higher than in most years since 2007. On the other hand, by 2023, Hispanic families continued to lag considerably behind their 2007 peak.

Figure A

Employment rate of prime-age low-income parents

Examining changes in the prevalence of full-time earners within the household can provide us with a sense of the impact that crises have on the annual labor market attachment of families. But it does not capture monthly changes in the employment situation of parents over the business cycle. This is particularly important in the context of the pandemic recession since it represents the shortest economic recession in U.S. history. To best capture the impact that this economic contraction had on the employment situation of economically vulnerable parents of color, we examine changes in the employment-to-population (EPOP) ratio of low-income parents between the ages of 25 and 54.

In Figure B, prime-age Hispanic parents enjoyed higher employment rates than their Black and white peers before the pandemic. This pattern is also consistent with those shown in Figure A. Leading to the pandemic in January 2020, 94.7% of low-income Hispanic parents between the ages of 25 and 54 were employed, compared with 89.8% of white parents and 88.6% of Black parents, who face the greatest employment disadvantage historically.

As evidenced in Figure B, the gap in employment between Black and white prime-age parents widened during the pandemic recession. Much of this is explained by the disproportionate impact that the pandemic recession had on parents of color. Between January 2020 and April 2020, the employment rate of prime-age low-income Black and Hispanic parents plummeted by more than 32.7 and 27.0 percentage points respectively. By April 2020, only around half (55.9%) of prime-age Black parents had a job. At this point, prime-age Hispanic parents also saw their employment rate drop to a low of 67.7%. While the employment rate of white parents declined by 17.6 percentage points between January 2020 and April 2020, these parents remained about 29% and 7% more likely to be employed in April 2020 than their Black and Hispanic peers respectively. 

While the employment rate of parents of color declined to historically low levels in 2020, the bold policy response to the pandemic recession led to a quick rebound in the labor market. By the end of 2023, 88.9% of prime-age low-income Black parents and 91.6% of their Hispanic peers had a job. The strong recovery of parents of color also helped narrow the racial gaps in employment seen at the height of the pandemic recession in April 2020.

Figure B

Poverty status: Prevalence of poverty and severe poverty

As low-income families are largely dependent on wage earnings to meet their financial obligations, business cycle fluctuations can significantly affect their economic vulnerability. Without a proportional policy response or adequate social protection systems, these families are the first to fall victim to material hardship during an economic downturn. The Great Recession and the pandemic recession exemplify this, as these crises pushed more low-income families of color into poverty and severe poverty. This is evident when we examine changes in the prevalence, severity, and distribution of poverty over time.

Prevalence of poverty

Leading to the Great Recession, economically vulnerable Black and Hispanic families were more likely than their white peers to fall below the federal poverty line (FPL).[7] In 2007, more than half (53.6%) of low-income Black families were poor, relative to 44.6% and 38.7% of Hispanic and white families respectively (see Figure C). The Great Recession and the inadequate policy response to the downturn pushed a larger share of these families into poverty quickly and for a prolonged period of time. By 2010, more than half (51.2%) of Hispanic families fell below the FPL. The poverty rate for Black families continued to rise the following year, reaching nearly 6 in 10 (58.5%) in 2011. The poverty rates of both Hispanic and Black families did not return to pre-Great Recession levels until 2015, more than half a decade later. While racial gaps first widened and then narrowed throughout the crisis and the slow recovery, poverty rates remained much higher among Black and Hispanic families, relative to their white counterparts. 

By the lead-up to the COVID-19 pandemic and the recession that followed, the poverty rates of families of color were lower than they were in 2007, but a large racial poverty gap remained. While less than half (49.3%) of Black families fell below the FPL in 2018, they remained about 30% more likely to suffer material hardship than their white peers.

Largely because of policy, the material situation of families was not impacted as severely by the pandemic recession as it was during the Great Recession. While Hispanic families experienced a marginal increase in poverty between 2019 and 2022, rising by 3.3 percentage points (relative to the larger increase, of 6.6 percentage points, during the previous downturn), the share of Black families that fell below the FPL during this period declined. By 2022, low-income Black families recorded the lowest poverty rate (44.1%) in the entire period between 2007 and 2023. After economic relief measures expired, poverty rates were relatively stable for Hispanic families but had increased for Black families.

Figure B

Prevalence of severe poverty 

Economic downturns don’t just push economically vulnerable families into poverty. Without the support of a strong social safety net, families can fall deeper into economic deprivation when parents lose their jobs during a recession. The parents struggle to make ends meet and provide their children with the resources they need to flourish and to participate in society without shame. This happened far too often during the Great Recession as an increasing share of low-income families experienced severe poverty, with an income below half (50%) of the federal poverty line. To place this figure in context, the severe poverty threshold for the 48 contagious states and Washington, D.C., amounts to $7,825 annually for a single individual in 2025 (HHS n.d.).

Before being hit by the Great Recession, more than 1 in 4 (26.1%) Black families suffered severe poverty in 2007 (see Figure D). At this stage, Black families were about 61% more likely than their white peers to fall among the poorest of the poor. While Hispanic families fared relatively better in 2007 (with a severe poverty rate close to that of white families), disparities quickly widened. By 2010, more than 1 in 5 (21.6%) Hispanic families fell among the poorest of the poor, and an even larger share (30.3%) of Black families experienced similar material hardship, compared with 18% of their white peers. The anemic policy response to the Great Recession left an elevated share of these families under a prolonged state of economic deprivation until about 2015.

The strong policy response to the pandemic recession prevented a large uptick in the prevalence of poverty, especially for Black families, but severe poverty rates rose significantly for families as the material shortcomings of the most vulnerable worsened. Between 2018 and 2020, the share of Black families that fell among the poorest of the poor increased by 4.7 percentage points, from 22.5% to 27.2%. Hispanic families fared slightly better, as the severe poverty rate for these families rose from 15.6% in 2018 to 18.9% in 2021.

While the exposure of families of color to severe poverty fell in 2022, reaching a historic low of 22% for Black families, severe poverty again rose once economic relief measures ended. By 2023, the share of Black and Hispanic families among the poorest of the poor remained above the pre-recession levels of 2018. In contrast, severe poverty among white families had returned to the pre-recession rate by 2023.

Figure D

Housing insecurity: Prevalence and severity

Business cycle downturns that lead to significant job losses don’t just leave low-income families more vulnerable to poverty. Recessions also leave families much more exposed to housing insecurity, irrespective of whether these families own or rent their homes. As we illustrate below, this is because housing represents a significant expense for resource-constrained families. Low-income families of color are particularly vulnerable to even more pain during downturns as they are also forced to contend with an economy that suffers from an obstinate deficit in affordable housing and one in which the housing and lending markets have historically discriminated against them (Moore and Maye 2024).

In this section, we examine the impact that both the Great Recession and the pandemic recession had on the rent and homeownership rates of families of color. We also look at how the cost burden of housing evolved for both renters and homeowners during and after the crises.

Renters and housing insecurity

Given the high economic barriers to homeownership, Black and Hispanic families are generally more likely to rent, relative to their white peers (see Appendix Table 1). But, as homeownership rates declined during the Great Recession, the share of low-income families who rent has increased. Leading to the COVID-19 pandemic, in 2018, more than 80% of Black families and more than 70% of Hispanic families were renters. In contrast, slightly more than half (55.3%) of white families rented their homes that same year. While the share of renters was lower post-pandemic, racial gaps widened in 2023 with Black and Hispanic families being 61% and 36%, correspondingly, more likely to rent than their white peers.

The pandemic and the short economic downturn that followed exacerbated the already precarious position that low-income renters found themselves in after the Great Recession. By 2017, nearly a decade after the Great Recession, the share of economically vulnerable families that spend 30% or more of their income on rent remained above the pre-recession levels of 2007 (see Figure E). In 2018, for example, more than 8 in 10 Black and Hispanic families that rent were housing poor. The strong pandemic recovery did little to shelter these families from the housing affordability crisis in the U.S. that was amplified by the global health crisis (Moore and Maye 2024). By 2023, racial gaps had widened as the share of Black and Hispanic families that spend over 30% of their income on rent climbed above the peaks reached in the aftermath of the Great Recession.

Figure E

The impact of the last two recessions on families fell most heavily on those that spend more than half of their income on rent. While some of these renting families had recovered by the time that the pandemic recession rolled in, the share of Hispanic families experiencing severe housing insecurity remained above pre-recession levels in 2019 (see Figure F). Black families were particularly disadvantaged. Nearly half (48.3%) of low-income Black families spent over half of their income on rent in 2019. The situation quickly worsened for all families, as the strong economic recovery failed to protect these families from the growing affordability crisis in housing. By 2023, a higher share of white, Black, and Hispanic families spent more than half of their income on rent than at any other point since 2007. Low-income Black and Hispanic families remain most disadvantaged, as more than half of these families spend over 50% of their income on rent.

Figure F

Homeowners and housing insecurity

The Great Recession deepened the racial divide in homeownership rates, as families of color were disproportionately touched by the crisis (see Appendix Table 1). The share of low-income Black families that owned their home declined from 21.5% in 2007 to 15.7% in 2016, and from 34.6% to 28.3% during the same period for their Hispanic peers. By 2017, a decade after the start of the crisis, the homeownership rate of families had yet to recover, and racial disparities had widened. At this stage, economically vulnerable white families were 169% and 48% more likely than their Black and Hispanic peers respectively to own their home. 

Despite the steep gaps in homeownership, the pandemic recession didn’t quite lead to a suppression of homeownership rates for families. Partly as a function of younger households transitioning toward ownership, low interest rates, and the generous (albeit temporary) economic relief measures enacted in response to the pandemic recession, the downturn failed to reverse the gains in homeownership that economically vulnerable families of color were already experiencing in 2018 and 2019 (Sanchez-Moyano 2024; Callis 2023).

By 2023, slightly more than one-third (34%) of low-income Hispanic families owned their home, compared with about 3 in 10 (29.7%) in 2018. Black families also experienced gains. During this period, the homeownership rate of low-income Black families increased by 5.3 percentage points, from 16.4% in 2018 to 21.7% in 2023. By 2023, the homeownership of low-income Black and Hispanic families had achieved a near full recovery from both the Great Recession and the pandemic recession. While these achievements in homeownership helped narrow racial disparities, economically vulnerable families of color remained significantly less likely to own their homes in 2023 compared with their white peers.

While owning a home can be an important step toward wealth creation, economically vulnerable homeowners spend a significant share of their income on housing costs associated with mortgage payments, taxes, insurance, and more (U.S. Census Bureau 2004). Leading to the pandemic recession, Black homeowners remained more likely to spend over 30% of their income on housing costs (see Figure G). At this stage in 2019, 65.2% of economically vulnerable Black families who owned their homes were housing poor, compared with fewer than 6 in 10 Hispanic and white families. Despite the economic relief measures that helped economically vulnerable families weather the shock of the pandemic recession, housing insecurity rose for nearly all families. By 2023, a slightly higher share of Black and Hispanic families who owned their homes spent over 30% of their income on housing than in 2019.

Figure G

The impact of the pandemic recession and the increasing cost of housing in the U.S. is even more evident when we examine the situation of low-income families suffering from severe housing insecurity (Moore and Maye 2024). These are homeowning families who spend over half of their income on housing. Despite the short duration of the most recent downturn, the share of economically vulnerable families who face severe housing insecurity climbed by more than four percentage points between 2019 and 2023 (see Figure H). By 2023, Black families remained disproportionately vulnerable to economic pain with a prevalence of severe housing insecurity comparable to the hardship they experienced in the lead-up to the Great Recession. Since 2007, more than 2 in 5 economically vulnerable Black families who own their homes were unable to escape severe housing poverty as a result of having to spend over 50% of their income on housing costs.

Figure H

Lessons learned: Key policy choices that made a difference during the pandemic recession and are still needed to break the cycle of economic vulnerability for families

By nearly every measure of economic well-being examined above, low-income families of color weathered the pandemic recession better than the Great Recession largely because of policy choices. The weak policy response to the Great Recession, centered on austerity at the federal and state levels, contrasted sharply with the bold response to the pandemic recession guided by economic relief measures and public investments. This enabled families to avoid a prolonged separation from the job market and a worsening of their material conditions.

The last two recessions and their distinct recoveries left us with a clear blueprint for action. The economic lessons are not unfamiliar:

• Full employment policies that create tight labor markets also promote economic equity for workers and their families.
• Good jobs are union jobs.
• A strong social safety net helps families avoid unnecessary and scarring economic deprivation.

Breaking the vicious cycle that leaves low-income families more susceptible to hardship during recessions will require a renewed commitment to full employment, stronger worker rights and unions, and a robust welfare state that meets the needs of families and children. While the policies that can accomplish these objectives commonly face political headwinds, actions taken by the Trump administration and Congress will create even worse conditions.

Full employment policies are equity-enhancing policies 

While economists debate the overall rate of unemployment that constitutes full employment, there is less debate about the equity-enhancing effects of a tight or “high-pressure” labor market, one in which willing workers can obtain access to a job and the working hours they prefer (Bivens 2021; Bivens and Zipperer 2018). Sustained periods of low unemployment can effectively boost the earnings of low-wage workers and help narrow persistent racial disparities in a labor market that disproportionately disadvantages the employment situation of workers of color and the economic well-being of their families (Wilson 2023; Bivens 2021). The narrowing of these gaps would not constitute full healing from the legacy and continued expression of structural racism and xenophobia in the U.S. economy, but it would be a step in the right direction. Historical evidence points to increased economic equity via low unemployment and rapid job growth. 

The recent economic recovery from the COVID-19 pandemic and the economic contraction that followed serves as a good example of a policy regime that aimed, in large part, to provide a strong or high-pressure labor market. Unlike the economic recovery from the Great Recession, the rebound from the pandemic recession has been characterized by bold fiscal policies, via much-needed relief and strategic public investments, and more accommodating monetary policy that kept downward pressure on unemployment (Wilson 2023; Bivens 2024; Bivens 2016). The results of this policy regime are unambiguously clear: Workers of color made historic gains over the last five years in both employment and earnings, with Black and Hispanic real wages (adjusted for inflation) growing more than three times faster over the last five years than the four decades prior (Cid-Martinez, Maye, and Marvin 2025).

Instead of providing continuity to the economic regime they inherited, the Trump-Vance administration is pursuing a macroeconomic and trade policy that is sowing economic uncertainty and chaos and has already led to a contraction of economic growth in the first quarter of 2025.

Unions help narrow economic disparities that hurt workers and their families

It is easy to envision growing income disparities that threaten the economic security of working families as endemic features of the U.S. economy. Between 1979 and 2023, for example, the real annual earnings for the top 1% of earners increased by 181.7%, while the earnings for the bottom 90% grew just 43.7% (Gould and Kandra 2024). This economic divide mirrors another increasing gap between economywide productivity and the hourly pay of the typical worker, a gap that is even more pronounced for the typical Black and Hispanic worker (Moore and Banerjee 2021). But none of these trends is inevitable.

Behind these rising inequities one finds a wide range of deliberate policies choices that have weakened labor standards and stripped workers of their ability to bargain collectively for better compensation and working conditions (Mishel and Bivens 2021), including the erosion of union membership since the late 1950s (Bivens et al. 2023b).

Workers of color have been disproportionately touched by the decline of union density in the U.S. economy since they typically receive a larger wage boost from union membership. Compared with the premium of the average worker, the union pay premium is higher for Black and Hispanic workers (Bivens et al. 2023a). Black workers, for example, are more likely than white workers to be unionized (13.1% vs 11.2%), and the wage advantage unionized Black workers receive from being covered by collective bargaining is 12.6% (EPI 2025f; EPI 2025h). This premium is higher than the 11.9% average wage premium for unionized white workers. While Hispanic workers have slightly lower union coverage (9.7%) than white workers, they claim a higher union wage advantage of 16.4%.

Unions can also protect workers from discrimination and improve working conditions. Because private employment in the U.S. is for the most part “at will,” employers can terminate workers for nearly any reason, without providing notice or severance. This power imbalance harms workers of color disproportionately, as they are more likely than their white peers to report unfair dismissals (Bivens et al. 2023a). Unions protect these workers with the provision of “just cause” rights that shelter workers from discriminatory and retaliatory practices and unfair dismissals. Unions also offer workers better employment conditions. This is important for economically vulnerable families who face care needs alongside scarce resources. Unionized workers, for example, are more likely than their nonunion peers to have access to paid sick days and employer-sponsored health and retirement benefits (Shierholz et al. 2024).

Low-income working parents stand to gain the most from union membership. However, few of them belong to a union. Only 8% of prime-age Black parents and 4.9% of Hispanic parents belonged to a union in 2023. Similarly, only 5.3% of economically vulnerable white parents between the ages of 25 and 54 belonged to a union in the same year.

Instead of strengthening the rights of workers to bargain collectively, President Trump has openly embarked on an anti-worker agenda centered on weakening the federal agency tasked with protecting the most basic and fundamental U.S. labor rights, the National Labor Relations Board (McNicholas et al. 2025). These efforts will leave families of color much more vulnerable to discrimination in the labor market and to wage theft and mistreatment at work.

The social safety net expanded in response to the pandemic, which demonstrated that poverty remains a policy choice

The welfare of economically vulnerable families of color and their children is not an insurmountable problem beyond the reach of public policy. This became most evident during the COVID-19 pandemic. The federal government responded to this crisis boldly with an array of economic relief measures, such as economic impact or stimulus payments; with provisional expansions of social programs like the Supplemental Nutrition Assistance Program and the unemployment insurance (UI) program; with temporary enhancements of tax credits, such as the Earned Income Tax Credit (EITC) and Child Tax Credit (CTC); and with increased federal assistance to state and local governments. Overall, these measures kept millions of people out of poverty in 2021 (Banerjee and Zipperer 2022). The economic impact or stimulus checks alone kept nearly 9 million people out of poverty in 2021, including more than 2 million children (Shrider and Creamer 2023).

The expanded social safety net had a notable impact on alleviating the material hardship experienced by families of color. This is most evident when we look at trends in the prevalence of child poverty. For this, we rely on child poverty rates based on the Census Bureau‘s Supplemental Poverty Measure, which accounts for cash and in-kind transfers as well as geographic differences in housing costs. By this measure, the post-pandemic social policy regime looks particularly effective in its ability to reach children of color and to alleviate the human suffering that accompanies deprivation at a young age. Between 2019 and 2021, for example, child poverty rates fell by more than half across nearly all groups, reaching their lowest levels in recorded history (see Figure I). Before the pandemic, more than 1 in 5 Black and Hispanic children fell below the supplemental poverty line in 2019. By 2021, these rates plummeted by nearly 60%, as the Black and Hispanic child poverty rate dropped to 8.3% and 8.4% respectively. The Asian American and AIAN child poverty rates also declined by more than 40% during this period, reaching historic lows of 5.1% and 7.4% respectively in 2021.

Many of the gains in poverty reduction were driven by the expansion of the Child Tax Credit (Gould 2022). Relative to all income transfers in 2021, the expanded CTC drove an estimated 44% of the reduction in child poverty that year (Parolin 2023). The impact was especially pronounced for children of color (Burns and Fox 2022). For example, this expanded credit lifted an estimated 1.2 million Hispanic children out of poverty in 2021. Similarly, more than 700,000 Black children and over 100,000 Asian children avoided falling below the supplemental poverty line in 2021 because of the expanded CTC. The rest of the social policy levers (aside from Social Security) that drove the bulk of the historic reduction in child poverty had also been provisionally expanded under the American Rescue Plan Act (ARPA), including EITC, SNAP, and UI benefits.

Despite the powerful effect these measures had in extinguishing poverty, nearly all the enhanced social safety net measures under ARPA expired by 2022. This purposeful expiration erased the bulk of the gains in poverty alleviation that families and children of color had achieved economically in 2021 (Cid-Martinez and Zipperer 2023). This is evident when we examine how the end of the expanded welfare state impacted the prevalence of poverty for children of color. Between 2021 and 2023, the poverty rates of Black, Hispanic, Asian, and AIAN children had more than doubled, returning to or exceeding 2019 levels (see Figure I). This increase marked an obliteration of the gains achieved in poverty reduction between 2019 and 2021. In fact, by 2023, the poverty rates of all groups were either higher, or no different, than the pre-pandemic estimates of 2019. 

Instead of expanding the CTC to help more low-income parents meet the basic needs of their children and reduce poverty, the Republican-led budget reconciliation bill that Trump signed into law fails to increase benefits for the 17 million children who receive less than the full value of the credit because their parents earn too little to meet the earnings requirement (Maag 2025). The Republican law is also particularly harmful to children of migrant parents, as it revokes the credit eligibility of children that are U.S. citizens if both spouses in a married couple lack a Social Security number (Tax Policy Center 2025). At least one spouse will now need to have a Social Security number in order for a U.S. citizen child to qualify for the CTC. While the Republican law increases the maximum credit from $2,000 to $2,200 per child, no significant changes in the refundability structure and earnings requirement mean that CTC benefits will remain out of reach for the children of the poorest of the poor, while middle- and high-income families continue to receive most of the benefits (Collyer et al. 2025; Crandall-Hollick, Maag, and Jha 2025).

The Republican budget reconciliation bill that the president signed into law also missed an opportunity to break the cycle of economic vulnerability that poor children face with the “Trump accounts.” These new tax-free investment accounts will provide a single government contribution of $1,000 to every child born in the next four years (Hamilton and Pressley 2025). The current administration is also discussing these accounts as a “back door for privatizing Social Security,” a program that helps narrow racial and income disparities, lifting more than one million children out of poverty in 2023 (Price and Mascaro 2025; Morrissey and Bivens 2025; Shrider 2024).

Unlike the more popular Baby Bonds, which require sustained contributions from the federal government throughout childhood with the goal of narrowing the racial wealth gap, the Trump accounts are built on the mistaken premise that low-income families lack an incentive to save when the real issue is that they lack enough discretionary income to put into a savings account (Markoff, Radcliff, and Hamilton 2025). The employment, income, and wealth disadvantages that low-income families with children face leave them in a perennial struggle to access basic necessities like health care, housing, and child care. These families are often an emergency away from falling into poverty or severe poverty. Helping families escape this generational challenge will require more than a new savings vehicle that will further widen the divide between the rich and poor by providing yet another giveaway to rich families.

Figure I

Conclusion

Low-income families of color were disproportionately impacted by the economic suffering that came in the wake of the last two recessions. Both the Great Recession and the pandemic recession worsened the employment security, poverty status, and housing insecurity of these families. In contrast with the Great Recession, policymakers responded to the pandemic with a show of strength that helped families recover their employment and bounce back from poverty significantly faster. But housing insecurity and poverty continue to leave these families particularly vulnerable when the next recession strikes.

While the prospects of a recession continue to rise due to the chaos and uncertainty generated by the Trump-Vance administration, they are deliberately ignoring the lessons of the past. This administration has failed to protect the strong labor market they inherited, has failed to empower workers to bargain for better pay and working conditions, and has failed to strengthen basic needs programs. Instead, the administration is proudly advancing an economic agenda that forces austerity on low-income families, strips away protection from discrimination for people of color, and offers more tax cuts for those who do not need it—the ultrarich. This economic agenda will push even more families into poverty and prolong the pain that follows a recession.

Appendix

Appendix Table 1

Acknowledgments

Support for this research was provided by the Robert Wood Johnson Foundation. The views expressed here do not necessarily reflect the views of the Foundation.

Notes

[1] Our classification of race and ethnicity is mutually exclusive, such that white families are non-Hispanic white, and Black families represent all families in which the head identified their race as Black in combination with other races. Hispanic families include those in which the head identified Hispanic origin, irrespective of race. Among the remaining pool, those who identified as American Indian in combination with other races are listed as AIAN, and respondents who identified as Asian or Pacific Islander in combination with other races (such as Asian and white or Pacific Islander and white) are listed as AAPI.

[2] Total family income is the sum of the individual incomes of each family member. Because unmarried partners are nonrelated household members, the unmarried partner’s total income is not incorporated in the primary family’s total family income. In cases where the income statuses of the household head and the unmarried partner are different, we use the income status of the household head.

[3] Similarly to race and ethnicity, the marital status of the family is informed by the status of the household head, such that married captures respondents who identify as married, irrespective of the presence of the spouse. All other responses are classified as not married.

[4] As we point out below, this disproportionately affected low-income families of color,  which are more likely to be headed by women.

[5] The unemployment rate here is captured by the seasonally adjusted unemployment rate of Hispanic women, 20 years old and over.

[6] The unemployment rate here is captured by the seasonally adjusted unemployment rate of Black women, 20 years old and over.

[7] This federal poverty line is informed by the official poverty measure (OPM) published annually by the Census Bureau since 1967. This measure uses a set of money income thresholds that vary by family size and composition to determine who is in poverty. While the Supplemental Poverty Measure (SPM) is considered to be a more accurate and comprehensive measure because it accounts for government transfers and geographic cost-of-living expenses, including housing, published estimates only go back to 2009 (Shrider 2024). For the purpose of this analysis, we rely on OPM to capture the impact of both the Great Recession and pandemic recession.

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Americans often tell pollsters that they think the economy is in recession, but this seems like a shorthanded way to express their frustration with the state of economic rewards in this country. And it is true that the U.S. economy—the richest in the history of the world—does a bad job of translating overall growth into true economic security for most families. Contrary to popular opinion, though, recessions rarely occur, and when they do, they make economic outcomes far worse and notably increase deprivation for typical families.

In short, the question of whether a recession is coming is not driven by political point-scoring, it cannot be assessed by quirky responses to poll questions, and it has dire and significant consequences for the material circumstances of tens of millions of American families.

Why have people been talking more about a possible recession lately?

Summary: Despite inheriting a strong and stable economy, the Trump administration has made policy announcements and commitments that are highly likely to cause a recession over the next year, unless they are reversed.

Read the full answer

Recent concerns about recession are 100% driven by poor policy decisions from the Trump administration. The macroeconomy was in an extraordinarily strong and stable state when it was handed off to the Trump administration. The historically high and broad tariffs the Trump administration has repeatedly threatened since early March would, by themselves, pose a recessionary threat to the economy. The chaotic way the administration has rolled out, retracted, changed, paused, and re-upped the tariffs have made things even worse by creating mammoth economic uncertainty as well, which nearly all economic observers think will lead to sharp contractions in several kinds of economic activity.

Figure A shows Google search trends for recessions, along with the dates of various tariff announcements.

Figure A

The International Monetary Fund said the following about global growth prospects in January 2025 (before President Trump’s inauguration):

The forecast for 2025 is broadly unchanged from that in the October 2024 World Economic Outlook (WEO), primarily on account of an upward revision in the United States offsetting downward revisions in other major economies…. Upside risks could lift already-robust growth in the United States in the short run, whereas risks in other countries are on the downside amid elevated policy uncertainty.

In April of 2025, a revision to these growth forecasts noted the following about the negative effects that the new tariffs would have:

Since the release of the January 2025 WEO Update, a series of new tariff measures by the United States and countermeasures by its trading partners have been announced and implemented, ending up in near-universal US tariffs on April 2 and bringing effective tariff rates to levels not seen in a century (Figure ES.1). This on its own is a major negative shock to growth. The unpredictability with which these measures have been unfolding also has a negative impact on economic activity and the outlook and, at the same time, makes it more difficult than usual to make assumptions that would constitute a basis for an internally consistent and timely set of projections.

Further, on April 9, the Goldman Sachs macroeconomic forecasting team moved their baseline scenario for the next year to recession, based on announcements of the “Liberation Day” tariffs. When the Trump administration announced a pause on tariffs, the forecast changed back to just under 50% chance of recession.

In short, there is universal agreement that the Trump tariff policy is bad for growth in substance and in implementation, and that this policy is driving increased risk of recession.

On top of the botched tariff policy, the other big threat to growth in the near term is a similarly chaotic effort to destroy capacity in the federal government. The administration has rolled back or ended federal employment and grants in numerous extralegal ways. These cutbacks could eventually be large enough to weigh on growth in the short term, and they will absolutely reduce longer-run growth as key public goods and services that complement private-sector growth-generating activities are no longer provided. Further, many of the key functions being hamstrung by recent cutbacks involve surveillance of potential economic risks—either financial, epidemiological, or climate-related. Impaired surveillance could well mean future risks (say of cascading bank failures or of another pandemic) wouldn’t be anticipated, and there wouldn’t be sufficient time to mount a strategic response, further harming growth.

All the uncertainty associated with bad policy implemented chaotically has led to the highest economic policy uncertainty readings since the beginning of the COVID-19 pandemic. This uncertainty is poison for all sorts of high-stakes spending decisions from businesses and households, and so these decisions will be deferred, and economic activity will begin contracting.

So far, the core data normally used to declare recessions have not signaled that a recession has begun. This could take a number of months (see answers to the questions below that talk a bit more about this data). But other data, often sentiment-based, is strongly signaling that a recession is very likely.

Are standard recession indicators clearly signaling an imminent economic contraction?

Summary: Not as of May 2025. Standard recession indicators do not look strongly contractionary at the moment. Since January 2025 there has been more weakening than strengthening in these indicators, but by themselves, they are not clearly showing signs of recession.

Read the full answer

As of May 2025 these standard indicators are not strongly signaling an imminent contraction. Table 1 shows a number of indicators used by the National Bureau of Economic Research to define recessions. It shows how these indicators slowed in the six months before the last two recessions before COVID-19 and then compares their pace of growth since January 2025 relative to their pace in 2024.

Table 1

In the last two nonpandemic recessions, growth in nearly all indicators slowed sharply in the six months before a recession hit. Since January 2025, of the 10 indicators for which data are available, growth has slowed in six and has not improved at all relative to 2024 for two indicators. Two indicators have seen faster growth so far in 2025 than in 2024.

So far, while more indicators are slowing in this table than not, without other information (discussed in more detail in the following question), this table would not generally raise huge concerns about a coming recession. But these indicators certainly bear watching.

Another commonly referenced recession predictor is the “Sahm rule” (when the rolling three-month average of the unemployment rate exceeds the lowest point this measure reached over the past 12 months by 0.5 percentage points, this often predicts a recession). The Sahm rule has already triggered one “false positive” in the past couple of years, but is not signaling a recession now (see Figure B for the Sahm indicator and thresholds).

Figure B

Do recessions clearly increase poverty and other measures of economic suffering?

Summary: Yes, recessions are strongly associated with higher poverty and greater material deprivation. During the pandemic recession and early recovery, government support was so unprecedentedly generous that the poverty increases spurred by the recession were swamped by poverty declines driven by government aid. But that recession was a clear outlier.

Read the full answer

The labor market is the main source of income for low-income families, and higher unemployment during a recession causes reductions in annual earnings, pushing more families below poverty income thresholds.

Figure C uses annual state-level data to show that higher unemployment rates are associated with higher poverty rates. In particular, a one percentage point increase in unemployment typically leads to a 0.6 percentage point increase in the standard poverty rate, or about 2.1 million additional people in poverty according to recent data.2

However, poverty rates are less likely to rise when there is stronger fiscal support to combat a recession, particularly when the fiscal support is targeted directly at lower-income households. This happened most recently during the COVID-19-induced recession in 2020 when expanded unemployment benefits, higher child tax credits, cash payments, and low interest rates directly benefited families and kept aggregate demand high. The annual unemployment rate more than doubled between 2019 and 2020, but the standard poverty rate based on pre-tax money income only rose by 1.0 percentage point. The supplemental poverty rate, which includes post-tax income, fell by 3.9 percentage points between 2019 and 2021, and only rose in 2022 after many of the COVID-19-related supports expired. Further, by the end of 2021, unemployment rates nearly returned to pre-recession levels.3

Figure C

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Notes:

2. A regression of state-level official poverty rates on unemployment rates from 1978 through 2023, with state and year fixed effects, weighted with mean state age 16 and over population levels, yields a coefficient of 0.623. In 2023, the poverty rate was 11.1%, and the poverty level was about 36.8 million people, so a 0.623 percentage point increase in poverty is equivalent to about 2.1 million people. Poverty rates, unemployment rates, and civilian population levels are available from the EPI State of Working America Data Library, retrieved May 9, 2025.

3. Official and supplemental poverty rates are available from the EPI State of Working America Data Library, retrieved May 9, 2025.

Who is hurt the most in recessions?

Summary: Workers with the least labor market leverage usually bear the largest costs of a recession. Concretely, this means that employment declines the most for Black and Hispanic workers, younger workers, and workers without a college degree.

Read the full answer

Due to discrimination and other structural inequalities in the labor market, Black and Hispanic unemployment rates are consistently higher than white unemployment rates. Black workers have unemployment rates that are twice as high as their white counterparts, and the 2:1 Black-to-white unemployment rate ratio implies that Black unemployment rates soar during a recession. Figure D shows that in every recession over the last four decades, Black and Hispanic workers have experienced a much larger fall in employment than white workers. During the Great Recession, for example, the Black prime-age employment-to-population ratio (the share of adults between the ages of 25 and 54 with a job) fell by 7.4 percentage points, while the white rate fell by 4.3 percentage points.

Moreover, Black workers experience higher unemployment for a longer period relative to white workers. White unemployment began to fall 19 months after the technical end of the Great Recession in June 2009, but Black unemployment only began falling after 26 months. Relative to their white counterparts, Black workers experienced higher unemployment rates, which have taken longer to fall in every recession since the 1980s. When there is a negative economic shock, Black workers experience larger declines and slower recoveries of prime-age labor force participation and employment rates. In addition, Black workers who remain employed see disproportionately lower wage growth than white workers during periods of higher unemployment.

Figure D

Summary: The large increase in inflation in 2021 and 2022 in the United States exposed just how little deep thinking had been done about the issue of inflation-control by macroeconomists and policy makers in preceding decades. The inflation of that time has often been attributed entirely to an excess of aggregate demand over potential output. But these years saw historically large shocks to the real economy stemming from COVID-19 and the Russian invasion of Ukraine. These shocks imposed extreme distortions on sectoral demand and supply, distortions which seem to have generated inflation globally, not just in the U.S. Further, temporary policies and circumstances (particularly pandemic fiscal relief and the whipsaw of massive layoffs and rapid rehiring efforts in labor-intensive service sectors) gave U.S. workers a pronounced but temporary boost in wage-bargaining with employers. Accordingly, a “shocks and ripples” analysis of inflation explains the data better than analyses based on movements in aggregate demand and supply.1

Starting in mid-2021, inflation in the United States rose to levels not seen since the early 1980s. This inflation followed on the heels of the economic shock imposed by the global COVID-19 pandemic and the significant fiscal policy interventions meant to smooth the fallout of this shock. As of October 2022, inflation—both headline and core measures—remained at historically high levels, though there are significant signs of softening in the near future (evidenced in part by the bending down of the quarterly data series shown in Figure A).

Figure A

This episode has sparked furious debate over the proper policy response, and it has exposed how little innovative thinking has been done on inflation by either macroeconomists or policy analysts since the 1980s price acceleration was ended by the Volcker shock. This report identifies a number of key questions raised by the inflationary outbreak of the past 18 months and offers some answers. A brief summary of these questions and answers is provided below. The remainder of the report then expands on these points.

Macroeconomic overheating is not necessarily the culprit for the inflationary surge of 2021 and 2022

In early 2021, debate raged about the potential economic effects of the American Rescue Plan (ARP). ARP, passed in early 2021, was explicitly designed as fiscal stimulus, with large and front-loaded transfers to households as its centerpiece, along with substantial aid to state and local governments.

Some critics of ARP worried about its potential effect on inflation. The most famous of these worriers was Larry Summers. Summers explicitly framed his concerns as centered around estimates of potential output. He posited that excess fiscal stimulus would push gross domestic product (GDP) well over the economy’s long-run potential to deliver, hence causing inflation. As he put it:

I agree with the general consensus of progressive economists that it would have been much better if the Obama administration had been able to legislate a much larger fiscal stimulus in early 2009, in response to the Great Recession. Yet a comparison of the 2009 stimulus and what is now being proposed is instructive. In 2009, the gap between actual and estimated potential output was about $80 billion a month and increasing. The 2009 stimulus measures provided an incremental $30 billion to $40 billion a month during 2009—an amount equal to about half the output shortfall.

In contrast, recent Congressional Budget Office estimates suggest that with the already enacted $900 billion package—but without any new stimulus—the gap between actual and potential output will decline from about $50 billion a month at the beginning of the year to $20 billion a month at its end. The proposed stimulus will total in the neighborhood of $150 billion a month, even before consideration of any follow-on measures. That is at least three times the size of the output shortfall. (Summers 2021)

This argument might benefit from an illustrative figure. The green line in Figure B shows the estimates of potential output referenced by Summers (“GDP in overheating scenario”). The blue line shows the Congressional Budget Office’s (CBO’s) predictions of what GDP growth would have been without ARP through the end of 2020, and actual GDP growth since that date. We then add in a line showing the path GDP would have taken had ARP pushed up actual GDP 1-for-1 with spending, leading real GDP to exceed potential in the manner described by Summers. In this figure, one can see the still considerable negative output gap (shortfall of actual GDP relative to potential) that persisted at the end of 2020, as well as the very large positive output gap that was projected by reasoning like Summers’s after ARP’s passage by the end of 2022.

Figure B

The emergence of higher levels of inflation by mid-2021 led many to assume this output gap-based reasoning had turned out to be true. They thought that the inflation was clearly the result of macroeconomic overheating (with the level of actual GDP far exceeding the level of potential GDP). But it is far from obvious that this is the correct interpretation. For one (as we show later), even with the American Rescue Plan, real GDP growth (the red line) has barely beaten pre-pandemic projections of what it would be by mid-2022.

Below we highlight evidence that further complicates the narrative that inflation is the result of simple macroeconomic imbalances driven by a too generous ARP.

International evidence complicates the domestic overheating story

The most straightforward reason to doubt this narrative comes from a look at the international experience of inflation.

A look across member countries of the Organisation for Economic Co-operation and Development (OECD) shows that rising inflation was not unique to the U.S. and was in fact a global phenomenon throughout 2021 and 2022. Figure C shows the acceleration in core inflation from May 2021 through September 2022, compared with two years of pre-pandemic “normal” inflation (2018–2019), for 35 OECD countries. We use core inflation, which strips out food and energy prices, to better represent broad inflationary pressures in each economy. Using core inflation also allows for a better comparison between the U.S. and Europe given the volatility in food and energy prices affecting Europe due to the war in Ukraine. 

Figure C

As Figure C shows, all 35 OECD nations we examined experienced an acceleration in core inflation throughout 2021 and 2022 compared with the pre-pandemic period. While above the median, and on the higher side of inflation experiences worldwide, the U.S. is by no means an outlier and is just below the average for all other OECD countries. This global phenomenon of rising inflation casts doubt on the claim that U.S. inflation was caused purely by domestic policy decisions leading to macroeconomic overheating.

One might argue that the global acceleration in inflation simply meant that many countries overheated their economies and generated excess demand through too much fiscal spending. However, the data do not support this argument. For one, Figure C shows OECD nations with a wide range of fiscal responses, from aggressive relief spending to little intervention. Despite the varying responses, all countries experienced some level of inflation acceleration.

Figure D examines more closely the argument that global inflation is simply a reflection of global excess demand. To do this, we examine core inflation acceleration on the vertical axis (the same numbers shown in Figure C). On the horizontal axis, we show change in unemployment between September 2022 and the pre-pandemic 2018–2019 unemployment. This measure indicates how much unemployment has improved recently compared with the pre-pandemic period (for example, a fall in the unemployment rate of 2 percentage points would be shown on the graph as a positive 2%). If inflation was caused by excess demand growth (proxied by lower unemployment rates today), one would expect to see a positive relationship between unemployment improvement and acceleration of inflation. The data do not show this.

Figure D

As Figure D depicts, there is no significant positive relationship between unemployment improvement and inflation acceleration. If anything, there appears to be a slightly weak relationship in the opposite direction whereby countries with higher unemployment (or lower improvement) relative to pre-pandemic times experienced higher inflation levels. The fact that countries with larger decreases in unemployment (perhaps brought about by more expansive fiscal policy and economic stimulus) do not show larger spikes in inflation strongly complicates the claim that macroeconomic overheating applies globally.

Overall, the shared 2021–2022 international experience of high core inflation strongly counters the argument that fiscal relief in the U.S.—such as the American Rescue Plan—either drove up inflation or contributed significantly to its unusual persistence.

Domestic evidence is also underwhelming for simple overheating explanations

Turning to the domestic U.S. evidence, the case for recent inflation being sparked by a simple macroeconomic imbalance of aggregate demand and potential output is also weak. Many have presented the steepening trend in nominal spending over the past year and a half as evidence for the overheating view. This is tautological. Faster nominal spending growth could simply be a reflection of faster inflation; it is not evidence of its cause.

Take a totally trivial example: Imagine there was a rapid consolidation of market concentration across the economy. Firms with greater market power would likely raise prices. If the price elasticity of demand was relatively low in the short run (which seems like a safe bet), this would in turn make nominal spending rise more rapidly (even while real spending would actually fall). This could happen with no implication at all for the state of macroeconomic balance.

More realistically, one could imagine a scenario—like what happened following the pandemic shock—wherein the allocation of demand across spending categories rotated sharply into sectors with either impaired supply or a higher elasticity of prices with respect to demand. As this happened, there would be an increase in prices even without the level of aggregate demand being particularly high relative to the economy’s potential output. In the long run, the inflationary effect of very large relative price changes set off by such a process could be muffled by macroeconomic policy, but claims that over a 1–2 year period such relative price changes cannot be major drivers of inflation seem obviously wrong.

Decomposition of inflation into ‘demand’ and ‘supply’ factors

One method some have used to assess the role of ARP and excess stimulus in generating inflation is to decompose the recent acceleration of inflation into “demand” versus “supply” factors. Probably the most well-done and transparent version of this exercise is by Shapiro (2022). The categorization of price changes in a given economic sector as being driven by demand or supply is done by estimating the price and quantity levels of an industry in each month. Then, the “unexpected” components of monthly changes (basically those that exceed or lag a running trend) in both prices and quantities are extracted. If a sector sees both price and quantity growth above trend, price increases in that sector are categorized as demand-driven. If price growth is above trend but quantity growth is below trend, then price increases are characterized as supply-driven. If either price or quantity growth is near trend, then the industry’s price growth is labeled ambiguous.

The Shapiro (2022) decomposition is certainly clever. Based on these results, the rise of core inflation over the past year can essentially be attributed equally to demand- and supply-side measures. This decomposition for recent years is reproduced in Figure E. However, this technique and how its results are interpreted have a couple of potential shortcomings.

Figure E

Shapiro’s technique for decomposing demand versus supply drivers of inflation might stumble on one potentially important issue—changes in the elasticity of price changes with respect to demand shocks. Take the example of an industry that has seen a very large price increase relative to trend but has seen steady growth in output. Under the Shapiro (2022) decomposition, this would qualify as the source of inflation in the sector being “ambiguous.” But this could easily be a supply issue. If during normal times a mild uptick in demand (a percentage point or two above trend) led to tame price growth, but since the pandemic this mild uptick was associated with very large price increases, this could well actually be a signal that it is supply-side factors that are binding. Further, even for sectors that are characterized as demand- or supply- driven, if the price change associated with any demand or supply mismatch (regardless of which side initially caused it) is greater than it was in the past, this could signal that sectoral frictions—not just macroeconomic factors—are causing the rise of inflation.

On the issue of the interpretation of the results, identifying a given inflationary episode as being driven by “demand” or “supply” can sometimes be akin to asking which blade of the scissors cuts the paper. As Larry Summers put it (fairly enough):

I think it restates what I think is a bit of a popular confusion in the following sense—supply is what it is. Monetary policy can’t change it. Fiscal policy can’t change it, except in the long-run. And so given what supply is, it’s the task of demand to balance supply. And if demand is greater than supply, then you’re going to have excess inflation and you’re going to have the problems of financial excess.

So the job of the demand managers, principally the Fed, is to judge what supply is and calibrate appropriately. It’s not an excuse for inflation to blame it on supply. It’s a reality in the environment that you have to deal with. And so the job is to look for measures of overheating, and when you see measures of overheating, to apply restraint. (Klein 2022)

Real-time estimates of actual and potential GDP don’t look particularly inflationary

Summers’s point that attributing the recent rise in inflation to “demand” or “supply” does not end the debate about the role of excess macroeconomic stimulus in driving today’s inflation is well taken. However, his claim that “supply is what it is” simplifies far too much. The most obvious disruption to potential output (or aggregate supply) in the wake of the COVID-19 shock was the 2.5% decline in labor force participation between February 2020 and the end of 2020. But should policymakers really have looked at this decline and just thought “it is what it is” and pulled back demand growth to match this? Or, instead, was the decline in labor force participation (which fell 3.5% in a single month in April 2020) better seen as a mostly temporary economic casualty of the pandemic that would eventually heal?

So, in some sense it is true that categorizing some inflationary shocks as “supply-driven” does not map perfectly onto a recommendation to keep demand policy stable. But the larger claim that inflation is ipso facto evidence of aggregate demand overshooting supply and hence requires contractionary macroeconomic policy does not follow.

We can get some sense of how much the aggregate levels of demand and supply have shifted relative to pre-pandemic trends using data on GDP and potential output. At the end of 2019, the Congressional Budget Office made projections of both of these variables for the coming years while forecasting little to no change in inflation (or interest rates). The Summers argument above is that either GDP began rising faster than forecast in 2019 (due to excessively expansionary fiscal policy) or that potential output shrank, with either influence (or both influences) leading to a positive “output gap” that drove up inflationary pressures.

Figure F shows real GDP and potential output, both as ratios to what CBO projected they would be before the pandemic. For the measure of potential output, we allow developments since the pandemic to affect the CBO projection. Specifically, we reduce the labor input into potential output by assuming that the decline in the labor force participation rate is driven solely by supply-side factors.2

We also account for changing capital services input and total factor productivity growth relative to CBO projections. For capital services, we construct a measure of growth of the aggregate capital stock that accounts for the nonresidential fixed investment (NRFI) that has occurred since the pandemic and we compare this against CBO projections of capital services input growth. For total factor productivity, we employ the utilization-adjusted measure of total factor productivity growth compiled by John Fernald (2023) and compare that with the CBO forecast.

As can be seen in Figure F, potential output fell sharply (not as sharply as GDP, but still noticeably) in the immediate post-pandemic shock period. As of the third quarter of 2022, it still remained a bit under 2% below what CBO forecast it would be in that quarter. GDP fell very sharply in the pandemic recession, but by the third quarter of 2022 sat roughly 1% beneath what CBO forecast it would be before the pandemic struck.

Figure F

There was a period of time during 2021 when GDP rose above our adjusted measures of potential output for a stretch. Over the five quarters from the end of 2020 to the end of 2021, the cumulative positive output gap (GDP exceeding potential output) was 5.8%, with an average gap of around 1.2% in each quarter.

That GDP exceeded potential output as inflation rose gives some plausibility to claims that macroeconomic overheating contributed to the recent inflationary spike, but the magnitude of the spike makes it highly unlikely that this overheating played a starring role. There is a well-established literature on how much each 1 percentage point positive output gap should be expected to drive up the inflation rate. These estimates do not exceed 0.5% and cluster more tightly around 0.3% or even lower. This implies that the 1.2% average output gap in that five-quarter stretch should be expected to raise subsequent inflation by roughly 0.4–0.6%, or by about a tenth of its actual acceleration over this period.

A historical example might help make this clearer. According to CBO estimates, the U.S. economy ran a cumulative positive output gap of over 17% of potential output, with an average gap of 1.2%, over the period from 1997 to 2000. This was the same average gap as that seen in 2021, but sustained for four times as long. Yet there was no inflationary increase at all during this period. In short, running the economy this “hot” for a year is not supposed to yield anywhere near the degree of inflation that we have witnessed since the middle of 2021.

Figure G shows the history of output gaps since 1995. For the last two years, we show the gap with an unadjusted measure of potential output from CBO’s last pre-pandemic projection, plus the gap with our adjusted measure of potential output. Even with our adjusted measure, which accounts for pandemic damage to the economy’s aggregate potential output, the positive output gaps of the past 18 months are utterly unremarkable relative to recent U.S. economic history—a history that saw no similar inflationary spike.

Figure G

Tight labor markets usually boost—not reduce—labor’s relative bargaining power

Finally, we highlight some evidence from the labor market to assess the claim that a straightforward story of macroeconomic overheating is at the core of recent inflation. Generally, claims that inflation accelerations are driven by an excess of aggregate demand over potential output rest on theories of labor market overheating. As aggregate demand exceeds potential output, unemployment falls. In turn, this boosts workers’ bargaining position with employers and accelerates wage growth. If nominal wage growth begins exceeding price inflation, this leads to a rise in labor’s share of income.

The general logic that lower rates of unemployment boost nominal wage growth more than price inflation is sound and supported by empirical evidence. As the recent inflationary episode began in 2021, it was often accompanied by stories of labor shortages in many sectors. This led far too many to assume that wage pressures were pushing up price growth, and the simple story of the labor market overheating due to a macroeconomic excess of aggregate demand over potential output gained credence.

The first bit of evidence against the claim that rolling labor shortages across sectors led to prices rising can be seen in Figure H. This graph shows the acceleration in price inflation and the acceleration in nominal wage growth across 61 industries. It measures acceleration of prices and wages as their annualized growth rate between the second quarter of 2020 and the third quarter of 2022 relative to the annualized growth rate that prevailed on average between 2018 and 2019. There is no discernible correlation at all between these measures.

Figure H

Moreover, while nominal wage growth did accelerate in 2021, it never exceeded price inflation. This means that real (inflation-adjusted) wages have been falling since early 2021. This also led to a pronounced fall in the labor share of income in the corporate sector, which has largely not recovered from its post-pandemic low. It seems odd that a labor shortage could somehow be the source of inflation given this data—it is rare for services in short supply to command less and less income growth on a per-unit basis.

This fall in real wages and the labor share of income is absolutely not the norm for the U.S. economy as it “heats up” in recoveries. This fact has been missed by far too many commenters. Many have made implicit claims that a sharp fall in the labor share of income and real wages is the norm for an economy with positive output gaps. Rampell (2022), for example, writes:

The greedflationists argue that something fishy is afoot because companies are not merely “passing along” their higher costs; their profit margins are expanding, too. But this is exactly what you’d expect when flush customers are buying more stuff and willing to pay whatever’s necessary to get what they want. Prices and profits rise.

Read “flush customers willing to pay whatever’s necessary to get what they want” as “high levels of aggregate demand relative to potential output.” Is it really true that historical experience would lead one to expect that high levels of aggregate demand lead to prices and profits rising?

Not really. Figure I shows the labor share of income in the corporate sector since 1949. The cyclical dynamics of the labor share are slightly complicated: The labor share is not “countercyclical” as it is sometimes described. It does rise sharply during outright recessions, as more volatile profits decline sharply during economic downturns. But in early recoveries with unemployment still high, the labor share universally falls sharply. Then, in mid-recovery as unemployment starts to approach (or fall beneath) pre-recession lows, the labor share begins to rise as unemployment falls—or, as the economy “heats up.”

Figure I also shows variability and potential decade-specific trends in labor’s share. This explains why a simple scatterplot of the relationship between the change in labor’s share of income and the unemployment gap is very noisy, with only a mild (if statistically significant) downward correlation, which indicates that low unemployment gaps (signifying tight labor markets) are weakly associated with an increased labor share.

After we control for decade-specific dummy variables and decade-specific trends, this relationship dramatically strengthens, as shown in Figure J. The figure shows the coefficient on the unemployment gap from a regression of the change in the labor share on the unemployment gap, plus decade-specific dummy variables, decade-specific trends, and productivity growth. It shows this regression for all periods in our data (quarterly data from 1949 to 2018), as well as periods when the unemployment gap is greater than 1, less than or equal to 1, greater than 0, and less than or equal to 0. An unemployment gap of 0 or below indicates a tight labor market with actual unemployment either equal to or less than estimates of the natural rate. An unemployment gap of 1 or below indicates an economy operating below full employment but within shouting distance of it. An unemployment gap of above 1 indicates an unhealthy labor market.

What does this tell us? That it is extremely unusual for labor’s share of income to fall (or even stagnate) even as unemployment falls beneath 5%: Higher profits are not the expected signature of an overheating economy. In this sense, the recent low levels of labor’s share and the poor performance of real wages are signs that the current economy does not look anything like a typically overheating economy.

Figure I

Figure J

If not macroeconomic imbalances, then what? Sectoral shocks and their ripples

If the driver of recent inflation was not large macroeconomic imbalances, then what was it? Put simply, extraordinarily sharp sectoral shocks and the large ripples these shocks generated drove recent inflation. Tobin (1972) provides probably the best description of how large sectoral shocks can cause persistent inflation. Key to his reasoning is the empirical finding that nominal wages are extremely rigid downward. Given this downward nominal wage rigidity, adjusting to sectoral shocks to demand and supply will always require inflation (rising nominal wages in expanding sectors) rather than deflation or neutral aggregate wage and price growth (i.e., rising or flat nominal wages in expanding sectors matched by falling nominal wages in contracting sectors). These insights are profound enough to quote at length:

The overlap of vacancies and unemployment—say, the sum of the two for any given difference between them—is a measure of the heterogeneity or dispersion of individual markets. The amount of dispersion depends directly on the size of those shocks of demand and technology that keep markets in perpetual disequilibrium, and inversely on the responsive mobility of labor. The one increases, the other diminishes the frictional component of unemployment, that is, the number of unfilled vacancies coexisting with any given unemployment rate. A central assumption of the theory is that the functions relating wage change to excess demand or supply are non-linear, specifically that unemployment retards money wages less than vacancies accelerate them. Non-linearity in the response of wages to excess demand has several important implications.

First, it helps to explain the characteristic observed curvature of the Phillips curve. Each successive increment of unemployment has less effect in reducing the rate of inflation. Linear wage response, on the other hand, would mean a linear Phillips relation. Second, given the overall state of aggregate demand, economy-wide vacancies less unemployment, wage inflation will be greater the larger the variance among markets in excess demand and supply. As a number of recent empirical studies have confirmed (see George Perry and Charles Schultze), dispersion is inflationary. Of course, the rate of wage inflation will depend not only on the overall dispersion of excess demands and supplies across markets but also on the particular markets where the excess supplies and demands happen to fall. An unlucky random drawing might put the excess demands in highly responsive markets and the excess supplies in especially unresponsive ones. Third, the nonlinearity is an explanation of inflationary bias, in the following sense. Even when aggregate vacancies are at most equal to unemployment, the average disequilibrium component will be positive. Full employment in the sense of equality of vacancies and unemployment is not compatible with price stability. Zero inflation requires unemployment in excess of vacancies. (p. 10)

If Tobin is right that “dispersion [of sectoral shocks] is inflationary,” then the mammoth response of inflation to the COVID-19 shock becomes very easy to understand—this pandemic effect was the mother of all shocks to sectoral dispersion. Further, specific features of the 2021 economy meant that any shock to sectoral imbalances would have led to large ripple effects, mostly through shocks’ effects on the labor market, which saw nominal wages respond to nonlabor cost shocks and support inflation to an unexpected degree.

These “ripple” effects stem in part from the distributional conflict resulting from inflationary shocks as various economic groups try to protect their real incomes. As Ros (1989) puts it: “A common form of [conflict inflation] arises when the real wage reflecting the balance of power in the labour market, and expressing the expectations created in wage bargains, is not validated by the real wage implied by price formation in other markets” (p. 8). So, if a shock to the cost of nonlabor inputs (say lumber used in home building and chips used in automobile production) pushes up prices, workers might respond by bargaining for higher nominal wages to protect their living standards. In turn, firms may accommodate their own workers’ nominal wage demands (or at least some of them) yet maintain or even expand profit margins to protect their own incomes.

This conflicting-claims view of U.S. inflation is not well known or often wrestled with in most macroeconomic commentary. There’s one pretty good reason for this—for decades, it has largely not been an issue, as a number of policy changes have so disempowered U.S. workers that their efforts to protect real incomes from any shocks have been limited enough to leave almost no mark on inflationary dynamics. Ratner and Sim (2022) provide compelling evidence that the extremely low inflation that characterized the 30 years before COVID-19 is likely largely explained by a pronounced shift in bargaining power from workers to firms. Yet in 2021, these conflicting claims on real output following large exogenous shocks led to the large and persistent ripple effects in inflation.

What are the analytical and policy stakes in distinguishing between inflation driven by macroeconomic overheating (imbalances in the level of aggregate demand and potential output) versus a “shocks and ripples” theory? Even if they are large, as long as the ripple effects following inflationary shocks dampen rather than amplify the initial inflationary shock, then macroeconomic policymakers should not have to pursue aggressively contractionary policies to rein inflation back in. This is not simply tautological—sometimes shocks really do set off ripple effects that amplify the initial impulse and need some external force (looser labor markets in the current context) to provide dampening. But so long as wage growth lags behind price inflation, the ripple effects—large as they might be—will steadily dampen the initial shocks and return inflation to more normal levels over time, even absent any effort to engineer looser labor markets.

Below we more sharply distinguish just what the economic shocks caused by COVID-19 and the Russian invasion of Ukraine were. We also outline how the ripple effects kept inflation more persistent than what many forecast going into this episode, though the effects still look set to fade as long as the shocks stop coming.

What were the shocks?

The main shocks to the U.S. economy from the pandemic and war were the economic distortions that they created in both demand and supply patterns. On demand, the composition of GDP shifted with a historically rapid reallocation in spending and demand away from services and government and into durable goods consumption and residential investment. On the supply side, the pandemic and war contributed to massive supply chain snarls, further heightened by port shutdowns and the global spike in raw material, energy, and commodities prices.

Demand shocks: consumption patterns and the underappreciated role of housing

The shift in demand patterns away from face-to-face, high-contact services (such as gyms, movie theaters, travel) and toward durable goods and residences (cars and houses) was clearly a consequence of the pandemic, and it has shown remarkable persistence. Figure K displays the shock to the composition of demand in historical context from 1980 through the present. We examine the share of GDP made up of durables and residential investment and demonstrate how it has changed relative to the average of the previous two years. Clearly, the onset of the pandemic led to a historically unprecedented jump in the share of durable goods consumption and residential investment (the last rise, though at a much slower rate, can be seen in the early 2000s). In recent years, the share of durables consumption and residential investment has moved a bit closer to normal, but it remains at a high level relative to historical averages. (In Figure K, one can see that the level of demand as of 2022 Q3 was roughly in line with what it has been for the past two years—i.e., the line hovers near zero—and these past two years have been dominated by the COVID-19 patterns of spending.) This historically sharp swing in demand across sectors is certainly a large enough shock to explain the beginning of the recent inflationary episode.

The swing toward durable goods consumption and away from face-to-face services is intuitive to understand (the classic example being the substitution of Peloton purchases for gym memberships). However, the boost to housing demand driven by the pandemic is even better documented by the data. Apparently, the prevalence of remote work led to a large positive shock in housing demand as more people worked from home, first out of necessity of social distancing for public health, but then (for many) out of choice. Working from home in turn inspired demand for more space and smaller households, leading to a large surge in new purchases and household formation that ran far ahead of population growth for 2021.

Figure K

This pandemic shock to housing demand had profound implications for subsequent inflation. Housing is a key component of inflation, making up 40% of core consumption spending in the CPI. Housing prices (including rents) have also increased dramatically since 2019. Figure L shows the tight relationship between remote work and the growth in home prices, as shown in Mondragon and Wieland (2022).

Figure L (taken directly from Mondragon and Wieland 2022) shows a strong positive relationship between home price growth and exposure to remote work, meaning that the areas most exposed to remote work had home price growth twice as high as the areas least exposed. Their model further estimates that remote work raised aggregate home prices by 15.1%, accounting for well over half of the rise in housing prices over that time. Clearly, the pandemic shock to housing demand and subsequent price growth is a crucial component of the 2021 inflation story. 

Though housing prices have been high through the pandemic, they seem to have been assigned less blame in the recent inflation episode compared with the overheating or fiscal over-stimulus arguments. Why has housing been such an underrated contributor to high inflation in economic policymaking discussions? Mostly because official measures of housing costs were one of the last components of inflation to noticeably accelerate. The measurement of housing prices is one of the most backward-looking price indicators, with increases in new rents and home prices in many industry data sources only visibly pushing up costs in the CPI 6–12 months later.

Figure L

Given this lag and the backward-looking nature of housing measurement, a shock to housing demand generally does not manifest in an increase in housing prices and rents until the following year. This means that many policymakers and economic commentators were unable to track the extent of price changes as they occurred. Figure M shows the correlation between annual growth in the Case-Shiller home price index, lagged one year, and annual growth in the shelter component of the CPI since 1989.

This lag between home price changes and when they are reflected in falling shelter in the CPI meant that the 2021 positive shock to housing demand stemming from the pandemic only pushed up official measures of inflation later in 2022. However, it is also important to note that the reverse dynamic is likely to characterize rental prices going forward—substantial weakness in early-warning measures of rental prices will show up only in a slower rate of CPI growth with a significant lag.

Figure M

Supply shocks: Supply chains and much spikier effects on labor supply than appreciated

While the pandemic shocks to the demand side are evident, the pandemic created important supply shocks as well.

The most well-known shocks were pandemic-driven snarls in global supply chains of durable goods and materials for construction. These supply-chain snarls were largely due to rolling port shutdowns throughout East Asia in key manufacturing hubs. The Federal Reserve Bank of New York maintains an index of global supply chain pressure. Figure N shows that this index hit its highest points on record in 2021, and only by late 2022 had the index begun showing real signs of normalizing. The pandemic supply-chain shock was quite persistent.

Figure N

Another underappreciated part of the pandemic’s effect on the U.S. economy’s supply side was its effect in temporarily sidelining millions of employed workers each month. This effect became historically pronounced during the omicron wave of January 2022. Figure O shows the number of people who were employed with a job but were not at work due to illness or medical problems in the reference week of the Current Population Survey (the survey used to calculate the unemployment rate and other key labor market indicators). While there are spikes in this series in 2020 and when the delta variant was spreading in summer 2021, the number skyrockets to over 3.5 million people in January 2022 during the omicron wave. This rolling shock in labor supply very likely disrupted the labor market and economic system as well but shows some hopeful signs of normalizing in recent months.

Figure O

Large—but settling—labor market ‘ripples’

Perhaps one of the most notable elements of the 2021 labor market was the growth in nominal wages. Nominal wage growth in 2021 was extraordinarily fast relative to recent history and is even turning out to have been fast relative to what has prevailed in 2022—even as other measures of the labor market have seemingly tightened. Many policymakers have claimed that increased nominal wage growth has been a key driver of inflation since early 2021. This claim is not totally implausible—historical episodes of price-wage spirals really have occurred and required some exogenous forcing mechanism to bring down wage growth as part of the anti-inflationary strategy. However, a close look at the evidence indicates that the focus on wage growth as a key driver of inflation in the past 18 months seems misplaced. Further, it seems quite likely that the abnormally fast wage growth of the past 18 months can be normalized without a significant forcing mechanism (like substantially higher unemployment rates engineered by Fed interest rate hikes). Indeed, wage growth already seems to be normalizing pretty quickly.

In short, the rapid nominal wage growth of 2021 should not be understood as a major cause of the inflation of 2021 and should not be expected to continue (even if the unemployment rate remains low) going forward. To support these claims, we highlight a number of features of the 2021 labor market that allowed for this nominal wage growth in the first place and argue that they are largely unique to that year.

Put simply, workers had high degrees of bargaining power in 2021 relative to what the overall unemployment rate might have indicated. Well before the unemployment rate approached its pre-pandemic levels, employers were pushed to raise wages in order to attract and retain workers. Most notably, this wage growth occurred in industries in which workers often have the least bargaining power and face the lowest pay: retail, services, food, and accommodations.

There were likely two major changes to labor markets in 2021 that provided temporary boosts to workers’ bargaining power. First, the massive level of layoffs and business closures that accompanied the pandemic meant that labor market frictions that gave employers a degree of monopsony power over their workforce were dissolved in one fell swoop. These frictions are highly powerful in preventing workers from even obtaining information about jobs with higher wages in their immediate area (Jager et al. 2022). By the end of 2020, tens of millions of employee-employer ties had been severed by the pandemic, but at the beginning of 2021, the extremely large fiscal relief convinced employers to staff up quickly. This rapid staffing-up happened in the context of workers facing far fewer frictions tying to their current employer (and muting upward wage pressure) than is the norm. As more and more new employee-employer matches were cemented as 2021 turned into 2022, the same forces that introduce frictions into workers’ job searches and competitive searching seem highly likely to reassert themselves.

The second major component of workers’ empowerment in 2021 was the role of pandemic aid in providing a wealth buffer (we present evidence on the size of this buffer in Figure V). This buffer bought workers time to find employment that suited them while still covering their costs, rather than being forced back into the first available job regardless of its fit for them. Chetty (2008), for example, has identified the powerful role that having some liquid wealth buffer has in allowing workers to be choosier in their job searches.

Economic impact payments (EIPs, often called stimulus checks), expanded unemployment insurance, and the monthly Child Tax Credit gave workers the ability to build up savings and accumulate a level of financial security that had been largely unavailable for tens of millions of workers any time before the pandemic. This translated into significant bargaining power in the labor market. However, while this support was unprecedented, it was also short lived, and both employers and workers knew with a high degree of certainty when this aid would turn off. The last stimulus check was mailed in January 2021. Enhanced unemployment insurance and the CTC phased out in fall and winter 2021, respectively. This wealth buffer for all made job searches and wage offers in 2021 far different than they were during normal times.

One could imagine how policy efforts to restrain employers’ monopsony power and to give workers a better fallback position in the face of job loss could have permanent effects. If, for example, a major change to labor law allowed workers to unionize even in the face of today’s hostile employer class, then this could easily provide a permanent source of countervailing power to monopsony (see, for example, Benmelech, Bergman, and Kim 2021). Aspects of the pandemic relief (particularly the enhanced child tax credit and an increase in the protectiveness of the UI system) could have also been made permanent. But the simple fact is that none of the underlying boosts to workers’ bargaining power that characterized the 2021 labor market continue to exist today. This fact strongly suggests that any unexpected labor market worker power experienced in 2021 is likely to be temporary rather than permanent.

Why were the large wage ripples such a surprise—and why are we sure they’ll settle?

We noted before that the primary policy-relevant distinction between a view that sees recent inflation as the result of macroeconomic overheating and a view that sees it as a series of shocks and ripples concerns the role of demand management. If inflation is the result of aggregate demand exceeding potential output (and if one imagines potential output is fixed—“it is what it is”), then the only remedy is to slow demand growth, even if that leads to higher unemployment. If, instead, inflation has been driven by shocks and ripples, and if the ripples eventually settle, then inflation can normalize without engineering higher unemployment.

We also noted that wage growth in 2021 and early 2022 was quite rapid in historical terms, and the ability of U.S. workers to shield their real incomes from inflationary shocks was unexpectedly robust. This raises a couple of questions: (1) If the ripple effects of higher wage growth following inflationary shocks were so large, why can we be sure that they will eventually dampen on their own?; and (2) Was the inflation of the past 18 months driven by wage growth or not?

On the first question, the simplest answer is that for decades American workers’ wages have responded only weakly to price shocks in the short run. Figures P1 and P2 highlight two separate time periods—1949–1988 and 1989–2019. In each period, the growth of wages and growth in prices lagged just two quarters is shown. In the earlier period, shown in Figure P1, wage growth was tightly linked to price inflation even in the short run. In the latter period, shown in Figure P2, there is essentially no durable relationship at all. In sum, recent decades seemed to break any quick link between price spikes and immediate changes in wages. It’s certainly possible that the pattern that held between 1989 and 2019 was somehow completely overturned in the post-pandemic period, and we are headed back to an era in which wages will respond quickly to price shocks. But there needs to be a long period of compelling evidence on this before we should assume this tight link has been reestablished. If instead the nonrelationship that has prevailed for the last 30 years is the better predictor of future wage-price dynamics—particularly once the temporary sources of bargaining power we highlighted previously are behind us—then it seems a safe bet that the wage ripples from recent price shocks will settle soon.

Figure P1

Figure P2

Further, as long as nominal wage growth adjusts only partially to price shocks and lags at all behind inflation, then wages are providing a dampening effect on inflation. This has clearly been the case in the recent period. Since May 2021, for example, CPI inflation has risen at an average annualized rate of 6.8%, while average hourly earnings have risen at a rate of 5.0%.

Even more compelling, the ripple effect of faster wage growth clearly seems to be abating now that large shocks have stopped coming (and temporary labor market supports have ended). This is true even as quantity side measures of the labor market (like the unemployment rate) remain quite strong. Figure Q shows the growth of average hourly earnings and unemployment over the past two years (note that we suppress the very large wage jump accompanying the pandemic-driven layoffs of mostly low-wage workers in mid-2020). Besides showing a pronounced nonrelationship between unemployment and wage growth in recent times (casting some doubt on a simple story of labor market overheating), this graph also shows a pretty clear recent deceleration of wage growth.

Figure Q

On the second question (“was the inflation of the past 18 months driven by wage growth or not”), the answer is nearly as simple: largely not. It is true that if nominal wage growth had not budged from the 3% pace that persisted pre-pandemic then inflation would have been slower over the past 18 months. But it still would have been a historically large inflationary spike.

Further, given that most of the price pressure started from outside labor markets and would have happened anyway, the ability of nominal wage growth to accelerate over this period really did protect workers’ real incomes. If all policymakers cared about was keeping inflation as close to the Federal Reserve’s 2% inflation target as possible, then the nominal wage growth acceleration of the past 18 months was a problem. If instead one also cared about protecting the living standards of U.S. workers in the context of nonexplosive inflation, this wage growth was clearly beneficial.

Figures R1 and R2 provide some rough simulations showing the inflationary effect of various paces of nominal wage growth. They use real data on wage growth and then infer what portion of overall inflation was driven by other factors over the past 18 months. They then subtract out the influence of the faster wage growth seen over the pandemic recovery while allowing these other factors’ contribution to inflation to persist. Figure R1 compares the resulting evolution of actual inflation against the counterfactual in which nominal wage growth does not accelerate past its pre-pandemic pace. Flat wage growth would have indeed lowered inflation, but a historically notable spike still would have occurred. Finally, Figure R2 highlights how much lower inflation-adjusted wages would be today had nominal wage growth not accelerated but other inflationary forces were felt over the past 18 months. Even with the higher inflation rates prevailing in the model in which nominal wages partially adjust to price shocks, real (inflation-adjusted) wages fall less in the scenario with partial wage adjustment relative to the one in which wage growth remains flat in the face of price shocks.

Figure R1

Figure R2

The role of mark-ups

The price of just about everything in the U.S. economy can be broken down into the three main components of cost. These are labor costs, nonlabor inputs, and the “mark-up” of profits over the first two components. Good data on these separate cost components exist for the nonfinancial corporate (NFC) sector, which accounts for roughly 60% of the entire private sector (and likely has strong effects on price setting even throughout the noncorporate sector).

Since the trough of the COVID-19 recession in the second quarter of 2020, overall prices in the NFC sector have risen at an annualized rate of 7.3%—a pronounced acceleration over the 1.8% price growth that characterized the pre-pandemic business cycle of 2007–2019. As Figure S shows, 40.8% of the increase in the former period (since the recession’s trough in 2020 Q2) can be attributed to fatter profit margins, with labor costs contributing less than a quarter of this increase. Some have argued that starting this measurement from 2020 Q2 could represent cherry-picking that overstates this effect. Measuring from the previous business cycle peak of 2019 Q4 still sees fatter profit margins accounting for a third of the rise in prices in the current business cycle. This is a very high share. From 1979 to 2019, profits contributed only about 11% to price growth (and—not shown in this figure—labor costs contributed over 60%). Through the end of 2021—the period of greatest price acceleration—profits contributed well over half of the entire increase in prices.

Figure S

Do fatter profit margins imply more corporate power—or just power channeled differently?

The rise in profit margins that accounts for a disproportionate share of price growth in the current recovery has led to speculation that increased corporate power has been a key driver of recent inflation. Corporate power is clearly playing a role, but an increase in corporate power likely has not happened recently enough to make it a root cause of the inflation of 2021–2022. In fact, the rapid rise in profit margins and the decline in labor’s share of income during the first six quarters of the current recovery is not that different from the rise in the first few years following the Great Recession and financial crisis of 2008. Figure T shows that starting from the trough of the recession (zero on the horizontal axis), the fall in the labor share of income was actually more pronounced during the early recovery from the Great Recession than it has been so far in the recovery from the COVID-19 recession.

Figure T

In the recovery from the Great Recession, increased corporate power did not manifest in faster price growth that made room for fatter profit margins—price growth was actually quite subdued (Bivens 2015). Instead, corporate power manifested itself in extreme wage suppression (aided by high and persistent levels of unemployment). Unit labor costs actually declined over a three-year stretch from the recession’s trough in the second quarter of 2009 to the middle of 2012. The general pattern of the labor share of income falling during the early phase of recoveries characterized most of the post-World War II recoveries, though it has become more extreme in recent business cycles (see Figures G and H in Bivens and Shierholz 2014).

Given that the rise in profit margins was similar in the 2008 recovery and the current one, it is hard to say that some recent rise in corporate power is the key driver of current inflation. Rather, a chronic excess of corporate power has built up over a long period of time, and it manifested in the current recovery as an inflationary surge in prices rather than successful wage suppression. What was different this time that channeled this power into higher prices rather than slower wage growth? Put simply, the main influence conditioning the recovery from the Great Recession was anemic growth in aggregate demand, whereas the main influences conditioning recovery post-2020 were the pandemic and the Russian invasion of Ukraine.

In previous recoveries—like the one following the Great Recession—domestic demand growth was slow and unemployment was high in the early phases of recovery. This led firms to become desperate for more customers but also gave them the upper hand in negotiations with potential employees, which led to subdued price growth and wage suppression.

This time around, the pandemic drove demand through the roof in durable sectors, and employment has rebounded rapidly, but the bottleneck in meeting this demand on the supply side was largely not labor (Bivens 2022). Instead, it was shipping capacity and other nonlabor shortages. Firms that did happen to have supply on hand as the pandemic-driven demand surge hit had enormous pricing power vis-à-vis their customers.

Policy in hindsight

Inflation has reached higher peaks and been more persistent than many would have predicted in early 2021. Given this, it is natural to ask what (if anything) should have been done differently by policymakers over this time. If one restricts this policy revisionism to, say, things that could have been done differently only since the end of 2020, obvious answers like “invest more in pandemic preparedness or more resilient supply chains” are off the table.

The most pressing policy debate concerns the actions of the Federal Reserve. Many inflation hawks would claim that the Fed has been far “behind the curve” on inflation. It’s not always entirely clear just what this means, however. Almost by definition, if the Fed had raised interest rates far enough and fast enough, inflation could have been significantly reduced. But the collateral damage of simply raising rates until inflation returns to 2% no matter the broader consequences could have been immense and made this approach easily not worth pursuing.

It is crucial to remember that inflation—particularly a short-run inflation that does not persist for years—generally has no aggregate cost. Instead, it is a purely distributional event. One actor’s cost is another actor’s income: As some group (workers, say) must pay more at stores for their consumption goods, the higher nominal prices feed directly into higher nominal incomes for somebody else. We may not like the pattern of redistribution caused by the current inflation (I certainly don’t), but it does not follow from this that it carries large aggregate costs.

Unemployment, conversely, really does carry high aggregate costs. By definition, an increase in unemployment caused by insufficient demand is economic waste—useful resources that could be deployed to produce more goods and services instead sit idle.

Costless rate hikes through expectations management?

A serious case that the Fed had gotten too far “behind the curve” on inflation would wrestle much harder with this potential trade-off. If the claim was that raising interest rates sooner would have squelched inflation while not requiring much increase in unemployment, this would be a compelling argument. This case is theoretically possible. If one believed that inflation expectations were the driver of nominal wage growth and subsequent price increases in 2021, these expectations (or at least expectations of inflation over the next year) really did move up sharply, and efforts—like starting rate increases sooner—that could have kept expectations in check might have helped.

But this assumes that expectations strongly condition subsequent inflation and that interest rate increases—even if they do not materially affect unemployment—have strong effects on these expectations. Neither of these propositions are well supported by the data.

The role of interest rates and housing

Outside of expectations, the one area where arguments about quicker rate hikes taking out some inflationary steam without harming the economic recovery more generally have some potential validity is housing. As we noted earlier, private industry data indicate a very sharp bounce-back of both rent inflation and housing prices by early 2021. Subsequent research by Mondragon and Wieland (2022) shows that the shift to remote work constituted a large positive shock to housing demand in 2020 and 2021.

Housing is by far the largest single component of price indices, and an acceleration of housing costs in mid-2022 was a key reason why core inflation remained substantially above the 2% target for most of this year. All of this provides some support for claims that the Fed should have raised rates more quickly on the heels of the passage of the American Rescue Plan.

In real time, however, it is not a complete certainty that this should have happened based on trends in the housing market. The Mondragon and Wieland (2022) results clearly imply that the housing price increases have a strong transitory element—unless a growing share of the population switches to remote work each and every year for the rest of the decade, there is little reason to think the upward price pressure imposed by this boost to housing demand will be sustained.

Further, if one thought that the shock to housing demand was transitory, then raising interest rates in response has potentially mixed effects. In the longer run, higher interest rates are clearly associated with reduced housing construction, limiting supply and exacerbating any excess demand. But Dias and Duarte (2016) have found evidence that, even in the short run, interest rate increases can actually increase rent inflation. The mechanism is through tenure choice—as interest rate increases boost the user cost of homeownership, prospective buyers switch into the rental market. In time, if the higher user cost pushes down purchase prices of homes enough, homeowners may choose to rent out rather than sell their homes when they wish to move, thus boosting rental supply. If in the short run the effect of interest rate increases on housing prices is ambiguous, and in the longer run it is potentially inflationary, it becomes less clear that the housing channel provides strong evidence that the Fed should have raised rates sooner in the current inflationary episode.

That said, the recent Fed rate hikes do seem to have relatively quickly released much inflationary pressure in housing markets, first in home prices and then (relatively quickly) in rental markets. As of October 2022, a few months of actual rent declines had occurred in many cities, and forecasters were predicting sharp rental price declines in 2023.

Was the American Rescue Plan the original sin of today’s inflation?

Previously, we highlighted evidence casting doubt on the claim that the American Rescue Plan was a primary contributor to the 2021–2022 inflation episode. Among other issues, the decomposition of inflation into “demand” and “supply” factors by Shapiro (2022) indicates that above-trend demand can account for just about 1 percentage point of core inflation acceleration by August 2022. One would have to attribute the entirety of this above-trend demand influence on inflation to ARP to use this evidence to indict ARP as more than a bit player in the inflation acceleration. But ARP’s spending impulse into the economy had largely petered out by the last quarter of 2021. Since the beginning of 2022, the federal fiscal impulse had actually turned historically contractionary. Figure U shows the change in federal net borrowing (-) or lending (+) over the previous year.

What it shows is that net borrowing by the federal government declined by an average of 10% of GDP over the first three quarters of 2022 (see the large upward spikes at the right edge of Figure U). This is roughly three times as much as the largest pre-pandemic reduction of borrowing (3.4%), which occurred in 2013 when fiscal austerity was widely acknowledged to be dragging heavily on growth from the Great Recession. Before 2007, the largest change in year-over-year borrowing was just 2.0%, a fiscal contraction less than a fifth as intense as the one in 2022. 

For further perspective, note that the swing in net borrowing by the household sector and financial crisis of 2008 was roughly 9% of GDP, but was spread over more than two years (for this calculation, see Bivens 2011). In that episode, the deflating housing bubble led families to reduce spending to make up for lost wealth driven by falling home prices. This bursting of the housing market bubble is why the Great Recession began and why it was so damaging. Further, this private-sector contraction in borrowing in 2006–2009 was even larger than the one that led to the Great Depression in the 1930s. In short, this evidence should make it hard to blame fiscal policy writ large for inflation that has persisted (and even accelerated) after fiscal policy swung hard from expansionary to historically contractionary.

One possibility for ARP’s effects to spill over well into 2022 is the ability of households to spend down the “excess savings” made possible by the fiscal aid in 2021. This is certainly plausible. The fiscal aid was almost surely largely saved (which is why actual GDP did not spiral rapidly above potential GDP in 2021 and early 2022). Figure V shows the increase in net worth of the bottom 50% of households and the size of pandemic fiscal relief. This relief can easily explain the rise in net worth, and this in turn can explain a potential “long fuse” of ARP as the aid initially boosted personal savings rates and then was spent out over time.

Figure U

Figure V

Some have pointed to the recent rapid falls in personal savings rates as evidence that this built-up excess savings from ARP was being rapidly spent down in 2022 and fueling too-fast demand growth (see Figure W for recent fall in savings rate).

Figure W

However, much of the rapid decline in personal savings might be mostly a statistical quirk unrelated to households spending down their pandemic assistance. This savings rate is measured as one minus the ratio of personal outlays divided by disposable personal income. As disposable personal income falls, the ratio of outlays to income rises and the measured savings rate falls. A very rapid increase in tax collections in 2022 led to a sharp fall in personal disposable income. Further, this increase can be almost fully explained by “nonwithheld” income taxes—which largely consist of capital gains taxes. Crucially, capital gains taxes push down measures of disposable personal income, but capital gains themselves are not included in measures of income. So as these collections rise, the savings rate is pushed down mechanically. Figure X shows the very sharp rise in federal income taxes as a share of personal income in recent quarters and shows that nearly all of this rise is accounted for by nonwithheld personal income taxes.

Could the American Rescue Plan have been structured differently to have caused less inflation?

With the benefit of hindsight, there are some changes to ARP one could have imagined. One reasonable-sounding change that was discussed in real-time—spreading the disbursement of funds over a longer time span—would likely not have made much of a difference. As Figure W shows, the large rise in pandemic aid was associated not with a huge wave of new spending, but instead with a large rise in savings (and net worth). Almost by definition, the large spike in savings kept much of the pandemic aid from translating quickly into new demand. Over time the excess savings have been rundown, but in a sense, households’ decisions smoothed out the spend-out of pandemic aid by themselves. A legislated “longer fuse” on this spending would not have slowed the spending much relative to what actually occurred.

The highest value of this pandemic aid—even when not spent—may have been the potential boost it gave to job seekers’ fallback positions when searching for jobs and the resulting acceleration of nominal wage growth. This wage growth is often seen solely as a contributor to inflation. But as we show in Figure R, most of the inflation seen over the past 18 months would have occurred even if nominal wage growth had not accelerated at all. Given this, the nominal wage acceleration was valuable in protecting workers’ real incomes against the inflationary spike.

The alternative changes to ARP that could have potentially blunted inflation in 2021 and early 2022 would have required simply a significantly lower level of spending or would have been seen as extremely heterodox. Simply reducing ARP’s spending levels would have led to marginally less inflation, but also would have led to significantly higher unemployment and even larger losses to real (inflation-adjusted) wages.

In terms of heterodox changes, one could imagine making some of the fiscal relief come in the form of vouchers that could be spent only on goods with a substantial lag. This would have given supply chains time to heal and provided an incentive to firms to invest heavily in repairing these distribution networks, knowing that customers would be waiting.

Another heterodox policy that could have blunted some of the major drivers of inflation was a temporary excess profits tax. We pointed out before the large role of widening profit margins in driving price increases. Imposing a large windfall tax on profits exceeding pre-pandemic margins could have blunted the incentive for firms to respond opportunistically to pandemic distortions (like impaired supply chains) that had temporarily reduced competitive pressures to keep prices low. There were some sectors in which the pros and cons of such a tax would have needed to be carefully weighed. Oil drilling and refining, for example, has been plagued for years with depressed investment, and this investment has responded sluggishly even to the extraordinary profits of recent years. This investment dearth has made the energy price spike in the U.S. historically large. An excess profits tax could have even further reduced this type of investment and made the energy price spike even worse. Then again, if investment in oil drilling and refining did not respond robustly to the highest profit margins in history for the sector, maybe relying on high after-tax profit margins to relieve price pressure in this sector was never going to work?

Figure X

What do macroeconomists and policy analysts need to know about inflation going forward?

There is a lot of truth to claims by macroeconomists that monetary policy can eventually neutralize the effect of relative price changes and restore inflation to a target level. It is also true that looking at the contributions to overall inflation in a given month made by specific sectors and then removing those sectors to find reassurance that what remains is not-that-fast inflation is a bad way to do policy analysis.

But throughout the current inflationary episode, a stronger claim has been often made: Relative price changes (and the sectoral shocks that caused them) are irrelevant to inflation even in the short run. Inflation is, in this view of the world, by definition evidence of a macroeconomic imbalance that needs to be rectified by changing macroeconomic aggregates.

This absolutely does not follow. The initial surge of inflation in 2021 occurred with unemployment still substantially higher than it was in the two years before the pandemic. As unemployment fell and other measures of macroeconomic tightness surged in late 2021 and early 2022, core inflation largely stabilized and key measures like nominal wage growth began falling.

Restoring intellectual respectability in policy debates to explanations that hinge on key sectoral imbalances is a key task for inflation analysis moving forward. It really should not be that hard. Analyses that highlight the crucial importance of particular sectors (and shocks to them) loom large in macroeconomic theories of long-run growth (see Blanchard and Kremer 1997 and Jones 2006). It hardly seems like a huge stretch to go from sectoral shocks causing long-run collapse in aggregate output to sectoral shocks causing an increase in medium-run (say 3–5 years) inflation dynamics.

Another crucial task for making inflation analyses smarter going forward is returning conflicting claims explanations of inflation’s persistence to prominence. Again, Tobin (1981), writing about the last large American inflation, expressed much wisdom that has seemingly been lost:

[I]nflation is the symptom of deep-rooted social and economic contradiction and conflict. There is no real equilibrium path. The major economic groups are claiming pieces of pie that together exceed the whole pie. Inflation is the way that their claims, so far as they are expressed in nominal terms, are temporarily reconciled. But it will continue and indeed accelerate so long as the basic conflicts of real claims and real power continue. (p. 28)

This will become especially important in any happy scenario in which the decades-long effort to shift bargaining power away from workers and toward employers is overturned. Distributional conflict—and nearly every other determinant of inflation’s persistence—has been easy to ignore for decades, simply because this conflict was well and truly settled in capital’s favor and inflation remained entirely quiescent. This settlement on capital’s terms was a disaster for the living standards of the vast majority, and it should be a progressive priority to overturn it and restore some bargaining power back to typical workers. But doing this—as 2021 demonstrated—will require keeping a close eye on inflationary dynamics.

Finally, today’s inflationary episode raises many questions about housing. The most obvious one is whether or not more timely measures of rent inflation can be used in analysis of macroeconomic stabilization policy. The backward-looking nature of housing prices in official indices really did leave many of us behind the curve on both the upslope and downslope of price changes. Adams et al. (2022) have done much of the work in demonstrating that more timely measures of building inflationary pressure in housing can be constructed. These more timely measures should be a bigger part of the monetary policy “dashboard.”

Another obvious issue in regard to housing is how it responds to interest rate hikes. There are potentially cross-cutting effects. Higher interest rates that slow growth of labor income will reduce demand for all types of housing. But if higher interest rates increase monthly costs of homeownership more rapidly than prices decline, there can be a period of time when these rate increases reduce the demand for homeownership, but this in turn increases the demand for rental housing. Because inflation as measured in the CPI or PCEPI is rent inflation, this means that interest rate hikes could actually raise housing inflation. Dias and Duarte (2016) provide evidence that this effect could be relevant empirically. All in all, the evidence of the current episode supports a view that interest rate increases reduce housing and rental prices, but the issues of tenure choice highlighted by analyses like Dias and Duarte (2016) should at least make policymakers think hard over the time horizon in which they are hoping prices will respond to rate increases.

Another issue, however, regards the treatment of housing in macroeconomic models. Rognlie (2015) has demonstrated that much of the rise in wealth documented by Piketty (2014) was driven by the rising price of housing. A number of analyses of the current inflationary period (and not just journalistic accounts) have argued that a very “hot” economy should naturally lead to rising profit shares and margins (i.e., debates over whether or not mark-ups were pro-cyclical). Earlier in this report, we show that this really did not seem to be the case for the corporate sector. But the corporate sector does not include housing. If housing is in quasi-fixed supply over the short run, then it really could be the case that hot economies start directing more and more income to landlords (and homeowners) than either workers or capital owners.

There is real reason to think this dynamic is getting more likely over time. Figure Y shows the share of personal consumption expenditures going to housing (either tenant-occupied rent or owners’-equivalent rent). It shows the actual share, as well as the share that would have prevailed had the price of housing risen at the same rate as nonhousing consumption expenditures. This counterfactual actually shows the share of housing rising more quickly than it actually did in the years leading up to 1979—meaning that housing prices rose consistently more slowly than nonhousing prices. Beginning in the early 1980s, there is a steady upward trend (punctuated by up and down spikes driven by the early 2000s housing bubble and the pandemic) in the actual housing share and a steady downward trend in the counterfactual, meaning that housing prices are rising substantially faster than nonhousing prices.

In short, if there were some wealth class in the economy that threatened to generate “forced savings” away from workers as the economy heats up over the course of a business cycle, it seems like housing might be it. The policy agenda to combat this is a whole new topic, but incorporating the dynamics of housing prices in a wider macroeconomic model could be a fruitful range of research spurred by the current inflationary episode.

Figuring out the impact of a global pandemic and war on inflation dynamics was always going to be challenging. Even worse, smart analyses of inflation, its causes, and proper remedies atrophied over recent decades as inflation seemed nearly permanently tamed. It is highly likely that in a few years, once the pandemic shock has passed, inflation will have returned to near irrelevance. But we should realize now that shocks happen: If smart analysis is not in economists’ mental toolkits, less smart reflexes will dominate policy discussion.

Figure Y

Notes

1. This report is a lightly-edited version of a working paper written in December 2022.

2. The decline in labor force participation likely slightly overstates the size of the supply shock hitting the labor market in recent years. Much of the decline in this measure is driven by older workers who did not work full time before the pandemic. Hence, the decline in potential output driven by a given percentage-point decline in labor force participation among this workforce is likely less than if it were driven by reduced participation among full-time and younger workers.

References

Adams, Brian, Lara Loewenstein, Hugh Montag, and Randal Verbrugge. 2022. “Disentangling Rent Index Differences: Data, Methods, and Scope.” Bureau of Labor Statistics (BLS) Working Paper no. 555, October 6, 2022.

Benmelech, Efraim, Nittai Bergman, and Hyunseob Kim. 2020. “Strong Employers and Weak Employees: How Does Employer Concentration Affect Wages?” Journal of Human Resources 58, no. 3.

Bivens, Josh. 2011. “The Stimulus: Two Years Later.” Testimony for a hearing before the Committee for Government Oversight, U.S. House of Representatives, Washington, D.C., February 16, 2011.

Bivens, Josh, and Heidi Shierholz. 2014. Lagging Demand, Not Unemployability, Is Why Long-Term Unemployment Remains So High. Economic Policy Institute, Briefing Paper #381, August 2014.

Bivens, Josh. 2015. A Vital Dashboard Indicator for Monetary Policy: Nominal Wage Targets. Center for Budget and Policy Priorities, June 2015.

Bivens, Josh. 2022. “U.S. Workers Have Already Been Disempowered in the Name of Fighting Inflation: Policymakers Should Not Make It Even Worse by Raising Interest Rates Too Aggressively.” Working Economics Blog (Economic Policy Institute), January 21, 2022.

Blanchard, Olivier, and Michael Kremer. 1997. “Disorganization.” The Quarterly Journal of Economics 112, no. 4: 1091–1126.

Bureau of Economic Analysis (BEA). 2022a. Gross Domestic Product (GDP) by Industry, various tables. Accessed November 2022.

Bureau of Economic Analysis (BEA). 2022b. National Income and Product Accounts (NIPAs), various tables. Accessed November 2022.

Bureau of Economic Analysis (BEA). 2022c. “Table 1.1.5. Gross Domestic Product,” National Income and Product Accounts (NIPAs). Accessed November 2022.

Bureau of Labor Statistics (BLS). 2022. Current Employment Statistics. Accessed November 2022.

Chetty, Raj. 2008. “Moral Hazard Versus Liquidity and Optimal Unemployment Insurance.” Journal of Political Economy 116, no. 2: 173–234.

Congressional Budget Office (CBO). 2021. Budget and Economic Outlook, 2021–2031. February 9, 2021.

Dias, Daniel A., and João Duarte. 2016. The Effect of Monetary Policy on Housing Tenure Choice as an Explanation for the Price Puzzle. International Finance Discussion Papers no. 1171, Federal Reserve Board, June 2016.

Economic Policy Institute (EPI). 2022. Current Population Survey Extracts, Version 1.0.36, https://microdata.epi.org.

Federal Reserve Bank of New York (Fed NY). 2022. Global Supply Chain Pressure Index. Accessed November, 2022.

Fernald, John. 2023. Total Factor Productivity, data page. Accessed November 2022.

Jones, Charles. 2006. “Intermediate Goods and Weak Links in the Theory of Economic Development.” American Economic Journal: Macroeconomics 3, no. 2: 1–28.

Klein, Ezra. 2022. “Transcript: Ezra Klein Interviews Larry Summers.” New York Times, March 29, 2022.

Mondragon, John, and Johannes Wieland. 2022. “Housing Demand and Remote Work.” Federal Reserve Bank of San Francisco Working Paper 2022-11, May 2022.

Organisation for Economic Co-operation and Development (OECD). 2022. OECD.Stat online database. Accessed November 2022.

Piketty, Thomas. 2014. Capital in the Twenty-First Century. Translated by Arthur Goldhammer. London, United Kingdom: Belknap Press of Harvard University Press.

Rampell, Catherine. 2022. “An Inflation Conspiracy Theory Is Infecting the Democratic Party.” Washington Post, May 12, 2022.

Rognlie, Matthew. 2015. “Deciphering the Fall and Rise in the Net Capital Share.” Brookings Papers on Economic Activity, spring 2015: 1–54.

Ros, Jaime. 1989. “On Inertia, Social Conflict, and the Structuralist Analysis of Inflation.” Working Paper no. 128, Kellogg Institute for International Studies, Notre Dame University, August 1989.

Shapiro, Adam. 2022. Supply- and Demand-Driven PCE Inflation. Federal Reserve Bank of San Francisco Economic Research.

Summers, Lawrence. 2021. “The Biden Stimulus Is Admirably Ambitious. But It Brings Some Big Risks, Too.” Washington Post, February 4, 2021.

Tobin, James. 1972. “Inflation and Unemployment.” American Economic Review 62, no. 1/2: 1–18.

Tobin, James. 1981. “Diagnosing Inflation: A Taxonomy.” In Development in an Inflationary World, edited by M. June Flanders and Assaf Razin. Cambridge, Mass.: Academic Press.

Zhou, Xiaoqing, and Jim Dolmas. 2022. “Rent Inflation Expected to Accelerate Then Moderate in Mid-2023.” Federal Reserve Bank of Dallas, August 16, 2022.

• Inflation is already normalizing rapidly in the U.S.—a recession is not needed to move it down faster than it is already receding, and hence there is no need to tolerate a recession for longer than normal in the name of normalizing inflation.
• Recessions reliably put downward pressure on inflation and nominal wage growth. Given today’s trajectory of inflation and wage growth, and given the normal downward pressure recessions put on these, any recession will end with the Fed’s inflation target very close to being met regardless of the policy response.
• Even before the COVID-19 recession, there were persuasive arguments that the Federal Reserve’s 2% inflation target was too low. If this is true, it is obviously not necessary to tolerate a recession for longer than normal to get all the way back down to 2%.
• Some claim that the “Volcker shock” of the 1970s and early 1980s showed the benefit of not providing stimulus in the face of a steep recession as it was this steadfastness in tolerating high unemployment that broke the inflation of the 1970s. Much of this is wrong—but most fundamentally, Paul Volcker’s Fed reduced interest rates significantly when an actual recession hit.
• In 2008, a shock to oil prices pushed up inflation modestly even while the U.S. economy was in the beginning of what would turn out to be a fierce recession. This modest inflation shock delayed strong actions from the Fed, making the subsequent recession worse.
• Finally, this debate reinforces how important strong automatic stabilizers are for the economy—and the U.S. currently lacks these. Automatic stabilizers would pull much of the debate about the appropriate response to any given recession out of a polarized political realm and would instead respond simply based on hard economic metrics.

Below, I provide more background on why these observations are true and should guide policymakers.

The economics of recessions and what it means for policy

Contrary to what many think, economics has provided a near certain remedy for ending recessions: using the tools of monetary and fiscal policy to boost economywide spending. The main monetary policy tool is lowering interest rates, and the main fiscal policy tools are transfers of resources to spending-constrained households and the direct expansion of public goods and services. There is a long and convincing research literature demonstrating conclusively that such remedies work if applied together and at scale (and that other proposed remedies are either a sideshow or totally ineffective).

When the economy has remained stuck in a recession or a too slow recovery for extended periods, it is because these tools have not been used concurrently or at the proper scale. The clearest example is the decade-long period when the economy operated in a depressed state following the financial crisis and Great Recession of 2008–2009. This period is fully explainable by the failure to use fiscal policy appropriately during that time, with spending austerity throttling growth and job market recovery after 2011.2

The post-2011 fiscal austerity that impeded growth from the Great Recession had clear political roots: Republican policymakers—both at the federal and the state level—thought that the political credit for a rapid recovery would accrue to the benefit of the Obama administration and so actively sought to slow it with spending austerity. This spending austerity was promptly reversed once the Trump administration took power.3

Inflation is no excuse to meet the next recession with austerity

Given the divided government after the 2022 midterm elections, the prospect of the Republican House majority blocking needed recovery efforts if a recession occurs in 2023 or 2024 seems likely. In the earlier episode after 2011, Republican austerity was enforced by gamesmanship over the debt ceiling, and the rationale for this austerity used vague appeals to fiscal responsibility.

The debt ceiling remains a troubling potential tool that could be used to enforce spending austerity in coming years. But another problem is that the rationale for austerity—the need to enforce fiscal discipline—will likely receive undue respect in much economic reporting and commentary. The burst of inflation in 2021 and 2022 has often been blamed on overly generous fiscal relief in response to the COVID-19 recession. Further, it is often claimed that getting inflation back to the Federal Reserve’s 2% inflation target is the policy goal that must trump all others. If one believed both of these claims, the argument for not fighting the next recession with aggressive fiscal aid if the recession starts with inflation at elevated levels might make some sense.

But neither of these claims is true. The inflation of the past two years is not the result of excessive fiscal stimulus—it is instead the result of enormous global economic shocks (pandemic and war) hitting the U.S. economy and causing large (but steadily dampening) ripples. Further, whenever recession does hit, it will put ferocious downward pressure on all sources of inflation. Whatever inflation is when the next recession starts, it will be very close to—or even below—the Fed’s target when the recession ends, even if we appropriately fight the recession with monetary and fiscal policy.5

Recessions almost always occur when economywide spending by households, businesses, and governments (aggregate demand, in the jargon of economists) falls short of the economy’s productive capacity. This productive capacity (sometimes called potential output) is a measure of the value of goods and services that could be produced in the economy if all productive resources were fully employed. The most important of these productive resources is, of course, labor. Thus, the economy’s potential output can be reached only when unemployment is very low. Other productive resources include the economy’s capital stock—factories, equipment, and real estate needed for businesses or the public sector to produce goods and services.

If aggregate demand is weak, there are too few customers (including of public goods) to justify using all available resources in production (because some of the output produced would go unsold). The answer to this imbalance of aggregate demand and potential output is simple—cut interest rates to encourage more spending and less saving, and use the power of the federal government to run deficits to finance direct transfers to low- and middle-income families (the ones most likely to translate these increased resources into new spending right away) and to directly provide more public goods and services (for example, pull forward infrastructure investments).

This recommendation does not really ever change depending on the state of inflation, and it certainly does not change for the U.S. economy of 2023. For one, recessions put completely predictable downward pressure on inflation. For example, since the 1960s, price inflation has fallen 1.8% on average between the beginning and end of recessions, while nominal wage growth has fallen 1.6% on average.6 Given the consistent normalization of inflation and nominal wage growth that already occurred in the second half of 2022, a price and wage deceleration of these amounts would be fully sufficient to quickly return the economy to growth rates consistent with the Fed’s 2% price inflation target. We do not need a recession to restore inflation to normal, and a recession should not be allowed to linger in the name of fighting inflation.

Theoretically, one could imagine entering a recession with inflation far above the Fed’s 2% target (say 6%) and exiting the recessionary period (if it is very short) with inflation still higher than this (say 4%). The first thing to note about this hypothetical is that if inflation is thought to be too high at both the beginning and the end of a recession, then inflation almost by definition is not being driven simply by excess demand (as recessions are evidence of deficient demand). Given this, imposing a “cure” (allowing a recession to grind on) that utilizes aggregate demand restraint is not a direct solution.

In the 1970s, there was much talk of this kind of inertial inflation, in which too high inflation persists through recessions. It is true that inertial inflation can be broken by a long and steep recession. But making this an intentional policy goal would impose far too large a collateral cost relative to the benefit of doing this.8 Bringing down inertial inflation (which again, is not the type afflicting the United States today) should be done with gradual tools that don’t require mass unemployment. Further, even before the COVID-19 shock there was a convincing case to be made that the Fed’s 2% inflation target was too low.9 The benefit of returning the economy to this potentially excessively low target certainly cannot be worth extending a recession.

Even Paul Volcker pivoted and slashed interest rates when outright recession hit

The inflation of the late 1960s and 1970s was reduced significantly in the early 1980s by a long and extremely costly recession. (Unemployment rates peaked at just under 11% in 1982.) This recession was largely caused by the Federal Reserve—then led by Chair Paul Volcker—raising interest rates to just under 20%. This so-called Volcker shock is often interpreted as Volcker steadfastly refusing to relent on raising interest rates even as recession hit. It is clearly true that interest rates were historically high (and likely inappropriately so—though that’s another debate) for much of the recession and recovery period. But it’s not true at all to say that Volcker did not cut rates as recession struck. In fact, as Figure A shows, the Fed cut interest rates rapidly and sharply as the unemployment rate rose.

Figure A

Further, this easing of monetary policy occurred even as fiscal policy pivoted to being extremely expansionary in the recession and early recovery. Figure B (reproduced from Bivens 2016) shows that real per capita public spending grew far more rapidly following the 1980s recession than in any recession since.

Figure B

In short, it is untrue to suggest that the early 1980s “Volcker shock” showed the benefits of keeping macroeconomic policy contractionary even in the face of outright recession. Instead, both monetary and fiscal policy were made far more stimulative as recession hit. There is no historical episode proving the benefits of failing to fight recessions in order to fight inflation.

Even small delays in implementing anti-recession policy can hurt

In 2008, as the economy was clearly already in a recession (which had been modest up to that point but would turn out to be devastating), oil prices surged due to global factors. This high oil price inflation became a big political issue and led the Fed to delay its full recession-fighting actions. At a Federal Open Market Committee (FOMC) meeting in September 2008—just one month before the collapse of Lehman Brothers kicked recessionary job losses into a much higher gear—the Fed decided against implementing further monetary stimulus. Transcripts of the meeting have subsequently shown that this decision was largely due to worry about the oil price shock: Participants in the meeting seemed more concerned with inflation as the greatest imminent danger to the economy. History decided very quickly which side of that debate was right, and less than a month later the FOMC called an emergency meeting to undertake expansionary policy moves.

This was not an instance of the Fed intentionally tolerating a longer or worse recession per se. It was mostly poor judgement about whether the monetary stimulus the Fed had already undertaken (along with the modest fiscal stimulus that had already occurred) would be sufficient to end the recession. But intentions aside, this example shows that when inflationary fears are used to delay or water down recession-fighting efforts, there are severe consequences.

Automatic stabilizers would shield this debate from partisan politics

This danger that some policymakers might opportunistically use the higher inflation of the past year to block needed fiscal stimulus during the next recession highlights again that a more robust system of automatic stabilizers should be a key priority. Automatic stabilizers are programs that put more resources into the economy when it slows on a formulaic basis and without the need for ad hoc legislation. Examples are unemployment insurance, food stamps, Medicaid, and progressive income taxes.

However, in the U.S. automatic stabilizers are far too weak. In the recovery after the Great Recession, this was a problem because policymakers cut off fiscal aid more quickly than a strong system of conditions-based automatic stabilizers would have.12 For those worried about the potential inflationary effects of large fiscal aid packages passed in 2021, automatic stabilizers that ramped down as the unemployment rate hit conditions-based targets earlier than expected could have perhaps allayed their fears.

Regardless of whether one thinks that the primary problem of fiscal aid in recent decades is that it has been inappropriately long-lived or inappropriately stingy (I certainly weigh in on the “too stingy” side), this dispute could be solved to everybody’s satisfaction if automatic stabilizers were more robust. The fact that partisan political positioning becomes a key concern every time the proper scope of fiscal relief following a recession needs to be determined is a big problem for the U.S. economy.

Notes

1. For relatively recent review of effectiveness of fiscal policy, see Wilson 2020. For evidence on monetary policy effectiveness, see Blinder and Zandi 2010. There is lots of evidence that monetary policy is asymmetric—it’s much stronger in a contractionary phase than an expansionary phase. There is also evidence that monetary policy gets less and less effective the closer to zero interest rates get. Nevertheless, if one wants more aggregate demand and the only tool available is interest rates, they should be moved lower.

2. For evidence on this, see Bivens 2016.

3. For evidence on this, see Bivens 2018.

4. See Banerjee and Bivens 2022.

5. On the disinflationary effect of recessions and higher unemployment, see Blanchard, Cerutti, and Summers 2015. While this paper mostly emphasizes a reduction in the responsiveness of inflation to unemployment over time, the estimates still indicate that higher unemployment is associated with lower inflation. Further, the previous time periods when the relationship between unemployment and inflation was stronger saw inflation rates much closer to today’s rate. There is a lot of reason to think that the responsiveness of inflation to unemployment is substantially stronger when inflation starts at a higher pace.

6. Author’s calculations based on Federal Reserve Bank of St. Louis data n.d.

7. See Bivens 2022 on this consistent normalization.

8. On the different types of inflation—including inertial—see Tobin 1974.

9. On the Fed’s 2% inflation target being too low, see Bivens 2017.

10. Many accounts highlight the damaging role that excess unemployment played in harming wage growth for typical workers after 1979 (see, for example, Bivens and Mishel 2021). But the excess unemployment (i.e., unemployment that could have reliably been avoided with different Federal Reserve policy) in the 1979–2007 period occurred mostly during the recovery and expansionary phase of the business cycle, not during the recession. During recessions, the Fed has traditionally tried reasonably hard to engineer lower unemployment. But during recoveries, it has unnecessarily kept interest rates (and hence often unemployment) higher than they need to be to keep inflation in check. In short, the real damage of too-austere monetary policy was that it cut recoveries and expansions short.

11. See Appelbaum 2014 on how the Fed misread this moment in 2008.

12. For steps to improve the unemployment insurance system, see Bivens et al. 2021.

References

Appelbaum, Binyamin. 2014. “Fed Misread Crisis in 2008, Records Show.” New York Times, February 21, 2014.

Banerjee, Asha, and Josh Bivens. 2022. “Lessons from the Inflation of 2021-202(?).” Working Paper presented at Political Economic Research Institute Conference, December 2, 2022.

Bivens, Josh. 2016. Why Is Recovery Taking So Long—And Who’s to Blame? Economic Policy Institute, August 2016.

Bivens, Josh. 2017. Is 2% Too Low? Rethinking the Fed’s Arbitrary 2% Inflation Target to Avoid Another Great Recession. Economic Policy Institute, June 2017.

Bivens, Josh. 2018. “The ‘Boom’ of 2018 Tells Us That Fiscal Stimulus Works, but That the GOP Has Only Used It When It Helps Their Reelection, Not When It Helps Typical Families.” Working Economics Blog (Economic Policy Institute), October 26, 2018.

Bivens, Josh. 2022. “Recent Data Indicate That a ‘Soft Landing’ Is Still in Reach—the Fed Should Try to Secure It: Ignoring Disinflation Signs Heightens Risk of Recession.” Working Economics Blog (Economic Policy Institute), October 31, 2022. 

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

Bivens, Josh, and Lawrence Mishel. 2021. Identifying the Policy Levers Generating Wage Suppression and Wage Inequality. Economic Policy Institute, May 2021.

Blanchard, Olivier, Eugenio Cerutti, and Lawrence Summers. 2015. “Inflation and Activity—Two Explorations and Their Monetary Policy Implications.” International Monetary Fund Working Paper no. 15/230, November 2015.

Blinder, Alan S., and Mark Zandi. 2010. “How the Great Recession Was Brought to an End.” Working Paper, July 27, 2010. 

Bureau of Economic Analysis (BEA). n.d. “National Data: National Income and Product Accounts” (data series). Accessed December 2022.

Federal Reserve Bank of St. Louis. n.d. “Federal Reserve Economic Data (FRED)” (database). Accessed December 2022.

Tobin, James. 1974. “There Are Three Types of Inflation.” New York Times, September 6, 1974.

Wilson, Daniel J. 2020. “The COVID-19 Fiscal Multiplier: Lessons from the Great Recession.” Federal Reserve Bank of San Francisco Economic Letter, May 6, 2020.

This panic is unwarranted, and the Federal Reserve should not feel free to ratchet up interest rates without regard to the risk of recession. Years from now, a recession induced by the Fed raising rates too quickly will be seen clearly as a policy mistake that could have been avoided. This conclusion stems from several simple facts:

• Both real output and the economy’s underlying productive capacity (potential output) are essentially in line with what pre-pandemic forecasts projected by mid-2022. None of these pre-pandemic forecasts indicated this would imply economic overheating by now. Given this, the macroeconomic balance between demand and supply cannot be so out of alignment that it explains a large share of the acceleration of inflation in the past 15 months.
  • Crucially, potential gross domestic product (GDP) was clearly above actual GDP for most of 2021 when inflation started. This is very hard to square with macroeconomic imbalances driving the rise of inflation.
  • Finally, there is rich, existing literature on the degree of inflation to expect given an overshoot of aggregate demand over potential supply. These estimates imply substantially less inflation than we’ve seen to date, meaning that factors besides simple macroeconomic imbalances are likely at play.
• While the May price data were discouraging, there is reason to think that some of the drivers of inflation in recent months may be losing steam.
  • Profit margins are still at historically high levels but have come down significantly in 2022.
  • Wage growth has lagged inflation over the entire episode and has even decelerated in recent periods. This means that wages’ role as a dampener of inflation looks set to continue (and maybe even strengthen) in coming months.
• The main channel through which higher interest rates will put downward pressure on prices runs through a softer labor market (higher unemployment) reducing growth in labor incomes, which reduces demand and reduces pressure on prices from the cost side as well. But, labor income growth has not been a key driver of inflation so far; in fact, wage growth has significantly dampened the growth of inflation over the past 15 months. In the past six months, hourly wage growth is actually running at a pace entirely consistent with the Federal Reserve’s 2% long-run inflation target.

It has become fashionable to confidently assert that the Fed was “caught flat-footed” by the rise in inflation. This assertion combines bad judgement on two fronts. First, it’s a far too-confident political judgement that inflation clearly reflects worse on policymakers’ judgement than a recession would. Second, it’s a clearly flawed economic judgement about the sources of the inflationary surge in 2021 and 2022, as well as what is necessary to return inflation to normal levels. Put simply, the primary inflation-relevant variable that the Fed’s policy actions can affect—labor income growth—has been dampening inflation over this entire period. Given this, it is far from clear that the Fed should have acted much more aggressively or that the Fed’s seeming turn to a more-aggressive policy going forward is welcome.

However, the Fed is absolutely setting themselves up to get caught flat-footed in the near future if a steady diet of interest rate increases throws the economy into recession. The recently oft-repeated formulation that the Fed must do “whatever it takes” to push down inflation is downright reckless. Monetary policy operates with a lag. By the time it’s clear in the data that the labor market has been deeply damaged by interest rate increases, it will be too late to avoid a recession.

The fact of faster inflation is not proof of large macroeconomic imbalances

There is a growing willingness to point to the simple fact of fast inflation as evidence that it has been caused by a large macroeconomic imbalance of aggregate demand running far ahead of the economy’s productive capacity, and that only contractionary policy can remedy this imbalance. This is flawed economic reasoning, for a couple of reasons.

For one, the level of output currently being produced in the United States, and the underlying productive capacity of the economy, are essentially in line with projections made for early 2022 by forecasters before the pandemic. These forecasts had no sign of inflation in them. If we’re in line with those, then, it is quite unclear why the current level of output could not be produced without lots of inflation.

For another, past episodes of the economy “heating up” as unemployment falls and inflation accelerates have been universally accompanied by real (inflation-adjusted) wage growth and a rising labor share of income. The past 15 months have seen the opposite: falling real wages and a rising profit share.

Figure A below shows both real gross domestic product (GDP) and potential GDP (what the economy could produce if unemployment was roughly 4%). Each line is the ratio of the current estimate relative to pre-pandemic forecasts. For a current estimate of potential GDP, I adjust for the lower labor force participation rate and the (slight) shortfall in business investment that has occurred since the pandemic began. It is perhaps underappreciated how little gap remains now between pre-pandemic forecasts of potential GDP and reasonable estimates of its current value—the labor force participation rate is near-totally recovered and investment has been growing tolerably well since the pandemic recession in 2020.

Figure A

Crucially, in the months when inflation began rising rapidly (mid-to-late 2021), actual GDP remained below potential GDP by these measures. It was only in the last quarter of 2021 when GDP mildly overshot potential GDP (by roughly 0.8%).

This overshoot is nowhere near large enough to have driven the rapid rise in inflation. There is a rich pre-pandemic literature relating inflation and positive output gaps (i.e., inflation arising due to GDP overshooting potential). Even the largest of these estimates (which allow for highly non-linear relationships between output gaps and inflation, with inflation rising more rapidly the more GDP overshoots potential) indicates that a 1% positive output gap should raise inflation by roughly 0.3%. These estimates would require positive output gaps (GDP overshooting potential) of about 10-15% to generate the increase in inflation we’ve seen over the past year if this macroeconomic imbalance was the only cause. This doesn’t seem credible.

This kind of gap analysis is admittedly far from dispositive. But it’s important to walk through for one important reason: Many of those arguing for the most aggressively contractionary stances from the Fed are claiming authority from having been vindicated in their claims that the fiscal relief packages passed in 2021 might spur inflation. But, the predictions that these relief packages would spur inflation were based exactly on this type of gap analysis reasoning. The only difference is that the predictions in early 2021 were explicit that real GDP would be pushed far above potential GDP for an extended period of time, and that is why inflation would result. This overshoot has not happened. There is no serious vindication of their analytical predictions here and hence their arguments should get no special privilege going forward.

Shocks, ripple effects, and components of price growth

Pitted against the view that recent inflation is caused solely by a macroeconomic imbalance is a view that instead sees inflation caused by a series of large shocks (pandemic and war), which set off ripple effects as various economic actors tried to pass on the inflationary shock to others. For example, as pandemic distortions pushed up durable goods prices, workers targeted higher nominal wages while firms looked to protect (or even fatten) profit margins. The shocks have been more frequent and longer lasting than many might have imagined back in March 2021, and the ripple effects larger.

But, based on this view, there is no evidence that the ripple effects are amplifying the initial (and inevitable) inflationary shocks. After a year of pushing up prices significantly, profit margins have started to thin in recent quarters (they’re still fat in historical perspective, but clearly coming down, as shown below in Figure B). Wages have been dampening the initial shocks throughout the past 15 months and show signs of decelerating further. If growth slows throughout the rest of 2022, as is generally projected, it is hard to see the ripple effects of the past year’s shocks doing anything but fading out.

Figure B

It is worth ending with more discussion about wages. The one point of seeming agreement between those arguing for an aggressive reaction by the Fed to brake growth and those arguing against this aggressive reaction is that the key variable to monitor going forward is wage growth. The way the Fed’s interest rate increases would eventually slow inflation largely runs through their effect in raising unemployment and sapping workers’ bargaining power which restrains wage growth. Since wages are both a key source of demand and a cost for firms, this will put downward pressure on inflation.

But in the most recent quarter (March–May), wages grew by just 4.3% (at an annualized rate) compared with the previous quarter (December–February). In the last two months, monthly wage growth (expressed at an annualized rate) has averaged 3.8%. These are wage growth numbers fully consistent with the Fed’s long-run inflation target of 2%. (For more on why a 2% inflation target is consistent with 3.5-4.5% wage growth, see the discussion around Figure C here.)

Using aggressive contractionary monetary policy to squash wage growth even more will put a huge burden on workers to restrain inflation—when they have been the primary victims of it so far. Further, this strategy will leave all the other determinants of inflation—which actually are contributing to its above-normal level—largely untouched, until at least a pronounced slowdown or recession results.

The current panicked demands that the Fed raise rates until something breaks is terrible advice based on bad economic and political analysis. The Fed should instead lay out some real guideposts for how they think their rate increases will slow economic activity and what would constitute an excessively fast deceleration of growth. They should have a plan to pivot and stop rate hikes if there’s evidence they’ve gone too far—that is, if they might cause a recession. They should begin publicly highlighting high-frequency data on wages to assess just how much more labor market softness really would be needed to normalize inflation through labor market channels. In short, they should know that unless wage growth really does become a key amplifier of inflation, then a Fed-induced recession will be seen as a clear policy error and there should be no preemptive permission to make this mistake.

What this report finds: The U.S. unemployment insurance (UI) system has historically underperformed as a macroeconomic stabilizer. While UI, like other automatic stabilizers, is designed to automatically spur aggregate demand when private spending falls (in UI’s case by temporarily replacing some lost wages of jobless workers), the boost is weaker than it could be. The UI system’s fuller potential was highlighted by the extraordinarily large but temporary UI expansions enacted by Congress during the COVID-19 pandemic, which made more workers eligible for benefits, raised benefit levels, and lengthened the duration of benefits. With these expansions, UI benefits as a share of wage and salary income provided an economic boost roughly four times as great during the pandemic as during any previous recession.

Why it matters: Weak automatic stabilizers mean that recessions last longer and inflict more damage than they need to—unless Congress and the president act nimbly and in concert to pass discretionary relief. Even then, the discretionary programs end earlier than they should. Consider for example the UI expansions enacted during the Great Recession that were turned off in 2014— well before a full recovery had taken hold. The less that American families have to rely on ad hoc relief offered only when there is political comity, the better it is for their economic security. As the pandemic UI programs showed, more forceful UI interventions are possible during recessions. If these expansions were set on autopilot, then future recessions would be shorter and less painful, and recoveries would come more quickly.

What we can do about it: Make UI a more powerful macroeconomic stabilizer by enacting reforms along three key dimensions or margins: eligibility, duration, and benefit levels. For example, program parameters could be strengthened to ensure that a larger share of unemployed workers are eligible for benefits, that benefits last long enough to bridge a jobless spell, and that benefits replace a high-enough share of previous earnings to minimize hardship.

The unemployment insurance (UI) system provides critical support during economic downturns, with cash benefits bolstering both the incomes of working people who have lost jobs as well as a flagging macroeconomy (Bivens et al. 2021; Hickey 2021). Signed into law as part of the Social Security Act in 1935 during the Great Depression, the system has historically been one the first lines of response to a downturn, providing immediate financial relief to households whose spending helps stabilize the economy  by boosting economywide consumer spending.

However, weaknesses in the UI system have limited its effectiveness as an automatic stabilizer relative to its potential. Automatic stabilizers are parts of the federal budget—either spending increases or tax cuts—that boost aggregate demand when private spending falls even with no change in legislation. Optimal stabilizers trigger on in a timely fashion as private spending begins slowing, provide a larger boost to aggregate demand as private spending falls further, and only begin ramping down as private spending begins recovering. Today’s UI system is not automatic enough.  

The UI system also has serious flaws as a social safety net program, including troubling racial disparities in recipiency, stringent work requirements, and more. The focus of this report, however, will be UI’s potential as a macroeconomic stabilizer during downturns. In this paper, we highlight three aspects of the UI system that can be augmented to make the system a more-effective macroeconomic stabilizer. Specifically, these areas where—or margins along which— the UI system’s stabilizing effects can be enhanced are the duration of UI benefits (how many weeks benefits last), the generosity of UI benefits (the benefit level), and the eligibility of UI benefits (which occupations or classes of workers can get benefits). We use evidence from the response to the COVID-19 pandemic—when Congress enacted temporary emergency measures that significantly raised benefit amounts, added additional weeks of benefits, and extended eligibility to a much greater share of workers—to show the macroeconomic benefits of permanent, versus ad hoc, expansions to UI. Our main findings are:

• The muted UI response to economic downturns before the COVID-19 shock show that it has long underperformed its potential as a macroeconomic stabilizer, due to short duration, low generosity, and limited eligibility.

• The emergency extended UI benefits that Congress provided in response to the pandemic provided a far larger boost to personal income during the COVID-19 crisis than any previous recession—probably ever, but certainly since personal income data began being systematically collected in 1960. This large boost to personal income meant UI had a far larger effect as a macroeconomic stimulus in 2020. It has the potential to do so again in future downturns.
  • UI as a share of personal income was four times as high in the year after the 2020 recession than the year following 2007–2009 Great Recession.

• • UI as a share of total wage and salary income—a different measure than personal income— reached 13% in 2020, compared with just 2.5% in the aftermath of the Great Recession in 2010.

• Pandemic UI programs—most notably Pandemic Unemployment Assistance (PUA), extending eligibility to workers who previously could not receive UI, and Pandemic Unemployment Compensation (PUC), providing an additional $600 per week on top of existing UI benefits—met the urgent need and filled gaps traditional state UI could not meet.
  • Traditional state UI made up just 20% of all UI by June 2021
  • At its height in the summer of 2020, the PUA program covered nearly 15 million workers who accounted for half of all UI claimants.
  • PUA and other pandemic UI programs were transferring more than $60 billion into personal incomes per percentage of unemployment within a few months after the March 2020 passage of the CARES Act.
• A key barrier to structurally reforming UI to make it a more-powerful macroeconomic stabilizer is that the need for reform is most apparent when the reforms look most expensive in terms of how the Congressional Budget Office (CBO) would score them. In downturns there is more need, which costs more, which makes reforms seem costly if undertaken during recessions. If this skewed cost score prevents policymakers from taking action now, they should consider these reforms when the overall economy begins a strong recovery.

Background on UI—and potential margins of improvement to UI as a macroeconomic stabilizer

The UI program—funded by states and the federal government and mostly administered by states— serves as both social insurance and a macroeconomic stabilizer. In addition to providing immediate relief to struggling households in the form of cash benefits covering a share of lost income, unemployment insurance stimulates a contracting economy by providing unemployed workers with benefits income they can spend in their communities and the broader economy. However, the macroeconomic stabilization function— in other words, the ability for UI to cushion against recessions and spur faster recoveries—has never lived up to its potential.

Since its inception in 1935, the UI system has had clear shortcomings in its ability to deliver robust macroeconomic stabilization in the face of an economic downturn. These shortcomings, which largely fall under three key margins of UI coverage, are insufficient duration of benefits (too few weeks of benefits), inadequate generosity of benefits (low benefits amounts), and limited eligibility (key worker occupations and classes are excluded from benefits). While the federal government sets some basic parameters for the program, state governments are in charge of the details, such as how long benefits last, the benefit amount, and the kind of work history people must prove to claim benefits. Benefits duration and generosity have proven inadequate during normal economic times and fail to automatically ramp up sufficiently during downturns.

Over the decades following its inception, legislative fixes at the federal level tinkered with these gaps in the UI system and offered some improvements. For example, previously excluded workers, most notably agricultural and domestic workers, were finally included. The longtime exclusion of farm and domestic workers, along with the uneven state and local role in administering UI, meant that in practice millions of Black and Hispanic workers were denied and excluded from any UI relief. Also, the duration of benefits got an automatic extension during periods of economic distress with the Extended Unemployment Compensation Act of 1970, which created a mandatory permanent program of extended benefits (EB) (Price 1985). Under the EB program, special EB benefits would be “triggered on” if a certain unemployment rate was reached. Despite this automatic program, Congress still saw a need to address major economic distress among U.S. households after major recessions such as the downturns in 1974, 1982, 1991, 2002, and significantly, 2008, by enacting ad hoc federal temporary programs of supplemented UI, such as the Emergency Unemployment Compensation (EUC08) program (CRS 2014).

However, the most dramatic changes to the UI system came in the wake of the recent 2020 crisis. This sharp downturn, driven by the COVID-19 pandemic, forced millions out of work in mere weeks, and spurred a rapid congressional response to temporarily reinforce and expand existing UI programs. The temporary expanded unemployment insurance programs created in the Coronavirus Aid, Relief, and Economic Security (CARES) Act of 2020 expanded traditional UI on three margins: duration, generosity, and eligibility.

Duration: The Pandemic Emergency Unemployment Compensation (PEUC) program provided up to 53 weeks of additional UI payments that laid-off workers could tap into after exhausting traditional UI benefits and EB.

Generosity: The Pandemic Unemployment Compensation (PUC) program provided an additional $600 per week on top of existing UI benefits. This program was allowed to expire in July 2020. The Lost Wages Assistance (LWA) program, which provided six weeks of additional $300 weekly UI from disaster relief funds, was authorized until September 2020. Congress renewed the PUC at $300 per week in an appropriations bill in December 2020 and then in the American Rescue Plan (ARP) Act of 2021.

Eligibility: The Pandemic Unemployment Assistance (PUA) program extended UI eligibility to workers who previously could not receive UI, such as workers classified as independent contractors, app-based and “gig” workers, part-time workers, and workers with short or irregular work histories. PUA also extended eligibility to workers who voluntarily left jobs in response to public health fears spurred by the pandemic and the closures of schools and day care centers.

This paper focuses on the UI program’s role as a macroeconomic stabilizer and will explore the ways UI could be augmented as an automatic stabilizer. Research from before the 2020 crisis shows the relatively modest boost that the UI system provided at the outset of past economic downturns. For example, Chodorow-Reich and Coglianese (2019) estimate that all of the extended UI benefit programs—both standard EB programs and the ad hoc emergency unemployment compensation programs passed in 2008—probably served to lower the overall unemployment rate by only about 0.2% in 2010 (the labor market trough of the Great Recession, when unemployment was 5 percentage points higher than in the pre-recession years of 2006 and 2007).

However, the 2020 UI modifications and improvements were the most significant in history, and they likely provided a much larger potential stabilizing role for the economy.1 This paper will analyze the extended UI programs enacted in response to the 2020 crisis to compare the counter-cyclical fiscal boost provided by the 2020 UI programs with UI response in previous downturns. Even as policymakers allowed the pandemic UI to cease completely by September 2021, the performance of UI as a potential macroeconomic stabilizer in 2020 ought to be examined carefully as a lesson for future downturns if policymakers return to the issue of long-term reforms of the UI system.

UI as an income stabilizer during the COVID-19 crisis compared with previous downturns

UI supplements household income after a job loss and provides a buffer to economywide consumption spending in the face of sudden earnings losses. Looking at UI’s share of household personal income (which includes wage and salary income as well as government social benefits such as Social Security, Medicare, Medicaid, and UI) before and after recessions can give a rough estimate of the boost provided solely by UI. Figure A shows the average boost from UI to personal income across business cycles from 1960.

Figure A

The first bar in each pair indicates UI income as a share of personal income during the official recession period, relative to the year prior to the recession. The second bar compares the share of personal income accounted for UI during the first year of recovery relative to the year prior to the recession. As can be seen, because in many recessions, employment losses have lagged behind other measures of recession, the boost from UI is often greater in the first year of recovery than during the official recession.

The most striking finding of the figure, however, is that expanded UI produced a dramatically larger boost to personal income both during and after the COVID-19 crisis compared with prior recessions. In past downturns, UI provided only a very modest boost to personal income. For example, even in the Great Recession of 2008–2009, UI boosted personal incomes only by about 0.3% in the depths of the recession, compared with just under 1% in the COVID-19 crisis. Critically, in 2020, UI also boosted personal incomes in the immediate recovery: UI’s share of personal income rose 2.3% (in the first year of recovery from the Great Recession, UI’s share rose a mere 0.6 percentage points).

In some sense, looking at the UI’s boost to overall personal income during the COVID-19 crisis can understate how transformational it was for the lives of workers. COVID-19 relief legislation included many large transfers besides UI expansion, such as the stimulus checks and expanded Child Tax Credit (CTC), which boosted personal income as well. Given that UI serves explicitly as a replacement for lost labor earnings, Figure B isolates this role by looking at UI as a share of wage and salary income plus UI payments. Examined this way, the UI response to the COVID-19 recession far overshadows any previous downturn since 1979.

Figure B

The impact of the expanded UI provisions from the CARES Act passed in late March 2020 is most evident from May to July 2020 when UI reached a staggering 13% of wage and salary income. The sharp fall after July mostly reflects the failure of Congress to extend the supplemental UI programs.2

From a macroeconomic point of view, UI boosting personal incomes (and labor earnings) both during a recession and immediately after is supremely valuable. With UI payments, households headed by those who have lost jobs have more funds to cover their rents, living expenses and debts, and hence consumption throughout the economy is buttressed even as earnings fall. This dynamic also works in reverse: If UI is cut prematurely when the labor market is still weak, the reductions in household incomes put downward pressure on consumption spending, which then slows economic growth.

What we learn from looking at UI support during and after recessions since 1960 is that policymakers have never used UI as effectively for macroeconomic stabilization as they did for the 2020 COVID-19 crisis. By expanding UI so significantly in duration, generosity, and eligibility during the crisis, federal policymakers greatly augmented UI’s potential role as a macroeconomic stabilizer. Given how the U.S. economy has taken longer and longer to regain pre-recession health after each recession since the early 1980s, any lessons on improving automatic stabilizers and fostering more rapid recoveries should be examined closely (Freeman 2013).

In the next section, we provide some rough quantification of how important changes to each of the three critical elements—duration, generosity, and eligibility—are to UI’s outsized performance in stabilizing incomes during the COVID-19 crisis. We then evaluate how expansions in these three areas could be incorporated into a long-term reform of UI. It is well-known by now that UI generally does not respond automatically enough or at sufficient scale to downturns (Bivens et al. 2021). Even more glaringly, sometimes recession-driven expansions are pulled back before full economic recovery is reached (Bivens 2016). Enhancing the margins along which UI can effectively stabilize the macroeconomy and having those margins respond automatically to downturns could provide a much better buffer against future recessions and too-slow recoveries.

How the pandemic UI programs expanded benefit duration, generosity, and eligibility

Historically, the changes to UI duration, generosity, and eligibility have been relatively modest, even in the face of recessions. Regarding eligibility, some states have opted to relax eligibility requirements during recessions (CRS 2020; Congdon and Vroman 2021). The federal “extended benefit” (EB) program operating in all states is meant to trigger-on automatically as the unemployment rate rises, but it has serious flaws (Bivens et al. 2021). Largely due to these flaws, UI duration is often extended on an ad hoc basis by Congress during national recessions. Finally, benefit levels have traditionally been very modest in standard UI programs (generally replacing substantially less than 50% of workers’ wages) and have been only rarely boosted in response to recessions, and even then, only modestly. For example, the American Recovery and Reinvestment Act of 2009 boosted weekly UI benefits by $25.

Gauging the need for expanded eligibility 

The large pandemic changes to UI eligibility can be seen clearly in Figure C, which shows weekly claimants of UI from 1986, with special programs highlighted.

Looking at UI program by claimants tells us a few things, even before we get to issues of eligibility. First, before the 2008–2009 Great Recession, nonstandard UI programs (either EB or EUC) provided only very small shares of total UI coverage. Second, the 2020 COVID-19 recession, in both severity and federal fiscal response, was unprecedented in nature compared with previous downturns since 1986. From 1986 through 2007, weekly claimants never rose above 7 million. While the downturns between 1986 and 2007 were certainly less severe, many potential claimants were likely shut out of UI or undercompensated due to the lack of extended benefits duration and eligibility and lack of expanded benefit amounts.

Figure C

Crucially for eligibility, the impact of the PUA program (the pandemic program expanding eligibility to workers not traditionally covered by UI) in 2020 and 2021 is striking. With over 30 million claiming unemployment insurance at the height of the downturn, traditional UI declined heavily as a source of UI coverage, falling from 100% of all UI (pre-CARES Act) claims to just 20% by June 2021. At its peak in August 2020, PUA was covering 15 million workers, and made up half of all UI claimants. PUA recipients are generally workers who just would not have been covered at all under traditional UI, and who would hence have had no income support to buffer their spending as jobs dried up.

Figure D provides another way of highlighting the importance of PUA and the eligibility expansion to macroeconomic stabilization. It shows the total dollar contribution of UI to personal income divided by the unemployment rate. This is a measure of how much UI adds to personal income for each percentage-point increase in the overall unemployment rate.3 The figure separates out the PUA program contribution from all other UI programs. Within a few months following the CARES Act, non-PUA UI programs were transferring more than $60 billion into personal incomes per percentage point of measured unemployment, and even as of spring 2021 were transferring more than $40 billion per percentage point of unemployment. PUA programs, however, were transferring almost exactly as much as non-PUA UI in the summer of 2020 and the winter of 2021, effectively doubling the effectiveness of the entire pandemic UI system. This highlights just how important modernizing the eligibility component could be for boosting the UI system as a macroeconomic stabilizer.4

Figure D

Gauging the need for benefits that last longer 

Looking at claimants in the 2008–2009 crisis in Figure C also offers key insights about potential benefit duration (i.e., the maximum number of weeks of UI benefits that applicants meeting the criteria could obtain). First, extended programs have provided some nontrivial expansions of UI coverage in the past. At its peak in 2010, the EUC program enrolled an average of 4.6 million workers (the EUC program is reflected in the Nonstandard (discretionary) federal programs stack in Figure C). However, a sharp cutoff of the EUC program in 2014 is clearly visible as well—this cutoff, which happened due to congressional whim rather than any serious assessment of labor market health—occurred with the unemployment rate still over 7%, a higher level than occurred at any point during the labor market recession of 2001–2003. This 2014 cutoff likely had serious effects on the pace of recovery in subsequent years (Shierholz and Mishel 2013).

One reason why the EUC program was so important was because the automatic state-administered EB programs were so flawed, and many states saw the EB benefits trigger-off even at quite-high unemployment rates. In Figure C, this can be seen in how small EB enrollments were relative to EUC in the pre-2014 years of the recession and recovery.

Despite its importance, the EUC program was cut off too early, depriving workers of benefits they would have gotten were the UI program designed to extend benefits while the labor market is still in serious distress. Figure E demonstrates just how premature the 2014 cutoff of EUC was by showing how many states would have allowed workers access to extended potential benefit durations if these extended benefits triggered off only when the state unemployment rate fell to 6%, 5.5%, or 5%.

Figure E

The results are striking. By January 2014, EB programs had all triggered off and the EUC program had lapsed. In 2014, workers in 37 states would have been able to access extended benefit durations if 5% was the benchmark for triggering-off these provisions, and 27 states would have kept extended benefits available to unemployed workers even with a 6% benchmark. Even in 2016, a 5% benchmark would have allowed 21 states to continue offering extended benefits, with seven states keeping them with a 6% benchmark.

Gauging the need for higher benefit levels

Perhaps the most well-known changes to UI made during the pandemic concerned the level of benefits. The FPUC program within the CARES Act provided a $600 boost to weekly benefits. The $600 figure was chosen to ensure at least 100% wage replacement for essentially all workers. This high replacement ratio arguably made economic sense in this context. During the peak spread of the virus in 2020, it was essential from a public health standpoint that people not work in person; non-employment was actually a policy goal during this brief period and hence any moral hazard concerns regarding the effect of UI recipiency on incentives to search for jobs were rightly considered insignificant. The original $600 boost was cut off in August 2020. In January 2021, a $300 boost provided by congressional appropriators in December 2020 was codified in the American Rescue Plan. In July and August, a number of states chose to end the PUC programs early. By early September all pandemic UI programs had lapsed, and as of early October, prospects for any resuscitation of these programs seem extremely remote.

There is no evidence the original $600 top-up in additional UI benefits throttled economic recovery, as the extraordinarily rapid bounceback from the first wave of COVID-19 shutdowns began before the $600 benefit expired in summer 2020. Additionally, significant economic research has emerged showing that states that cut off the $300 boost early, claiming that it dissuaded job search activity, have not seen sustained job growth or hiring either. Knowing that the benefit expansions did not cut off economic recovery can inform UI reforms that incorporate large benefit extensions for future downturns.

Parsing out how expanded benefits eligibility, duration, and levels contributed to stabilizing the pandemic economy 

All three pandemic UI programs and the expansions they provided along crucial margins—PEUC (duration), PUC (generosity), and PUA (eligibility)—boosted the income support provided by UI enormously. Figure F shows the relative contribution of each pandemic UI program to wage and salary income since March 2020.

Figure F

We can see the efficacy of the three programs in tandem as well as the dramatic impact of letting the $600 weekly PUC program expire in summer 2020 and resume at a lower level in 2021. While the impact of PUA (expanded eligibility) is relatively steady throughout 2020 and 2021, the importance of PEUC (additional weeks) appears only from October 2020 onward as more claimants exhausted other UI options and the number of long-term unemployed persons increased. The extended duration of the PEUC program also made a larger impact than the EB program, which shows a much smaller contribution to income in late 2020 and 2021. As shown before in Figures A and B, the cumulative impact of these programs was huge, and each program provided a crucial role.

These dramatic expansions and their salutary macroeconomic effect should inform policymakers as they ponder long-term reforms to the nation’s UI system.

Issues in assessing the likely 10-year fiscal costs of UI reforms 

The UI system’s weaknesses as a macroeconomic stabilizer have been known for some time—and were particularly apparent during the long and slow recovery following the Great Recession. There are likely many political reasons why these weaknesses have not been addressed—many not unique to UI and likely related to why the U.S. has such a small fiscal footprint across-the-board. But some oddities in how the fiscal cost of these reforms might be scored add to the difficulties of reform.

Policy efforts to make automatic stabilizers like the UI system more responsive and more effective in supporting aggregate demand during economic downturns suffer greatly from a problem of timing inconsistency—the minds of the public and policymakers are focused on this need most when undertaking a permanent reform will look expensive as scored by the Congressional Budget Office (CBO). As explained below, reform will only look substantially cheaper in CBO scores precisely when the need for reform seems less urgent (during expansionary periods).

House Speaker Nancy Pelosi summarized the issue when asked why Congress had not taken up permanent reform to the UI system as part of efforts to respond to the economic shock caused by COVID-19.

At a May 14 press conference, House Speaker Nancy Pelosi laid it out. ‘I’m a big supporter of having stabilizers in the bill,’ she said. She blamed their absence on the Congressional Budget Office (CBO), which estimates the costs of legislation, because under CBO’s rules, the likely cost of the stabilizers ‘counts in the bill today.’” (Klein 2020)

The reason for this time-inconsistency issue is straightforward: the CBO essentially assumes the economy moves from its current state of slack (weak economic demand and weak demand for labor) to a state of full employment within a few years, and that developments four years or more out cannot be precisely forecast. In practice, this means if the economy is currently experiencing high unemployment and a permanent reform to the UI system was proposed, the CBO would (sensibly) forecast unemployment to be elevated for the next few years before settling down closer to full employment. In these first few years with elevated unemployment, a substantially more-generous UI system would be scored as being quite expensive in the short-run as many unemployed workers would be drawing benefits. Conversely, if the economy were currently experiencing quite low unemployment and a permanent reform of UI was proposed, the CBO would forecast low unemployment over the entire 10-year budget window, having no real capacity to forecast otherwise more than a few years down the road. A low unemployment rate over the entire 10-year budget window would in turn make reforms to UI look significantly cheaper when implemented in this hypothetical low-unemployment year than if implemented during a recession.

Of course, it should be noted that when the national unemployment rate rises during and after recessions, Congress has tended to do something to boost the generosity of the UI system, even with no “automatic” spending that the CBO could reliably put into a budget forecast. Further, these ad hoc UI enhancements (longer benefit durations generally, along with an occasional small boost to weekly benefits) have added to federal spending. So the refusal to pass a permanent change to UI during recessions makes little sense in real-world fiscal terms: Automatic or not, UI spending rises during recessions, regardless of what the CBO has previously forecast for such spending. Any reluctance to undertake structural reform to automatic triggers during times of labor market distress really seems to be a case where costs forecast by the CBO are somehow more daunting to policymakers than costs accompanying the passage of real-time legislation during recessions.

Would the CBO score UI reform as “free” if undertaken during an expansion? 

It is not quite the case that a structural reform to UI that increased UI payments during labor market downturns would be forecast as essentially free by the CBO if scored when unemployment was low. The CBO has little basis to forecast the timing of recessions outside of the next year or two, but it does (sensibly) recognize that recessions are likely to occur in any such 10-year window.

Consider, for example, a scenario in which the unemployment rate is 4.5% in the current year and a UI reform is proposed that only provides higher levels of UI funding (longer durations or more-generous benefits) if the unemployment rate rises above 5.5%. In this situation, the baseline CBO forecast will show essentially constant 4.5% unemployment over the next 10 years. But the CBO will draw on historical experience to estimate a probability that unemployment will rise over 5.5% for a given period of time over that window. In a paper explaining this process, the CBO refers to this as “estimating the costs of one-sided bets.”5

In practice, if a UI reform that contained the elements we highlighted above were passed today, the CBO score of its cost over the next 10 years would likely add up its “normal” cost (cost increases during time when the national unemployment rate was below any “trigger”) and then would add on the expected value of recession-driven costs. The rest of this section aims to provide a very rough estimate of how these issues would be estimated in the context of ambitious UI reforms.

What would UI expansions along all three margins cost?

The rest of this section addresses these questions of a UI reform’s fiscal cost and how a reform package might be scored by the CBO. For an archetype reform, we look at the budgetary cost of a reform that makes the following changes:

• doubles UI recipiency rates (share of unemployment workers receiving UI benefits) during times of non-elevated unemployment
• increases UI benefit levels by a factor of 1.75
• provides for automatic triggering of extended potential benefit durations during times of high unemployment, with the longest maximum potential benefit duration rising to 95 weeks when unemployment hits 10%
• boosts benefit levels during recessions by an average of $100 per week (over already-augmented benefit levels in normal economic times). These reforms are very roughly in line with a set of reforms suggested by Dube (2021) and Bivens et al. (2021).

These parameters are slightly more generous than those suggested in a recent policy white paper released by the offices of Sens. Ron Wyden (D-Ore.) and Michael Bennet (D-Colo.).

Likely budgetary costs of making UI a more effective macroeconomic stabilizer

Rough budgetary costs for the first two margins—expanded eligibility and more-generous normal benefit levels (bullets one and two above)—are relatively straightforward to calculate for periods of low unemployment (i.e., before any recession-driven triggers kick-in). However, assessing the cost of longer potential benefit durations and increases in benefit generosity that rise as labor market conditions deteriorate (bullets three and four) requires drawing on others’ research.

Costs of expanded eligibility and increased standard benefit levels 

A number of UI reform proposals (Dube 2021 and Bivens et al. 2021) include measures both to expand eligibility and to raise benefit levels even during periods of low unemployment. To get a very rough estimate of the budgetary cost of proposals like this, we can look at average UI spending between 2016 and 2019 and then adjust it for a counterfactual where eligibility requirements were expanded such that the recipiency rate doubled, and where there was an across-the-board increase in benefit levels.

Table 1 provides most of the information needed for this calculation. It shows that in 2016–2019, the unemployment rate averaged 4.2%, and average spending on UI was $29.6 billion annually. The recipiency rate averaged 27.3% and the average replacement rate for benefits was 39.2%. If the recipiency rate doubled and replacement rates increased by a factor of 1.75 (from 39.2% to 68.6%), then spending would increase an estimated $36.3 billion in those years ($65.9 billion minus $29.6 billion), or, roughly 0.15% of gross domestic product.

Table 1

Adding the costs of automatic expansion of potential benefit durations and higher weekly benefits during labor market recessions 

Assessing costs for new parameters that depend upon the state of the business cycle is a much more complicated task. Luckily, Chodorow-Reich and Coglianese (2019) have done extensive work in simulating how the cost of various UI reform proposals would vary depending on the severity and length of potential recessions. Table 2 uses their findings as a baseline to assess costs of the UI reform outlined in the four bullets earlier, but then shows how the probability of recession affects these costs. A fuller explanation of how we derived costs in this table is provided in the appendix.

Table 2

The first row of Table 2 simply shows the 10-year cost of current law regarding UI and the 10-year cost of the reform detailed above if no recession occurs over those 10 years. We include two columns for the “current law” estimate because we assess this cost under two assumptions: that Congress passes no emergency boost to UI during recessions, or that Congress provides the same emergency boost that it has typically legislated in past recessions. In the first row, because no recession is assumed, these costs are identical in the two “current law” scenarios. The cost under reform starts from the $65.9 billion cost estimated in Table 1 for the first year, and then accounts for inflation and labor force growth.

The next two rows provide estimates of the incremental 10-year UI costs spurred by either a mild or severe recession. Under current law, assuming no discretionary response from Congress, the incremental cost is driven by the fact that the federal government finances half of the extended benefit (EB) programs that trigger-on at the state level when unemployment rises.

For a severe recession, we assess the costs of current law assuming a discretionary response by applying the incremental boost to UI spending provided between 2008 and 2013—the period of labor market distress caused by the Great Recession. For the mild recession, we mark-down the spending in the severe recession by 45%, a ratio we obtain from the Chodorow-Reich and Coglianese (2019) estimates of UI costs during recessions of different intensity. Finally, for the incremental cost of recession under reform, we take the Chodorow-Reich and Coglianese (2019) estimate of their proposed reforms and wedge them up to reflect the increased costs of the archetype 2021 reform relative to their proposals. For example, their reform calls for a $50 per week increase in benefit levels during recessions, but our enhancements call for an average increase of $100 during recessions (over already-augmented benefit levels in normal economic times). Accordingly, we double their estimate of the cost of a benefit increase during mild or severe recessions.

Over the next 10 years, assuming no recession, UI spending would be $330 billion under current law, but would rise to $690 billion under our reform. In the case of a mild recession at some point during the decade, under current law and with no discretionary action from Congress, UI spending would be $373.6 billion over the next 10 years ($330.0 billion plus the incremental cost of recessions of $43.6 billion shown in Table 2). Under current law but with discretionary actions by Congress similar to past recessions, UI spending would be $547.7 billion over the next 10 years if there were a mild recession during that period. Under our archetype reforms, spending over the next 10 years would be $924.1 billion over the next 10 years if there were a mild recession during that period.

The last row translates these scenarios to an average annualized cost over the next decade when factoring in the 1-in-3 chance that the economy experiences no recession, the 1-in-3 chance that it goes through a mild recession, and the 1-in-3 chance it suffers a severe recession over the next 10 years. Under current law but assuming no emergency spending measures enacted by Congress during recessions, average annual costs would be $37.1 billion for the next decade. Under current law but assuming Congress acts as it has in the (pre-COVID-19) past during recessions, average annual costs would be $53.3 billion. Under the archetype reforms outlined earlier (doubled UI recipiency rates and almost doubled benefit levels during times of non-elevated unemployment, maximum potential benefit duration rising to 95 weeks when unemployment hits 10%, and an additional $100 per week boost to benefit levels during recessions), average annual costs would be $106.6 billion.

Conclusion

In previous economic downturns, benefits paid out under the current unemployment insurance system provided only modest boosts to aggregate demand, and thus has had a limited role as an automatic stabilizer. However, the pandemic UI programs greatly boosted the contribution that UI benefits made to personal income. These programs enhanced the UI system’s effectiveness in boosting personal income along three crucial margins: expanding eligibility to more workers, extending the potential number of weeks that eligible workers could claim benefits, and increased benefit levels. Policymakers going forward should examine this episode closely to see how eligibility, benefit levels and duration enhancements could be part of a structural reform of the UI system to make UI a more effective macroeconomic stabilizer.

Appendix: Table 1 and 2 methodology

The first column of Table 1 reports the average values over 2016–2019 for the unemployment rate, the share of unemployed workers receiving UI benefits (the recipiency rate), the average share of wages replaced by UI benefits (the replacement rate), and annual UI spending (in billions of dollars). Between 2016 and 2019, overall unemployment was low by historical standards, so the annual UI spending can be interpreted as what could be expected in years when the labor market is not seriously damaged by current or recent recessions.

The next column shows what the recipiency rate, the replacement rate, and average annual spending would have been in those years if the broad reforms described in the paper were made. Note that in practice this means what the rates and spending would be under implementation of the two of the four broad reforms that have to do with eligibility and benefits levels during standard times. The table assumes reforms that would boost recipiency during nonrecessionary times by 100% (pushing the recipiency rate to 54.5%) and would boost the replacement rate of UI benefits by 75% (boosting the replacement rate to 68.6%). Given more people collecting higher benefits, annual UI spending would more than double, rising from just under $30 billion to almost $66 billion.

We use these numbers as inputs for the calculations made in Table 2, which shows in very broad strokes how the CBO might be likely to score large reforms to UI. The first row of Table 2 shows the likely 10-year cost of UI spending under current law and under the reform if no recession occurs over the 10-year window. The current law trajectory includes two different scenarios: one where Congress provides no emergency response to a recession with discretionary spending measures, and one in which Congress provides a discretionary response that is similar to the congressional response to past recessions. This second scenario is necessary for a realistic assessment of the incremental cost of UI reform that strengthens the system’s automatic response to recessions. In the absence of automatic change in UI parameters, the realistic alternative is not no change at all to UI during recessions—Congress routinely steps in and provides some extra boost to UI during recession (even if this discretionary boost is often insufficient and too short-lived).

The next two rows in Table 2 show the incremental cost over and above the “no recession” scenario that would be imposed by a severe or mild recession. Under this scenario, the two additional reform measures outlined in our report (maximum potential benefit duration rising to 95 weeks when unemployment hits 10%, and an additional $100 per week boost to benefit levels during recessions) would kick in. To assess the costs of these reforms, we draw on calculations in Table 2 of Chodorow-Reich and Coglianese (2019), who assess the incremental costs of current UI law under a range of recessionary scenarios. They then assume three UI reforms which are largely in line with our reforms. We use the ratio of their reform costs to current law costs in recessionary scenarios as a “multiplier” to apply to our own reform costs during recessions. Further, when our reforms are more expensive than the Chodorow-Reich and Coglianese reforms, we inflate estimates of our reforms appropriately. For example, Chodorow-Reich and Coglianese (2019) call for a $50 weekly supplement to UI during recessions, while under our reform the boost would be $100 a week. Similarly, because our reforms call for modestly longer potential benefit durations during recessions than do Chodorow-Reich and Coglianese, we boost the estimated costs of these by 20% relative to their estimates.6

Finally, the last row calculates the annualized cost of each of the three policy regimes: current law with no emergency or discretionary response, current law with emergency response during recessions, and the archetypal reform outlined in our report. To calculate these annualized costs we assume there is a one-third probability each of: no recession during the next 10 years, a mild recession during that time, or a severe recession. Under the current-law no-emergency response policy scenario, annualized UI costs would average $37.1 billion each year over the next decade. Under the current-law, emergency response scenario, these costs would rise to $53.3 billion annually. Finally, under the enhancements outlined in this report, the costs of UI would average just under $107 billion annually.

Acknowledgments

This report was made possible by support provided by the Peter G. Peterson Foundation (PGPF). Melat Kassa and Jori Kandra provided research assistance and Lora Engdahl edited.

Endnotes

1. We say “potential” stabilizing role because the large UI expansions in the CARES Act were not entirely meant to stabilize macroeconomic measures like GDP. In most recessions, a prime goal of expanding UI would be precisely to stimulate economic activity. But in a pandemic-driven recession where much economic activity was shut down due to public health concerns, the primary role of UI was social insurance and redistribution. That said, the very rapid bounceback of economic activity after the first wave of pandemic shutdowns was certainly aided by the income boost provided by the CARES Act UI expansions—and that is true for the rapid bounceback of activity so far in 2021, following the UI expansions in the American Rescue Plan (ARP).

2. A small share of the drop-off after July is due to improving labor market conditions.

3. This measure allows us to get a measure of UI generosity by controlling for the fact that UI mechanically rises as the unemployment rate rises.

4. Alongside independent contractors and gig workers, the PUA program also expanded eligibility to those who were unemployed or unable to work due to COVID-19, including caring for someone with the virus, providing care to a child or family member whose school or care facility was closed, or refusing to work in an unsafe work environment. This array of eligibility extensions meant that a not-insignificant share of PUA recipients were those who quit their jobs due to fear of the virus, contagion, and unsafe work conditions or who left the workforce due to school closures and lack of affordable and safe child care. These eligibility criteria were specifically included due to the particular nature of the public health crisis directly impacting employment. Future UI reform programs expanding eligibility will very likely not contain such broad eligibility conditions. Therefore, we would not expect structural UI reform at the federal level to boost eligibility as much as the 2020 PUA program. Unfortunately, specific recipient and eligibility breakdowns within the pandemic UI programs are not available. While the U.S. Department of Labor compiles the aggregate PUA figures, more specific tracking within programs has not been possible, partially due to state administering of UI and variance of reporting requirements, as well as the state administrative burden of implementing the pandemic programs.

5. The “natural rate” of unemployment is the rate below which further increases in economywide spending will mostly lead to accelerating inflation rather than greater output. In a well-managed macroeconomy, any time spent 1% over the economy’s natural unemployment rate should be matched by an equivalent amount of time spent 1% below the economy’s natural unemployment rate. But, because in most proposed reforms UI benefits do not get cheaper or less expansive as the unemployment rate falls beneath the natural rate, this does not provide one-for-one countervailing savings that cancel out the fiscal effect of UI benefit expansions that kick in as unemployment rises.

6. This 20% is likely an overestimate. Chodorow-Reich and Coglianese (2019) show that potential benefit durations of over 46 weeks did very little to boost overall UI spending during the Great Recession.

References 

Bivens, Josh. 2016. Why is Recovery Taking So Long—And Who’s to Blame? Economic Policy Institute, August 2016.

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

Bureau of Economic Analysis (BEA). 2021b. “Table 2.1: Personal Income and its Disposition”, National Income and Product Accounts. Accessed July 2021.

Bureau of Economic Analysis (BEA). 2021a. “Effects of Selected Federal Pandemic Response Programs on Personal Income.” March 2021.

Bureau of Labor Statistics (BLS). 2021a. “State Unemployment Rates Over the Last 10 years, Seasonally Adjusted: June 2011 to June 2021.” State Employment and Unemployment Chart Package, 2021.

Bureau of Labor Statistics (BLS). 2021b. Unemployment Rate Data Series ID LNS14000000 [Excel file], Accessed July 2021.

Chodorow-Reich, Gabriel, and John Coglianese. 2019. “Unemployment Insurance and Macroeconomic Stabilization.” In Recession Ready: Fiscal Policies to Stabilize the American Economy, edited by Heather Boushey, Ryan Nunn, and Jay Shambaugh, 153–179. Washington, D.C. Brookings Institution.

Chodorow-Reich, Gabriel, John Coglianese, and Loukas Karabarbounis. 2019. “The Macro Effects of Unemployment Benefit Extensions: A Measurement Error Approach.” Quarterly Journal of Economics 134, no. 1: 227–279.

Congdon, William J. and Wayne Vroman. 2021. Extending Unemployment Insurance Benefits in Recessions: Lessons from the Great Recession. Urban Institute, February 2021.

Congressional Research Service (CRS). 2014. Extending Unemployment Compensation Benefits During Recessions. CRS Report RL34340, October 2014.

Congressional Research Service (CRS). 2020. Comparing the Congressional Response to the Great Recession and the COVID-19-Related Recession: Unemployment Insurance (UI) Provisions. CRS Report R46472, July 2020.

Dube, Arindrajit. 2021. “Aggregate Employment Effects of Unemployment Benefits During Deep Downturns: Evidence from the Expiration of the Federal Pandemic Unemployment Compensation.” National Bureau of Economic Research Working Paper no. 28470, February 2021. https://doi.org/10.3386/w28470.

Freeman, Richard B. 2013. “Failing the Test? The Flexible U.S. Job Market in the Great Recession.” National Bureau of Economic Research Working Paper no. 19587, October 2013.

Hickey, Sebastian. 2021. “New Personal Income Data Show the Need for Broad and Permanent Unemployment Insurance Reform.” Working Economics Blog (Economic Policy Institute), April 23, 2021.

Klein, Ezra. 2020. “The Vital Missing Piece of the Democrats’ Stimulus Bill.” Vox, May 28. 2020.

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Price, Daniel N. 1985. “Unemployment Insurance, Then and Now, 1935-85.” Social Security Bulletin 48, no. 10: 22–32.

Shierholz, Heidi, and Lawrence Mishel. 2013. Labor Market Will Lose 310,000 Jobs in 2014 if Unemployment Insurance Extensions Expire. Economic Policy Institute, November 2013.

U.S. Department of Labor Employment and Training Administration (U.S. DOL-ETA). 2021. Unemployment Insurance Data: Continuing Claims, All Programs [Excel file]. Accessed April 2021.

This report assesses the potential macroeconomic impact of two pieces of legislation pending in Congress: the Infrastructure Investment and Jobs Act (IIJA), which incorporates elements of the American Jobs Plan (White House 2021a, 2021c, 2021d), and Congress’s $3.5 trillion (over 10 years) budget reconciliation bill, still being written in Congress, which incorporates measures proposed under the Biden administration’s American Families Plan of the Build Back Better agenda (White House 2021b). The investments and social insurance expansions provided for by these plans will boost productivity and provide key relief to family budgets in coming years. The benefits from these policies will be realized even if the economy has reached full employment when they take effect. Moreover, these plans also provide a valuable backstop against the possibility that the economic recovery falters after 2022 as the effect of the American Rescue Plan (ARP) fades, as was the case when fiscal support for recovery ended prematurely following the Great Recession. This report highlights just how strong a fiscal backstop the plans will provide.

The two pieces of legislation, amounting to just over $4 trillion in new spending over 10 years, reflect versions of the Biden-Harris administration’s economic agenda that have been scaled back in order to strike political compromises necessary to earn support for passage in Congress. In departing from more ambitious plans, Congress will reduce the level of insurance the legislation provides against a flagging recovery in coming years (Zandi and Yaros 2021). Nonetheless, together these two pieces of legislation would provide much needed support to a still-recovering job market, enhance equity and long-term economic performance, and take serious steps toward addressing the climate crisis we can already see unfolding. The report finds:

• Combined, the IIJA and budget reconciliation package would provide fiscal support for more than 4 million jobs per year, on average, over the course of the 10-year budgeting window, through direct spending and increased indirect demand in related industries. The analysis does not account for dynamic effects of the planned investments, though these policies are also certain to raise business and worker productivity, and to create faster and more equitably distributed long-run economic growth and increased tax revenues.
• The budget reconciliation package under consideration would support a far greater number of jobs than the IIJA. On its own, the IIJA will provide fiscal support for 772,400 jobs per year, or 19% of the total jobs supported by the combined package. In comparison, the budget reconciliation is expected to support more than 3.2 million jobs per year, or 81% of the total jobs. The budget reconciliation’s outsize economic impact flows from its more significant financial commitment to public investments.
• Manufacturing industries would see a significant boost under these combined plans, with more than 556,000 jobs supported annually.
• The planned investments would support more than 312,000 jobs annually in construction industries.
• The budget reconciliation would vastly expand caregiving jobs to address unmet needs in child care and elder care, supporting 1.1 million jobs per year. Such investments in universal pre-K, child care, and long-term care would not only disproportionately provide jobs for women—and particularly for women of color—but would also enable millions to participate more fully in the workforce at higher productivity and to earn higher compensation. This social infrastructure investment would facilitate increased accumulation of human capital critical for America’s long-term economic growth prosperity; and it would provide crucial relief to family budgets straining to balance work with the costs of caregiving.
• Climate-related and other environmental provisions in the legislation would support more than 763,000 jobs annually. This includes jobs supported by investments in electric vehicle infrastructure and federal procurement of clean technologies, public transit, power infrastructure, climate resilience, agriculture and forestry innovations, environmental remediation, and scientific research and development, among other measures.

In the sections that follow, we first explain the spending plans embodied in the IIJA and Congress’s anticipated budget reconciliation bill. Next, we explain the methodological approach we use to assess what job impacts can be expected from the proposed legislation, and we present the detailed results of our analysis. Finally, we summarize the opportunities legislators now have to rebuild the American economy stronger and better than before.

Plans to rebuild the economy for all

Our analysis assesses the impacts of just over $4 trillion in new spending on a range of policy initiatives over a 10-year budget window, specified in Table 1. First, the Infrastructure Investment and Jobs Act reflects a bipartisan compromise—modeled on the American Jobs Plan—negotiated by President Biden and a bipartisan group of senators to expand investments in surface transportation, public transit and rail, water, and broadband internet infrastructure, along with new investments in renewable energy and electric vehicles (White House 2021a, 2021c, 2021d). Although the media often report this bill as having a $1.2 trillion price tag, the package encompasses much previously budgeted and paid-for infrastructure spending; thus, the analysis here focuses only on the nearly $550 billion in net new infrastructure investments the bill would authorize.1

Table 1

These investments target sorely needed renewal and expansion of America’s physical infrastructure, which has been allowed to deteriorate for more than a decade (Ayres Steinberg and Hersh 2013; Bivens 2017). The American Society of Civil Engineers (ASCE 2021) estimates that the depreciation of existing public infrastructure assets alone will cost the United States $10 trillion in gross domestic product, 3 million jobs, and $2.4 trillion in lost exports as a result of increased costs of doing business by 2039.

Spending on infrastructure yields immediate benefits due to the labor- and capital-intensive demands of these investment projects, and it continues to yield economic dividends for years to come by allowing people, goods, and ideas to move around more efficiently (Bivens 2019). Estimates of the longer-term economic impacts of infrastructure spending find that returns on investment range from 17% to 73% (Bivens 2017; Heintz 2010; Berechman, Ozmen, and Ozbay 2006) as businesses more efficiently reach markets, workers access more job opportunities, and families find it easier to access quality education and health care.

Although the bipartisan IIJA agreement tees up significant new infrastructure investments, the compromise still falls roughly $2.5–3 trillion short of the U.S. economy’s actual infrastructure demands over the next decade, in addition to $400–600 billion per year needed to achieve carbon net neutrality (Pollin, Chakraborty, and Wicks-Lim 2021). This shortfall leaves significant jobs and economic growth potential on the table. In fact, in some of the states where political opposition to green investment has been highest—and most influential on national policy—such investments in infrastructure and climate change could add a significant number of jobs: These include West Virginia (41,000 jobs), Ohio (235,000 jobs), and Pennsylvania (243,000 jobs) (PERI 2021).

Separate from the IIJA, a budget framework being advanced by congressional Democrats would provide $3.5 trillion in spending over 10 years for priorities set out in the Biden-Harris administration’s American Families Plan (White House 2021b) of the Build Back Better agenda, with offsetting revenues largely derived from tax increases on America’s wealthiest individuals and largest corporations. Congress is still formalizing this legislation; for the purpose of our analysis, we infer the composition of new spending from the original American Families Plan proposal and the scale of the budget resolution that passed both the House and Senate in August and that is expected to be formalized in a forthcoming budget reconciliation bill this month (Table 1). As the budget reconciliation is still under negotiation, it is possible that the resulting legislation could differ significantly from assumptions employed here, with the resulting job impacts differing in turn.

This Build Back Better agenda expands upon more traditional infrastructure investments in the IIJA in ways that promise to be transformative for social equity, manufacturing renewal, energy efficiency, and environmental sustainability. To highlight several themes of these initiatives:

• Expanded Child, Earned Income, and Child and Dependent Care Tax Credits (CTC, EITC, and CDCTC) would provide a boost in financial security to families, providing stability that is shown to increase academic performance, attainment, and lifetime economic mobility (Sherman et al. 2021).
• Investments in child and elder care and universal prekindergarten would address the inequities and inadequacy of America’s caregiving infrastructure, which leave children without the opportunities for early learning and development and leave parents—primarily women of color—with diminished opportunities for work and career advancement that have come to define the pandemic’s “she-cession” (Glynn 2021; Savage 2019). Providing aid for child and elder care also lowers the costs of some of the key stressors of family budgets (Gould and Blair 2020). Finally, creating quality jobs in the caregiving economy would provide substantial economic benefits to a long-marginalized workforce and enhance productivity in the overall economy (Gould, Sawo, and Banerjee 2021; Palladino and Lala 2021).
• Proposed investments in the manufacturing sector and a broad range of technological research and development, alongside commitments to invest in renewable energy generation and climate change resilience and mitigation strategies, carry the potential to revitalize America’s industrial base, reduce energy costs for businesses and households, and prevent future catastrophic losses and economic disruptions from extreme climate events.

Even though it largely finances new expenditures with current revenues, the budget reconciliation plan would still provide an important macroeconomic backstop to aggregate demand in coming years by taking advantage of what economists refer to as the “balanced budget multiplier”: By shifting expenditures from areas with a low propensity to stimulate additional activity elsewhere in the economy to areas with a high propensity to promote downstream economic activity, it is possible to achieve a stimulative effect without fundamentally altering overall fiscal balances.

Although tax increases generally may dampen economic activity, there are two strong reasons to expect the measures proposed in the budget reconciliation plan to impose only a very small fiscal drag. First, the vast majority of families, small businesses, and farm holders would be exempt from the tax increases (Buffie and Lord 2021). The measures would instead focus on raising revenues from America’s highest earners, including the wealthiest individuals and largest corporations—many of whom avoid paying taxes altogether. The plan would exempt those with earnings below $400,000 annually and, in the case of provisions pertaining to untaxed capital gains, those with less than $1,000,000 in income from paying higher taxes.

Second, these rich individuals and big corporations exhibit exceptionally low propensities to spend from additional increases in income. The extremely muted effect on aggregate demand stemming from tax changes could be seen following the passage of the 2017 Tax Cuts and Jobs Act (TCJA), which focused primarily on cutting taxes for corporations and top income earners. The TCJA largely failed to fulfill its defenders’ stated goal of boosting investment because excess economic slack remained in the U.S. economy after its passage; instead of making real investment, beneficiaries of the tax cuts gorged on corporate stock repurchases (Troise 2019). The failure of a quite large (in fiscal terms) tax cut to take up the remaining slack in 2018 and 2019 highlights just how weakly top-end tax changes affect aggregate demand. Gale and Haldeman (2021) document the failure of the TCJA to boost investment; this record is in line with previous experiments with supply-side tax cuts aimed at the top of the income and wealth distribution (Hungerford 2011). Thus, revenues raised from incomes of exceedingly rich individuals and the largest corporations will yield much bigger economic effects spent through this plan than parked in their bank and brokerage accounts.

Analyzing support for widespread employment in good jobs

In assessing the likely employment impacts of any macroeconomic policy change, it is important to be explicit in the concept of jobs being modeled. This report employs the concept of jobs “supported”—the labor inputs required in various industries of the economy to fulfill a given level of economic activity—rather than the concept of jobs “created,” or net increases in the overall level of employment. This distinction reflects the complicated nature of considering the employment effects from significant macroeconomic changes sustained over a relatively long time frame (more than two years, for example).

When an economy operates with pervasive unemployment, an increase in net aggregate demand—typically from additional government investments or from an increase in net exports—requires increased employment of idled labor and capital resources. Thus, the boost to demand generates net increases in total employment. Such excess unemployment and growth constrained by too-slack aggregate demand defines the U.S. economy today. Despite marked recovery in employment from the depths of the COVID-19 recession, labor and capital underutilization persist (BLS 2021b; Federal Reserve 2021). The economy still exhibits an employment shortfall of 6.5 to 9 million jobs (EPI 2021), and—even before the pandemic—conventional measures of unemployment tended to understate economic slack, relegating workers of color to perpetually disproportionately high unemployment (Hersh and Paul 2021).

At some point in the future, it is likely that recent past policy interventions (the American Rescue Plan, most notably) and the expansive policies under consideration with the IIJA and forthcoming budget reconciliation bill will eliminate current economic slack. After this point, the macroeconomic effect of additional spending would largely be to reallocate some employment from one industry to another, rather than adding net new jobs to the economy. Although recent data on consumer prices have some commentators and analysts concerned about the potential for inflation, sober analysis of the available evidence suggests that current inflation is transitory in nature and unlikely to persist once pandemic-related supply-chain bottlenecks are relaxed (Bivens and Thompson 2021). But even at full employment, additional benefits can be derived from spending to support economic activity: Such spending could help shift the composition of overall employment toward better-compensated jobs; eliminate labor market slack, increasing the bargaining power of workers to achieve real wage gains; and direct workers and capital resources into higher-productivity uses that expand America’s economic potential. Further, the broader economic benefits of the Build Back Better agenda—increased productivity through public investment and relief for families through more expansive social insurance—will be realized regardless of the state of labor market slack.

Given these considerations, the best way to view the economic impact of the IIJA and the Build Back Better agenda is to assess the number of jobs its spending supports and the insurance it provides to sustain high growth and tight labor markets in coming years. If economic growth is strong even absent this fiscal boost, then the jobs supported will mostly be reallocations that lead to a fairer and more productive economy. If growth outside this fiscal boost begins to flag, the jobs supported by these programs will constitute net new additions to employment, providing a macroeconomic buffer against worsening unemployment.

To obtain our empirical measures of jobs supported, we utilize the Department of Labor’s domestic Employment Requirements Matrix (ERM: BLS 2020) to estimate the number of jobs from spending in the IIJA and expected budget resolution. The ERM breaks down the economy into 206 sectors and tabulates the number of full-time jobs required for a given level of economic output in a given sector, as well as the jobs required to produce intermediate inputs (in other industries) that are used by that industry. We map the underlying policies proposed in the IIJA and the budget plan (Table 1) onto these 206 industries. We follow the work of Pollin and Chakraborty (2020) to analyze data on renewable energy and a range of other climate change-related investments. For other industries, we analyze data from the Bureau of Economic Analysis’s national income accounting input-output tables (BEA 2021).

Jobs supported by policy

Table 2 presents the results of our analysis, indicating the number of jobs that would be supported by the legislation under consideration. As the timing of this proposed spending is uncertain, we report the average number of jobs supported per year over the 10-year budgeting window, and we disaggregate the results to show the discrete contributions of each underlying policy. The results include both jobs supported directly in each industry in which spending occurs and jobs supported indirectly in industries that supply key inputs required for production in the primary industry.

In total, these policies would support more than 4.0 million jobs annually, with 772,400 jobs supported per year by the IIJA and more than 3.2 million jobs supported per year by budget reconciliation. To be clear, these average annual number of jobs supported cannot be summed together over 10 years. If, for example, all of the spending ramped up in Year 1 and then persisted, then 4.0 million jobs would be supported in the first year and then this number would persist but not grow. Over the 10-year window, one could cumulate these job numbers and classify them as “job-years”—a measure of total hours of work supported by this spending over the next decade.

A portfolio of investments in the Build Back Better agenda will tackle head-on the climate change crisis unfolding before our eyes, with efforts to mitigate and prepare for climate change that would support more than 763,000 jobs annually. These policies would combine investments in hard infrastructure with investments to develop new green technologies to make the economy cleaner and more efficient across a range of industries, and investments to make infrastructure, agriculture, and other key sectors of the economy resilient to potential climate-related disruptions. These measures include investments in electric vehicles infrastructure, public transit, power infrastructure and electric grids, environmental remediation and resilience, clean energy tax incentives, creation of a national infrastructure investment bank and a Civilian Conservation Corps, federal procurement of clean technologies, agriculture and forestry investments, weatherization upgrades to commercial and residential buildings, place-based clean energy economic development initiatives, and a range of research and development initiatives.

Another suite of policies would address America’s ongoing caregiving crises, with investments in child care, elder care, and early learning and development. Investments to make pre-K schooling universal and expand access to quality, affordable child care and long-term care would support 1.1 million jobs per year.

Table 2

Jobs supported by industry

Table 3 provides an alternative view of the analysis, summarizing the number of jobs supported by industry. To simplify interpretation of the results, we compile the detailed 206 industries identified by the Bureau of Labor Statistics into 23 larger sectoral groupings, with underlying detail provided for a selection of key manufacturing industries. Overall, the health care and social assistance sector would see the largest number of jobs supported, nearly 1.1 million annually, owing to significant new investments to expand access to quality health care, child care, and elder care services. The legislation would support 556,300 jobs annually in manufacturing industries and 312,200 jobs annually in construction industries, owing to the significant investments in physical infrastructure, electric vehicles, renewable energy generation, installation of new climate change-related technologies, and initiatives to strengthen critical manufacturing supply chains. The manufacturing industries poised to see the most benefit include electrical equipment, industrial machinery, construction products, fabricated metals, and motor vehicles and parts—together making up half of all manufacturing jobs supported by the policies.2

Table 3

Conclusion

Supporting more than 4 million jobs annually, the proposed Infrastructure Investment and Jobs Act, combined with Congress’s anticipated budget reconciliation, would provide a significant boost to America’s job market as it recovers from the pandemic economic shock and would sustain high-pressure labor markets critical to broadly rising wages. This could well turn out to be a vitally needed backstop to growth in coming years as the fiscal boost from the ARP winds down. These policies would accomplish much more than the immediate boost to employment, transforming the U.S. economy to be more efficient, equitable, sustainable, and prosperous for the long run.

Acknowledgments

The author would like to thank Zane Mokhiber and Jori Kandra for meticulous research assistance, Rob Scott and Josh Bivens for thoughtful input, and Krista Faries for editorial assistance.

Notes

1. The analysis here follows Congressional Budget Office (2021) methodology mandated by the Balanced Budget and Emergency Deficit Control Act of 1985 in assuming that expenditures authorized for less than the 10-year budgeting window will continue to be funded at the same level in each subsequent year.

2. These manufacturing industries include: Other electrical equipment, appliances, and components; HVAC and miscellaneous industrial machinery; architectural and structural products; boiler, tank, and shipping containers; other fabricated metal products; and motor vehicles and motor vehicle parts.

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The growing evidence that high-pressure labor markets can narrow these gaps calls for macroeconomic policies that test the absolute limits of how low unemployment can be pushed. Macroeconomic policymakers frequently weigh the potential benefits of higher-pressure labor markets against the potential risks, namely accelerating price inflation driven by excessively fast wage growth. The potential to close race-based gaps in the labor market should be counted as a substantial benefit in these deliberations and should convince policymakers to take on more inflation risk. Furthermore, running labor markets at the maximum sustainable pressure will provide much-needed information on what else we need to do to foster racial equity in labor markets.

This paper explores the promise and limits of high-pressure labor markets in reducing racial labor market gaps and how too-slack labor markets have helped thwart progress in closing the gaps. It then draws lessons from these investigations for policymakers. Its main findings are:

• Reductions in the unemployment rate boost hourly wages of typical (median) Black workers more than they boost hourly wages of typical white workers.
  • In 2019, the median Black worker was paid 32.2% less in hourly wages than the median white worker, up from 28.6% in 1973. Had the unemployment rate averaged 1 percentage point less annually from 1973 to 2019, the median Black–white wage gap could have declined to 18.0%. If the unemployment rate had averaged 2 percentage points less (a very ambitious target), the median Black–white wage gap could have fallen to just 5.4% (an 80% reduction in the size of this wage gap).
• Reductions in the unemployment rate provide an even bigger relative boost for median Black annual earnings, by increasing both hours worked and hourly wages.
  • In 2019, the annual earnings of the typical (median) Black worker amounted to just 80% of the annual earnings of the median white worker. Had the unemployment rate averaged 2 percentage points less annually over the 1970–2019 period, the Black–white median earnings gap (measured as a ratio) could have essentially closed. Had the unemployment rate averaged 1 percentage point less annually over that period, the typical Black worker in 2019 could have been paid 90.1% as much as the typical white worker—reflecting a 50% decrease in the Black–white median annual earnings gap.
• The Black–white unemployment gap (how much, in percentage points, the Black unemployment rate exceeds the white unemployment rate) closes significantly when the overall economy has fewer idle resources (i.e., when potential output climbs closer to actual output, leading to a rise in the measured “output gap”). For example, the Black unemployment rate falls more than twice as much as white unemployment when the economy’s output gap rises by 1 percentage point.
  • Even this disproportionate reduction in Black unemployment might understate how equalizing overall economic tightening can be. When the output gap measure rises 1 percentage point, the share of Black persons who are employed (the Black employment-to-population ratio, or EPOP) actually rises nearly seven times as much as the share of white persons employed (the white EPOP). But because the share of Black persons who are either working or actively looking for work (the Black labor force participation rate) also rises faster than white labor force participation when the output gap improves, the Black unemployment rate reduction is muted relative to gains in employment.
• Sustained high-pressure labor markets may have more power than we thought to close the Black–white unemployment ratio. For decades, the Black unemployment rate has been, on average, roughly twice the white unemployment rate. This persistent and distressingly high Black–white unemployment ratio (the Black unemployment rate divided by the white unemployment rate) has traditionally been seen as much more resistant to closing with high-pressure labor markets. However, the Black unemployment rate has only been included in most data sets since the early 1970s and, since then, genuinely high-pressure labor markets have been quite rare. Pre-1970s data that provide a potential proxy for the Black–white unemployment ratio show that sustained high-pressure labor markets may well actually reduce it significantly.

The policy lessons from this data are clear. While overall wage and price inflation remain the proper targets of policy (employment measures are not reliable enough to make good policy guides), policymakers need to change how they balance those targets:

• As they weigh the potential benefits of higher-pressure labor markets against the risks, policymakers should count, on the benefits side, potential reductions in chronic racial gaps in labor market outcomes.
• More forbearance should be exercised as wages and prices rise during economic recoveries and expansions, and at a bare minimum wage and price targets should be kept symmetric over business cycles: Every year that sees wage and price inflation come in 1% below target must be matched by a year with wage and price inflation coming in 1% above target.
• The potential to close race-based gaps in the labor market should convince policymakers to take on more inflation risk than they otherwise would have (that is, they should wait for actual and sustained, rather than forecast, inflation to appear before raising interest rates).

Background on the unemployment and inflation trade-off

All else equal, policymakers should aim for an unemployment rate so low that it reflects only the transitory and voluntary shifts of workers in and out of work or between employers. However, because of the way policymakers have traditionally sought to affect the rate of unemployment, they have instead aimed for a rate that was high enough to avoid any chance, even remote, of sparking inflation.

The primary way policymakers influence the unemployment rate is through measures that change the pace of aggregate demand growth. Aggregate demand is economywide spending of households, businesses, and governments. When this spending is strong, employers need workers to produce the output of goods and services needed to satisfy customer demand, which keeps unemployment low and employment growth strong. When this spending lags, less output and hence fewer workers are needed to satisfy demand, so employment growth lags and unemployment rises.

If policymakers boost economywide spending too much, however, demand might outstrip the productive capacities of firms. As demand runs ahead of supply, this puts upward pressure on wages and prices as firms scrambling to meet demand find they need to hire more workers and can charge customers a bit more for scarce goods. This “inflation barrier” to further efforts to boost demand—the point of tightness in labor markets that sparks an upward drift of inflation—may well be hit before the unemployment rate that reflects only voluntary job transitions is attained.

This balancing between demand growth that is strong enough to keep unemployment low, but not strong enough to generate accelerating inflation, is a central problem of macroeconomic policy (often called stabilization policy). Traditionally, the entity doing this balancing in the United States has almost always been the Federal Reserve, which tries to spur demand primarily by lowering interest rates and can brake escalating demand by raising interest rates. However, the Great Recession exposed the extreme limits of the Fed’s ability to generate strong enough demand growth and has elevated the role of fiscal policymakers (Congress and the president) in boosting (or failing to boost) demand by adjusting spending levels and taxation in the economy.1

Far too often in recent decades, policymakers have erred in targeting—or at least unnecessarily tolerating—demand growth that was too weak to generate enough pressure in labor markets to give workers leverage in wage negotiations with employers.2 This toleration of low-pressure labor markets was often done in the name of keeping inflationary pressures in check. But given that genuine inflationary pressures in the U.S. economy have been extraordinarily rare since the 1970s, the targeting of too-weak demand growth has often been about guarding against even the risk of inflation. A growing body of recent research notes that the benefits of low unemployment are large enough to justify taking on substantially more inflation risk than has previously been tolerated.

The most obvious benefits of low unemployment are more job opportunities for more people and more hours of work available to U.S. families. A less obvious benefit, but one that shows up strongly in the data, is faster hourly wage growth for the vast majority of U.S. workers, a particularly important benefit given the anemic pace of wage growth for these workers in recent decades.3 Yet another increasingly discussed benefit of low unemployment is its ability to put sustained pressure on compressing race-based gaps in the labor market. The rest of this paper largely tries to put some empirical bounds on just how large this last benefit might be.

Why aim for ‘high-pressure’ labor markets and not ‘full employment’?

The Fed’s legal mandate is to pursue maximum employment consistent with price stability. Over the years “maximum employment” has often been referred to as “full employment.” However, there is no universally agreed upon definition of full employment. For some, full employment simply means that anybody who wants a job can find a job. For others, particularly macroeconomists, it means attaining the rate of unemployment (often called “the natural rate”) below which further increases in economywide spending will mostly lead to accelerating inflation rather than greater output. “High-pressure” labor markets just mean labor markets characterized by low unemployment, fast rates of job creation, rapid job-finding among the unemployed, and sustained effort by employers to keep their enterprises properly staffed. Labor markets can be “high pressure” yet still tolerate further reductions in unemployment without leading to unsustainable wage or price inflation, and the term “high-pressure” may better connote a continuum of labor market states rather than a single fixed point.

Further, old theories of “disguised unemployment” and new developments in advanced capitalist economies (the rise of “gig work”) argue that “full employment” and “high-pressure labor markets” might not always coincide.

Joan Robinson (1936) defined “disguised unemployment” as follows:

In a society in which there is no regular system of unemployment benefit, and in which poor relief is either nonexistent or “less eligible” than almost any alternative short of suicide, a man who is thrown out of work must scratch up a living somehow or other by means of his own efforts. And under any system in which complete idleness is not a statutory condition for drawing the dole, a man who cannot find a regular job will naturally employ his time as usefully as he may. Thus, except under peculiar conditions, a decline in effective demand which reduces the amount of employment offered in the general run of industries will not lead to “unemployment” in the sense of complete idleness, but will rather drive workers into a number of occupations—selling match-boxes in the Strand, cutting brushwood in the jungles, digging potatoes on allotments—[that] are still open to them.

The modern U.S. economy obviously does not totally lack relief for the unemployed, and the reach and influence of the gig economy is often wildly overstated. But it seems clear that one margin of survival that many U.S. workers draw on when regular work is slack due to weak aggregate demand is to engage in gig or otherwise irregular work. But gig work generally does not provide high-quality jobs or economic security. In some deeply unsatisfactory sense, the rise of gig work could theoretically help fulfill the promise of one definition of full employment—that anybody “who wants a job can find a job.” But, in an economy with measured unemployment kept low only by a large incidence of gig work, if policymakers boosted aggregate demand, it is highly likely that many gig workers would leave the gigs behind and look for and find more regular work. In short, describing labor markets as “high pressure” might better describe the condition that employers are competing actively among themselves to attract workers.

High-pressure labor markets and median racial wage gaps

Since 1979, wage gaps between Black and white workers have widened significantly. Figure A shows the gap in two ways: how much less in percent terms the median Black worker earns in hourly wages than the median white worker, and the percent by which the average hourly wage of Black workers is less than the average hourly wage of white workers, holding other characteristics constant. The latter, a regression-adjusted average gap, controls for educational attainment, gender, ethnicity, and age. Both gaps widened significantly over time, but the median gap started larger and has expanded more rapidly since the late 1970s.

Figure A

Previous work has indicated that median Black wage growth responds more strongly to changes in unemployment than does median white wage growth.4 Figure B confirms this. The figure shows the relationship between the unemployment rate and wage growth. Specifically, it shows the change in wage growth that occurs if the unemployment rate rises by 1 percentage point. For white median hourly wages, a 1-percentage-point increase in overall unemployment is associated with wage growth that is 0.52% slower. For Black median wages, wage growth declines by 0.76%. As the figure shows, the coefficient for median Black wage growth is nearly 50% larger than for median white wages.5

Figure B

Figure C uses the estimated coefficients from Figure B and calculates counterfactual median Black–white wage gaps under three scenarios: unemployment rates that averaged 1, 1.5, and 2 percentage points lower over the 1973–2019 period. These scenarios are plausible alternatives of what might have been under a policy regime that determinedly aimed for high-pressure labor markets. Over this period, the unemployment rate was high, averaging 6.2%. One closely watched measure of the unemployment rate consistent with stable inflation—the nonaccelerating inflation rate of unemployment (or NAIRU) estimated by the Congressional Budget Office (CBO)—averaged 5.3% over this same period, almost a full percentage point lower. Additionally, between 1947 and 1973, the unemployment rate averaged 4.7%, exactly 1.5 percentage points lower than in the post-1973 period, and inflation before the oil price shock of 1973 was generally contained. Finally, when unemployment fell more than 2 percentage points beneath the 1973–2019 average in the late 1990s, and again in 2018–2019, there was no marked uptick in wage or price inflation requiring that macroeconomic policymakers slow demand growth.

Figure C

We should be clear that examining a counterfactual that assumes substantially lower unemployment on average does not reflect an assumption that recessions never happen. Instead, it simply assumes that macroeconomic policymakers do their job and ensure that every period of above-average unemployment is matched by an equivalent period of below-average unemployment. Estimates of the natural rate of unemployment are not hard floors below which the economy is never meant to go; instead they are averages that the unemployment rate should fluctuate both above and below. Running the economy far above even too-conservative natural rate estimates over decades is a policy failure that can clearly be addressed.

Achieving and sustaining high-pressure labor markets since the early 1970s would have dramatically narrowed the median Black–white wage gap. Had unemployment averaged 2 percentage points less over the entire period, 80% of the median Black–white wage gap that appeared in 1973 could have been erased (as the gap shrank from 28.6% to 5.4%). With unemployment averaging just 1 percentage point less (essentially just hitting conventional measures of the natural rate of unemployment), the median wage gap could have fallen slightly (to 18.0%) rather than rising by almost 8 percentage points over this period. In short, high-pressure labor markets hold great potential to reduce this particular measure of racial inequality in the labor market.

The gap-narrowing power of high-pressure labor markets is even more evident when looking at median annual earnings. Annual earnings can be affected by tighter labor markets not only through higher hourly wages but also through increased hours worked during the year. As shown in Figure B, the decline in Black worker annual earnings associated with an uptick in the unemployment rate is an even larger decline than the decline in Black worker hourly earnings. Applying the same counterfactual scenarios of unemployment rates that average 1, 1.5, and 2 percentage points lower over the 1973–2019 period yields dramatic results for the median Black–white annual earnings gaps, shown in Figure D. In this figure, the gaps are presented as ratios—how much Black workers earn as a share of what white workers earn.

Figure D

Between 1970 and 2019, the ratio of Black to white annual earnings rose from 62.4% to 80.0%. If the unemployment rate had averaged 1 percentage point lower after 1973, then this ratio could have surpassed 90% by 2019. If the unemployment rate had averaged 2 percentage points lower, the Black–white annual earnings ratio would have essentially been 1, indicating near-complete equality in this measure.

High-pressure labor markets and gaps in employment and unemployment

As we have frequently noted, the Black unemployment rate has been, on average, roughly twice the white unemployment rate since 1972 (the first year that Black unemployment is measured by the Bureau of Labor Statistics). Further, as shown in Figure E, this rough 2-to-1 ratio prevails if one looks at the measure of “nonwhite” unemployment compiled by the BLS before 1972 (Black workers accounted for a very large majority of nonwhite workers over that pre-1972 period).

Figure E

The Black–white unemployment ratio shrinks only slightly if one adjusts for age, educational credentials, and gender composition of the workforces. In the figure, this ratio is calculated by comparing the “Black adjusted” line (see figure note) with the line for the white unemployment rate. For example, between 1976 and 2019, the overall Black–white unemployment ratio averaged 2.3 while the adjusted ratio averaged 2.0. This is an improvement for sure, but a depressingly small one, at roughly 15%.

One conclusion that can be drawn from Figure E is that the ratio of Black to white unemployment is pretty stubborn: It does not seem to fall quickly during periods of labor market tightness (when all rates fall together). However, even if the Black-to-white unemployment ratio never moved, the raw gap in unemployment rates between Black and white workers (simply the Black unemployment rate minus the white unemployment rate) would shrink rapidly during periods of overall labor market tightness, and would expand rapidly during periods of overall labor market distress. At a minimum, this means that Black workers see disproportionate gains and losses from effective and ineffective macroeconomic stabilization policy, respectively. Thus, getting macroeconomic stabilization policy right is a key issue for racial equity.

Figure F confirms this intuition, using the output gap as a proxy for overall economic, and thus labor market, health.6 The output gap is a measure of how fully the economy’s resources are being utilized at any given point in time (resources including potential workers). Specifically, it is calculated as the quotient of actual gross domestic product (GDP) divided by a measure of potential GDP (what GDP could have been had the economy’s resources been fully utilized), minus 1. When actual GDP is lower than potential GDP, the output gap is negative. As actual GDP falls further and further behind potential GDP, the gap measure becomes more negative; as it comes closer to potential GDP, it rises.

Figure F

Given this, as the gap rises, resource utilization increases and the overall unemployment rate generally falls. The figure shows the relationship between the overall output gap and Black and white labor market indicators. As can be seen, the Black unemployment rate is twice as responsive as the white unemployment rate to a change in the output gap: specifically, a 1-percentage-point increase in the output gap (moving actual GDP 1% closer to potential GDP) is associated with a 1.57-percentage-point decline in the Black unemployment rate, compared with a 0.64-percentage-point reduction in the white unemployment rate. Because the BLS measures the unemployment rate of Black workers only after 1971, we also include a measure of the responsiveness of what the BLS labels “nonwhite” unemployment—a series that goes back to 1954. In the years before 1972, Black workers made up more than 90% of those labeled nonwhite.7 The advantage of using a series with a longer historical perspective is that one can examine a period of very tight labor markets that were achieved in the mid-to-late 1960s. The overall unemployment rate, for example, fell to under 4% for three straight years in the late 1960s. In this longer time series, the overall responsiveness of the nonwhite unemployment rate to an increase in the output gap measure (-1.54) is quite close to the responsiveness of Black unemployment in the more recent series.

These differential rates of responsiveness translate into substantial closing of the gap between Black and white unemployment rates when the overall economy tightens up, with this gap defined simply as the Black unemployment rate minus the white unemployment rate (i.e., the gap is by how many percentage points the Black unemployment rate exceeds the white unemployment rate). The figure shows that each percentage-point increase in the output gap (i.e., a tightening of the economy and labor market generally) is associated with a 0.70-percentage-point reduction in the Black–white unemployment gap. Each percentage-point increase in the output gap is also associated with a 0.90-percentage-point reduction in the nonwhite–white unemployment gap. It is possible that relatively greater responsiveness of the nonwhite–white unemployment gap is due to the inclusion of workers who are not Black in the nonwhite unemployment calculation. It is also possible that the difference is due to the longer time series available with the nonwhite–white unemployment rate gap. By restricting this series to just post-1971 data points (to make it consistent with the Black unemployment rate coverage), the responsiveness of the nonwhite–white unemployment gap to a 1-percentage-point reduction in the output gap shrinks to 0.83 percentage points.

Race-based differentials in the responsiveness of labor market indicators to a change in the output gap are even larger when examining the responsiveness of the Black and white employment-to-population ratios. The Black EPOP rises by 1.2 percentage points as the output gap increases, while the white EPOP rises by 0.18 percentage points, just over a seventh as much.

If the ratio of Black to white unemployment rates was constant, then the change in the gap between these rates would also just equal this ratio multiplied by the change in the white unemployment rate. Given the relative stubbornness of the Black–white unemployment ratio (for example, as seen in Figure E), it might seem that it is essentially constant regardless of the state of labor market pressure. But it may not be.

Can high-pressure labor markets reduce Black–white unemployment ratios, not just gaps?

Looking at the Black and white unemployment rates over time—like those displayed in Figure E—can easily convince observers that the ratio of Black to white unemployment is nearly constant. In good times and in bad, the Black unemployment rate looks to be roughly twice the white unemployment rate. But there are actually some reasons for optimism—tempered, to be sure—that this ratio is not as unyielding to change as it seems. For one, there seems to be a shallow but steady downward trend in this ratio over time. For another, more detailed evidence indicates that the Black–white unemployment ratio may indeed respond measurably to high-pressure labor markets. That evidence is highlighted in the discussion of the next two figures, which show the overall unemployment rate and the Black–white unemployment ratio (Figure G) and the nonwhite–white unemployment ratio (Figure H) prevailing at business cycle peaks. Both show a clear positive relationship between the overall unemployment rate and the respective ratios (i.e., an increase in one measure coincides with an increase in the other). All else equal, this would indicate that a higher-pressure labor market overall does indeed put downward pressure on the Black–white unemployment ratio.

Figure G

Figure H

However, the positive relationship in Figure G is likely driven in some part by the trend in the Black–white unemployment ratio coinciding with the fact that, since 1976, later business cycles have consistently achieved lower unemployment rates. Between the business cycle peaks of 1979 and 2019, the Black–white unemployment rate ratio actually declined by a bit over 20% (as did the adjusted ratio, a ratio that estimates what the Black unemployment rate would have been had the composition of the Black labor force shared the same age, educational credentials, and gender mix as the white labor force). This trend likely would have led to successively lower Black–white unemployment ratios in 1989, 2000, and 2019 anyhow. But on top of this trend, unemployment rates in these business cycle years were successively lower over time. Given this, it is not clear if it is a given year’s unemployment rate or a long-running trend that drives the pattern in Figure G.

To test the connection, Figure H includes data on nonwhite unemployment back to 1959 and thus includes business cycles not characterized by uniformly lower overall unemployment rates over time. The strong positive relationship between rising overall unemployment and an increasing Black–white unemployment rate ratio still holds.

Figure I looks at the responsiveness of various labor market ratios (not gaps, as was analyzed above in Figure F) to changes in the output gap while controlling for a time trend. The first three data points come from a regression that used a lagged measure of the output gap. They show a significant decline in the Black–white and the nonwhite–white unemployment rate ratios associated with each percentage-point increase in the output gap (remember, as the economy improves and actual GDP gets closer and closer to potential GDP, the output gap rises). As before, this analysis includes a look at the coefficient on the nonwhite–white unemployment ratio from this regression just in the years after 1971 to see if some of the difference between its responsiveness and the responsiveness of the Black–white unemployment ratio is simply due to different timespans. The responsiveness of the nonwhite–white unemployment ratio is roughly same (but actually increases slightly) when just looking at the post-1971 period.

Figure I

The results from estimating the responsiveness of ratios of EPOPs and labor force participation rates (LFPRs) demonstrates a similar pattern as that shown by Black–white employment gaps. When the output gap rises, the Black–white ratio of EPOPs rises, meaning that the share of Black persons employed approaches closer to the share of white persons employed. A similar increase holds for the ratio of nonwhite-to-white EPOPs and, again, the responsiveness of this ratio falls a bit when only the post-1971 period is examined. The ratio of Black to white LFPR rises when output gaps rise as well, meaning Black labor force participation approaches closer to white labor force participation. Again, the responsiveness of the ratio of nonwhite–white LFPRs is greater than for the Black–white ratios, but much of this seems due to the different time periods; when only post-1971 years are included, the responsiveness is very similar.

The upshot of this examination is that there is some suggestive evidence that even key labor market ratios (not just absolute gaps) that compare labor market performance for Black and white workers might indeed narrow during periods of high-pressure labor markets. This more hopeful interpretation may have been missed by those looking only at raw measures of the Black and white unemployment rates over time (like those shown in Figure E).

First, the post-1971 period might not contain enough episodes of truly tight labor markets to allow the relationships between high-pressure labor markets and the Black–white unemployment ratio to be well estimated. Figure I has some slight suggestive evidence of this: The responsiveness of the nonwhite–white EPOP and LFPR is greater when the pre-1971 period is included. This pre-1971 period includes a long stretch in the 1960s when unemployment was beneath 4% for four straight years (1966–1969). Further, Aizer et al. (2020) found that many racial gaps in labor markets (like the Black–white earnings gap and the measures of occupation segregation) fell significantly in the 1940s. These declines were concentrated in areas with more defense spending. This spending not only contributed to tighter labor markets but also often came attached with anti-discrimination conditions. The authors could not disentangle the precise effect of each of these influences, but the large spillovers of reduced race-based gaps in industries not directly affected by the defense spending suggests a large role for high-pressure labor markets generally. And the U.S. labor market of the 1940s was high pressure in a way not seen since: The unemployment rate was below 2% for three straight years between 1943 and 1945. In short, since we have begun measuring the Black unemployment rate specifically, we just may not have seen enough periods of genuinely high-pressure labor markets to get a solid statistical read on what happens to the Black–white unemployment ratio when labor markets get truly tight and are kept that way for a sustained period of time.

Second, while the employment rate of Black workers rises significantly faster than for white workers as the output gap rises, the labor force participation rate of Black workers also rises faster, muting any disproportionate decline in unemployment for Black workers. If the measure is simple joblessness and not unemployment, then it seems clear that the Black–white jobless ratio clearly declines when labor markets tighten up.

Part of the reason why the stronger responsiveness of the Black–white EPOP to output gap increases translates weakly into a reduction in the Black–white unemployment ratio is likely due to different dynamics of labor force participation over the business cycle. A recent paper by Cajner, Coglianese, and Montes (2020) makes a significant contribution in our understanding of the cyclical behavior of labor force participation. Their main finding is that the LFPR is indeed affected by the state of labor market tightness, but that it responds substantially more slowly to positive or negative shocks than employment or unemployment. They further find that the Black LFPR responds substantially more strongly to a negative shock to the overall labor market. So when economic growth slows and the labor market develops slack, the rise in the Black unemployment rate relative to the white unemployment rate can be somewhat muted because of a larger labor supply response from Black workers. This means that the Black–white unemployment ratio may actually fall during recessions. Just to buttress this point, it is striking that the two lowest annual Black–white unemployment ratios on record occurred in 2009 and 2020—two of the worst years for economywide labor market health in the past 70 years or more.

As recoveries begin, Black EPOPs respond more strongly to improving economic conditions. All else equal, this should lead to a reduction in the Black–white unemployment ratio. But because the Black LFPR recovers more quickly than the white LFPR , the progress in reducing the racial unemployment gap is blocked by faster labor force growth among Black workers. By the time late in recoveries when labor markets are getting tight again, the white LFPR likely begins recovering more strongly, which allows for a reduction in the Black–white unemployment ratio. This modestly complicated series of dynamics likely explains part of why the salutary effect of lower unemployment rates on the Black–white unemployment ratio might be harder to detect in a simple eyeballing of trends. In 2019, the last business cycle peak, the Black–white unemployment ratio hit its lowest point at any business cycle peak on record. This likely reflects both a shallow but nontrivial downward trend over time and pressure that tight labor markets put on compressing the ratio. Additionally, the prolonged (if too slow) recovery following the Great Recession allowed ample time for the white LFPR to recover from the negative shock of the Great Recession and to stop putting downward pressure on the white unemployment rate.

Policy implications

The upshot of this examination is that sustained periods of high pressure in U.S. labor markets might significantly narrow racial gaps in unemployment and other key labor market measures. Given the long history of structural racism in the United States and the intentional policy efforts that created these gaps, it seems incumbent upon policymakers to use every tool available to try to close them. High-pressure labor markets look as promising as (or more promising than) any other tool. The large benefits—moral, political, and economic—of closing these labor market gaps call upon macroeconomic policymakers to consider them when assessing the benefits and costs of a “go for growth” strategy targeting high-pressure labor markets. To be explicit: The potential of more aggressive expansionary macroeconomic policy to help close race-based gaps in the labor market is worth taking on more risk of sparking inflation.

This policy recommendation for macroeconomic policymakers (including the Federal Reserve) to take on extra inflation risk in the name of narrowing racial gaps in the labor market is likely frustratingly imprecise to some. Some policymakers would prefer the clarity of, say, a numerical target for the Black unemployment rate. However, excess confidence in the ability of macroeconomic policymakers to use hard-and-fast ex ante labor market targets that precisely define “high pressure” has backfired in the past. Specifically, that unfounded confidence is a prime reason why labor markets were kept too slack for so long in recent decades, as hard targets such as estimates of the NAIRU turned out to be wrong, leading to unemployment rates in excess of what was needed for reasonable inflation control. Further, if using overall unemployment rates as precise labor market targets has proven to lead to unsatisfactory outcomes (and it has), using the Black unemployment rate as a specific target might be even worse, as one would be implicitly targeting not only the overall rate, but also how robustly the ratio between the Black and the overall rate changed as overall unemployment rose and fell depending on labor market conditions.

One of the most direct and thoughtful calls for having the Federal Reserve aim for narrower racial gaps in the labor market was by Bernstein and Jones (2020b). Their paper is often described as calling on the Fed to “target the Black unemployment rate,” but it does so only in the sense described above: It calls upon the Fed to consider the benefits of narrower gaps, and explicitly make them part of their criteria for decision-making. As the authors explain, “It is not just asking the chair to tell us about the gaps; it requires him or her to make closing them a part of their mandate” (Bernstein and Jones 2020a).

These sensible calls to narrow labor market gaps do raise an important question: Why is there reticence to demand that macroeconomic policymakers achieve a full elimination of labor market gaps? The answer is because it is unlikely that macroeconomic policy by itself can neutralize the centuries-long legacy of structural racism. This legacy has led to disadvantages Black workers face along numerous margins in the labor market, and while high-pressure labor markets can help to ameliorate these disadvantages, high-pressure labor markets likely cannot completely undo them before inflationary pressures require some moderating of expansionary policy.

For example, some of the gap in unemployment rates between Black and white workers represents differing levels of educational credentials. As we showed earlier (Figure E), adjusting the Black unemployment rate under a scenario that gives the Black and white workforces the same age and educational profiles does reduce the Black–white unemployment ratio by a small amount, around 15%. This gap in educational credentials obtained by Black and white workers is itself largely a function of historic discrimination, but it is unlikely to be solved simply by boosting aggregate demand. Further, even at the same level of educational credentials, it is certainly possible for the quality of educational investments to differ systematically between Black and white workers. Research has shown that educational investments are not only larger in white neighborhoods, but they have also been systematically reduced in schools with larger shares of Black students.8 Thus it seems likely that equalizing labor market outcomes will require interventions over and above expansionary macroeconomic policy to address the differences in education investment.

Despite these caveats, the results in this paper and previous research clearly show that expansionary macroeconomic policy can have profoundly equalizing effects. It also seems clear that policymakers have not fully accounted for these benefits when weighing benefits against the potential cost of sparking inflationary pressure. Further, ignoring these potential benefits may even result in worse analytical forecasting. Concepts like the natural rate of unemployment and the level of potential output for the U.S. economy often are estimated by assuming a given Black–white unemployment gap that does not close as the economy heats up.

An oft-cited example is the Congressional Budget Office (CBO) estimate of the natural rate of unemployment. The CBO assumes the overall unemployment rate reached in 2005 is consistent with the economy’s natural rate. It then takes group-specific unemployment rates that prevailed in 2005 and allows the overall natural rate to change only as the group-specific shares of the labor force change over time due to demography or immigration flows (Shackleton 2018). In some sense, this method implicitly assumes that group differences in unemployment that prevailed in 2005 are set in stone. Some have gone so far as to call this assumption racist. This seems wrong. The existence of the gaps is evidence of racism. But it would be odd indeed to ignore them entirely when doing forecasting given how persistent they have been. Instead, it seems that this assumption of ever-persisting gaps is evidence more of pessimism (much of it arguably well-earned) than of racism. 

But if these gaps do indeed close further as labor markets enter high-pressure periods, then any estimate of the natural rate of unemployment can be lower and estimates of potential output can be higher than one would otherwise forecast. In essence, we will never know the full extent of other policy interventions that need to be done to foster racial equity until we have fully maximized the reach of high-pressure labor markets. To put this another way, we won’t even know the size of the Black–white unemployment gap until we are sure we have reached the lowest rate of overall unemployment consistent with sustainable inflation. And yet for the vast majority of years over recent decades, we have not been close to this minimum unemployment rate.

In recent months, handwringing about the possibility of eventually “overheating” the U.S. economy due to excessively generous fiscal stimulus has begun. It is true that we are not completely certain about how low unemployment can go or how much the economy’s supply side will respond to growth in aggregate demand—so signs of overheating should indeed be monitored. But we should be very cautious about premature declarations of overheating. We have not seen sustained and broad-based wage and price inflation in the U.S. economy for decades. And we now know much more than in previous years about just how equalizing a high-pressure labor market can be, both for compressing wage growth among low-, middle-, and high-wage workers and for closing race-based gaps in labor market measures. These benefits are utterly enormous, and maximizing them is worth the risk of being very patient before aiming to deflate high-pressure labor markets through policy.

Endnotes

1. See Bivens 2016 for the central role of fiscal policy in conditioning economic growth after the Great Recession of 2008–2009.

2. See Bivens and Zipperer 2018 for some evidence of this.

3. See Mishel and Bivens 2021 for the central role of low-pressure labor markets in suppressing wage growth for most of the post-1979 period. See Gould 2020 for a broad overview of wage trends over the same period.

4. See Wilson 2015 for evidence on this.

5. While the differences between the coefficients are not statistically significant at most conventional levels, the difference in magnitude is economically large and is consistent and robust across the various regression specifications and time periods.

6. We switch to using an output gap measure for the state of the overall economy in this section because there is an arithmetic relationship between the overall unemployment rate and disaggregated measures of unemployment and employment by group. When, for example, the Black unemployment rate falls, this will by definition also reduce the measured overall unemployment rate. Our output gap measure does not have any arithmetic relationship to disaggregated labor force measures, so we use it for the rest of this paper.

7. See Hobbs and Stoop 2002 for evidence of this.

8. See Derenoncourt 2021 for evidence that as neighborhoods’ share of Black residents increased over time, public investments shifted more heavily toward policing and incarceration and white students saw higher enrollments in private schools. See Johnson 2011 for evidence that racial segregation led to lower resources for students in schools with higher shares of Black students.

References

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