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

This dashboard was initially created to display a range of data not collected or disseminated by FSAs to shed some light on the economy during the pause in federal data collection during the 2025 government shutdown. Now—perhaps even more importantly—it serves to provide an accountability check against efforts to manipulate FSA data in the future.

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

Indeed job postings vs. BLS JOLTS

       

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

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

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

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

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

ADP employment vs. BLS private-sector payrolls

       

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

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

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

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

Revelio vs. BLS employment data

       

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

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

Challenger, Gray & Christmas vs. BLS unemployment rate

       

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

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

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

State-level UI claims vs. BLS unemployment rate

       

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

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

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

Google Trends vs. BLS unemployment measures

       

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

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

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

Economic policy uncertainty vs. recession indicators

       

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

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

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

University of Michigan consumer sentiment data vs. recession indicators

       

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

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

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

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

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

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

Data Accountability Dashboard

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

       

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

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

Key takeaways

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

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

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

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

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

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

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

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

Nonresponse reduces sample size in the Current Population Survey

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

Figure A

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

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

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

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

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

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

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

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

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

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

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

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

Figure C

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

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

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

Conclusion

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

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

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

References

American Community Survey (ACS). 1-Year 2023 microdata, Accessed via IPUMS USA, University of Minnesota, www.ipums.org.

American Community Survey (ACS). 2019–2023 pooled microdata, Accessed via IPUMS USA, University of Minnesota, www.ipums.org.

Center for Migration Studies. 2026. Estimates of Undocumented and Eligible-to-Naturalize Populations by State. Retrieved July 13, 2026.

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

Economic Policy Institute (EPI). 2024. Current Population Survey Extracts, Version 1.0.60, https://microdata.epi.org.

Escobari, Marcela, Ian Seyal, and Paul Beach. 2026. Shock, Awe, and Economic Fallout: The Employment Effects of ICE Enforcement in U.S. Cities. The Brookings Institution, May 2026.

Peri, Giovanni, and Reem Zaiour. 2021. Citizenship for Undocumented Immigrants Would Boost U.S. Economic Growth, Center for American Progress, June 2021.

U.S. Bureau of Labor Statistics, Consumer Price Index for All Urban Consumers (CPI-U), Accessed via Zipperer, B (2025). realtalk: Price Index Data for the US Economy. R Package Version 0.19.0, https://economic.github.io/realtalk/.

U.S. Citizenship and Immigration Services (USCIS). 2024. Count of Active DACA Recipients by State or Territory, as of September 30, 2024.

Wilson, Jill H. 2025. Temporary Protected Status and Deferred Enforced Departure. Congressional Research Service Report RS20844, August 2025.

Wong, Tom K., Ignacia Rodriguez Kmec, Diana Pliego, Karen Fierro Ruiz, Silva Mathema, Ben Greenho, and Rosa Barrientos-Ferrer. 10th Annual DACA Survey: 2024 Findings Reveal What’s at Stake for Recipients and the United States. Center for American Progress, August 2025.

Zipperer, Ben. 2025. Trump’s Deportation Agenda Will Destroy Millions of Jobs. Economic Policy Institute, July 2025.

Last updated September 2026

Key takeaways

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

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

In summary, we find:

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

The labor market recovery softened in 2025

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

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

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

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

Figure A

Wage inequality increased in 2025

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

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

Figure B

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

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

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

Figure C

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

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

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

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

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

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

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

Key takeaways:

• So-called right-to-work (RTW) laws undermine workers’ ability to form unions. Unionization rates are clearly lower in RTW states—and since unions raise wages, that suppression lowers pay.   

• States with RTW laws are also more likely to have other anti-worker laws and generally weaker labor standards. This is likely because both RTW and other anti-worker policies stem from the same anti-worker political roots, and because RTW’s suppression of unions deprives these states of strong potential political champions (unions) for other pro-worker policies.  

• Non-RTW states are more likely to have pro-worker policies like higher minimum wages and prevailing wage laws, restrictions on noncompete agreements, pay transparency policies, and more protective unemployment insurance benefits. 

• As a result, workers in RTW states are paid 6.7% less on average than workers in non-RTW states—more than double the 3.2% wage penalty we found in 2015. That means the RTW wage penalty has increased in recent years and now translates to over $4,000 less per year for a median full-time worker in a RTW state.

• The RTW wage penalty is steeper for women (7.3%) than for men (6.3%), and for Black (9.7%) and Hispanic workers (10.0%) than for white workers (5.4%).   

• Lawmakers already have the policy tools they need to boost wages and improve other outcomes for workers: 

• • At the state level, rolling back existing RTW laws is the most powerful lever.  

• • At the federal level, the Protecting the Right to Organize Act (which includes a ban on RTW) would be transformational for efforts to organize workers.  

• • Policymakers could also make progress on numerous other fronts, such as making UI systems more protective and raising minimum wages. 

In the United States, so-called right-to-work (RTW) laws are anti-union state policies promoted by big business interests to weaken unions and limit workers’ bargaining power. Despite the name, RTW laws do not provide any sort of job protection or right to a job. Rather, the deceptively named policy starves unions of resources, making it harder for them to negotiate collectively for better wages, benefits, and working conditions.

RTW laws emerged in the 1940s as part of anti-union campaigns to suppress worker organizing and maintain Jim Crow labor relations in Southern states; these campaigns worsened economic inequality and racial disparities (Childers 2024). Today, 26 states have active “right-to-work” statutes.{{1}}

As intended, RTW laws reduce union density (the share of workers who are either members of a union or covered by a union contract). These policies prohibit unions and employers from negotiating over union security—the contract terms under which workers covered by a union contract either join the union or pay an agency fee covering their share of representation costs. This deprives unions of critical resources and suppresses union membership (Sherer et al. 2026). RTW states—specifically those with RTW laws for at least 25 years—have an average union density rate of 6.2%, far less than half the union density rate in non-RTW states (16.0%) (see Appendix Table 1).

RTW laws not only reduce the number of workers with collective bargaining agreements but also limit unions’ political power to advocate for stronger labor standards for workers more broadly. This is, in part, why states without anti-union restrictions are more likely to pass protections such as prevailing wage mandates, restrictions on noncompete agreements, higher minimum wages, and pay transparency laws.

To assess the effects of RTW laws on outcomes for workers, we analyze whether wages are lower in RTW states after controlling for key demographic-, job-, and state-level characteristics (see Appendix Table 1 for full demographic controls as well as median and average wages by RTW status). We find that wages in “right-to-work” states are, on average, 6.7% lower than in non-RTW states. This penalty is worse for Black and Hispanic workers, as well as young workers and those without college degrees. Notably, the penalty is also larger for nonunion workers. This is because strong unions benefit workers across the state, not just those in unionized workplaces (Shierholz et al. 2026). In RTW states with weaker unions, nonunionized workers do not experience these positive “spillover” effects.

Pro-worker policies are more common in states without RTW laws

The strong correlation between wages and states’ RTW status is not surprising. Not only do RTW states have lower unionization rates, leaving workers with less leverage to bid up wages, but they often maintain other anti-worker policies. Combined, these anti-worker policies tilt bargaining power toward employers, weakening workers’ ability to garner higher wages. States without RTW laws are more likely to have a wide array of stronger labor standards in place that raise pay, protect workers’ ability to switch jobs, and support those who lose one. These same states—where unionization rates have not been suppressed by RTW laws—have a better safety net and stronger labor standards in part because stronger unions give workers more political power and the ability to better lobby for pro-worker policies writ large (Shierholz et al. 2026).

Figure A displays the incidence of these labor standards for states with and without anti-union RTW laws.{{2}} This is far from a complete list of relevant policies that may correlate with RTW status and wage levels, but they are illustrative.

Figure A

Prevailing wage

Prevailing wage laws apply to certain contracts for public works and require that contractors and subcontractors pay the employees performing such work a prevailing wage rate. The prevailing wage rate is defined as the average wage paid to similarly employed workers in a specific occupation in the area of intended employment. Federal law requires this of federal contracts while state and local laws may apply to state and local contracts.

Prevailing wage laws are more common in non-RTW states. Figure A shows that nearly all (96.0%) of non-RTW states have prevailing wage laws, while only 23.1% of RTW states have these protections for workers on state contracts.{{3}} Without prevailing wage requirements, contractors may reduce their workers’ wages to win bids on government contracts—putting contractors who pay their workers fair wages at a disadvantage.

Restrictions on noncompetes

Noncompete agreements are employment provisions that ban workers at a company from joining a competing business or starting their own for a set period after leaving a job. Noncompetes undermine economic dynamism and innovation; they depress business formation and labor mobility, hurt productivity and growth, raise prices, shrink workers’ wages, and restrict workers’ freedom (Shierholz 2024).

One of the most effective ways workers achieve higher wages is by securing another offer, and then either renegotiating their current salary or leaving for the new higher-paying job. It is not surprising then that workers in states that enforce noncompetes are paid less than similar workers in states that do not enforce noncompetes (Starr 2019). States without anti-worker RTW laws are nearly four times as likely to restrict noncompetes as RTW states (44.0% vs. 11.5%).{{4}} In this analysis, we include only full bans on noncompetes and states with income-based restrictions. States with only small carve-outs for certain occupations provide a much weaker standard and are, by definition, less broad, so those aren’t included.

Minimum wage

Raising the minimum wage is particularly important for lower-wage workers. While the federal minimum wage has sat at $7.25 an hour since 2009, losing over 30% of its purchasing power, workers in 31 states enjoy a higher wage floor (Zipperer 2026). Non-RTW states are three times as likely to have minimum wages higher than the federal minimum compared with RTW states (92.0% vs. 30.8%). This is not a small difference. As of 2026, the average value of the minimum wage in non-RTW states is 60% higher—$5.36 more per hour—than in RTW states.{{5}}

Pay transparency

Pay transparency laws prevent employers from lowballing wage offers by requiring them to include wage information in job postings. While they vary, all laws include some requirement that employers provide salary information in job postings or if directly requested by applicants. Lack of knowledge about wages and benefits keeps potential workers in the dark and limits their ability to learn about and apply for better paid opportunities. A study on Colorado’s newly passed wage transparency law found that wages increased 4.2% faster than those in neighboring states without such laws (Shedge 2025). Further, wage transparency has the potential to reduce gender- and race-based discrimination by arming jobseekers with more information and limiting employers’ ability to pay different amounts to similarly qualified candidates. Only two RTW states have a pay transparency law, compared with 64% of non-RTW states.{{6}}

Unemployment insurance

Access to unemployment insurance (UI) also shapes workers’ ability to seek better wages. When a worker is laid off and their household income falls, unemployment insurance supports them and their family until they find another job. UI is a joint federal-state program that relies on state UI systems to effectively deliver benefits to unemployed workers. States differ in their rules and approaches under the federal UI framework, leading to wide variation in the share of unemployed workers receiving UI benefits (the UI recipiency rate).

Better UI not only cushions workers and their families but also provides workers with additional leverage in the labor market. When UI access and generosity fall, job seekers are forced to settle for lower wages and employers leverage this by offering less (Dahl and Knepper 2026). On the flip side, research shows a positive relationship between more UI generosity and wages (Rinz and Wasser 2026). The UI recipiency rate is significantly higher in non-RTW states compared with RTW states (32.8% vs. 18.7%).{{7}} This is not surprising because non-RTW states have stronger unions, which fight to increase UI eligibility, ease of access, benefit levels, and benefit duration—to the benefit of all workers, union and nonunion (Hertel-Fernandez and Gould-Werth 2020). As with other pro-worker policies, better UI access can contribute to higher wages in non-RTW states.

Other policy levers

Not only do workers in non-RTW states enjoy higher wages, but they also benefit from increased economic security thanks to higher health insurance rates, higher public education spending, paid family and medical leave access, and no preemptions against higher labor standards. Every non-RTW state expanded Medicaid compared with fewer than two-thirds of RTW states (61.5%).{{8}} Unsurprisingly, the uninsured rate is higher in RTW states than in non-RTW states (8.9% vs. 6.2%).{{9}}

Investments in public education deliver a more productive workforce and more informed and engaged society. Increased funding for schools not only improves educational attainment, but also increases wages and family incomes (Jackson, Johnson, and Persico 2016). Non-RTW states spend 45% more on public education than RTW states ($24,084 vs. $16,620).{{10}} Paid family and medical leave provides essential benefits that help workers maintain their livelihoods while taking care of themselves and their families. These laws are also shown to increase labor force participation, job retention, and earnings (Glynn 2020). Only one RTW state has comprehensive paid family and medical leave provisions for private-sector workers, compared with 56% of non-RTW states.{{11}}

Finally, some cities, counties, and other local governments enact policies that raise standards for working people, but some state legislatures force those standards back down with preemption—the use of state law to void local ordinances. Preemptions apply to policies such as minimum wage, prevailing wages, paid leave, and fair scheduling (EPI 2025). Preemption laws interfere with local governments’ ability to set job quality standards. They suppress wages, exacerbate racial inequities, and reduce worker power (Sherer, Cohn, and Ahdoot 2025). These preemptions are more common in RTW states.

Workers in RTW states are paid less

Our analysis of the relationship between wages and RTW status puts states into three categories: long-term RTW states, always non-RTW states, and “switcher” states that have changed their RTW status since 2011.{{12}} Appendix Table 1 provides descriptive statistics for these three groups of states, and Appendix Figure A provides a map of states by RTW status. Our estimates focus on comparisons between long-term RTW states and always non-RTW states.

A simple comparison of hourly wages, the primary variable of interest, reveals that average wages are 22.9% higher in non-RTW states ($40.28 in non-RTW states vs. $32.78 in RTW states). Median wages are 19.2% higher in non-RTW states ($28.79 vs. $24.16). Because there are differences between worker-, job-, and state-level characteristics in RTW and non-RTW states, and since some of these characteristics will directly impact workers’ wages, it is important to control for these factors in a multivariate regression model. This allows us to more accurately identify the relationship between RTW status and wages.

We estimate log wage equations using Bureau of Labor Statistics Current Population Survey Outgoing Rotation Group (CPS-ORG) data for 2023–2025. We pool three years of data to minimize any spurious year-specific economic relationships, thereby helping us achieve more precise estimates. The total sample consists of 234,155 workers, ages 16+, who earn wages and salaries. About 42% of the sample lives in states with RTW laws (see Appendix Table 1 for the sample’s full demographic breakdown).{{13}}

In Table 1, we construct a regression model, starting with an unadjusted framework and building up to a model that controls for the full range of explanatory variables. The dependent variable is the natural log of hourly wages.

The variable of interest is an indicator variable when the worker lives in a long-term RTW state. We also include an indicator in the regression for a switcher state, though that is not our focus of interest (see Appendix Table 2 for a complete set of regression results, including the coefficient for switcher states). There are currently 26 states with RTW laws on the books and 25 without them including Washington, D.C. (see Appendix Figure A). There are five switcher states that have adopted RTW in recent years: Indiana (2012), Michigan (2013), Wisconsin (2015), West Virginia (2016), and Kentucky (2017). In 2023, Michigan became the first state to repeal its RTW statute. We separate the five switcher states from the analysis to better isolate the relationship between wages and the long-run effects of RTW.

The naïve model, without any controls, suggests that workers in RTW states are paid 17.8% less than workers in non-RTW states (Model I in Table 1).{{14}} But many factors contribute to wage differences: demographic characteristics such as age, race/ethnicity, gender, and level of education are relevant as well as job-related factors such as work hours, occupation, and industry. Since these vary across states, they reduce the measured relationship between RTW status and wages. Model II shows that when the analysis compares more similar workers with each other, the RTW penalty drops to 14.0%.{{15}}

There are other factors that are different in RTW states, aside from these individual and job-related characteristics. Most importantly, the cost of living. The cost of living in non-RTW states is higher than in RTW states, as shown in Appendix Table 1. In prior research, Gould and Kimball (2015) showed that choice of price indicator makes no material difference on the measured relationship between RTW and wages. Here we include the Bureau of Economic Analysis’ Regional Price Parity index: The regional price parity index is higher in non-RTW states.{{16}} Not surprisingly, this correlates with wage levels and therefore is important to include in the model. As with earlier studies, we also include state unemployment rates to control for differences in economic conditions.

After including the full set of demographic, individual-, and state-level labor market and cost of living controls (Model III), our analysis finds that workers in RTW states are paid 6.7% less than similar workers in non-RTW states. For the average worker, this is a difference of $2.70 per hour, or more than $5,600 for full-time workers at 2,080 hours over the year. However, because the average is skewed upward due to wage inequality, an assessment at the middle of the wage distribution provides a more conservative but perhaps more robust estimate of the RTW wage penalty. Acknowledging that this is a likely understatement of the full relationship, the RTW wage penalty for the median worker at full-time hours is over $4,000 for the year.

Table 1

This does not mean that RTW laws are a causal explanation for this 6.7% wage penalty. As demonstrated earlier in this report, RTW status correlates strongly with a number of other anti-worker policies. Other research has attempted to calculate the causal effects of RTW laws on wages. Using the switcher states in the most recent period, Fortin, Lemieux, and Lloyd (2022) found smaller wage penalties, which is to be expected given the shorter time frame for measurement post-adoption. Our wage penalty for switcher states—shown in the final column of Appendix Table 2—is much smaller (closer to zero) than the coefficient for long-term RTW states, though not statistically significant at conventional levels. Dasgupta and Merchant (2023) also examine states recently adopting RTW laws and find a statistically significant decline in annual wages by almost $1,900. Again, these states are more recent RTW adopters, so the full effects we find may take time to materialize.

We find that this relationship between long-term RTW status and wages remains economically and statistically significant under alternative specifications of our econometric model. For instance, removing major industries and occupations changes the coefficient to -0.071. Restricting the model to RTW status as of 2026—removing the separate indicator for states that switched since 2011—yields a coefficient estimate of -0.060. Doing the same but dropping Michigan (since its status changed in the measurement period) results in a coefficient of -0.064. In our final model, we do not include an indicator for unionization, unlike Gould and Kimball (2015). If we reintroduce that variable, the coefficient is -0.063.

In each of our regressions discussed above, we include a three-year average as it improves data reliability and allows us to run smaller groups of the data (see next section). When we run our analysis using just 2025, our results do not change. In fact, when we run our three-year final model for the periods 2021–2023, 2022–2024, and 2023–2025, our coefficients remain in the -0.070 to -0.068 range.

Wage penalties are steeper for women, Black, Hispanic, and nonunion workers in RTW states

The RTW penalty is not uniform across demographic groups and other labor market characteristics. Table 2 below shows the results of a series of final-model regressions (comparable to Model III in Table 1) for a set of demographic groups.

We find that women’s wages in RTW states are penalized at a higher rate (7.3%) than men’s (6.3%). The wage penalty also persists across all racial and ethnic groups, but it is almost twice as large for Black (9.7%) and Hispanic (10.0%) workers as for similar white workers (5.4%) and more than twice as large as for Asian American and Pacific Islander (AAPI) workers (4.6%). Young workers between the ages of 16 and 24 face a greater penalty (8.4%) than older workers. And workers without a college degree experience a much higher penalty (7.8%) than workers with a college degree (4.7%).

Table 2

It is particularly important to note that RTW laws have a statistically significant negative effect on the wages of nonunion workers, as shown in the last row of Table 2. Our analysis indicates that nonunion workers in RTW states have wages that are 6.3% lower, on average, than their counterparts in non-RTW states. Union members likely experience a smaller penalty (3.6%) because their wages tend to be higher than those in nonunionized workplaces, regardless of the state’s RTW status (McNicholas et al. 2025). However, the wage impact of unions extends beyond those directly covered by a union contract. Unions lift wage standards across entire industries, meaning that nonunion workers in states with higher union density are more likely to receive better pay.

As the gap in wages and labor standards between RTW and non-RTW states has grown, so has the wage penalty

Using our final model (Model III in Table 1) with pooled 2023–2025 data, we find a 6.7% RTW wage penalty—a larger penalty than we found in earlier examinations. For example, we found a 3.2% wage penalty using data for 2009 (Gould and Shierholz 2011) and pooled 2010–2012 data (Gould and Kimball 2015). Some of the increase in the current estimate of the RTW wage penalty reflects small changes (likely improvements) in our methods. But part of the higher estimate persists even when we apply our current methods to earlier data: Applying these methods to the 2010–2012 data yields an RTW wage penalty of 4.7%.

One method change concerns “switchers”—states that changed from non-RTW to RTW status (or back) since 2019. In the 2010–2012 period, there were no switchers to affect the data.{{17}} In our analysis, we isolate switchers from the long-term RTW group, but the RTW penalty remains negative and significant no matter how one deals with the issue of switcher states. For example, recategorizing the five switchers to match their 2012 status (all non-RTW) lowers the measured RTW wage penalty in the 2010–2012 period to 4.1%, but it remains significant.

Other changes relative to our earlier research include controlling for public-sector status; removing union as an independent variable from the regression; using the full working age range of 16 and up (as opposed to 18–64); and correcting an issue with nonrandom missing values to the metropolitan variable. We’ve further clustered standard errors at the state level as suggested by Douglas (2024), which does not affect the size of the coefficients, only the size of their standard errors and resulting statistical significance.{{18}}

Setting those minor model differences aside, a consistent comparison over time sees the RTW wage penalty rising from 4.7% in 2010–2012 to 6.7% in 2023–2025. One possible reason why this RTW wage penalty grew could be the increasingly divergent policy trajectories of RTW and non-RTW states over this period.

For example, the gap between minimum wages in RTW states and non-RTW states has grown since 2010, largely because policymakers in most RTW states have refused to increase their minimum wage despite the fact that the federal minimum wage has been stagnant in nominal terms since 2009. In that year, the average minimum wage in RTW states was $7.25 while the average minimum wage in non-RTW states was $7.54. That gap has grown enormously, from just $0.29 per hour in 2009 to $5.36 per hour by 2026 ($14.24 in non-RTW states vs. $8.89 in RTW states).

There were other potentially relevant policy changes between 2012 and 2025. The first state-level pay transparency law was passed in Maryland in 2020. Seventeen states followed suit in subsequent years, 15 of which were non-RTW states. On the flip side, six states have repealed their prevailing wage laws since 2012—all of which were RTW. Only one state, Michigan, reinstated its prevailing wage law. It did so in 2023, the same year it repealed RTW. While this is far from an exhaustive list, it’s not surprising that the measured RTW wage penalty has grown over time.

Repealing anti-union “right-to-work” laws and strengthening labor law is key to raising wages

The wage penalty for workers in RTW states has grown since the last time we conducted this research a decade ago. Long-standing and more recently enacted anti-union RTW laws in 26 states, in tandem with other anti-worker policies, have further eroded workers’ collective bargaining power, suppressed wages, and lowered labor standards. These outcomes are linked to clear policy choices, and lawmakers at every level of government have the tools they need to restore workers’ union rights, strengthen labor standards, and lift wages. Across the U.S., 56 million workers say they want a union in their workplace, yet only 10% of all workers have one (Shierholz et al. 2026). Current federal and state labor laws—including anti-union RTW laws—place too many obstacles in workers’ path to unionizing and give employers too much power to interfere with workers’ free choice.

First and foremost, states with RTW laws should follow Michigan’s recent lead and repeal them. Repealing state RTW laws will enable workers to unionize and raise wages across the country. Indeed, recent EPI research finds that equalizing collective bargaining rights across all states by repealing RTW laws that affect private employees and ensuring collective bargaining rights for public employees would increase national union density by almost 50% (from 9.9 to 14.4%) (Shierholz et al. 2026). States should also consider passing constitutional amendments that affirm collective bargaining rights and explicitly bar RTW-style restrictions, such as the 2022 Workers’ Rights Amendment in Illinois (Sherer 2026).

At the federal level, lawmakers should pass the Protecting the Right to Organize (PRO) Act. The PRO Act is designed to address major weaknesses of the National Labor Relations Act (NLRA), which has been severely eroded by amendments and court decisions. Among many other reforms, the PRO Act would eliminate the option for states to maintain anti-union RTW laws—restoring full bargaining rights to workers in all states as intended when the NLRA was originally passed in 1935 (McNicholas, Poydock, and Rhinehart 2021). Since its first introduction in 2019, the PRO Act has passed the House of Representatives twice with bipartisan support (Shierholz et al. 2026).

In addition to proposed PRO Act reforms that would enable newly unionized workers to pursue arbitration to achieve a first contract (if an employer fails to negotiate in good faith), federal labor law should set a minimum standard that such contracts include a cost-of-living adjustment (COLA). To further expand the benefits of collective bargaining, Congress should amend the NLRA to require default collective bargaining at any firm where CEO-to-worker pay ratios exceed 100 times what a typical worker makes in their industry (as this ratio would be one proxy for whether conditions at an employer are particularly unequal) (Shierholz et al. 2026). 

Legislators at both the state and federal level should also look to the list of anti-worker laws that are typically found in RTW states for more opportunities to rebalance unequal power in the labor market and improve wages and working conditions. These policies include:

• Raising the minimum wage;
• Banning noncompete agreements;
• Strengthening federal unemployment insurance guidelines and state UI systems;
• Removing state restrictions that preempt local governments from raising wages and strengthening labor standards.

These are among just a few of the policy levers states can use to raise wages and standards (EPI 2026b).

Our analysis suggests that repealing anti-union RTW laws and enabling workers to increase unionization levels are key to raising wages, both because RTW laws directly suppress unionization rates (and unions raise wages), and because weakening unions limits workers’ collective ability to shape other public policies.

Acknowledgements

The authors are grateful to Josh Bivens, Jennifer Sherer, Hilary Wething, and Ben Zipperer for their helpful comments and expertise.

Appendix

Appendix Figure A

Appendix Table 1

Appendix Table 2

Notes

{{1.}} See Appendix Figure A for RTW status. As of 2026, these states are Alabama, Arizona, Arkansas, Florida, Georgia, Iowa, Idaho, Indiana, Kansas, Kentucky, Louisiana, Mississippi, North Carolina, North Dakota, Nebraska, Nevada, Oklahoma, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Wisconsin, West Virginia, and Wyoming.

{{2.}} States are categorized as “RTW” or “non-RTW” based on their status as of 2026.

{{3.}} Authors’ analysis of prevailing wage laws from DOL (2023) and state legislative websites.

{{4.}} Authors’ analysis of noncompete restriction policies from EIG (2026).

{{5.}} Authors’ analysis of minimum wage data from EPI (2026c).

{{6.}} Authors’ analysis of pay transparency laws from GovDocs (2026).

{{7.}} Authors’ analysis of UI recipiency rate data from DOL-ETA.

{{8.}} Authors’ analysis of Medicaid expansion policies from KFF (2026).

{{9.}} Authors’ analysis of uninsurance rates by state, 2023 through 2025, from Carter (2025).

{{10.}} Authors’ analysis of per-pupil education spending data from NCES-NPEFS (2024).

{{11.}} Authors’ analysis of paid family and medical leave policies from Wielk (2026).

{{12.}} Prior to 2012, the last state to change its status was Oklahoma in 2001.

{{13.}} This analysis builds on earlier work by Gould and Kimball (2015); see the report for a full description of the methodology and list of controls.

{{14.}} Interpreting the results from these semilogarithmic functions requires utilizing the exponential function on the coefficient. Specific to the binary variable coefficient (β1) for RTW, the percent change in workers’ wages resulting from a state being RTW can be calculated by the formula: 100*[exp(β1)-1]. Typically, the result of this equation will be very close to the coefficient itself but will differ more as the coefficient becomes larger. We show the coefficient in the first row of Table 1 and the exponentiated result as a percent in the third row.

{{15.}} Full regression results for covariates in all three models can be found in Appendix Table 2.

{{16.}} Because the 2025 BEA RPP data were not yet available at the time of publication, we assign an average of 2022–2024 data to all years in our sample (2023–2025).

{{17.}} Gould and Kimball (2015) classify Indiana as non-RTW as its RTW law had just taken effect.

{{18.}} We do not control for state-level fixed effects, as Douglas (2024) suggested, because state-level fixed effects perfectly correlate with RTW status and would deem our results uninterpretable.

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Gould, Elise, and Heidi Shierholz. 2011. The Compensation Penalty of “Right-to-Work” Laws. Economic Policy Institute, February 2011. 

GovDocs. 2026. “Pay Transparency Laws by State and Province.” Last modified July 2026.

Hertel-Fernandez, Alexander, and Alix Gould-Werth. 2020. Labor Organizations and Unemployment Insurance: A Virtuous Circle Supporting U.S. Workers’ Voices and Reducing Disparities in Benefits. Washington Center for Equitable Growth, October 2020.

Jackson, C. Kirabo, Rucker C. Johnson, and Claudia Persico. 2016. “The Effects of School Spending on Educational and Economic Outcomes: Evidence from School Finance Reforms.” The Quarterly Journal of Economics 131, no. 1: 157–218. https://doi.org/10.1093/qje/qjv036.

KFF. 2026. “Status of State Medicaid Expansion Decisions.” Last modified May 21, 2026. 

McNicholas, Celine, Margaret Poydock, and Lynn Rhinehart. 2021. “How the PRO Act restores workers’ right to unionize” (fact sheet). Economic Policy Institute, February 4, 2021. 

McNicholas, Celine, Margaret Poydock, Heidi Shierholz, and Hilary Wething. 2025. Unions Aren’t Just Good for Workers—They Also Benefit Communities and Democracy. Economic Policy Institute, August 2025.

National Center for Education Statistics, National Public Education Financial Survey (NCES-NPEFS). 2024. Public data series accessed via the Common Core of Data database. Accessed July 1, 2026. 

Rinz, Kevin, and David Wasser. 2026. “Unemployment Insurance Generosity and Wage Determination.” Federal Reserve Bank of Cleveland Working Paper no. 26-11, May 2026. https://doi.org/10.26509/frbc-wp-202611.

Shedge, Nirav. 2025. Pay Transparency Laws and Wage Dynamics: Evidence from Colorado. Social Science Research Network, November 2025. 

Sherer, Jennifer. 2026. Rights to Unionize and Collectively Bargain: State Solutions to the U.S. Workers Rights Crisis. Economic Policy Institute, February 2026.

Sherer, Jennifer, Emma Cohn, and Ruby Ahdoot. 2025. “Updated EPI Tracker Shows More States Obstructing Progress on Workers’ Rights: Harmful Preemption Laws are Increasing Inequality and Repressing Democracy.” Working Economics Blog (Economic Policy Institute), March 6, 2025.

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This report updates a two-decade body of research tracking the teacher pay penalty—the growing pay gap between public school teachers and their college-educated peers.{{1}} Because public school teachers must attain at least a bachelor’s degree to teach in the U.S., this research compares weekly earnings of public school teachers (elementary, middle, and secondary){{2}} with those of college graduates who chose other careers. Documenting the widening divergence between the wages of teachers and their college-educated counterparts over time allows for a historical analysis of an issue that is critical to the future of the United States: the quality of our education. If teachers’ compensation doesn’t catch up with that of similarly educated and experienced professionals, schools will struggle to retain and attract qualified workers into the profession.

Data and relevant information

In analyzing differences in pay between public school teachers and other college graduates, I use two sources of data, both from the Bureau of Labor Statistics (BLS).{{3}} First, I use Current Population Survey Outgoing Rotation Groups (CPS-ORG) data for the weekly wage analyses (BLS 2025a). I focus on weekly wages, rather than weekly hours worked or the length of the work year, to account for the “summers off” issue that affects teachers but not other college graduates.{{4}} The sample is restricted to full-time workers (working at least 35 hours per week) aged between 18 and 64, with at least a bachelor’s degree, since teachers today need at least a bachelor’s degree to teach. Note that the 2025 annual data do not include October due to the U.S. federal government shutdown.

The sample is further limited to those who reported their wage information directly (those who didn’t respond and whose wages were estimated by BLS are excluded).{{5}} To preserve data confidentiality, the BLS records weekly wages only up to a defined threshold, so the wage amounts above this threshold aren’t specifically identifiable in the data. This is called top-coding. Historically, the threshold was rarely updated. As a result, a growing share of workers are assigned top-coded wages that are below their actual wages, which has generated a growing understatement of college graduate wages relative to those of teachers. EPI replaces original top-coded values with Pareto-distribution implied means above the original CPS top-code separately for men and women.{{6}} CPS demographic variables (e.g., gender, race/ethnicity, state of residence, marital status, age) are also used for the regression analyses.

The BLS’s National Compensation Survey’s Employer Costs for Employee Compensation program (BLS 2025b) is the second data source. Specifically, I pull data on employer costs per hour worked for detailed categories of compensation for “primary, secondary, and special education school teachers” in the public sector, and the same data for “civilian professionals,” which is the broadest category available that largely corresponds to college graduates. “Benefits,” in this analysis, refer to employer costs for health and life insurance, retirement plans, and payroll taxes (covering Social Security, unemployment insurance, and workers’ compensation).

The remaining components of compensation are “W-2 wages,” a measure that corresponds to the wages captured in the CPS data used above. W-2 wages are the wages reported to employees and to the Internal Revenue Service. They include “direct wages,” defined by the BLS as “regular payments from the employer to the employee as compensation for straight-time hourly work, or for any salaried work performed,” and other wage items, including “supplemental pay.” Supplemental pay includes premium pay for overtime, bonus pay, profit-sharing, and paid leave.

Findings

I present the results of this research in four sections. First, I examine trends in the simple (i.e., not regression-adjusted, but adjusted for inflation) average weekly wages for public school teachers and other college graduates from 1979 through 2025. Second, I report annual estimates of the relative national teacher weekly wage gap. The relative gap is estimated using standard regression techniques to control for systematic differences in age, education, state of residence, and other factors known to affect wage rates. Third, I analyze the regression-adjusted estimates of the teacher wage gap for each state and the District of Columbia. Lastly, I factor in nonwage benefits to estimate a total compensation penalty that accounts for the estimated teacher wage penalty, along with the teacher “benefits advantage”—teachers’ relatively larger share of compensation coming from benefits, like health insurance or retirement plans. I use these figures to estimate a total compensation differential at the national level (which is not possible to calculate for each state).

Simple level differences: Weekly wage trends

The average weekly wages of public school teachers and other college graduates are shown in Figure A. These data are national annual averages adjusted only for inflation (i.e., not regression-adjusted). It is important to keep in mind that real improvements in living standards require wages to outpace inflation, which has not been the case for teachers—but has for other college graduates. 

Figure A

Figure A shows that the inflation-adjusted average weekly wages for teachers were relatively flat from 1996 through 2021, indicating that teacher wages, on average, were just keeping up with the rate of inflation. By 2025, teacher wages were 6.2% less than they were on average in 1996. The average weekly wages of other college graduates also experienced a stretch of stagnation, but for a shorter time span (2002–2014), after which real increases ensued. Since 1996, the wages of other college graduates increased by 28.8%.

Illustrated in Figure A is a noteworthy fall in teacher wages that occurred in 2022 due to high rates of inflation. A similar decline did not occur in the wages of other college graduates as private-sector wages can be more responsive to economic conditions, whereas that is not possible with public-sector teacher pay. At the time, I posited that a new, lower trend in teacher wages would likely occur post-2022. History has shown that teacher pay has barely kept up with moderate rates of inflation—as indicated by the flat trend in Figure A—and pay increases following 2022 seemed unlikely to be large enough to recoup that significant decline. Thus far, they have not.

Addressing the long-term stagnation of teacher wages requires that future increases in pay meet and exceed rates of inflation in the future to recover the decline in wages since 2021, and to drive an increasing trend in teacher wages to close the gap relative to other college graduates.

Relative differences: Regression-adjusted trends

The discussion of weekly wages shown in Figure A is centered around simple averages—meaning, they are not adjusted for fundamental differences that may exist between the samples of teachers and other college graduates. In this section, I move to regression adjusted estimation, which helps to account for ways the two groups may differ fundamentally on factors that typically affect pay—such as age, educational attainment, race/ethnicity, and state of residence. For instance, all else being equal, one would expect experienced workers to earn more than younger workers who are just starting out in their careers. Controlling for age within a regression model accounts for such differences across the two samples. Thus, I employ standard regression techniques to estimate weekly wages of public school teachers relative to other similarly situated college graduates working in other professions, which can provide a more apples-to-apples comparison of earnings.{{7}}

Figure B reports regression-based results that show how much less (or more) teachers earn in weekly wages relative to other college graduates. A weekly wage “penalty” for teachers is reported when the regression estimates suggest that teachers, all else equal, are paid less than other college graduates. Teachers’ weekly wage penalties are reported as negative numbers in Figure B. When teachers are paid relatively more, the reported gap is positive and is referred to as a “premium.” The regression analysis provides estimates for all teachers (which includes a gender control), as well as separately for women and men. 

Figure B

The historical trends in relative teacher pay are depicted in Figure B. The overall trend represents three decades of teacher wages faring ever more poorly compared with other similarly qualified professionals. In the pre-1994 period, the teacher wage gap averaged 8.7%, but the relative gap worsened considerably starting in the mid-1990s. The teaching penalty hit a record of 26.9% in 2024, before slightly improving to an estimated 25.2% in 2025. However, this slight improvement is unlikely to be sustained, given that similar improvements throughout this long series have historically proven temporary.

In sum, teachers earned on average 74.8 cents on the dollar in 2025 compared with what similar college graduates earned working in other professions—much less than the relative 93.9 cents on the dollar that teachers earned in 1996.

Separating the analysis by gender shows that in the period from 1979 through 1993, the relative female teacher weekly wage (i.e., comparing female teachers with other female college graduates) was at a premium that averaged 3.3%. But starting in 1996, the female teacher wage gap quickly went from a small premium to an ever-increasing penalty—landing at a 20.0% penalty in 2025.

My previous research (using decennial Census data) confirmed that, over a longer timeframe, the relative wage estimates for female teachers moved from significant premiums to large penalties. For example, I documented that relative female teacher earnings were at a 14.7% premium in 1960, which lessened to 10.4% in 1970 and to near parity in 1980 (pre-1979 years not shown in Figure B). Using the estimates from 2025, the cumulative change has been a 34.7 percentage-point deterioration in the relative wage of female teachers since 1960.{{8}}

There is an important story behind the declining relative wages experienced by female teachers. Historically, the teaching profession relied on a somewhat captive labor pool of educated women who had few employment opportunities. This is thankfully no longer the case, but increased opportunity costs are a part of the story, and they are reflected in these results. Expanding opportunities for women enabled them to earn more as they entered occupations and professions from which they were once barred.

The wages of male teachers have long been outpaced by those garnered by male college graduates who chose other professions. My previously documented estimates going back to 1960 have never been even close to parity. But similar to their female counterparts, the relative male teacher penalty grew considerably over time—from 20.5% in 1960 to 34.5% in 2025.{{9}}

The historically large and worsening male teacher penalty partly explains why about 3 in 4 teachers today are women—a ratio that has not changed much since 1960. The pay penalty experienced by male teachers is unfortunate given the recent statistics and reporting of boys struggling in school. Performing poorly in school is associated with problems encountered later in life—including addiction, mental and physical health issues, and involvement with the criminal justice system.{{10}} Further, Thomas Dee (2010) found that a teacher’s gender has large effects on student test performance, teacher perceptions of students, and students’ engagement with academic material.

It shouldn’t be surprising, then, that today a much smaller share of college-educated women choose the teaching profession over expanding opportunities with better pay—even as three-quarters of teachers are women. Moreover, the very large, persisting male teaching penalty goes a long way in explaining why men who may want to teach are compelled to choose other career paths, which are on average much more lucrative.

Relative teacher weekly wage penalties by state

To this point, I have reported the relative teacher wage gaps for the country as a whole, but there is a lot of state-by-state variation. To produce regression estimates by state, I pool six years (2020–2025) of CPS data to assure ample sample sizes for each state. Again, I compare public school teachers with nonteacher college graduates within each state and estimate regression-adjusted weekly wage gaps for each state and the District of Columbia.

Figure C

As in previous reports, Figure C shows that in no state does the relative (i.e., regression-adjusted) weekly wage for teachers equal or surpass that of their nonteaching college graduate counterparts. The results in Figure C are sorted from the largest (40.7%) to the smallest (10.4%) penalties across the U.S.

The teaching penalty was at least 25% in 25 states, and at least 30% in 11 states. Colorado’s 40.7% teacher penalty is the first time in this research series that a penalty was estimated at or above 40%; on average, teachers in Colorado earned 59.3 cents on the dollar compared with similar college graduates in 2025.

The map in Figure D illustrates the state penalties reported in Figure C.

Figure D

Adding benefits to the analysis

This section adds a nationwide analysis of benefits to see how they affect total compensation between teachers and other college graduates. Teachers are thought to have a “benefits advantage,” which refers to the understanding that, on average in the U.S., teachers generally receive a larger share of their total compensation in benefits—such as health insurance, other insurance, and retirement plans—compared with employment benefits received by other professionals.

Keep in mind that a larger share of total compensation via benefits means a smaller wage share, given that total compensation is made up of these two components. Here, I calculate how the relatively more generous benefits package for teachers partially offsets the large teacher wage penalty.

The BLS Employer Costs for Employee Compensation (ECEC) series measures the average employer cost per employee hour worked for total compensation, wages and salaries, benefits, and costs as a share of total compensation. I compare benefits packages of primary, secondary, and special education public school teachers with those of comparable workers (specifically, workers in professional occupations).{{11}} Table 1 shows a summary of my calculations.

Table 1

The first two columns in Table 1 under “W-2 wage share of compensation” report the share of W-2 wages that make up total compensation for professionals in all occupations and for state and local K–12 public school teachers. The shares of compensation for W-2 wages and benefits add up to 100. The W-2 shares allow for an examination of how important wages are relative to benefits in the total compensation package.

In 2025, W-2 wages made up 69.4% of teachers’ total compensation, while the share was 79.3% for nonteaching professionals. That means that for every dollar of teachers’ total compensation, 69.4 cents went to wages, and 30.6 cents went to benefits. For professionals, 79.3 cents went to wages, and 20.7 cents went to benefits. Therefore, for every dollar of total compensation, public school teachers receive more in benefits than other professionals, but less in wages. I refer to this as the “benefits advantage.”{{12}}

The right-side columns in Table 1 provide the information needed to assess total compensation on average for the United States from the “public school teachers” vantage point. The “wage penalty” column reports the teacher wage penalty estimates from Figure B, followed by the benefits advantage calculation for teachers. Combining the two gives us a measure of how teachers compare with other professionals on total compensation, which is reported in the last column. Per usual, the benefits advantage for teachers partially offsets their estimated relative wage disadvantage, but teachers are still left with a significant total compensation gap of 14.5% in 2025—down somewhat from 16.7% in 2024. This slight change was due to a 0.5 percentage point relative increase in the teacher benefits advantage, and a 1.7 percentage point decrease in the relative teacher wage penalty.

As reported in Table 1, the teacher total compensation gap over the last decade has varied in a rather narrow range from 10.2% in 2019 to a high of 17.0% in 2022. Generally, over the long run, the teacher wage penalty has been worsening as the teacher benefits advantage has grown larger—albeit at a slower rate than the wage penalty. Of course, even if the teacher benefits advantage exceeded the large teacher wage penalty, the standard of living for teachers would likely fall as they would have little in the way of earnings to make ends meet.

How much further can teacher pay fall behind?

Teaching is one of the most consequential professions—not just for kids and their families, but for the country as a whole. Educating each and every child, regardless of means, is among our highest ideals as a country, and the future of the U.S. economy depends on it. The highest standard is still worth fighting for, even as we have always fallen short of the ideal.{{13}}

Given the critical role that teachers have on student outcomes (Chetty, Friedman, and Rockoff 2014), I have been updating this series on teacher pay for over 20 years. After Larry Mishel, Sean Corcoran, and I wrote two books on the subject in 2004 and 2008, it was not obvious that the trends we depicted would continue to get worse—but overall, they have.

The nearly 50-year trends documented in this paper have no doubt already taken a serious toll on the teaching profession. That toll shows up in teacher retention, recruitment, and staffing (Fortin and Fawcett 2023; NCES 2023); college students forgoing teaching careers citing pay as a main barrier (Croft, Guffy, and Vitale 2018); parents actively steering their children into professions that pay better than teaching (PDK 2019); fast-tracking credentials in response to permanent teacher shortages (Povich 2023); the heavy use of unqualified teachers (Tamez-Robledo 2023; Lopez and Van Overschelde 2024); and the reliance on unqualified substitute teachers (Franco and Kemper Patrick 2023).

I have long asserted that providing teachers a standard of living commensurate with that of similar nonteacher professionals is not simply a matter of fairness—teacher pay is a central issue in public education, and thus a matter of national consequence. The quality of a public education hinges on our willingness to fairly and sufficiently invest in both schools and teachers, including the full public school workforce, its infrastructure, and essential wrap-around services (Wething and Bivens 2025).

It would be willful blindness to ignore the toll that the decades-long teacher pay penalty has had on the quality of public education. Regrettably, policymakers have failed to deliver sustained and effective interventions capable of mitigating—let alone substantially improving—the trends outlined in this long-running series. This is an unfortunate reality, especially in a country as wealthy as the United States, with more than enough resources for its public schools to be the envy of the world.

Notes

{{1.}} See Allegretto, Corcoran, and Mishel 2004, 2008; Allegretto and Tojerow 2014; Allegretto and Mishel 2016, 2018, 2019; and Allegretto 2023 and 2024.

{{2.}} The teacher sample does not include kindergarten or pre-kindergarten; if included, the teacher pay penalties would be even larger. 

{{3.}} Allegretto and Mishel 2019, Appendix A provides a comprehensive discussion of the data and methodologies that were used to produce our teacher weekly wage and total compensation estimates. 

{{4.}} In Allegretto and Mishel 2019, we provide evidence that teachers work weekly hours similar to those of other professionals.

{{5.}} Our earlier work documents that BLS’s imputation method overstates teacher earnings, which is not the case for the other college graduate sample (Allegretto, Corcoran, and Mishel 2008, 9).

{{6.}} For more about top-code adjustments, see Economic Policy Institute 2026b.

{{7.}} The wage model includes controls for both public and private school teachers. The weekly wage penalty estimates are based on the coefficient on the public school teacher indicator. Regression for all teachers includes a gender control. The percentage gap is calculated as (eb -1) x 100. See Allegretto and Mishel 2019, Appendix A, for specification details.

{{8.}} See Allegretto, Corcoran, and Mishel 2008 for 1960, 1970, and 1980 estimates using decennial censuses.

{{9.}} The 1960 results are not shown in Figure B. They can be found in Allegretto, Corcoran, and Mishel 2008, 7.

{{10.}} See Abrams 2023.

{{11.}} The ECEC provides compensation data for a narrower category of “primary, secondary, and special education school teachers” and for a broader category of “teachers.” I analyze the narrower category, which closely matches the definition of teachers in the CPS-ORG data, using data limited to state and local public-sector workers. The inclusion of kindergarten and special education teachers in the benefits analysis does not produce any more substantial differences than if they were excluded (as they are in the CPS sample used to estimate the wage penalty). Greater methodological detail is provided in Appendix A of Allegretto and Mishel 2019.

{{12.}} My analysis accounts for differences in annual weeks worked, as it is based on the usual weekly wages of teachers and other college graduates, not hourly wages or annual earnings. One reason health and pension costs are higher for teachers is that teacher health benefits are provided for a full year, while teacher salaries are for less than a full year.

{{13.}} See Allegretto, Garcia, and Weiss 2022. This paper describes inequities in public education funding. We also argue that the federal government should play a larger role in funding public education.

References

Abrams, Zara. 2023. Boys Are Facing Key Challenges in School. Inside the Effort to Support Their Success. American Psychological Association, April 2023.

Allegretto, Sylvia A., Sean P. Corcoran, and Lawrence Mishel. 2004. How Does Teacher Pay Compare? Methodological Challenges and Answers. Washington, D.C.: Economic Policy Institute.

Allegretto, Sylvia A., Sean P. Corcoran, and Lawrence Mishel. 2008. The Teaching Penalty: Teacher Pay Losing Ground. Washington, D.C.: Economic Policy Institute.

Allegretto, Sylvia A., Emma García, and Elaine Weiss. 2022. Public Education Funding in the U.S. Needs an Overhaul: How a Larger Federal Role Would Boost Equity and Shield Children from Disinvestment During Downturns. Economic Policy Institute, July 2022.

Allegretto, Sylvia A., and Lawrence Mishel. 2019. The Teacher Weekly Wage Penalty Hit 21.4 Percent in 2018, a Record High. Economic Policy Institute, April 2019.

Allegretto, Sylvia A., and Ilan Tojerow. 2014. Teacher Staffing and Pay Differences: Public and Private Schools. Monthly Labor Review. U.S. Department of Labor, Bureau of Labor Statistics, September 2014.

Blad, Evie. 2024. Teachers Report Lower Pay, More Stress Than Workers in Other Fields. Education Week, June 19, 2024, sec. Teaching & Learning, Teaching Profession.

Bureau of Labor Statistics (BLS). 2025a. Current Population Survey.

Bureau of Labor Statistics (BLS). 2025b. Employer Costs for Employee Compensation Historical Listing: National Compensation Survey, data tables. Accessed July 12, 2026.

Chetty, Raj, John N. Friedman, and Jonah E. Rockoff. 2014. Measuring the Impacts of Teachers II: Teacher Value-Added and Student Outcomes in Adulthood. American Economic Review 104, no. 9 (September 2014): 2633–2679.

Croft, Michelle, Gretchen Guffy, and Dan Vitale. 2018. Encouraging More High School Students to Consider Teaching. ACT Research & Policy, June 2018.

Dee, Thomas S. 2010 The Why Chromosome. Education Next, January 26, 2010.

Economic Policy Institute (EPI). 2026a. Current Population Survey Extracts, Version 2026.7.8, https://microdata.epi.org. Accessed July 6, 2026.

Economic Policy Institute (EPI). 2026b. “Methodology: Wage Variables.” EPI Microdata Extracts documentation.

Fortin, Jacey, and Eliza Fawcett. 2023. How Bad Is the Teacher Shortage? Depends Where You Live. New York Times, August 29, 2023.

Franco, Marguerite, and Susan Kemper Patrick. 2023. State Teacher Shortages: Teaching Positions Left Vacant or Filled by Teachers Without Full Certification. Learning Policy Institute, July 2023.

Lopez, Minda, and James P. Van Overschelde. 2024. Unlicensed Teachers Now Dominate New Teacher Hires in Rural Texas Schools. The Dallas Observer, June 20, 2024.

Merod, Anna. 2023. Low Pay, Long Hours Top Reasons Teachers Consider Leaving. K-12 Dive, September 12, 2023.

National Center for Education Statistics (NCES). 2023. Most Public Schools Face Challenges in Hiring Teachers and Other Personnel Entering the 2023-24 Academic Year. October 2023.

Phi Delta Kappan (PDK). 2018. Teaching: Respect but Dwindling Appeal. The 50th Annual PDK Poll of the Public’s Attitudes Toward the Public Schools. Supplement to Kappan magazine.

Povich, Elaine S. 2023. Plagued By Teacher Shortages, Some States Turn to Fast-Track Credentialing. Stateline, July 24, 2023.

Steiner, Elizabeth D., Ashley Woo, and Sy Doan. 2023. All Work and No Pay — Teachers’ Perceptions of Their Pay and Hours Worked: Findings from the 2023 State of the American Teacher Survey. RAND Corporation, September 12, 2023.

Tamez-Robledo, Nadia. 2023. These States Have the Most ‘Underqualified’ Teachers Stepping in to Fill Open Positions. EdSurge, April 4, 2023.

Wething, Hilary and Josh Bivens. 2025. U.S. Investment in Public Education is at Risk: Vouchers, State Budget Austerity, and Federal Attacks on the Department of Education Threaten Children’s Futures. Economic Policy Institute, August 2025. 

2026 Q2 • Updated August 2026

The second quarter of 2026 saw persistent racial inequality in unemployment rates across states

By Kyle K. Moore 

EPI analyzes national and state unemployment rates by race and ethnicity, and racial/ethnic unemployment rate gaps on a quarterly basis to generate a consistent sample to create reliable and precise estimates of unemployment rates by race and ethnicity at the state level.

We report estimates for all states and subgroups, flagging those for which constructed unemployment rates are heavily weighted by national level data with an asterisk (*) (see methodological note). The following analysis contains data on the second quarter of 2026.

Second-quarter 2026 state unemployment rates, trends, and ratios 

The second quarter of 2026 saw a weak labor market and slowing economic growth, and thus, little progress in narrowing labor market gaps between groups across states

The national unemployment rate for all workers for the second quarter of 2026 remained at 4.3%, unchanged from the previous quarter and the 2025 annual average. Again, twenty-seven states (including Washington, D.C) saw overall unemployment rates above 4%.

Washington, D.C., once again had the highest overall unemployment rate and the only rate above 6% nationwide, at 6.1%. Eight states (including D.C.) had overall unemployment rates above 5% in the second quarter. South and North Dakota had the lowest overall unemployment rates at 2.1% and 2.4% respectively.

Overall unemployment rates across states saw little improvement through the second quarter of 2026. Economic growth slowed compared with the first quarter, while inflation continued to stay above the Federal Reserve’s 2% target. Job growth was weak across the quarter as well. Given that strong economic growth helps to support tighter labor markets that narrow racial labor market disparities, the current weak levels of government spending and investment are not helping a move toward equity. As long as Black and brown workers continue to face higher rates of unemployment and lower wages than their white and AAPI counterparts do, slow overall growth and persistent inflation will affect those communities more severely as well.

Interactive Map

Click to view data

Interactive Map

Second-quarter 2026 trends among white workers 

Every state had a white unemployment rate below 5% in the second quarter of 2026. Six states had white unemployment rates at or above 4%: in ascending order, Florida, West Virginia, Oregon, California, Nevada, and Washington. Twenty-one states had white unemployment rates at or below 3%. The national unemployment rate for white workers was 3.3% in the second quarter of 2026, largely unchanged from the first quarter. No state saw a change in its white unemployment rate of more than one percentage point in either direction.

Second-quarter 2026 trends among Black workers 

Most states (46, including D.C.) saw Black unemployment rates at or above 5% in the second quarter of 2026. Michigan had the highest Black unemployment rate and the only rate above 10% in the country, at 11.4%. Georgia had the lowest Black unemployment rate in the second quarter among states with large-enough Black worker populations for precise estimates, at 4.9%. South Dakota had the lowest-recorded Black unemployment rate, irrespective of sample size, at 3.6%.

The national unemployment rate for Black workers in the second quarter of 2026 was 7.2%, unchanged from the previous period. Black unemployment rates fell by one or more percentage points in Ohio (-1.3 percentage points), California (-1 percentage point), and New Jersey (-1 percentage point). Black unemployment rates rose by one or more percentage points in seven states, with Connecticut seeing the largest increase (2 percentage points, though with a small Black worker sample), followed by Virginia (1.5 percentage points).

The national Black-white unemployment ratio for 2026 Q2 was 2.2-to-1; in other words, across the nation Black workers were over twice as likely to be unemployed as white workers. Michigan and South Carolina were tied for the highest Black-white unemployment ratio at 3-to-1. Several states tied for the lowest Black-white unemployment ratio in states with large-enough sample sizes of Black workers for precise estimates, at 1.8-to-1: Massachusetts, Nevada, New Jersey, and Ohio. Black workers were twice as likely or more to be unemployed than white workers in 35 states (including Washington, D.C.) in the second quarter of 2026.

Second-quarter 2026 trends among Hispanic workers

Pennsylvania and Washington, D.C., had the highest Hispanic unemployment rates in the second quarter of 2026, at 8.1% and 8% respectively. South Dakota had the lowest Hispanic unemployment rate at 2.5%, but its Hispanic worker sample size is small. North Carolina had the lowest Hispanic unemployment rate among those states with large-enough Hispanic worker sample sizes for precise estimates. Only North Carolina, North Dakota, and South Dakota had Hispanic unemployment rates below 3%.  Connecticut was the only state with a change in the Hispanic unemployment rate greater than one percentage point, increasing by 1.2 percentage points to 6.8% through the second quarter. The national Hispanic unemployment rate in the second quarter of 2026 was 5%.

In the second quarter of 2026, the nationwide Hispanic-white unemployment ratio remained at 1.5-to-1, meaning Hispanic workers were 50% more likely to be unemployed than white workers nationwide. Hispanic workers were twice as likely or more than white workers to be unemployed in Rhode Island (2.1-to-1), Washington, D.C. (2.2-to-1), and Pennsylvania (2.4-to-1). Florida and North Carolina remained the states with the lowest Hispanic-to-white unemployment rates in the second quarter of 2026, at 1-to-1, meaning these were the only states where Hispanic workers were as likely as white workers to be employed.

Second-quarter 2026 trends among Asian American and Pacific Islander (AAPI) workers

In the second quarter of 2026, the AAPI unemployment rate was highest in Washington, D.C., at 5.5%, though D.C. has a small AAPI worker sample that does not allow for precise estimates. Washington state had the highest AAPI unemployment rate among those states with sufficient AAPI sample sizes, at 4.9%. South Dakota had the lowest AAPI unemployment rate, at 1.9%, though its AAPI worker sample size is small; Hawaii had the lowest AAPI unemployment rate among those states with large-enough sample sizes for precise estimates, at 2%. The national AAPI unemployment rate for the second quarter of 2026 was 3.8%, largely unchanged from the previous quarter.

Table 1

Table 2

Methodology

The unemployment rate estimates in this report are based on the Local Area Unemployment Statistics (LAUS) and the Current Population Survey (CPS) from the Bureau of Labor Statistics (BLS). The overall state unemployment rates are taken directly from the LAUS. CPS 12-month ratios are applied to LAUS data to calculate the rates by race and ethnicity. For each state subgroup, we calculate the unemployment rate using the past 12 months of CPS data. We then find the ratio of this subgroup rate to the state (or national) unemployment rate using the same period of CPS data. This gives us an estimate of how the subgroup compares with the state overall.

We also leverage national-level data to construct weighted unemployment ratios, utilizing a greater share of national-level data for states with a high amount of volatility in race/ethnicity sample sizes. This allows for more consistent reporting of unemployment rates for Black, Hispanic, and AAPI workers. For more detail on our methodology, see the technical report. 

Notes

{{1.}} Marokey Sawo and Daniel Perez, Detailing the New Methodology Behind EPI’s Quarterly State Unemployment Rates by Race and Ethnicity Series, Economic Policy Institute, December 2022.

Read more:

• State unemployment by race and ethnicity, 2026 Q1
• State unemployment by race and ethnicity, 2025 annual summary
• State unemployment by race and ethnicity, 2025 Q3
• State unemployment by race and ethnicity, 2025 Q2
• State unemployment by race and ethnicity, 2025 Q1
• State unemployment by race and ethnicity, 2024 Q4
• State unemployment by race and ethnicity, 2024 Q3
• State unemployment by race and ethnicity, 2024 Q2
• State unemployment by race and ethnicity, 2024 Q1
• State unemployment by race and ethnicity, 2023 Q4
• State unemployment by race and ethnicity, 2023 Q3

Imagine union membership tripling in the United States. It may sound radical—if you’ve forgotten history. In fact, more than 1 in 3 private-sector workers belonged to a union in the 1950s. The results? Wages grew in tandem with the economy. The middle class thrived. Black-white wage gaps shrank. Broadly shared economic growth was a reality, not an aspiration. That’s because when workers have bargaining power, they win better wages, benefits, and working conditions. This report shines a light on what we stand to win if we rebuild union power.

Over the last four decades, big corporations and the billionaires who run them have waged a relentless campaign against unions. And they have largely succeeded in reshaping the U.S. economy. By making it harder and harder for workers to organize and bargain collectively, the rich seized more and more income and wealth, destroying the U.S. middle class. Now the wealth of the richest Americans has exploded: The richest 0.1% own more than five times the combined wealth of the entire bottom half of the country.

And yet, workers haven’t given up. In 2025, unionization ticked upward. Public approval of unions has reached some of its highest levels in decades, and more than 50 million nonunion workers say they’d join a union tomorrow if they could. That’s because they know what unions deliver. In an economy that has been rigged against working people for decades, unions serve as a counterweight to corporate power—reducing inequality and building the kind of middle class that underpins a strong and inclusive economy.

It will take serious policy change to reverse nearly 50 years of deliberate attacks on working people and their institutions. It will require that politicians stand up to the superrich and corporate interests. It will require that workers continue to build power. But, as this report shows, we have much to gain from stronger unions. An organized and empowered workforce has powerful and far-reaching economic benefits.

Nearly four decades ago, I helped found the Economic Policy Institute because working people needed a voice in the economic debates that shape their lives. This report is exactly the work we envisioned: rigorous research that puts workers at the center of economic policy, and that arms all of us with the facts to fight for them. At a time when our economy is held in relatively few hands, we need this work—and we need unions—more than ever. 

Robert Reich
Professor, writer, and former Secretary of Labor

Executive summary

Union membership in the U.S. ticked up in 2025, breaking a decades-long trend of declining unionization. But today’s unionization rate doesn’t reflect the tens of millions of workers who want a union but can’t get one. This report examines what we stand to gain if we triple current union membership to 30%—restoring it to 1950s levels, when union strength delivered rising wages, narrowing racial wage gaps, and a thriving middle class.

Tripling union membership would:

• Deliver a 14.5% raise for the median worker—amounting to more than $7,700 annually, or nearly $270,000 over a 35-year career. These life-changing increases would benefit union and nonunion workers alike.
• Shift $1.2 trillion to workers annually. This would reverse a third of the increase in inequality experienced since 1979.
• Significantly narrow racial wage gaps. Because unions tend to boost wages more for Black and Hispanic workers than for white workers, tripling union membership would close racial wage gaps by more than one-third.
• Boost the number of people with health insurance. Since unions increase other forms of compensation, like health insurance benefits, the number of nonelderly people without health insurance would fall by about 25%. Unions further reduce uninsured rates by advocating for increased public benefits like Medicaid.
• Strengthen communities. States with high union density invest more in public education, have higher unemployment insurance recipiency rates, and have all adopted Medicaid expansion.
• Protect democracy. Unions boost voter turnout, equip workers with civic skills, and actively defend voting rights. States with high union density have passed far fewer voter restriction bills than low-density states.

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Roadmap for tripling union density

Reversing decades of political neglect that has stealthily undermined workers’ rights to unions and collective bargaining will require comprehensive reform that weaves together tested approaches with bold new ideas, at both federal and state levels.

Two bills with bipartisan support could help restore collective bargaining

• The Protecting the Right to Organize Act would restore private-sector workers’ right to organize and bargain collectively. It would streamline the union formation process, establish penalties for labor law violations, override so-called “right-to-work” laws, and ban “captive audience” meetings.
• The Public Service Freedom to Negotiate Act would be the first federal law that guarantees all public-sector workers at the federal, state, and local levels the right to organize and collectively bargain.

Two bold new proposals could expand the benefits of collective bargaining and help tackle the affordability crisis

• Guaranteed annual raises for newly unionized workers. Legislation providing that newly unionized workers can use arbitration to achieve a first contract (if an employer fails to negotiate in good faith) should set a minimum standard that such contracts include a cost-of-living adjustment (COLA). For the typical worker, a 3% COLA means roughly $2,000 extra a year.
• Default collective bargaining when CEO-to-worker pay ratios exceed 100:1. Declining unionization and the stratospheric rise in CEO pay are deeply connected. Strengthening the bargaining power of workers in severely imbalanced companies would enable them to capture a larger share of the wealth their work creates.

States can remove anti-union laws and protect collective bargaining

Removing so-called “right-to-work” laws and restrictions on public-sector bargaining alone would increase union density nationally from 9.9% to 14.4%. Beyond removing those unionization barriers, states can also:

• Extend collective bargaining rights to workers currently excluded from federal law (in-home child care, home health care, agricultural, and gig workers);
• Protect workers’ right to refuse mandatory, anti-union “captive audience” meetings; and
• Extend unemployment insurance eligibility to workers on strike.

Introduction

In 2025, 14.7 million workers—10% of all wage and salary workers—were union members, an increase from 9.9% in 2024.{{1}} Though small, the increase marks a departure from prior years’ downward trend in union density and coincides with record high public favorability of unions.{{2}}

This report examines what the U.S. might look like if union membership were to triple to 30%, restoring it to roughly its 1950s peak. We analyze the economic, social, and democratic impacts of this increase; examine the potential impact on state union density rates if all states were to remove anti-union policies; and offer policy recommendations to expand union membership.

While tripling union membership is an ambitious goal, it is fully consistent with workers’ own demand for unions. Recent survey data show that 43% of nonunion workers would vote to unionize if given the opportunity—the equivalent of about 56 million wage and salary workers (Ahlquist, Grumbach, and Kochan 2024; McNicholas, Poydock, and Shierholz 2026). If all these workers unionized, union density would rise from 10% to 48.7%—well above the 30% goal we examine in this paper.

Union decline, wage suppression, and affordability

As union membership has declined, workers’ wages have been suppressed and inequality has skyrocketed. The gap between typical workers’ pay and economy-wide productivity is at a historic high.{{3}} Since 1979, productivity has grown 2.7 times as much as pay for typical workers (Figure A). This divergence reflects both rising wage inequality—high earners experiencing much stronger wage growth than typical workers—and a shrinking share of the economy’s income going to workers overall. Between 1979 and 2023, real (inflation-adjusted) earnings for the top 0.1% grew 354% (from $618,000 to $2.8 million), while earnings for the bottom 90% of households grew just 44% (from $30,000 to $43,000) (EPI 2026a). And workers are now taking home a historically low share of corporate-sector income—meaning shareholders and other capital owners are capturing more than ever before (EPI 2026b).

Figure A

Inequality has grown since 1979 because of intentional policy choices that suppressed wages for typical workers to accelerate income growth at the top. If pay for typical workers had kept pace with productivity over the past nearly five decades, their paychecks today would be more than 40% larger (EPI 2026c). Though affordability pressures are often framed as a problem of high prices, the real problem is this wage shortfall—and reversing that shortfall must be central to any serious affordability agenda. Collective bargaining is the most effective mechanism workers have to raise their wages and secure their fair share of economic growth. Expanding union membership and collective bargaining is central to addressing the affordability squeeze.

Unions raise wages for all workers

One of the most well-studied benefits of unions is the ability of collective bargaining to raise pay—resulting in a “union wage premium.”{{4}} Historically, that premium has fluctuated around 15–20% (EPI 2026d). Unions also reduce inequality by compressing the wage distribution within firms, with the largest benefits going to workers at the bottom and middle. This is one reason the union wage premium is typically larger for those with less education, and for Black and Hispanic workers relative to white workers (Bivens et al. 2023).

Less appreciated is that unions also boost wages for nonunion workers. Higher wages at unionized firms make those jobs more attractive to nonunion workers, indirectly pressuring nonunion firms to raise wages to keep their workers. Nonunion firms may also raise wages to avoid unionization, especially when union density is already high in the relevant sectors and occupations.

Finally, unions also advocate for progressive changes in the tax and benefit system—indirectly raising pre-tax pay for low- and middle-wage workers. This happens in two main ways: First, when taxes on top incomes are higher, corporate executives have less incentive to maximize their own income at the expense of workers’ wages.{{5}} Second, more generous social benefits like SNAP and Medicaid increase the bargaining power of lower-paid workers by making them less economically vulnerable and better able to reject low-quality jobs (Bivens 2026).{{6}}

These “spillover” effects of unions on the nonunion sector are significant and increase when union density is high. Rosenfeld, Denice, and Laird (2016) and Farber et al. (2021) find strong evidence that unions raise the wages of nonunion workers. Consistent with this, Fortin, Lemieux, and Lloyd (2021) estimate that between 1979 and 2017, declining unionization was responsible for 37% of the increase in inequality between the 90th and 50th percentiles of male workers—and more than half of that impact occurred because, as unions weakened, nonunion employers faced less pressure to offer higher wages.

Tripling union density would shift $1.2 trillion a year to working people

Our analysis of the relationship between union density and state median wages finds that for every 10 percentage point difference in union density, real median wages are about 7.2% higher.{{7}} If we tripled union density from 10% to 30%, the real median wage for all workers (including both union and nonunion workers) would rise from $25.67 in 2025 to $29.39 per hour—a 14.5% increase.{{8}} A full-time, full-year worker earning that wage would see annual pay rise by more than $7,700.

To put this into perspective, consider the substantial growth in the gap between pay and productivity between 1979 and 2025. A full-time, full-year worker at the 2025 median wage was paid about $53,400 per year—but would have earned about $76,400 had their pay kept pace with productivity growth (EPI 2026e). Through direct wage increases for union members and unionization’s spillover effects on nonunion workers, tripling union density would close roughly one-third of the productivity-pay gap, increasing annual pay to $61,100.

To contextualize the gain in another way, consider that the median annual cost of a mortgage in the U.S. is $18,252. An additional $7,700 per year would cover more than 40% of that cost.{{9}}

Perhaps more strikingly, consider that an extra $7,700 a year adds up to nearly $270,000 (in today’s dollars) over the course of a 35-year career—a life-changing increase for a working family. Adjusting the USDA’s latest estimate of the cost of raising a child to 2025 dollars yields a current cost of roughly $317,000 to raise a child from birth through age 17, including food, housing, transportation, health care, clothing, child care, education, and other expenses (USDA 2017). The additional $270,000 in career earnings that a typical worker would receive if union density were tripled would cover 85% of that cost.

Or, according to the College Board, the average annual cost of attending a four-year in-state public college, including room and board, is about $31,000 (Ma, Pender, and Hu 2025). Over four years, that comes to $124,000 per student—so the additional $270,000 in career earnings would more than cover the cost of sending two children to college.

Yet another way to show how transformational these effects would be for the U.S. economy and the economic security of typical families: Assuming the 14.5% wage boost we estimate from a tripling of union density applies to the bottom 80% of the U.S. workforce, this would raise these workers’ combined pay each year by $1.2 trillion.{{10}} 

Several useful reference points help illustrate the scale of this $1.2 trillion increase in workers’ annual pay. First, the increase would be nearly three times as large as the $430 billion U.S. families received in “COVID checks”—and unlike those one-time checks, these gains would be permanent and recurring.{{11}} Second, the $1.2 trillion that tripling union density would shift to workers slightly exceeds the Pentagon’s 2025 budget—a redistribution of income on a scale comparable to the entirety of the U.S. military-industrial complex.{{12}} Third and most revealingly, this increase would claw back a full third of the increase in income inequality since 1979. Between 1979 and 2022, the share of market income going to the richest 20% of households rose by 12.0 percentage points (with nearly all of that increase—10.1 percentage points—accruing to the richest 1%). A $1.2 trillion increase in the incomes of the bottom 80% of households would reverse a third of that shift, 4.0 of the 12.0 percentage points.{{13}}

Our estimates likely underestimate future gains

It’s worth noting that while our estimates show large wage gains to workers from tripling union density, they are likely being significantly held down by the fact that union density in the U.S. is starting from such a low level (10%). Our estimates therefore likely understate the wage gains workers will experience once the labor market reaches a higher level of union density. Fortin, Lemieux, and Lloyd (2021) find that the wage payoff to union density is much larger where density is already high, and this shows up clearly in our analysis as well: Below 15% union density, a one percentage point increase in density is associated with just a 0.2% increase in the median wage; above 15%, the median wage increases by 0.9%—a wage response more than four times as large (see Figure B).{{14}}

The economic intuition behind this 15% threshold is that a minimum scale of unionization is needed for collectively bargained wages to exert a strong influence on pay scales—both union and nonunion—throughout the broader economy. While every additional percentage point of unionization gives another 1% of workers the union pay premium, it has a more limited effect on wage-setting throughout the broader labor market until overall union density reaches around 15%.

Today’s typical state has a union density of about 10%, which means the wage gains from each additional percentage point of unionization—while still significant—are muted relative to the gains that occur once union density exceeds 15%. In essence, the policy assault on unions in recent decades has pushed density so low that we need a 50% increase—from 10% to 15% union density—just to start realizing the “normal” gains unions can bring to a high-road economy. Raising density from 10% to 30% would carry the labor market across that 15% threshold and well into the higher-density regime, where each additional percentage point increase in unionization delivers substantially larger gains for the median worker. This is why a transformational policy effort is needed: We must rebuild union density from the depressed levels created by decades of political neglect to the point where the full wage benefits of widespread collective bargaining can be realized.

Unions reduce racial wage gaps

Because unions increase wages for Black and Hispanic workers more than for white workers, unions reduce racial wage gaps. And this dynamic is not new—research shows that the union premium was already higher for Black workers than for white workers by the mid-20th century, meaning that the spread of unionization in that era was one of the country’s greatest forces for racial justice (Farber et al. 2021; Bivens et al. 2023). But with the decline in unionization over the past 45 years, racial wage gaps have widened and are now substantially worse than they were in 1979—damage that restoring union power would more than reverse. In 2025, the median Black or Hispanic worker earned 76.5% of the median white worker wage—a wage gap of 23.5%. Tripling union density would close more than one-third of that gap, reducing it to 14.6%.{{15}}

Unions boost benefits, not just pay

Unions also increase other forms of compensation, like health insurance benefits. In 2025, 95% of union workers had employer-sponsored health insurance, relative to 71% of nonunion workers. In addition, as discussed later, unions further reduce uninsured rates by advocating for increased public benefits like Medicaid. Figure C shows that nonelderly uninsurance rates are substantially lower in states with higher union density. To do this analysis, we divided the 50 U.S. states plus the District of Columbia into three equally sized groups based on their current (2023–2025) level of union density.{{16}} Most low-union-density states have double-digit uninsured rates, but these rates typically fall to the single digits in medium- and high-union-density states. If union density tripled and all states were high-density states, the national nonelderly uninsured rate would fall by about a quarter, from 9.8% to 7.3%.

Figure C

Unions benefit communities

Unions don’t just improve workers’ pay and benefits—they give workers a voice in shaping the social fabric of their communities, lifting standards for union and nonunion workers alike. The data reveal a strong correlation between higher levels of unionization and a range of economic and personal well-being measures. When more workers are in unions, states have more equitable economic and social structures (McNicholas et al. 2025). Meanwhile, states with anti-union policies have lower union density and consistently worse outcomes across these measures.

Economic well-being

We first examine economic well-being—broadly defined as working people having the means to support themselves—using two indicators: the gap between productivity and pay, and unemployment insurance recipiency rates.

As discussed earlier, there has been a growing gap since 1979 between productivity—the value of the output generated by a worker in the U.S. economy in an hour of work, on average—and typical workers’ hourly compensation. Far from accidental, this divergence stems from deliberate policy choices in the U.S. beginning around 1980 that allowed the gains from economic growth to be increasingly captured by the highest earners, shareholders, and other capital owners—rather than being broadly shared across low-, middle-, and high-income households (Shierholz 2024).

The degree to which productivity gains have translated into higher pay for typical workers varies widely across states. Figure D shows that in states with smaller declines in unionization since 1979, a larger share of productivity gains translated into higher pay for typical workers. In other words, in places where unions remained stronger, it wasn’t just those with high incomes and wealth who benefited from economic growth—working people, both unionized and nonunionized, saw a bigger share of the gains.

Figure D

Unemployment insurance (UI) recipiency rates also offer insight into economic well-being. When a worker is laid off and their household income falls, unemployment insurance supports them and their family until they find another job. UI is a joint federal-state program that relies on state UI systems to effectively deliver benefits to unemployed workers. States differ in their rules and approaches under the federal UI framework, leading to wide variation in the share of unemployed workers receiving UI benefits (the UI recipiency rate).

Studies show a strong correlation between higher UI recipiency rates and high union density (Clegg et al. 2022); Figure E illustrates this strong positive relationship. In recent years, the average UI recipiency rate in high-union-density states was 36%, double the 18% rate in low-union-density states.

Unions fight to increase UI eligibility, ease of access, benefit levels, and benefit duration—to the benefit of all workers, union and nonunion (Hertel-Fernandez and Gould-Werth 2020). The strong correlation between union density and state UI recipiency rates suggests that expanding unionization by removing anti-union policies would result in higher UI recipiency rates.

Figure E

Personal health and well-being

Next we examine personal health and well-being—which we define as an individual’s physical and mental health—using one indicator, Medicaid expansion.

As we noted earlier, almost all union workers (95%) have access to health insurance, and uninsured rates are lower in high-union-density states. To show how unions influence health care coverage beyond explicitly bargained workplace plans, we examine whether a state has expanded Medicaid under the Affordable Care Act to broaden eligibility. The Medicaid public insurance program provides critical health coverage to families and individuals with low incomes. Research has found that Medicaid expansion has expanded access to health care; improved health outcomes, including fewer premature deaths; lowered uncompensated costs; bolstered financial security; and boosted economic mobility (CBPP 2020). While the Medicaid program has broad federal guidelines, it is administered by states—and a 2012 Supreme Court decision gave them the power to decide on eligibility and expansion. Since 2014, 40 states plus the District of Columbia have adopted Medicaid expansion; 10 states have not (Alabama, Florida, Georgia, Kansas, Mississippi, South Carolina, Tennessee, Texas, Wisconsin, and Wyoming).

Figure F shows a stark divide between high- and low-union-density states in terms of Medicaid expansion. All 17 high-union-density states have expanded Medicaid. Out of 17 medium-union-density states, 14 have adopted Medicaid expansion (Alabama, Kansas, and Wisconsin are the only medium-union-density states that have not adopted expansion). Just 10 out of 17 low-union-density states have adopted Medicaid expansion (Florida, Georgia, Mississippi, South Carolina, Tennessee, Texas, and Wyoming are the low-union-density states that have not adopted expansion).

There is a strong correlation between union density and Medicaid expansion. If states removed anti-union policies and became high-union-density states, they would be joining a group of states in which Medicaid expansion is currently universal, potentially helping to close the Medicaid coverage gap that currently leaves 1.5 million adults uninsured (Zhang 2026).

Figure F

Spending on public education

Union density also intersects with public education investment. Investment in public education helped make the U.S. the richest country in the world in the 20th century. The benefits of universal education are many—including a more productive workforce, and a more informed and engaged democratic society equipped to think critically. Unions play a key role in negotiating public spending on education. At the school district and state level, education unions advocate for increased funds for schools. 

We can measure the relationship between union density and public education investment by looking at states’ level of per-pupil spending. Adequate levels of per-pupil spending are crucial to maintaining quality education; low per-pupil spending limits the support students receive toward achieving their learning goals and makes it harder for districts to retain teachers and staff by offering competitive salaries or benefits. Increased per-pupil funding pays off for students. Research has consistently shown that increased funding for schools improves educational attainment, student achievement, and economic outcomes in adulthood (Jackson and Mackevicius 2023). In one study, researchers examined the impact of school finance reforms between 1972 and 2010 and found that a 10% increase in school spending for 12 years leads to increased high school graduation rates, 7% higher wages, and 10% higher family incomes in adulthood for children from districts that saw the spending increase (Jackson, Johnson, and Persico 2016).

Figure G shows that states with higher rates of unionization spend substantially more per pupil on education—demonstrating the impact of union advocacy on education investment and building a more educated society.

Figure G

Voting rights and democratic participation

Many states disproportionately disenfranchise people of color (Johnson and Feldman 2020), and the number of voter suppression laws enacted across the country is high and rising. These restrictions threaten democratic participation and the stability of our democracy.

Unions strengthen democracy by encouraging civic engagement and helping workers become informed voters. Unions communicate with their members about issues and candidates to make sure workers have the information they need when they go to the polls. And as democratic institutions where members elect leaders and ratify contracts, unions serve as “schools of democracy,” equipping workers with civic skills that carry over to public life (Andrias and Hertel-Fernandez 2026). More broadly, because many organizations that shape policy represent elite or corporate interests, unions are a countervailing force, bringing working people’s voices into legislative debates and building coalitions that can win against well-resourced opposition.

Research shows that these effects translate into greater political participation. Union members are more likely to vote than the general public, and voter turnout is higher in states with greater unionization (EPI 2021). Conversely, turnout is lower in states with “right-to-work” (RTW) laws, which weaken unions and in turn the civic engagement they foster. Feigenbaum, Hertel-Fernandez, and Williamson (2018) found that RTW laws reduced presidential election turnout by 2%, a substantial effect given the narrow margins that often decide presidential elections.

We build on this evidence by examining the relationship between union strength and laws that restrict voting. Figure H shows that there is a strong correlation between union density and voter suppression legislation. A large majority of low- and medium-union-density states passed at least one voter restriction bill between 2023 and 2025, while a large majority of high-union-density states passed none. Among high-union-density states, 14 out of 17 did not pass any voter restrictions during this period, while only eight of the medium-union-density states and three of the low-union-density states can claim this distinction.

These results are consistent with evidence that unions actively defend voting rights. Unions have long mobilized members to oppose voter suppression laws, educated communities about their rights, and turned out to vote despite increasing barriers (Bondy 2025). Unions have also expanded access to voting: Dean, McCallum, and Grumbach (2023) found that county-level union density was associated with greater access to ballot drop boxes—a highly secure way to increase access to voting—during the 2022 midterm elections. Together, these findings suggest that stronger unions not only increase voter participation but also help preserve and expand access to the ballot.

Figure H

State policy and union density

Increasing union density across all states—including those where anti-union policies have historically suppressed unionization—is essential to strengthening both the economy and democracy, improving all workers’ wages, and expanding access to public goods like health care, retirement, and education.

As the previous section made clear, residents of high- and low-union-density states face starkly different economic and social realities. These wide variations in union density across states—and highly variable economic outcomes—are strongly correlated with variations in state labor policies. For example, the union rights of millions of public-sector, agricultural, and domestic workers (including home health care and in-home child care providers) vary by state because workers in these occupations are excluded from coverage under federal law. And even for private-sector workers whose union rights are covered under federal law, collective bargaining rights are limited by anti-union “right-to-work” laws in many states. Research shows that anti-union state policies result in lower union density. Union density averages 6.2% in states with anti-union RTW laws compared with 15.8% in non-RTW states, and states that limit or prohibit public-sector collective bargaining have lower overall union density than other states (Sherer and Gould 2024; Sherer and Morrissey 2026).

Here, we consider what union density would be if states with certain anti-union laws adopted the policies of states that better protect workers’ rights to unionize and collectively bargain. We consider two policy changes: 1) requiring state and local governments to bargain with public-sector workers who choose to unionize; and 2) repealing so-called “right-to-work” laws that limit collective bargaining rights of private-sector workers. These are two of many policies that states can adopt to remove barriers to unionization, but we focus on them because of their clearly documented, large-scale impact on large numbers of workers across much of the country. At present, roughly half of U.S. states have RTW laws in effect and do not require public employers to bargain with unionized public employees. Modeling changes to these two policies lets us estimate what would happen to union density if we removed large state-by-state labor policy disparities and created a stable “floor” for collective bargaining for workers across all states. This provides an important starting point for considering how additional, stronger state labor policies might affect union density, worker wages, and democracy.

Public-sector workers face wide disparities in bargaining rights across states

Variations in collective bargaining rights for public-sector workers are rooted in history, notably in Southern states where systemic racism drove the enactment of anti-union policies (Childers 2023; Dixon 2007; Kaufman 2018; Stelzner, Hoyt, and Ramchurn 2019). By the 1980s, most states had enacted public-sector collective bargaining policies, though these statutes varied in strength and coverage (Freeman and Ichniowski 1988). In more recent decades, many states have repealed or harshly limited formerly robust public-sector collective bargaining statutes, while a few states have expanded them. A key distinction is whether state and local government employers have a legal duty to bargain with unionized employees over pay and working conditions, rather than being merely permitted to bargain—or outright banned from doing so.

Sherer and Morrissey (2026) classify state public-sector bargaining rules across five categories of workers: teachers, police officers, firefighters, other local government employees, and other state government employees. States vary widely in which categories they cover and how strongly, and that variation maps closely onto union density. In states with strong, uniform duty-to-bargain rules across all five categories, public-sector union density can be close to 50% or higher, while in states that ban bargaining across most categories, state and local density can fall as low as the single digits. Pay consequences track these differences. Across the country, public-sector employees earn less than their private-sector counterparts with similar experience and education. This public-sector pay gap is smaller when bargaining rights are strong: Sherer and Morrissey (2026) estimate that in states with robust duty-to-bargain rights, public-sector workers earn 14.3% less than private-sector workers; the gap widens to 19.6% in states where bargaining is only permitted, and to 22.5% in states where it is banned.

“Right-to-work” laws weaken union density and suppress wages for all workers

“Right-to-work” laws prohibit unions and employers from negotiating over union security—the contract terms under which workers covered by a union contract either join the union or pay an agency fee covering their share of representation costs. State RTW laws first emerged as part of anti-union industry campaigns to suppress multiracial worker organizing and maintain Jim Crow labor relations in Southern states following the passage of the National Labor Relations Act (Pierce 2017). By making union finances more unpredictable and leaving unions more vulnerable to ongoing employer interference, these laws weaken unions’ stability, suppress union density, and limit workers’ bargaining power. As a result, RTW laws generate negative outcomes for all workers—with or without a union. States with RTW laws have lower unionization rates and higher income inequality, and workers in RTW states on average have lower wages and benefits (Fortin, Lemieux, and Lloyd 2022). Sherer and Gould (2024) document that workers in RTW states earn 3.2% less than otherwise comparable workers in non-RTW states—about $1,670 per year for a full-time worker.

There are currently 27 states with RTW laws in place—including Colorado, which is not a traditional RTW state, but whose law has, since 1943, effectively imposed RTW conditions. By barring unionized workers from negotiating over union security unless they first win a second, state-administered election by a 75% supermajority of those voting or 50% plus one of all eligible workers—whichever is higher—Colorado’s anti-union policy has produced RTW-like outcomes, so we group it with RTW states.

Removing state anti-union policies would raise national union density from 9.9% to 14.4%

We estimate that these two policy changes—1) requiring state and local governments to bargain with public-sector workers who choose to unionize, and 2) repealing RTW—would substantially increase unionization in states that currently have more anti-union policies in place, as shown in Table 1.{{17}} In the 24 states without a duty to bargain with public-sector employees, establishing that duty would raise public-sector union density from 16.7% to 46.7%. In the 27 RTW states, repealing RTW would increase private-sector density from 3.4% to 8.8%. Overall, removing these anti-union policies would increase union density in 27 states from 5.4% to 14.3%. Nationally, union density would rise from 9.9% to 14.4%.{{18}} This is a conservative national estimate reflecting changes in union density only for the 27 states undergoing hypothetical policy changes and not including likely impacts on the 23 states and D.C. where stronger union policies are already in place. These states would likely also see some level of increased union density under this scenario, given that removal of anti-union state policies across the country would strengthen worker bargaining power and union organizing resources in all states.

Table 1

Removing state-level anti-union policies would increase median wages by up to $4,900 a year

Were the 27 RTW states to increase unionization to estimated levels, overall annualized median wages would rise by $1,600 to $4,900 for full-time, full-year workers, depending on the state. Table 1 shows that if Virginia’s density rose from 4.9% to 15.5% because of the removal of state-level anti-union policies, annual pay for full-time, full-year workers at the state median wage would increase by about $4,500. Removing these anti-union policies in Texas could cause a similar increase in density, raising annual pay by $3,400.

Of course, were workers in all states able to achieve 30% union density, the effects on median pay would be even larger. These impacts are shown in Figure I. The 23 percentage point increase in density in Alabama, for example, would increase annualized median pay there for full-time, full-year workers by about $8,500.

Figure I

Recent state policy changes show that anti-union laws lower union density

Recent “natural experiments” in states that have changed one or both of these labor policies also show the impact on union density. For example, in states that adopted new RTW laws since 2010, union density fell 3.8 percentage points between 2010 and 2023. By comparison, union density declined only 2 percentage points during this same period in non-RTW states (Sherer and Gould 2024).

Wisconsin is an example of a state that both repealed a previous duty to bargain with public employees (in 2011) and enacted a new RTW law (in 2015). Since adopting these anti-union policies, between 2011 and 2024, Wisconsin’s union density has fallen by half, from 14% to 7%. Over this same period, national union density declined just 2 percentage points, from 13% to 11%. With both a RTW law in place and no public-sector duty to bargain, Wisconsin’s union density is plummeting in comparison with national and regional trends (Dresser, Rogers, and Vasquez 2025). Other studies show that Wisconsin’s adoption of anti-labor policies and declining union density have generated a wide array of harmful outcomes for the state’s economy and democracy, including sharp decreases in public education spending, declining worker wages, widening public-sector pay gaps (including stark increases in gender pay gaps for teachers), and declining voter participation (Nack et al. 2019; García and Han 2021; Biasi and Sarsons 2022; Feigenbaum, Hertel-Fernandez, and Williamson 2018).

States have other policy options to enable workers to increase union density

Beyond these two policy changes, states have numerous other opportunities to increase union density by removing obstacles to unionization and ensuring more workers have full rights to collectively bargain (Sherer 2026). A few examples that have not yet been adopted in most states include:

• Creating pathways to collective bargaining for all workers in occupations not currently covered by federal labor law, including in-home child care and home health care workers, agricultural workers, and rideshare or delivery drivers treated as “independent contractors” by digital platform companies;
• Protecting workers’ freedom to refuse mandatory “captive audience” meetings on political or religious topics not related to work duties, including mandatory anti-union meetings employers typically hold when attempting to block workers from unionizing;
• Ensuring workers whose paychecks stop due to a strike or lockout are eligible to apply for unemployment insurance; and
• Establishing or expanding state agency capacities and public labor education programs that ensure workers can easily learn about their union rights.

We do not model the specific impacts of all possible state policy changes in this report. But our conservative, baseline estimate of increases in union density likely to result from removing two of the largest state obstacles to workers’ union rights—RTW laws in 27 states and the lack of a duty to bargain for public employees in 24 states—suggests that combining these changes with additional policy changes would likely lead to additional increases in union density across the country.

Federal policy and union density

Given the clear benefits of tripling union membership, it is critical that policymakers prioritize reforms that enable workers to organize and collectively bargain. It is tempting to search for a policy “silver bullet” to restore the promise of the National Labor Relations Act (NLRA), our primary labor law. But the reality is that policymakers must adopt comprehensive labor law reforms to eradicate the effects of decades of political neglect that has steadily undermined the effectiveness of U.S. labor law. As discussed above, these reforms must at a minimum reverse state anti-union policies, via state or ideally federal labor law reforms that end Jim Crow-era occupational exclusions, ensure equal union rights and pathways to collective bargaining for all workers in all states, and eliminate RTW laws.

Labor law reform has passed the House three times with bipartisan support

A consistent narrative maintains that such policy change is impossible, but that narrative relies on the mistaken notions that real reforms require more political power than the labor movement has and that our legislative process prevents labor law reform. It is true that winning policy fights takes significant political capital. But labor law reform must not be seen as solely a labor movement priority. It is central to any attempt to address affordability pressures and economic inequality. And in this moment, such reform is imperative to our democracy. While the Senate filibuster rules do prevent much legislative progress, they are not inevitable dictates but rather agreed-upon rules that, as history shows, can change. It is deeply destructive to our political system to convince working people that the system simply cannot be expected to serve their interests, which is what this flawed narrative around labor law reform reinforces. To be clear, policies favored by elites benefiting from the unequal status quo are far more likely to become law than even broadly popular ones. But these reforms have the potential to help rebalance this inequality.

In fact, in the last two decades, legislation to significantly reform labor law has passed the U.S. House of Representatives three times—with bipartisan support each time. Even in the current Congress, legislation aimed at restoring collective bargaining rights has managed to bypass Republican House leadership opposition via parliamentary procedure (discharge petition) and pass with bipartisan support.{{19}} Of the on average 12,000 bills introduced in a given Congress, labor law reform measures have had more success than roughly 95% of bills—passing a chamber with bipartisan support. Of course, Senate rules around the filibuster requiring 60 votes to proceed on consideration of various measures have been a significant impediment to the Senate passing these reforms. However, since 2013, the Senate has used the “constitutional option” to change its own rules for procedures and has eliminated the 60-vote requirement to proceed on specific debates three times. That could be done here, too.

Record high union approval strengthens the case for labor law reform

Labor unions today have significantly higher public approval ratings than when major labor law reform was last considered, polling more than 20 points higher.{{20}} Since 2021, approval for unions has remained high, with over 68% of people in the U.S. viewing unions favorably (Brenan 2025). This positive view of unions is shared across generations, with majorities of Boomers (59%), Gen X (58%), Millennials (61%), and Gen Z (63%) viewing unions favorably. Young adults (ages 18–35) have the highest favorability rate at 72% (Glass 2025).

Unions are viewed positively across party lines, with both Democrats (90%) and independents (69%) having high favorability rates for unions, and over 40% of Republicans approving of labor unions (Brenan 2025). Some conservative organizations recognize that unions are popular among workers: Research by American Compass (2025) finds that at least 46% of Republicans view unions somewhat favorably, with favorability increasing among young Republicans (60%).

Data from the American National Election Studies show that people in the U.S. favor unions over big business now more than ever—with the average rating for labor unions hitting a new high (60%), while big business hit a low (44%) (Sojourner and Reich 2025). Further, most people in the U.S. say the decline in union density is bad for the country (60%) and bad for working people (62%). Most young adults (69%), including young Republicans (52%) and young Democrats (82%), view the decline in union density as negative for working people (Van Green 2025).

Three bipartisan bills would pave the way toward restoring collective bargaining rights

As with many popular policies, high public opinion of unions has not translated into the enactment of labor law reform. Even though several bills that would reform aspects of our current labor law are being introduced and even passing with bipartisan support in the U.S. House of Representatives, the Senate has failed to act on the legislation. There are three main bills with bipartisan support that would help reform our current labor law system and each should be passed.{{21}}

• The Protecting the Right to Organize (PRO) Act would restore private-sector workers’ right to organize and bargain collectively. It would streamline the process of forming a union, create a roadmap to reaching a first collective bargaining agreement, establish civil monetary penalties for employers who violate labor law, among other reforms—such as expanding coverage to more workers, overriding state “right-to-work” laws, and banning “captive audience” meetings (McNicholas, Poydock, and Rhinehart 2021). Since its first introduction in 2019, the PRO Act has passed the House of Representatives twice with bipartisan support.
• The Public Service Freedom to Negotiate Act (PSFNA) would establish public-sector workers’ right to organize and bargain collectively. This would fill an important gap—there is currently no federal law that guarantees all public-sector workers at the federal, state, and local levels the right to organize and collectively bargain. As a result, more than half of U.S. states today lack comprehensive collective bargaining laws for state and local public-sector workers (Sherer 2026).
• The Protecting America’s Workforce Act (PAWA) would reverse President Trump’s executive order that revokes collective bargaining rights for federal workers. The bill would reestablish collective bargaining rights for more than 1 million federal workers. In December 2025, PAWA passed the House of Representatives by a 231-195 vote.

Beyond passing these important bills, policymakers should also consider additional policies to help workers access collective bargaining and union membership. We propose two concrete policies that complement the labor reforms above. While these two proposals alone will not result in tripling union membership, they could help more workers receive the benefits of collective bargaining, which serves as a corrective to the affordability crunch and the economic inequality that characterizes our economy.

Guaranteed annual raises for workers in first contract arbitration

When workers win a union and begin to collectively bargain with their employer, both parties have an obligation to bargain in “good faith.” However, given that the NLRA lacks meaningful penalties for violations, employers often engage in bad faith bargaining tactics with few consequences. In fact, it is well documented that many union-busting consultants view bargaining as a new phase of union-busting and advise employers to drag out bargaining for as long as possible. The goal is to avoid reaching a contract for a year or more, hoping that workers will then give up their union through decertification, which is permitted one year after the election. It is no coincidence that workers who have successfully formed a new union spend an average of 465 days bargaining for a first contract before reaching an agreement.

The Faster Labor Contracts Act, which overwhelmingly passed the U.S. House of Representatives last month, would discourage delay and promote good faith bargaining by establishing a mediation and binding arbitration process when employers refuse to bargain in good faith. Beyond guaranteeing workers first contract arbitration, we suggest the adoption of a mandatory cost-of-living adjustment (COLA) for workers whose first contract bargaining ends up in arbitration. This would establish an important guardrail for workers in the arbitration process, given that an arbitrator will ultimately impose a final contract on both parties. This provision would ensure that workers receive at least a COLA each year of their first contract. In other words, by voting for a union, workers would be voting for a guaranteed raise.{{22}}

For the average production, nonsupervisory worker, a 3% COLA would result in almost a $2,000 increase in annual earnings for a full-time, full-year worker. {{23}} Table 2 shows that, while these increases would vary widely by industry because pay varies widely by industry, workers in some of the lowest-paid industries would still see annual pay increases above $1,000.

Table 2

Default collective bargaining when CEO-to-worker pay ratios exceed 100:1

The outsized and ballooning gap in recent decades between CEO pay and the pay of typical workers is among the clearest signs that the economy’s rules have been rigged to allow the most powerful to claim oversized shares of income growth. This CEO-to-worker pay ratio rose nearly tenfold from 1978 to 2024, as the pay of CEOs rose over 1,000% while the pay of typical workers rose just 26%. The explosion of CEO pay was driven not by CEO’s rising productivity or skills, but by policy changes that boosted both the incentives and the ability of CEOs to raise their own pay.

When a firm’s CEO makes more than 100 times what the typical worker in their industry makes, effective corporate governance has clearly broken down—which threatens the ability of those outside the C-suite to receive their fair share of the firm’s income. The two main parties competing with executives to claim a share of a firm’s income are the shareholders and the firm’s workers. The best mechanism for ensuring that workers are able to bargain against CEOs and shareholders for their fair share of the income generated by the firm is collective bargaining.

We propose instituting default collective bargaining in any firm that meets or exceeds this 100:1 ratio. Securities and Exchange Commission (SEC) reporting already requires the annual disclosure of CEO pay (SEC 2007). We propose that these disclosures be reported not only to the SEC but also to the National Labor Relations Board. Comparing those disclosures with Bureau of Labor Statistics data on the pay of a typical worker economy-wide in various industries, the NLRB would determine which corporations meet the default collective bargaining ratio of 100:1.{{24}} The NLRB would then publish a public notice and notify specific corporations and their workers that the default collective bargaining ratio had been met, triggering default collective bargaining at the firm. The NLRB would then direct an election for a bargaining representative to be held within 45 days of the notification.{{25}}

Nonsupervisory workers at these firms would then have the opportunity to select a bargaining representative of their choosing—whether a labor organization or other representative. The NLRB would conduct the election for and certify a bargaining representative, after which bargaining would start. For purposes of default collective bargaining, the presumption for the bargaining unit would be a wall-to-wall unit—a model where all nonsupervisory employees join a single bargaining unit—ensuring comprehensive coverage under the collective bargaining process and resulting contract. This standard would apply absent an employer or employee representative demonstrating extraordinary circumstances.{{26}} The NLRB would then determine the appropriate bargaining unit, the same way the agency already accepts or rejects bargaining unit proposals. We propose that all such questions be resolved within 10 days of the NLRB’s notice of election for bargaining representative. This proposal would not apply to existing bargaining units, but in firms where unions are present, it would apply to any nonunionized nonsupervisory employees, as described below.

A threshold of 100:1 for the CEO-to-typical-worker pay ratio is reasonable and fair. A ratio this high clearly signals a fatal breakdown in the ability of the firm’s workers and shareholders to protect their income claims against executives looking to maximize their own incomes. A ratio this high will not affect most publicly traded companies but will be relevant to a large share of the U.S. workforce.

Comprehensive data on CEO pay are available only for a subset of firms: The Compustat Execucomp database tracks CEO pay for half of publicly owned companies (and most U.S. firms are not publicly owned). For the firms in the Compustat database, under half (41.7%) had a CEO-to-typical-worker pay ratio exceeding 100:1 in 2024. This proposal would provide the 30 million workers employed in firms that have higher ratios—representing about a fifth of total private-sector employment in the United States—with collective bargaining.

It is not a coincidence that the stratospheric rise in CEO pay was accompanied by an acceleration in the downward trend of unionization in the United States. The broader correlation between declining unionization and the rise of inequality is well established, and the highest-quality research documents that this relationship is clearly causal, with the decline of unions leading to a higher share of income claimed by households at the top of the income distribution (Farber et al. 2021).

To be clear, using a threshold CEO-to-worker pay ratio as a trigger for default collective bargaining will not alone solve the problem of excess CEO pay. We focus on this threshold as a policy trigger because it is a readily available and measurable indicator of the outsized control of executives over the distribution of the firm’s income. In the total absence of collective bargaining or any other strong corporate governance institutions, firm executives will shift income in a zero-sum fashion away from both the workers and the shareholders of a firm. If shareholders manage to assert some influence over CEO pay—e.g., through public pressure campaigns or say-on-pay mandates—one likely outcome will be CEOs looking to suppress the firm’s wages even further to make room for both their own outsized salaries and a return to shareholders that placates them. Only collective bargaining can protect the interests and earnings of workers in firms where executives pocket an outsized share of firms’ incomes.

If collective bargaining became widespread enough throughout the corporate sector, it would likely not only boost workers’ wages but also rein in excess executive pay broadly—actually helping shareholders at the same time. The research on this question is encouraging: Unions and collective bargaining have been found to significantly restrain excess CEO pay (Huang et al. 2017; Nanda, Nishikawa, and Prevost 2025; DiNardo, Hallock, and Pischke 2000). But even if expanded collective bargaining does not tamp down the CEO-to-worker pay ratio beneath our 100:1 threshold, it will at a minimum protect workers’ interests from excess executive power—without foreclosing any policy route shareholders take to restrain excess CEO pay.

Currently, a number of firms with at least some degree of unionization among their workforces have CEO-to-worker pay ratios that exceed 100:1. But this is not an argument against using this threshold as an indicator of dysfunctional corporate governance requiring a strong policy solution. For many of these firms, union coverage among their rank-and-file workforce is far from complete, so this proposal would help fill in glaring gaps. Most of these firms clearly do pay wages that are among the highest in their industries, which signals that the policy of default collective bargaining to protect workers’ interests in the face of dysfunctional corporate governance would largely work. Finally, one key empirical driver of high CEO pay is the simple size of the firm: The CEO-to- worker pay ratio rises steeply with the size of the firm, all else equal.{{27}} The firms with CEO-to-worker pay ratios above 100:1 and some degree of unionization among their workforces are large firms; it would take a very strong effect of collective bargaining on CEO pay specifically to have kept pay ratios at these large firms well below average.

In our world with only 10% union density (and less than this in the private sector), it should hardly be a shock that collective bargaining by itself has not been able to stem what has been an irresistible tide toward high CEO pay. Even large increases in executive pay are not enormous when compared with overall returns to shareholders. Given the strong policy and economic barriers to shareholder activism in restraining CEO pay, it takes truly outrageous pay scales to mobilize enough organized opposition from shareholders. In those firms where it is relatively strong, collective bargaining has protected workers’ interests, and that is the primary goal we are looking to achieve with this policy. The fact that in these firms the CEOs have felt free to shift income to themselves at the expense of other stakeholders (like the shareholders of the firm) is not a sign that default collective bargaining is a bad solution for protecting workers’ interests—it is only a sign that the problem of excess CEO pay needs to be addressed from other angles as well.

Tripling union density is what workers want—and it is entirely achievable

Restoring union density to 1950s levels is not a nostalgic pipe dream. Federal and state policymakers have a clear roadmap for tripling union density. While no single reform discussed in this report is a silver bullet for the problems facing the country, taken together they would address one of the worst: the erosion of workers’ right to bargain for their fair share of the wealth they produce. These reforms are meaningful steps toward tripling union density, and toward an economy where productivity gains are shared broadly, not captured by corporate elites and the superrich.

The evidence in this report shows what is at stake. Tripling union density would deliver nearly $270,000 in extra earnings over the median worker’s career and shift $1.2 trillion annually to working people—reversing a third of the rise in inequality since 1979. Rebuilding union power would narrow racial wage gaps by more than a third, and removing state anti-union policies would help dismantle the legacy of Jim Crow-era campaigns aiming to suppress multiracial organizing. States with higher union density deliver better economic and personal well-being outcomes to their residents, and they have healthier democracies with fewer voting restrictions. At a time when the voting rights of all citizens are under attack, rebuilding union power is a democratic imperative.

Acknowledgments

The authors thank Hilary Wething for her contribution to this report’s section on public education spending. We also thank Matthew Wich, Summer Labor Fellow from the Institute for Social Concerns at the University of Notre Dame, for his support of the project.

Appendix

Methodology

How we measure union density

The Bureau of Labor Statistics provides data on both union membership—workers who are full-fledged union members—and union representation, which includes both union members and workers who are not members but are covered by a collective bargaining agreement. As a result, the share of workers represented by a union is higher than the share of union members. For example, in 2025, 11.2% of workers were represented by a union, but 10% were union members.

In this report, we measure union density as the share of workers who are members of a union. Throughout this report, the terms “union density” and “unionization” refer to those who are members of a union. When measuring union density by state, data are averaged over three years (2023 to 2025) to give a more accurate estimate of state unionization rates and avoid temporary single-year changes due to small sample sizes in some states.

Estimating wage effects of tripling union density

To assess how much higher wages would be after tripling union density, we use state-level annual data on wages and unionization from 1979 to 2019 and compare median wages with unionization rates across states and over time. Specifically, we regress the state median wage on the state union membership rate, controlling for permanent differences in state characteristics, national annual shocks (like recessions), and annual state characteristics like state unemployment rate, minimum wage level, and education, race, age, gender, broad industry, and managerial shares.

Using state-level data from the Current Population Survey Outgoing Rotation Group for 1979–2019, we regress the log median wage on union density with state and year fixed effects and additional covariates: the log minimum wage, unemployment rate, and shares of those with less than a high school degree and just a high school degree, age group shares, and shares of those who are white, Black, Hispanic, married, and shares of those in the public sector, manufacturing, construction, services, and a managerial occupation. Regressions are weighted by state employment levels averaged over 1979–2019. The coefficient on union membership is 0.724 with a standard error, accounting for clustering at the state level, of 0.191.

To calculate effects of increasing union density on racial wage gaps, we use the same wage regression as before, except where the dependent variable is the state annual racial wage gap.

The calculation yielding the $1.2 trillion estimate of the annual increase in workers’ pay from tripling union density is as follows. First, the share of total labor income claimed by the bottom 80% is calculated from data provided by the Congressional Budget Office’s (CBO 2026) Distribution of Household Income data (we focus on the bottom 80% because research has generally identified the positive effect of unions on boosting pay as applying mostly to union and nonunion workers in the bottom 80% of the U.S. workforce). In 1979 this share was 60.5%, but by 2019 it had fallen to 50.1%. We use 50% for our calculations. Then we multiply the 14.5% boost to pay stemming from a tripling of union density by this 50% of labor income to get an estimate (7.25%) of how much total labor compensation would rise in the event of a tripling of union density. In the first quarter of 2026, the National Income and Product Accounts (NIPA) Table 2.1 from the Bureau of Economic Analysis (2026a) reports that total labor compensation was $16.1 trillion. Multiplying this by the 7.25% pay boost from tripling union density yields $1.16 trillion in higher pay for the bottom 80%. We believe this is the appropriate estimate for approximating how much higher wages would be for most workers if union density tripled. While potential caveats merit consideration, none, in our view, hold much force. For example, the regressions used earlier in the paper use median wages, not median total labor compensation, as the dependent variable. However, a long research literature has highlighted that benefit premiums stemming from unionization are likely even larger than wage premiums (Knepper 2020). To the degree that tripling union density works by giving all workers more leverage and bargaining power in labor markets, it seems clear that some of this leverage will be used to obtain broader and more generous coverage of benefits, not just higher wages. Another objection could be that union effects (both direct and indirect effects) are higher in the middle of the wage distribution than in either the lower or upper parts of the distribution, and hence the full 14.5% wage boost would only apply to (say) the second and middle fifths of workers while workers in the lowest and fourth fifth would see smaller wage boosts. However, in work that has estimated both the overall average effect of unionization on nonunion wages and the effect by wage percentile, the overall average effect is roughly one-half the effect at the median, a result that would be consistent with applying the 14.5% premium to half of all labor income, as we do (Fortin, Lemieux, and Lloyd 2021). Other research has similarly found that union effects at the median are very close to overall average effects (Baker et al. 2026).

For our analysis of how wage effects differ across union density levels, we use the same regression of log median wages on union density described above, modified to let the slope differ below and above 15% density using a piecewise-linear specification interacting union density with an indicator for density of at least 15%, while retaining the same controls and state and year fixed effects, weighted by state employment. The difference in slopes is statistically significant at the 1% level.

The scatterplot in Figure B uses 50 state-year bins to show this nonlinearity directly. The binned scatterplot groups the state-year observations into 50 employment-weighted bins by union density and plots each bin’s average real log median wage against its average union density, after partialing out the same controls and state and year fixed effects used in the regression.

State union density groupings

We divided the 50 U.S. states plus the District of Columbia into three equally sized groups based on their current (2023–2025) level of union density.

These groupings are shown in Appendix Table 1. We refer to the 17 states with the highest union density as “high-union-density states” (with 11.9%–25.1% union membership rates); the next 17 states (including D.C.) are “medium-union-density states” (6.8%–11.6%); and the remaining 17 are “low-union-density states” (2.5%–6.1%).

Appendix Table 1

Estimating union density effects of establishing a public-sector duty to bargain and repealing “right-to-work” laws

To estimate the effect of these two policy changes—1) requiring state and local governments to bargain with public-sector workers who choose to unionize, and 2) repealing RTW—we use the CPS Outgoing Rotation Groups for 2023–2025 to compute union density rates in states with stronger union policies (i.e., states with public sector collective bargaining and/or without RTW). We do this separately by industry and major occupation group for the private sector and by level of government (federal, state, and local) for the public sector. We then apply those rates to the workforce of each state that lacks the corresponding policy, holding each state’s industry, occupation, and government-employment mix fixed. Nevada is an exception on the private-sector side: Although Nevada is a RTW state, its private-sector union density is already comparatively high, so we hold its private-sector density at its current level.

Notes

{{1.}} “Union membership” refers to workers who are full-fledged union members, while “union representation” includes both union members and workers covered by a collective bargaining agreement but not members. The share of workers represented by a union is thus higher than the share of union members. In 2025, for example, 11.2% were represented by a union and 10% were union members.

{{2.}} In 2025, for the fifth consecutive year in a row, approval of unions reached record high levels last seen in the late 1950s, when union membership was roughly triple what it is now.

{{3.}} The productivity-pay gap is a measure of how much income is generated in an average hour of work.

{{4.}} “Union wage premium” refers to the additional wages paid to union members compared with nonunion workers with similar characteristics.

{{5.}} For example, when the top marginal tax rate was 91%, as it was in the 1950s and early 1960s, executives kept far less of each additional dollar of pay than they do under today’s 37% top rate, which reduced the payoff to pursuing ever-larger compensation packages.

{{6.}} Relatedly, expanded unemployment benefits during the pandemic boosted workers’ bargaining power and compelled employers to make higher wage offers (Bivens and Banerjee 2023).

{{7.}} See appendix for details about our methodology.

{{8.}} The real median wage is the wage of the person in the middle of the overall wage distribution, including both union and nonunion workers.

{{9.}} The median monthly cost of a mortgage in the U.S. is $1,521 according to Census (2025). Over the course of a year, that is $18,252.

{{10.}} See appendix for details about the calculation of this figure.

{{11.}} In 2020 and 2021, Congress authorized Economic Impact Payments—better known as the “COVID checks.” Those three rounds of payments added roughly $430 billion to U.S. families’ personal income in those years and were widely viewed as an historically ambitious economic intervention. Data on how much these checks added to personal income can be found at Bureau of Economic Analysis (2026c).

{{12.}} Data on federal defense spending in 2025 is from Bureau of Economic Analysis (2026b).

{{13.}} Data on the income shares by percentile come from CBO (2026), which contains data through 2022. The calculation of how much the $1.2 trillion gain to wages would reverse the rise in income shares of the top quintile uses data from BEA (2026a).

{{14.}} See appendix for details on how we estimated these wage effects.

{{15.}} See appendix for details on how we calculated the effects of increasing union density on racial wage gaps.

{{16.}} See Appendix Table 1, which shows how we grouped states into low-, medium-, and high-union-density categories.

{{17.}} For details on the data and methodology used to produce these estimates, see appendix.

{{18.}} For this state-level analysis, we use 2023–2025 averages of union density across states, which is 9.9%, rather than the 10% for 2025 cited earlier in this report.

{{19.}} See passage of Protecting America’s Workforce Act and Faster Labor Contracts Act.

{{20.}} The last time a major labor law reform was considered was in 2009 with the Employee Free Choice Act.

{{21.}} The Protecting the Right to Organize Act has two Republican co-sponsors, the Public Service Freedom to Negotiate Act has six Republican co-sponsors, and the Protecting America’s Workforce Act has nine Republican co-sponsors.

{{22.}} One way to determine the exact COLA amount is to use nonseasonally adjusted values of the national Consumer Price Index for All Urban Consumers (CPI-U) published by the Bureau of Labor Statistics. These price index values are easily available, less subject to revision, and widely covered in the media. The simplest COLA adjustment would be to use the annual rate of inflation measured as the percent change between the two most recent annual averages of nonseasonally adjusted CPI-U values. See BLS (2023) for other considerations.

{{23.}} CBO estimated CPI in 2026 at 2.8%, 2027 at 2.4%, and then 2.3% after—however those estimates were done before the U.S. war in Iran that increased energy prices, so we estimate COLA at 3% for purposes of the proposal. To calculate full-time, full-year worker wages, we used 2025 average production, nonsupervisory wage rates (EPI 2026f).

{{24.}} We specifically would recommend calculating the CEO-to-typical-worker pay ratio using the methodology detailed in EPI (2025). 

{{25.}} In order to appear on the ballot, an individual or organization would have to demonstrate a record of collective bargaining over the preceding three years or obtain 100 signatures or 10% of the workforce, whichever is less.

{{26.}} The showing of extraordinary circumstances is referenced in the acute care hospital rule: 29 CFR § 103.30 (1989).

{{27.}} This correlation between simple firm size and CEO pay is yet another piece of evidence that CEO pay is not about the skills or acumen of individual CEOs, but is driven by noncompetitive market structures and labor markets for executives.

References

AFL-CIO Tech Institute. 2026. “It’s Better in a Union!” (web page). Accessed July 7, 2026.

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American Compass. 2025. PRO-Tip: Only Some Labor Reforms Are Pro-Worker. May 1, 2025. 

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Defenders of the OBBBA cuts claim that, because a large share of these cuts result from introducing new bureaucracy around work-reporting requirements for “able-bodied adults without dependents” (ABAWDs), they will not fall on more vulnerable populations like children or retirees. This is not true. The OBBBA has many near-direct cuts to vulnerable populations’ participation in these programs. More importantly, these cuts will have large spillover effects through families and communities that will harm vulnerable populations—including children.

This post highlights how important Medicaid and SNAP spending is to children, with a particular focus on how these programs support public education. It then outlines some ways that the legislated cuts in the OBBBA will damage this support, either directly or through clear spillover effects through damage to local economies.

The importance of Medicaid and SNAP to children and schooling

Around 40% of school-age children are covered by Medicaid for health insurance, and nearly 30% of school-age children live in families that receive SNAP benefits. Medicaid funding is key for public education. It provides an estimated $7.5 billion annually to public schools to fund essential health and learning and development services. As a share of total K–12 student revenue, Medicaid provides up to 2% of school funding to some states and up to $325 per pupil in revenue in some states.

Medicaid is particularly crucial for special education. Public schools are required by law to provide appropriate care and services for individualized education plans, and Medicaid is a big source of funding for these plans. In a recent survey of school districts, 86% reported they use Medicaid funds for school health staff salaries, and 59% use the funds for contracted services for mental and behavioral health. When asked what they would have to cut if they lost Medicaid funding, 8 in 10 school district staff predicted reductions in school health personnel and services.

How Medicaid and SNAP cuts will still harm children through direct fiscal pressures

While the OBBBA cuts to Medicaid and SNAP do not directly harm children through cuts in children’s health insurance or their food stamp eligibility, changes to eligibility criteria and cost pressures on state budgets will make it onerous to maintain current spending levels for one of the main public institutions that support children: public schools. For example, if states want to maintain coverage for any ABAWDs who lose coverage because of the work requirements stipulated in the OBBBA, states will have to come up with funding for it themselves.  Additionally, the SNAP legislation requires that states now pay for 25% of their administrative costs that previously were fully funded from federal sources. With less federal money, states will either have to cut spending elsewhere in their budgets or (preferably, but politically difficult) raise revenue. None of these are easy political choices, and they all have some spillover effects. As one of the largest budget items in states, K–12 education funding will likely be squeezed in any state looking to maintain any of the services cut in the OBBBA without raising revenue.

How Medicaid and SNAP cuts will harm children through damage to local economies

Beyond these direct budgetary impacts, the OBBBA Medicaid and SNAP cuts could also reduce purchasing power in local economies and put upward pressure on unemployment rates, which could reduce economic security and opportunity for children in those areas.  Adults who receive Medicaid and SNAP don’t have to use their household budget to pay for health care or (some) groceries. Medicaid and SNAP allow them to maintain access to these necessities while also purchasing other goods in their local economy, such as electricity, child care, or rent. When these programs are cut, people face higher health and food costs, which can force them to cut back on purchases and reduce demand throughout the local economy.  

Moreover, areas particularly dependent on Medicaid and SNAP funding are least likely to be able to weather a reduction in aggregate demand for goods and services. Figure A shows that there is a clear positive relationship between a county’s unemployment rate and the income from Medicaid and SNAP. In other words, counties with high unemployment levels are also counties where a large share of their total income comes from Medicaid and SNAP funding.  

To be fair, at the national level, it is possible that the reduction in spending caused by Medicaid and SNAP cuts will be neutralized by policies that raise incomes and demand elsewhere (say, by the tax cut provisions of the OBBBA or a Federal Reserve interest rate cut). But areas that are already facing high unemployment are missing out on positive trends in the U.S. economy. For these counties, the demand shock caused by Medicaid and SNAP cuts could be large, leading to job loss in these counties.

Damage to local economies hurts students and workers

Job loss from the spillover effects of the OBBBA cuts to local economies will create stress and financial insecurity for families, a catastrophe that research has shown can harm student achievement.

Parental job loss plays a key role in reducing parent and child well-being  and has been shown to  reduce a child’s likelihood of grade completion. Moreover, parental job loss is associated with a lower likelihood of obtaining postsecondary education, particularly in Black families. Causal evidence on community level job losses found a reduction in test scores for students, following the closing of a business. The effects were stronger for older children and for children in lower-income households. Even if the Medicaid cuts mostly target adults (ABAWDS), the reduction in local aggregate demand stemming from these funding cuts will hurt all families in a given region, and particularly for children, stand to harm their educational achievement. 

Conclusion

The cuts to Medicaid and SNAP mandated by the OBBBA will harm children. Medicaid and SNAP currently fund key health and food services for public education, and while these functions aren’t directly threatened under the OBBBA, the cost pressures states will face from federal funding cuts will threaten the ability of these programs to serve students. Moreover, there are clear spillover effects through damage to local economies. By reducing the amount of available income in these areas, Medicaid and SNAP cuts run the risk of imposing a sharp anti-stimulus to local economies. This effect could be large in demand-constrained counties (studies on the multiplier effect of Medicaid consistently show it has large effects on spending).   The claim that OBBBA won’t harm children is patently wrong, and the harms from it will plague children for a long time to come.

Every month, the Bureau of Labor Statistics releases a report on the employment situation for the previous month. Their release includes data on job growth, unemployment, and wage growth, which gives us a snapshot of the health of the economy and whether it’s working for ordinary Americans.

 

Charting jobs and unemployment

Current Employment Statistics Charts

The Current Employment Statistics (CES) program, also known as the establishment survey, is a monthly survey administered by the Bureau of Labor Statistics (BLS) which provides estimates of employment, hours, and earnings based on payroll records of approximately 131,000 businesses and government agencies.

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Current Population Survey Charts

The Current Population Survey (CPS), also known as the household survey, is sponsored jointly by the Census Bureau and the Bureau of Labor Statistics (BLS). Each month, it provides data on the labor force, employment, unemployment, persons not in the labor force, hours of work, earnings, and other demographic and labor force characteristics. 

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Economic indicators

Longer-term labor market trends

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Past employment reports

News from EPI › Jobs report shows more than 25 million workers are directly harmed by the COVID labor market: Congress must pass the full $1.9 trillion relief package immediately

March 5, 2021 By Elise Gould Economic Indicators

News from EPI › The U.S. labor market remains 9.9 million jobs below pre-pandemic levels

February 5, 2021 By Elise Gould Economic Indicators

News from EPI › December jobs report provides a clear picture of Trump’s failed handling of the economy

January 8, 2021 By Elise Gould Economic Indicators

News from EPI › Recovery continues to wane: Expiring unemployment relief means more trouble around the corner

December 4, 2020 By Elise Gould Economic Indicators

News from EPI › October jobs report: Next president inherits a devastated economy with millions out of work

November 6, 2020 By Elise Gould Economic Indicators

News from EPI › Slowdown in jobs added means we could be years away from a full recovery

October 2, 2020 By Elise Gould Economic Indicators

News from EPI › Six months into the recession and a 11.5 million jobs deficit remains

September 4, 2020 By Elise Gould Economic Indicators

News from EPI › The bounceback deflates: Job gains slow considerably in July

August 7, 2020 By Elise Gould Economic Indicators

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