Class of 2026: A depressed hires rate is a major cause of labor market weakness for young college graduates
Key takeaways
- The depressed overall hires rate is a key driver of new labor market weakness for young college graduates, as it makes it harder for them to break into the labor market. This is true across industries, not just in those that disproportionately employ young college graduates—suggesting the culprit is not a structural change in the economy like AI but a labor market in which employers are hiring less and workers are holding onto the jobs they have.
- The information sector—posited to be more AI-exposed—has experienced recent job losses but employs only 2.3% of young college graduates.
- High-tech industries, which employ about 1 in 10 college workers, expanded at a historically rapid pace in the early 2020s but have shown signs of softening over the last three years.
The early 2020s labor market for young college graduates was strong. But, as we showed in this series’ first blog post, the Class of 2026 is graduating college into a labor market that has notably weakened in the past two years. A growing share of young college graduates are looking for jobs, but their employment rates have not kept pace—meaning unemployment is rising faster for young graduates than for the overall workforce. While their outcomes remain better than those of their noncollege counterparts, the uptick in unemployment has been a rising concern.
In this blog post, we delve deeper into the industries where young college graduates are likely to work,1 examining whether it has been relatively more difficult to secure employment in these fields as the labor market has weakened. Our analysis first examines employment changes, then turns to labor market flows, including hires and separations rates. We also scour the data for signs of contraction in the tech sector that may disproportionately affect the prospects for young college graduates as they enter the labor market.
In the third blog post in the series, we will examine the occupations where young college graduates work with particular attention to occupations that may have grown or shrunk, as well as to those most exposed to AI.
Young college graduates work in industries with strong growth in this business cycle
Over half of young college graduates work in private education and health services, professional and business services, or public-sector jobs. Figure A displays the share of employment in each industrial sector or sector grouping for young college graduates ages 22 to 27, all college graduates, and young workers without a four-year college degree. Industries in the figure appear in order of the share of young college graduates they employ, from largest to smallest.
The types of jobs where young college graduates work look similar to those of college graduates generally. Young workers without a college degree (i.e., noncollege) are far more likely to work in trade, transportation, and utilities; mining, construction, and manufacturing; or leisure and hospitality. All groups of workers are least likely to work in the information sector, closely watched for signs of AI-induced displacement.
Young college graduates are concentrated in sectors where college graduates in general work: Employment shares by industrial sector for select age and education groups, 2026
| Young college graduates (22–27) | All graduates | Young noncollege (22–27) | |
|---|---|---|---|
| Private educational and health services | 21.6% | 17.8% | 14.1% |
| Professional and business services | 18.5% | 18.2% | 8.1% |
| Public sector | 14.8% | 15.0% | 7.3% |
| Trade, transportation, and utilities | 12.1% | 13.2% | 26.4% |
| Mining, construction, manufacturing | 10.8% | 13.1% | 18.5% |
| Financial activities | 8.9% | 10.9% | 3.7% |
| Leisure and hospitality | 7.8% | 5.5% | 15.3% |
| Other services | 3.2% | 3.5% | 5.5% |
| Information | 2.3% | 2.6% | 1.1% |
Notes: Only nonfarm sectors are included for comparability with the Current Employment Statistics. Data for 2026 are a 12-month average of pooled data from April 2025 through March 2026.
Source: EPI analysis of the Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 2026.4.13, https://microdata.epi.org.
Figure B shows the change in employment in each sector between 2019 and 2026 and between 2023 and 2026, arranged in the same order as Figure A for comparison. The two fastest growing sectors since the last business cycle peak occurred in the two largest sectors for young college graduates: private education and health services and professional and business services.
Since the rollout of ChatGPT, many have looked at industries and occupations likely to be exposed to AI to see whether this has led to weaker job growth. Among the most closely watched of these industries is the information sector, which has seen an 8.5% employment decline since 2023.2 While these losses are notable—and especially relevant to understanding AI’s fingerprints on the labor market for young college-educated workers—it cannot be overemphasized just how small this sector is in the overall economy. Less than 2% of overall employment is in the information sector, including only 2.3% of young college graduates. Further, the sector saw a rapid employment expansion between 2019 and 2023—the employment loss between 2019 and today is just 2.0%.
All industries have grown since 2019, except for the Information sector: Percent change in employment by sector, since 2019 and 2023
| Change since 2019 | Change since 2023 | |
|---|---|---|
| Private educational and health services | 15.9% | 11.0% |
| Professional and business services | 5.5% | -1.8% |
| Public sector | 3.3% | 3.3% |
| Trade, transportation, and utilities | 3.8% | -0.6% |
| Mining, construction, manufacturing | 2.7% | 0.4% |
| Financial activities | 4.9% | -0.2% |
| Leisure and hospitality | 3.0% | 3.3% |
| Other services | 2.5% | 4.0% |
| Information | -2.0% | -8.5% |
Notes: Data are for the 12-month average of pooled data ending in March of each given year (e.g. 2026 refers to pooled data from April 2025 through March 2026).
Source: EPI analysis of the Bureau of Labor Statistics Current Employment Statistics (CES).
High-tech sectors have relatively more college graduates but haven’t experienced large AI-induced employment losses
In recent years, the Census Bureau has created an experimental data series on high-tech industries to better understand business dynamics. These include both manufacturing and service sector components of high tech.3 We translate their NAICS classification for high-tech industries into Census Industry Classifications used by the Current Population Survey (CPS) to determine the likelihood of young college graduates working in these sectors.
In the 2026 economy, about 5.6% of workers were employed in what the Census considers high-tech industries. Just about 1 in 10 (9.9%) of the college-educated workforce works in the tech industry. Young college graduates are similarly represented: 10.3% work in tech.
Overall, the Current Establishment Survey tells us that tech industry employment tracked changes in overall private employment in the prior business cycle (between 2007 and 2019) but expanded sharply in the early 2020s and has softened a bit in the last three years. Since 2023, the tech sector has fallen by 0.7%. While overall employment using CPS does show modest growth, neither shows large swings that suggest a large impact for young college graduates.4
Weak hires may be the biggest culprit to labor market weakness for young college graduates
The Job Openings and Labor Turnover Survey (JOLTS) can shed light on the question of whether entry-level workers—with or without college degrees—are facing a harder labor market to break into. While JOLTS doesn’t include demographic characteristics, it presents jobs openings as well as rates of hiring, layoffs, quits, and other separations. Today’s economy has substantially less churn than during the recovery from the pandemic, when millions of workers reentered the labor market after mass layoffs—many quit soon after as they searched for, and generally found, better opportunities.
Figure C shows the hires and separation rates. The lighter colors represent the monthly seasonally adjusted data for each series while the darker colors represent a 12-month moving average that provides a better overall picture of recent trends, smoothing out some data volatility. Over the last five years, the hires rate has steadily fallen and now sits at levels last seen in 2013 and 2014, when the labor market was still struggling to recover from the Great Recession.
The total separations rate includes quits, layoffs and discharges, and other separations.5 As with the hires rate, the separations rate has been declining over the last few years and now sits about where it was in 2014. Much of this is due to reductions in quits. Quits are higher when workers feel confident that they will find better job opportunities. Right now, workers are sitting tight, more so than any point in the past 10 years. Taken together, there is simply less churn in the labor market. But reduced churn is not inherently bad. If the frantic labor market of the early 2020s led to many workers and employers finding satisfactory matches, it could make sense that the following years would see less churn than normal. But for young workers looking to enter the job market, a reduction in hiring can make it harder to find a job.
The hires and separations rates are approaching historic lows: The hires and separations rate smoothed and unsmoothed, 2002–present
| Hires smoothed | Hires | Total separations smoothed | Total separations | |
|---|---|---|---|---|
| Jan-2002 | 3.70 | 3.7 | 4.01 | 3.9 |
| Feb-2002 | 3.70 | 3.7 | 4.00 | 3.8 |
| Mar-2002 | 3.67 | 3.6 | 3.95 | 3.6 |
| Apr-2002 | 3.70 | 3.8 | 3.93 | 3.8 |
| May-2002 | 3.70 | 3.7 | 3.89 | 3.7 |
| Jun-2002 | 3.70 | 3.7 | 3.87 | 3.7 |
| Jul-2002 | 3.71 | 3.8 | 3.85 | 3.9 |
| Aug-2002 | 3.71 | 3.7 | 3.82 | 3.7 |
| Sep-2002 | 3.71 | 3.7 | 3.81 | 3.8 |
| Oct-2002 | 3.71 | 3.7 | 3.76 | 3.6 |
| Nov-2002 | 3.71 | 3.7 | 3.73 | 3.6 |
| Dec-2002 | 3.71 | 3.7 | 3.74 | 3.8 |
| Jan-2003 | 3.73 | 3.9 | 3.73 | 3.8 |
| Feb-2003 | 3.72 | 3.6 | 3.73 | 3.7 |
| Mar-2003 | 3.70 | 3.4 | 3.73 | 3.6 |
| Apr-2003 | 3.68 | 3.5 | 3.71 | 3.6 |
| May-2003 | 3.67 | 3.6 | 3.70 | 3.6 |
| Jun-2003 | 3.66 | 3.6 | 3.69 | 3.6 |
| Jul-2003 | 3.64 | 3.6 | 3.67 | 3.6 |
| Aug-2003 | 3.63 | 3.6 | 3.66 | 3.6 |
| Sep-2003 | 3.63 | 3.7 | 3.64 | 3.6 |
| Oct-2003 | 3.64 | 3.8 | 3.64 | 3.6 |
| Nov-2003 | 3.64 | 3.7 | 3.64 | 3.6 |
| Dec-2003 | 3.65 | 3.8 | 3.63 | 3.7 |
| Jan-2004 | 3.63 | 3.7 | 3.62 | 3.6 |
| Feb-2004 | 3.64 | 3.7 | 3.61 | 3.6 |
| Mar-2004 | 3.69 | 4.0 | 3.63 | 3.8 |
| Apr-2004 | 3.73 | 3.9 | 3.63 | 3.7 |
| May-2004 | 3.74 | 3.8 | 3.63 | 3.6 |
| Jun-2004 | 3.76 | 3.8 | 3.64 | 3.7 |
| Jul-2004 | 3.77 | 3.7 | 3.65 | 3.7 |
| Aug-2004 | 3.78 | 3.8 | 3.66 | 3.7 |
| Sep-2004 | 3.79 | 3.8 | 3.67 | 3.7 |
| Oct-2004 | 3.80 | 3.9 | 3.67 | 3.6 |
| Nov-2004 | 3.82 | 3.9 | 3.69 | 3.9 |
| Dec-2004 | 3.83 | 3.9 | 3.69 | 3.7 |
| Jan-2005 | 3.84 | 3.9 | 3.71 | 3.8 |
| Feb-2005 | 3.87 | 4.0 | 3.73 | 3.8 |
| Mar-2005 | 3.87 | 4.0 | 3.73 | 3.9 |
| Apr-2005 | 3.88 | 4.0 | 3.73 | 3.7 |
| May-2005 | 3.88 | 3.9 | 3.75 | 3.8 |
| Jun-2005 | 3.90 | 4.0 | 3.76 | 3.8 |
| Jul-2005 | 3.93 | 4.0 | 3.76 | 3.7 |
| Aug-2005 | 3.94 | 4.0 | 3.78 | 3.9 |
| Sep-2005 | 3.97 | 4.1 | 3.80 | 4.0 |
| Oct-2005 | 3.96 | 3.8 | 3.81 | 3.7 |
| Nov-2005 | 3.97 | 4.0 | 3.79 | 3.7 |
| Dec-2005 | 3.97 | 3.9 | 3.80 | 3.8 |
| Jan-2006 | 3.97 | 3.9 | 3.79 | 3.7 |
| Feb-2006 | 3.97 | 4.0 | 3.80 | 3.9 |
| Mar-2006 | 3.98 | 4.1 | 3.80 | 3.9 |
| Apr-2006 | 3.96 | 3.8 | 3.80 | 3.7 |
| May-2006 | 3.97 | 4.0 | 3.82 | 4.0 |
| Jun-2006 | 3.97 | 4.0 | 3.83 | 3.9 |
| Jul-2006 | 3.98 | 4.1 | 3.84 | 3.9 |
| Aug-2006 | 3.97 | 3.9 | 3.83 | 3.8 |
| Sep-2006 | 3.95 | 3.9 | 3.81 | 3.7 |
| Oct-2006 | 3.96 | 3.9 | 3.83 | 3.9 |
| Nov-2006 | 3.96 | 4.0 | 3.84 | 3.9 |
| Dec-2006 | 3.95 | 3.8 | 3.83 | 3.7 |
| Jan-2007 | 3.95 | 3.9 | 3.84 | 3.8 |
| Feb-2007 | 3.93 | 3.8 | 3.83 | 3.7 |
| Mar-2007 | 3.93 | 4.0 | 3.82 | 3.8 |
| Apr-2007 | 3.93 | 3.9 | 3.83 | 3.8 |
| May-2007 | 3.93 | 4.0 | 3.81 | 3.8 |
| Jun-2007 | 3.92 | 3.8 | 3.79 | 3.7 |
| Jul-2007 | 3.89 | 3.8 | 3.78 | 3.8 |
| Aug-2007 | 3.89 | 3.9 | 3.79 | 3.9 |
| Sep-2007 | 3.89 | 3.9 | 3.80 | 3.8 |
| Oct-2007 | 3.89 | 3.9 | 3.79 | 3.8 |
| Nov-2007 | 3.87 | 3.7 | 3.78 | 3.7 |
| Dec-2007 | 3.86 | 3.7 | 3.77 | 3.6 |
| Jan-2008 | 3.84 | 3.7 | 3.76 | 3.7 |
| Feb-2008 | 3.83 | 3.7 | 3.77 | 3.8 |
| Mar-2008 | 3.80 | 3.6 | 3.75 | 3.6 |
| Apr-2008 | 3.78 | 3.6 | 3.74 | 3.7 |
| May-2008 | 3.73 | 3.4 | 3.72 | 3.5 |
| Jun-2008 | 3.71 | 3.6 | 3.72 | 3.7 |
| Jul-2008 | 3.68 | 3.4 | 3.69 | 3.5 |
| Aug-2008 | 3.63 | 3.4 | 3.67 | 3.6 |
| Sep-2008 | 3.58 | 3.3 | 3.65 | 3.6 |
| Oct-2008 | 3.53 | 3.3 | 3.63 | 3.6 |
| Nov-2008 | 3.48 | 3.0 | 3.63 | 3.6 |
| Dec-2008 | 3.43 | 3.2 | 3.63 | 3.6 |
| Jan-2009 | 3.38 | 3.1 | 3.62 | 3.6 |
| Feb-2009 | 3.33 | 3.0 | 3.60 | 3.6 |
| Mar-2009 | 3.27 | 2.9 | 3.60 | 3.6 |
| Apr-2009 | 3.21 | 2.9 | 3.59 | 3.6 |
| May-2009 | 3.17 | 2.9 | 3.57 | 3.2 |
| Jun-2009 | 3.10 | 2.8 | 3.53 | 3.2 |
| Jul-2009 | 3.07 | 3.0 | 3.50 | 3.2 |
| Aug-2009 | 3.03 | 2.9 | 3.46 | 3.1 |
| Sep-2009 | 3.00 | 3.0 | 3.43 | 3.2 |
| Oct-2009 | 2.98 | 3.0 | 3.38 | 3.1 |
| Nov-2009 | 2.98 | 3.1 | 3.34 | 3.1 |
| Dec-2009 | 2.98 | 3.1 | 3.31 | 3.2 |
| Jan-2010 | 2.97 | 3.0 | 3.26 | 3.0 |
| Feb-2010 | 2.97 | 3.0 | 3.22 | 3.1 |
| Mar-2010 | 3.00 | 3.3 | 3.18 | 3.1 |
| Apr-2010 | 3.03 | 3.2 | 3.13 | 3.0 |
| May-2010 | 3.07 | 3.4 | 3.11 | 3.0 |
| Jun-2010 | 3.09 | 3.1 | 3.12 | 3.3 |
| Jul-2010 | 3.11 | 3.2 | 3.13 | 3.3 |
| Aug-2010 | 3.13 | 3.1 | 3.13 | 3.1 |
| Sep-2010 | 3.13 | 3.1 | 3.12 | 3.1 |
| Oct-2010 | 3.15 | 3.2 | 3.11 | 3.0 |
| Nov-2010 | 3.16 | 3.2 | 3.11 | 3.1 |
| Dec-2010 | 3.18 | 3.3 | 3.11 | 3.2 |
| Jan-2011 | 3.18 | 3.1 | 3.12 | 3.1 |
| Feb-2011 | 3.20 | 3.2 | 3.12 | 3.1 |
| Mar-2011 | 3.21 | 3.4 | 3.13 | 3.2 |
| Apr-2011 | 3.22 | 3.3 | 3.13 | 3.0 |
| May-2011 | 3.20 | 3.2 | 3.14 | 3.2 |
| Jun-2011 | 3.22 | 3.3 | 3.13 | 3.2 |
| Jul-2011 | 3.22 | 3.2 | 3.12 | 3.1 |
| Aug-2011 | 3.23 | 3.3 | 3.13 | 3.2 |
| Sep-2011 | 3.25 | 3.3 | 3.13 | 3.2 |
| Oct-2011 | 3.26 | 3.3 | 3.14 | 3.1 |
| Nov-2011 | 3.27 | 3.3 | 3.15 | 3.2 |
| Dec-2011 | 3.27 | 3.3 | 3.14 | 3.1 |
| Jan-2012 | 3.28 | 3.3 | 3.14 | 3.1 |
| Feb-2012 | 3.30 | 3.4 | 3.16 | 3.3 |
| Mar-2012 | 3.30 | 3.4 | 3.16 | 3.2 |
| Apr-2012 | 3.30 | 3.3 | 3.18 | 3.2 |
| May-2012 | 3.32 | 3.4 | 3.18 | 3.3 |
| Jun-2012 | 3.32 | 3.3 | 3.19 | 3.3 |
| Jul-2012 | 3.32 | 3.2 | 3.19 | 3.1 |
| Aug-2012 | 3.32 | 3.3 | 3.19 | 3.2 |
| Sep-2012 | 3.31 | 3.2 | 3.18 | 3.0 |
| Oct-2012 | 3.31 | 3.3 | 3.18 | 3.2 |
| Nov-2012 | 3.31 | 3.3 | 3.18 | 3.2 |
| Dec-2012 | 3.31 | 3.3 | 3.18 | 3.0 |
| Jan-2013 | 3.31 | 3.3 | 3.18 | 3.2 |
| Feb-2013 | 3.31 | 3.4 | 3.18 | 3.2 |
| Mar-2013 | 3.29 | 3.2 | 3.17 | 3.1 |
| Apr-2013 | 3.30 | 3.4 | 3.18 | 3.3 |
| May-2013 | 3.30 | 3.4 | 3.18 | 3.3 |
| Jun-2013 | 3.30 | 3.3 | 3.17 | 3.2 |
| Jul-2013 | 3.31 | 3.3 | 3.18 | 3.2 |
| Aug-2013 | 3.33 | 3.5 | 3.18 | 3.3 |
| Sep-2013 | 3.35 | 3.5 | 3.21 | 3.3 |
| Oct-2013 | 3.35 | 3.3 | 3.21 | 3.2 |
| Nov-2013 | 3.36 | 3.4 | 3.21 | 3.2 |
| Dec-2013 | 3.37 | 3.4 | 3.23 | 3.2 |
| Jan-2014 | 3.38 | 3.4 | 3.23 | 3.2 |
| Feb-2014 | 3.38 | 3.4 | 3.23 | 3.3 |
| Mar-2014 | 3.40 | 3.5 | 3.25 | 3.3 |
| Apr-2014 | 3.41 | 3.5 | 3.25 | 3.3 |
| May-2014 | 3.42 | 3.5 | 3.25 | 3.3 |
| Jun-2014 | 3.43 | 3.5 | 3.26 | 3.3 |
| Jul-2014 | 3.46 | 3.6 | 3.28 | 3.4 |
| Aug-2014 | 3.46 | 3.5 | 3.28 | 3.3 |
| Sep-2014 | 3.48 | 3.7 | 3.29 | 3.5 |
| Oct-2014 | 3.51 | 3.7 | 3.32 | 3.5 |
| Nov-2014 | 3.53 | 3.6 | 3.33 | 3.3 |
| Dec-2014 | 3.55 | 3.7 | 3.34 | 3.4 |
| Jan-2015 | 3.57 | 3.6 | 3.37 | 3.5 |
| Feb-2015 | 3.58 | 3.6 | 3.38 | 3.5 |
| Mar-2015 | 3.59 | 3.6 | 3.41 | 3.6 |
| Apr-2015 | 3.61 | 3.7 | 3.43 | 3.5 |
| May-2015 | 3.62 | 3.6 | 3.43 | 3.4 |
| Jun-2015 | 3.63 | 3.6 | 3.45 | 3.5 |
| Jul-2015 | 3.63 | 3.6 | 3.45 | 3.4 |
| Aug-2015 | 3.63 | 3.6 | 3.47 | 3.5 |
| Sep-2015 | 3.63 | 3.7 | 3.48 | 3.6 |
| Oct-2015 | 3.63 | 3.7 | 3.48 | 3.5 |
| Nov-2015 | 3.65 | 3.8 | 3.50 | 3.6 |
| Dec-2015 | 3.67 | 3.9 | 3.53 | 3.7 |
| Jan-2016 | 3.67 | 3.6 | 3.53 | 3.6 |
| Feb-2016 | 3.68 | 3.8 | 3.55 | 3.7 |
| Mar-2016 | 3.69 | 3.7 | 3.55 | 3.6 |
| Apr-2016 | 3.69 | 3.7 | 3.56 | 3.6 |
| May-2016 | 3.69 | 3.6 | 3.58 | 3.6 |
| Jun-2016 | 3.70 | 3.7 | 3.58 | 3.6 |
| Jul-2016 | 3.72 | 3.8 | 3.59 | 3.5 |
| Aug-2016 | 3.73 | 3.7 | 3.60 | 3.6 |
| Sep-2016 | 3.73 | 3.7 | 3.58 | 3.4 |
| Oct-2016 | 3.72 | 3.6 | 3.58 | 3.5 |
| Nov-2016 | 3.71 | 3.7 | 3.58 | 3.5 |
| Dec-2016 | 3.69 | 3.7 | 3.56 | 3.5 |
| Jan-2017 | 3.71 | 3.8 | 3.57 | 3.7 |
| Feb-2017 | 3.70 | 3.7 | 3.55 | 3.5 |
| Mar-2017 | 3.70 | 3.7 | 3.55 | 3.6 |
| Apr-2017 | 3.69 | 3.6 | 3.54 | 3.5 |
| May-2017 | 3.70 | 3.7 | 3.54 | 3.6 |
| Jun-2017 | 3.71 | 3.8 | 3.55 | 3.7 |
| Jul-2017 | 3.70 | 3.7 | 3.56 | 3.6 |
| Aug-2017 | 3.71 | 3.8 | 3.56 | 3.6 |
| Sep-2017 | 3.71 | 3.7 | 3.58 | 3.6 |
| Oct-2017 | 3.73 | 3.8 | 3.59 | 3.7 |
| Nov-2017 | 3.73 | 3.7 | 3.60 | 3.6 |
| Dec-2017 | 3.73 | 3.7 | 3.61 | 3.6 |
| Jan-2018 | 3.72 | 3.7 | 3.60 | 3.6 |
| Feb-2018 | 3.73 | 3.8 | 3.61 | 3.6 |
| Mar-2018 | 3.73 | 3.8 | 3.62 | 3.7 |
| Apr-2018 | 3.75 | 3.8 | 3.63 | 3.7 |
| May-2018 | 3.77 | 3.9 | 3.64 | 3.7 |
| Jun-2018 | 3.78 | 3.9 | 3.64 | 3.7 |
| Jul-2018 | 3.78 | 3.8 | 3.65 | 3.7 |
| Aug-2018 | 3.79 | 3.9 | 3.66 | 3.7 |
| Sep-2018 | 3.80 | 3.8 | 3.67 | 3.7 |
| Oct-2018 | 3.82 | 4.0 | 3.67 | 3.7 |
| Nov-2018 | 3.83 | 3.9 | 3.69 | 3.9 |
| Dec-2018 | 3.85 | 3.9 | 3.70 | 3.7 |
| Jan-2019 | 3.87 | 3.9 | 3.71 | 3.7 |
| Feb-2019 | 3.87 | 3.8 | 3.73 | 3.8 |
| Mar-2019 | 3.87 | 3.8 | 3.73 | 3.7 |
| Apr-2019 | 3.88 | 4.0 | 3.73 | 3.8 |
| May-2019 | 3.88 | 3.8 | 3.73 | 3.7 |
| Jun-2019 | 3.87 | 3.8 | 3.73 | 3.7 |
| Jul-2019 | 3.88 | 3.9 | 3.75 | 3.9 |
| Aug-2019 | 3.88 | 3.9 | 3.75 | 3.7 |
| Sep-2019 | 3.88 | 3.9 | 3.76 | 3.8 |
| Oct-2019 | 3.87 | 3.8 | 3.76 | 3.7 |
| Nov-2019 | 3.87 | 3.9 | 3.74 | 3.7 |
| Dec-2019 | 3.87 | 3.9 | 3.75 | 3.8 |
| Jan-2020 | 3.87 | 3.9 | 3.76 | 3.8 |
| Feb-2020 | 3.88 | 3.9 | 3.76 | 3.8 |
| Mar-2020 | 3.84 | 3.4 | 4.35 | 10.8 |
| Apr-2020 | 3.77 | 3.1 | 4.77 | 8.8 |
| May-2020 | 3.96 | 6.1 | 4.75 | 3.5 |
| Jun-2020 | 4.09 | 5.4 | 4.76 | 3.8 |
| Jul-2020 | 4.14 | 4.5 | 4.74 | 3.7 |
| Aug-2020 | 4.18 | 4.3 | 4.72 | 3.4 |
| Sep-2020 | 4.20 | 4.2 | 4.70 | 3.6 |
| Oct-2020 | 4.24 | 4.3 | 4.71 | 3.8 |
| Nov-2020 | 4.26 | 4.1 | 4.73 | 3.9 |
| Dec-2020 | 4.26 | 3.9 | 4.73 | 3.9 |
| Jan-2021 | 4.26 | 3.9 | 4.72 | 3.6 |
| Feb-2021 | 4.28 | 4.1 | 4.71 | 3.7 |
| Mar-2021 | 4.35 | 4.3 | 4.13 | 3.8 |
| Apr-2021 | 4.44 | 4.2 | 3.72 | 3.9 |
| May-2021 | 4.28 | 4.1 | 3.74 | 3.8 |
| Jun-2021 | 4.20 | 4.5 | 3.75 | 3.9 |
| Jul-2021 | 4.21 | 4.6 | 3.78 | 4.0 |
| Aug-2021 | 4.21 | 4.3 | 3.83 | 4.0 |
| Sep-2021 | 4.23 | 4.5 | 3.87 | 4.1 |
| Oct-2021 | 4.25 | 4.5 | 3.88 | 3.9 |
| Nov-2021 | 4.29 | 4.6 | 3.89 | 4.1 |
| Dec-2021 | 4.34 | 4.5 | 3.91 | 4.1 |
| Jan-2022 | 4.38 | 4.3 | 3.96 | 4.2 |
| Feb-2022 | 4.41 | 4.5 | 3.98 | 4.0 |
| Mar-2022 | 4.42 | 4.4 | 4.01 | 4.1 |
| Apr-2022 | 4.43 | 4.3 | 4.02 | 4.0 |
| May-2022 | 4.43 | 4.2 | 4.03 | 4.0 |
| Jun-2022 | 4.42 | 4.3 | 4.04 | 4.0 |
| Jul-2022 | 4.38 | 4.2 | 4.03 | 3.8 |
| Aug-2022 | 4.38 | 4.2 | 4.03 | 4.1 |
| Sep-2022 | 4.33 | 4.0 | 4.01 | 3.8 |
| Oct-2022 | 4.29 | 4.0 | 4.00 | 3.8 |
| Nov-2022 | 4.24 | 4.0 | 3.98 | 3.8 |
| Dec-2022 | 4.20 | 4.0 | 3.96 | 3.9 |
| Jan-2023 | 4.18 | 4.1 | 3.93 | 3.8 |
| Feb-2023 | 4.13 | 3.9 | 3.90 | 3.7 |
| Mar-2023 | 4.08 | 3.8 | 3.88 | 3.9 |
| Apr-2023 | 4.04 | 3.8 | 3.85 | 3.6 |
| May-2023 | 4.02 | 3.9 | 3.83 | 3.8 |
| Jun-2023 | 3.98 | 3.8 | 3.80 | 3.6 |
| Jul-2023 | 3.93 | 3.6 | 3.78 | 3.6 |
| Aug-2023 | 3.88 | 3.7 | 3.74 | 3.6 |
| Sep-2023 | 3.86 | 3.7 | 3.72 | 3.5 |
| Oct-2023 | 3.83 | 3.7 | 3.69 | 3.5 |
| Nov-2023 | 3.79 | 3.5 | 3.67 | 3.5 |
| Dec-2023 | 3.76 | 3.6 | 3.63 | 3.5 |
| Jan-2024 | 3.72 | 3.6 | 3.60 | 3.4 |
| Feb-2024 | 3.69 | 3.6 | 3.58 | 3.5 |
| Mar-2024 | 3.67 | 3.5 | 3.53 | 3.3 |
| Apr-2024 | 3.64 | 3.5 | 3.52 | 3.4 |
| May-2024 | 3.61 | 3.5 | 3.48 | 3.4 |
| Jun-2024 | 3.57 | 3.3 | 3.45 | 3.2 |
| Jul-2024 | 3.55 | 3.4 | 3.43 | 3.4 |
| Aug-2024 | 3.52 | 3.3 | 3.41 | 3.3 |
| Sep-2024 | 3.49 | 3.4 | 3.39 | 3.3 |
| Oct-2024 | 3.46 | 3.3 | 3.38 | 3.3 |
| Nov-2024 | 3.44 | 3.3 | 3.36 | 3.3 |
| Dec-2024 | 3.42 | 3.3 | 3.33 | 3.2 |
| Jan-2025 | 3.39 | 3.3 | 3.33 | 3.3 |
| Feb-2025 | 3.37 | 3.3 | 3.31 | 3.3 |
| Mar-2025 | 3.36 | 3.4 | 3.31 | 3.3 |
| Apr-2025 | 3.35 | 3.4 | 3.30 | 3.3 |
| May-2025 | 3.34 | 3.4 | 3.29 | 3.3 |
| Jun-2025 | 3.35 | 3.4 | 3.31 | 3.4 |
| Jul-2025 | 3.34 | 3.3 | 3.30 | 3.3 |
| Aug-2025 | 3.33 | 3.2 | 3.30 | 3.3 |
| Sep-2025 | 3.33 | 3.3 | 3.30 | 3.3 |
| Oct-2025 | 3.33 | 3.3 | 3.29 | 3.2 |
| Nov-2025 | 3.32 | 3.2 | 3.28 | 3.2 |
| Dec-2025 | 3.32 | 3.3 | 3.29 | 3.3 |
| Jan-2026 | 3.33 | 3.4 | 3.28 | 3.2 |
| Feb-2026 | 3.31 | 3.1 | 3.28 | 3.2 |
| Mar-2026 | 3.32 | 3.5 | 3.28 | 3.4 |
Notes: Smoothed data is a 12-month moving average of seasonally adjusted monthly data.
Source: EPI analysis of the Bureau of Labor Statistics Jobs Openings and Labor Turnover Survey (JOLTS).
Table 1 breaks down the change in the hires and separations rate over the last three years, again using 12-month moving averages to smooth some volatility in the data. The industries are listed in order of the share of young college graduates they employ, similarly to Figure A. Overall, the hires rate fell 0.8 percentage points and the separations rate fell 0.6 percentage points between 2023 and 2026. The industries where young college graduates are more likely to work saw smaller reductions in both hires and quits than the overall. Industries where young workers without a college degree are more often found—over a quarter are in trade, transportation, and utilities—saw greater losses. Finally, leisure and hospitality, where young noncollege are more than twice as likely to work as young college graduates, saw the largest declines in hiring.
It does not appear that the industries where young college graduates tend to work are experiencing more weakness than other industries. Job gains are just as strong, if not stronger, and hiring hasn’t fallen as far in other industries. In short, there does not seem to be any profound structural change in the economy affecting the industry composition of employment—AI or anything else—that would easily explain the softening of the labor market for young college graduates in recent years. What it does appear to be is a harder labor market for young workers to break into when employers are less likely to hire and workers are more likely to sit tight in the job they have.
1. Throughout this blog post, we define young college graduates as people between the ages of 22 and 27 with only a four-year college degree. Unlike similar analyses of young workers, we do not exclude young college graduates that are currently enrolled in school, but the results here are robust either way. Unless otherwise noted, data for 2026 represent a 12-month average from April 2025 through March 2026 for the most up to date and reliable estimates, which removes seasonality and increases sample sizes.
2. ChatGPT was first introduced in November 2022 but took several months for more widespread usage.
3. High tech industries: Computer and Peripheral Equipment Manufacturing, Communications Equipment Manufacturing, Semiconductor and Other Electronic Component Manufacturing, Navigational, Measuring, Electromedical, and Control Instruments Manufacturing, Aerospace Product and Parts Manufacturing, Software Publishers, Data Processing, Hosting, and Related Services, Other Information Services, Architectural, Engineering, and Related Services, Computer Systems Design and Related Services, and Scientific Research and Development Services.
4. It’s not unusual for the CPS and CES to display small differences in employment levels or trends considering nontrivial differences in their methodologies.
5. Other separations include separations due to retirement, death, disability, and transfers to other locations of the same firm.
Enjoyed this post?
Sign up for EPI's newsletter so you never miss our research and insights on ways to make the economy work better for everyone.