Class of 2024: Young college graduates have experienced a rapid economic recovery

Key findings:

  • Following the pandemic economic shock, young college graduates have experienced a much faster bounceback in the labor market and stronger wage growth than any recovery in recent history.
    • The unemployment rate for college graduates—defined as workers ages 21 to 24—has recovered more than 2.5 times faster than the aftermath of the Great Recession of 2008–09 (3.3 years versus 8.5 years). Meanwhile, their underemployment rate has recovered in 2.25 years after the onset of the pandemic but never fully recovered following the Great Recession.
    • Young college graduates experienced 2.2% real wage growth between February 2020 and March 2024.
  • Racial and gender wage gaps remain large even among college graduates beginning their careers. On average, women are paid $5.30 less per hour than their male counterparts, while Black and Hispanic workers are paid $3.24 and $2.07 less per hour, respectively, than white workers.

The labor market for young college graduates today is stronger than it was before the pandemic and has been for quite some time. This strong recovery was not guaranteed—instead, it was a direct result of an aggressive fiscal policy response to the pandemic’s economic shock. This bounceback—not just for young college graduates but for all workers—has been much faster than recoveries following recessions over the past 30 years, when fiscal policy was not used at scale.

In this blog post, we first examine employment and enrollment outcomes to determine what young college graduates are doing. We then analyze the short- and long-run trends in unemployment, underemployment, and wages for young college graduates—defined as workers ages 21 to 24—with only a four-year college degree and who are not enrolled in further schooling.1

As of March 2024, 65.2% of young college graduates are “employed only” (not enrolled in further schooling), while only 10.0% are “idled” (not enrolled and not employed, which includes the unemployed). The share of young graduates who are “employed only” has been above its pre-pandemic level (64.3% in February 2020) in every month since February 2023. While the share of young college graduates who are neither employed nor enrolled in further schooling is lower relative to the pre-pandemic peak, there is a mild long-run upward trend in this share since 1989. Young people can be “idled” for many reasons, including caring for children (or other family members) or having a disability. “Idled” young adults lose vital work experience and further education, which translates to compounding losses in their lifetime earnings.

Next, we narrow the sample of young college graduates to those not currently enrolled in further schooling to assess the labor market for those looking to make work their primary activity. Figure A presents unemployment and underemployment rates for young college graduates, both of which shot up during the Great Recession and the pandemic economic shock. The unemployment rate reflects the share of the young college graduate population who are jobless yet have reported that they are actively seeking work. Unemployment rates for college graduates recovered nearly three times faster after the pandemic (3.3 years, February 2020 to June 2023) than after the Great Recession (8.5 years, December 2007 to May 2016).

Figure A also shows that the underemployment rate for young college graduates recovered in just 2.25 years after the onset of the pandemic (February 2020 to May 2022) but never fully recovered after the Great Recession. This rate includes the unemployed plus “involuntary” part-timers (those who work part-time but want full-time work) and “marginally attached” workers (those who want a job and have looked for work in the last year but have given up actively seeking work in the last four weeks and therefore are not captured in the official unemployment rate). Strikingly, both the unemployment and underemployment rates of young college graduates have never returned to their low points in the tight labor market in 2000.

Figure A

Young college graduates recovered much faster in pandemic business cycle compared with the Great Recession: Unemployment and underemployment for college graduates (ages 21–24) not enrolled in further schooling, 2000–2024

Unemployment rate Underemployment rate
Jan-2000 5.10% 7.66%
Feb-2000 5.19% 7.63%
Mar-2000 5.42% 7.85%
Apr-2000 5.44% 7.94%
May-2000 5.44% 8.04%
Jun-2000 5.26% 7.93%
Jul-2000 5.03% 7.78%
Aug-2000 4.88% 7.52%
Sep-2000 4.71% 7.36%
Oct-2000 4.50% 7.21%
Nov-2000 4.35% 7.08%
Dec-2000 4.28% 6.95%
Jan-2001 4.28% 6.94%
Feb-2001 4.17% 6.93%
Mar-2001 4.06% 6.90%
Apr-2001 4.09% 6.92%
May-2001 4.14% 6.92%
Jun-2001 4.23% 7.16%
Jul-2001 4.34% 7.29%
Aug-2001 4.89% 8.03%
Sep-2001 5.43% 8.65%
Oct-2001 5.54% 8.98%
Nov-2001 5.77% 9.25%
Dec-2001 5.90% 9.40%
Jan-2002 5.91% 9.49%
Feb-2002 6.13% 9.87%
Mar-2002 6.20% 9.89%
Apr-2002 6.26% 10.11%
May-2002 6.29% 10.16%
Jun-2002 6.24% 10.05%
Jul-2002 6.31% 10.14%
Aug-2002 6.07% 9.71%
Sep-2002 5.84% 9.48%
Oct-2002 5.86% 9.28%
Nov-2002 5.73% 9.10%
Dec-2002 5.74% 9.22%
Jan-2003 5.96% 9.56%
Feb-2003 5.98% 9.49%
Mar-2003 6.06% 9.76%
Apr-2003 6.09% 9.80%
May-2003 6.12% 10.02%
Jun-2003 6.22% 10.29%
Jul-2003 6.32% 10.54%
Aug-2003 6.37% 10.74%
Sep-2003 6.25% 10.68%
Oct-2003 6.38% 11.02%
Nov-2003 6.48% 11.31%
Dec-2003 6.42% 11.32%
Jan-2004 6.26% 11.28%
Feb-2004 6.23% 11.43%
Mar-2004 6.35% 11.52%
Apr-2004 6.29% 11.50%
May-2004 6.13% 11.26%
Jun-2004 6.24% 11.20%
Jul-2004 5.97% 10.89%
Aug-2004 5.72% 10.68%
Sep-2004 5.68% 10.68%
Oct-2004 5.56% 10.62%
Nov-2004 5.71% 10.52%
Dec-2004 5.92% 10.65%
Jan-2005 6.07% 10.66%
Feb-2005 6.13% 10.60%
Mar-2005 5.91% 10.43%
Apr-2005 5.93% 10.54%
May-2005 6.02% 10.65%
Jun-2005 5.75% 10.37%
Jul-2005 5.98% 10.47%
Aug-2005 6.13% 10.64%
Sep-2005 6.14% 10.55%
Oct-2005 6.05% 10.43%
Nov-2005 5.81% 10.33%
Dec-2005 5.48% 10.04%
Jan-2006 5.26% 9.83%
Feb-2006 5.13% 9.74%
Mar-2006 5.09% 9.59%
Apr-2006 4.90% 9.25%
May-2006 4.76% 9.07%
Jun-2006 4.88% 9.20%
Jul-2006 4.84% 9.22%
Aug-2006 4.77% 8.95%
Sep-2006 4.71% 8.83%
Oct-2006 4.83% 8.85%
Nov-2006 4.81% 8.77%
Dec-2006 4.99% 8.90%
Jan-2007 4.99% 9.01%
Feb-2007 4.96% 8.77%
Mar-2007 4.93% 8.73%
Apr-2007 5.07% 8.82%
May-2007 5.15% 8.88%
Jun-2007 5.17% 8.94%
Jul-2007 5.15% 9.04%
Aug-2007 5.24% 9.16%
Sep-2007 5.46% 9.51%
Oct-2007 5.48% 9.46%
Nov-2007 5.62% 9.61%
Dec-2007 5.52% 9.55%
Jan-2008 5.58% 9.30%
Feb-2008 5.57% 9.43%
Mar-2008 5.56% 9.35%
Apr-2008 5.50% 9.45%
May-2008 5.54% 9.59%
Jun-2008 5.54% 9.84%
Jul-2008 5.70% 9.94%
Aug-2008 5.77% 10.11%
Sep-2008 5.70% 10.01%
Oct-2008 5.78% 10.13%
Nov-2008 5.75% 10.30%
Dec-2008 5.93% 10.66%
Jan-2009 6.17% 11.24%
Feb-2009 6.52% 11.76%
Mar-2009 6.88% 12.56%
Apr-2009 7.16% 13.03%
May-2009 7.44% 13.41%
Jun-2009 7.80% 13.89%
Jul-2009 7.92% 14.31%
Aug-2009 8.27% 15.11%
Sep-2009 8.43% 15.68%
Oct-2009 8.68% 16.25%
Nov-2009 8.90% 16.73%
Dec-2009 9.07% 17.21%
Jan-2010 9.15% 17.47%
Feb-2010 9.19% 17.70%
Mar-2010 9.16% 17.61%
Apr-2010 9.29% 17.84%
May-2010 9.29% 17.99%
Jun-2010 9.32% 18.05%
Jul-2010 9.49% 18.25%
Aug-2010 9.38% 17.78%
Sep-2010 9.37% 17.98%
Oct-2010 9.36% 18.07%
Nov-2010 9.48% 18.09%
Dec-2010 9.58% 18.17%
Jan-2011 9.74% 18.35%
Feb-2011 9.80% 18.37%
Mar-2011 9.89% 18.54%
Apr-2011 9.75% 18.29%
May-2011 9.67% 18.15%
Jun-2011 9.73% 18.23%
Jul-2011 9.89% 18.42%
Aug-2011 9.93% 18.89%
Sep-2011 9.88% 18.67%
Oct-2011 9.79% 18.49%
Nov-2011 9.53% 18.36%
Dec-2011 9.34% 17.94%
Jan-2012 9.15%  17.74% 
Feb-2012 8.96% 17.64%
Mar-2012 8.67% 17.47%
Apr-2012 8.72% 17.45%
May-2012 8.73% 17.35%
Jun-2012 8.51% 17.19%
Jul-2012 8.27% 17.13%
Aug-2012 8.18% 16.98%
Sep-2012 8.00% 16.95%
Oct-2012 7.85% 16.72%
Nov-2012 7.89% 16.56%
Dec-2012 8.00% 16.82%
Jan-2013 8.02% 16.76%
Feb-2013 8.09% 16.77%
Mar-2013 8.24% 16.78%
Apr-2013 8.21% 16.89%
May-2013 8.25% 17.12%
Jun-2013 8.33% 17.08%
Jul-2013 8.29% 16.91%
Aug-2013 8.43% 16.84%
Sep-2013 8.59% 16.90%
Oct-2013 8.64% 17.09%
Nov-2013 8.62% 17.11%
Dec-2013 8.59% 16.87%
Jan-2014 8.61% 16.94%
Feb-2014 8.58% 16.84%
Mar-2014 8.47% 16.75%
Apr-2014 8.23% 16.38%
May-2014 8.01% 15.99%
Jun-2014 7.86% 15.90%
Jul-2014 7.88% 15.77%
Aug-2014 7.64% 15.40%
Sep-2014 7.64% 15.14%
Oct-2014 7.71% 15.09%
Nov-2014 7.64% 15.05%
Dec-2014 7.51% 15.12%
Jan-2015 7.38% 14.98%
Feb-2015 7.34% 15.05%
Mar-2015 7.24% 14.89%
Apr-2015 7.31% 14.85%
May-2015 7.29% 14.89%
Jun-2015 7.01% 14.50%
Jul-2015 6.73% 14.15%
Aug-2015 6.62% 14.09%
Sep-2015 6.55% 14.07%
Oct-2015 6.36% 13.82%
Nov-2015 6.23% 13.52%
Dec-2015 6.01% 13.19%
Jan-2016 5.82% 12.93%
Feb-2016 5.64% 12.47%
Mar-2016 5.58% 12.30%
Apr-2016 5.55% 12.30%
May-2016 5.46% 12.27%
Jun-2016 5.65% 12.45%
Jul-2016 5.54% 12.37%
Aug-2016 5.59% 12.27%
Sep-2016 5.42% 12.10%
Oct-2016 5.44% 12.09%
Nov-2016 5.44% 11.91%
Dec-2016 5.49% 11.88%
Jan-2017 5.56% 11.83%
Feb-2017 5.62% 11.83%
Mar-2017 5.65% 11.68%
Apr-2017 5.63% 11.57%
May-2017 5.61% 11.37%
Jun-2017 5.53% 11.14%
Jul-2017 5.64% 11.22%
Aug-2017 5.52% 11.32%
Sep-2017 5.68% 11.40%
Oct-2017 5.68% 11.36%
Nov-2017 5.60% 11.42%
Dec-2017 5.49% 11.27%
Jan-2018 5.48% 11.31%
Feb-2018 5.33%  11.17%
Mar-2018 5.37% 11.31%
Apr-2018 5.32% 11.34%
May-2018 5.45% 11.69%
Jun-2018 5.50% 11.67%
Jul-2018 5.38% 11.48%
Aug-2018 5.42% 11.24%
Sep-2018 5.36% 10.99%
Oct-2018 5.37% 10.84%
Nov-2018 5.50% 10.87%
Dec-2018 5.70% 10.91%
Jan-2019 5.64% 10.62%
Feb-2019 5.62% 10.58%
Mar-2019 5.57% 10.61%
Apr-2019 5.59% 10.54%
May-2019 5.61% 10.35%
Jun-2019 5.56% 10.35%
Jul-2019 5.80% 10.40%
Aug-2019 5.85% 10.33%
Sep-2019 5.85% 10.35%
Oct-2019 5.74% 10.40%
Nov-2019 5.59% 10.14%
Dec-2019 5.47% 10.16%
Jan-2020 5.49% 10.20%
Feb-2020 5.54% 10.36%
Mar-2020 5.52% 10.11%
Apr-2020 6.60% 11.58%
May-2020 7.40% 12.64%
Jun-2020 8.68% 14.18%
Jul-2020 9.65% 15.66%
Aug-2020 10.19% 16.75%
Sep-2020 10.42% 17.31%
Oct-2020 10.61% 17.62%
Nov-2020 10.85% 18.21%
Dec-2020 11.21% 18.65%
Jan-2021 11.52% 19.17%
Feb-2021 11.87% 19.54%
Mar-2021 12.10% 19.92%
Apr-2021 11.33% 18.70%
May-2021 10.76% 17.92%
Jun-2021 9.79% 16.71%
Jul-2021 8.90% 15.50%
Aug-2021 8.42% 14.58%
Sep-2021 8.17% 13.90%
Oct-2021 8.09% 13.47%
Nov-2021 7.99% 13.06%
Dec-2021 7.60% 12.46%
Jan-2022 7.26% 11.97%
Feb-2022 6.89% 11.44%
Mar-2022 6.70% 11.12%
Apr-2022 6.55% 10.96%
May-2022 6.26% 10.44%
Jun-2022 6.22% 10.33% 
Jul-2022 6.11% 10.09%
Aug-2022 5.89% 9.96%
Sep-2022 5.90% 10.04%
Oct-2022 5.80% 9.98%
Nov-2022 5.77% 9.91%
Dec-2022 5.79% 9.79%
Jan-2023 5.77% 9.67%
Feb-2023 5.74% 9.83%
Mar-2023 5.78% 9.82%
Apr-2023 5.66% 9.81%
May-2023 5.61% 9.85%
Jun-2023 5.39% 9.63%
Jul-2023 5.35% 9.64%
Aug-2023 5.52% 9.72%
Sep-2023 5.58% 9.87%
Oct-2023 5.68% 10.09%
Nov-2023 5.83% 10.25%
Dec-2023 5.81% 10.39%
Jan-2024 5.79% 10.34%
Feb-2024 5.92% 10.30%
Mar-2024 5.99%  10.26% 
ChartData Download data

The data below can be saved or copied directly into Excel.

Notes: This series is based on 12-month moving averages. The most recent data point uses pooled data from April 2023 through March 2024. Data sample includes only those college graduates ages 21–24 who have not attained an advanced degree and who are not enrolled in further schooling. Shaded areas indicate recessions.

Source: EPI analysis of the Current Population Survey basic monthly microdata, EPI Current Population Survey Extracts, Version 1.0.51 (2024), https://microdata.epi.org

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However, gaps in unemployment and underemployment rates remain significant between Black, Hispanic, and Asian American and Pacific Islander (AAPI) graduates and their white counterparts, as shown in Figure B. In the 36 months ending in March 2024, the unemployment rate for white graduates was 5.1%, much lower than for AAPI (8.7%), Black (8.0%), and Hispanic (7.6%) graduates. White graduates’ underemployment rates were also well below their Black, Hispanic, and AAPI counterparts. These gaps point to ongoing discrimination and unequal access to job opportunities.

Figure B

Black, Hispanic, and AAPI college graduates face higher unemployment and underemployment rates: Unemployment and underemployment rates for young workers ages 21–24 with a college degree and who are not enrolled, by race/ethnicity, March 2024

White Black Hispanic AAPI
Unemployment rate 5.1% 8.0% 7.6% 8.7%
Underemployment rate 8.7% 14.6% 13.1% 12.9%
ChartData Download data

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Notes: Data represent an average of the 36 months ending in March 2024. AAPI refers to Asian American and Pacific Islander. Race and ethnicity categories are mutually exclusive (i.e., white non-Hispanic, Black non-Hispanic, AAPI non-Hispanic, and Hispanic any race).

Source: EPI analysis of the Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.51 (2024), https://microdata.epi.org

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Young college graduates have experienced real (inflation-adjusted) wage growth for the first time this early in a recovery compared with the prior three business cycles. Figure C shows that real wage growth (even after accounting for unusually fast inflation) between February 2020 and March 2024 was 2.2% for young college graduates. By comparison, young college graduates faced outright wage losses of 4.9% after the Great Recession, 4.3% in 2001–2005, and 7.5% in 1990–1994. This means that real wage growth in the pandemic business cycle was 7.1 percentage points faster than in the aftermath of the Great Recession, 6.5 percentage points faster than in 2001–2005, and 9.7 percentage points faster than in 1990–1994. 

Figure C

Young workers have experienced strongest wage growth in the pandemic business cycle: Real wage changes for college graduates four years from prior peak, in current and last three business cycles

College graduates, 21-24
Jul 1990 – 
Aug 1994
-7.5%
Mar 2001 –
Apr 2005
-4.3%
Dec 2007 –
Jan 2012
-4.9%
Feb 2020 –
Mar 2024
2.2%
ChartData Download data

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Notes: Each month represents a 12-month moving average leading up to that month; for instance, March 2024 represents the average value from April 2023 to March 2024. Data sample includes only those college graduates ages 21–24 who have not attained an advanced degree and who are not enrolled in further schooling.

Source: EPI analysis of the Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.51 (2024), https://microdata.epi.org

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Despite this positive wage growth, racial and gender wage gaps remain large even among young college graduates who are just starting their careers. Figure D shows that women are paid $5.30 less per hour than their male counterparts, while Black and Hispanic workers are paid $3.24 and $2.07 less per hour, respectively, than white workers. This translates to women being paid, on average, 82.7% of their male counterpart’s wages and Black and Hispanic workers being paid, on average, 86.7% and 91.8% of white workers’ wages.

Figure D

Gender and racial wage gaps are wide among young college graduates: Average real wages for workers ages 21–24 with a college degree and who are not enrolled, by gender and race/ethnicity, March 2024

Demographic Wage
College $27.57
Women $25.34
Men $30.64
White $27.51
Black $24.27
Hispanic $25.44
AAPI $33.77
ChartData Download data

The data below can be saved or copied directly into Excel.

Notes: Data represent an average of the 36 months ending in March 2024. AAPI refers to Asian American and Pacific Islander. Race and ethnicity categories are mutually exclusive (i.e., white non-Hispanic, Black non-Hispanic, AAPI non-Hispanic, and Hispanic any race).

Source: EPI analysis of the Current Population Survey Outgoing Rotation Group microdata, EPI Current Population Survey Extracts, Version 1.0.51 (2024), https://microdata.epi.org

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These findings highlight the tremendous role that large fiscal relief and recovery packages, including expanded unemployment insurance coverage and aid to state and local governments, had on healing the labor market after the pandemic recession. Unlike previous business cycles, young workers were not left behind by policy. However, to ensure that these gains are fully realized and that racial and gender wage gaps are addressed, policymakers must prioritize full employment, increase the federal minimum wage, strengthen and enforce labor standards, and make it easier for workers to come together and form unions.

Note

1. Notes about our data sample: Because we are examining such a small subset of the population, we pool 12 or 36 months of data to increase the sample size and mitigate some of the volatility in the series. Unless otherwise specified, when looking at “overall” trends in the data, we pool 12 months of data to create a pooled moving average, which also has the added advantage of removing any seasonal effects. We use 36-month pooled data to look at trends by gender and race/ethnicity, since breaking the population down by demographics reduces sample size and data reliability.