Content
RAND Epstein Family Veterans Policy Research Institute
Jul 15, 2021
U.S. Army Spc. Sydney Buehler, an Army cannon crewmember with 3rd Infantry Division, attends a national job fair at Fort Stewart, Georgia. The fair was open to transitioning service members, military spouses, veterans, retirees, and their families.
Photo by Sgt. Jose Escamilla/U.S. Army
Newly separated service members face unique challenges as they enter the civilian labor market, so how can they manage their expectations during this critical period? Trends in veterans' employment since the Great Recession reflect some persistent patterns and some significant changes. A better understanding of veterans' employment support needs and how economic shocks affect veterans and nonveterans differently can help veterans, employers, policymakers, and veteran-serving organizations prepare for future disruptions and uncertainty.
Every year since 2009, an average of 180,000 active-duty service members have separated from the U.S. military (Bradbard and Maury, 2021). Many of these new veterans enter the civilian labor market, where they face challenges like other civilian workers. Today, those challenges include an economy that is still recovering from the "COVID recession." Historically, workers who enter the labor market during an economic downturn earn lower wages and experience higher unemployment rates, with the effects lasting for years or decades (Kahn, 2010; Schwandt and von Wachter, 2019; Rothstein, 2021). Both new veterans and nonveterans in this situation are at a disadvantage (Gutierrez and Wenger, 2017).
However, for new veterans, the difficulties transitioning from military to civilian life can compound the challenges of a weak economy. New veterans must make a variety of decisions beyond where to work—such as how to obtain health care, whether to pursue additional education, and where to move as they restart their civilian lives. Some veterans are also managing service-related injuries or posttraumatic stress disorder (PTSD), with a need to navigate their eligibility for U.S. Department of Veterans Affairs (VA) disability compensation and other benefits. Each of these factors can affect a veteran's civilian career opportunities.
On top of these questions, veterans seeking jobs must create a résumé and figure out how to market their military experience to potential civilian employers—a process that many are undertaking for the first time. Moreover, the training that service members receive in the military does not necessarily prepare them for a civilian career. For example, former infantry members who specialized in handling and firing mortars might find it difficult to explain to employers how this skill set translates to a particular civilian job. For this reason, the skill-matching process that is fairly straightforward for nonveterans is an added concern for many veterans. Reflecting these collective disadvantages, in a 2015 survey of 8,500 new veterans, 55 percent reported that finding a job was a significant challenge (Zoli, Maury, and Fay, 2015).
Given the various economic headwinds, how have new veterans fared in the labor market since the pandemic? And what can they expect during the next recession, whenever it may be? The next recession might be different from the two most recent economic crises—the Great Recession of 2007–2009 and COVID-19 pandemic that began in 2020. Historical trends reveal critical factors that should be monitored and analyzed going forward. In this Perspective, we analyze how veterans fared relative to nonveterans during these two most recent recessions to better understand how veterans might prepare for the next one. Finally, we highlight several unanswered questions that policymakers, veterans-serving organizations, and researchers should address to better prepare and support veterans as they transition to the civilian labor market.
Pressing Issues
Prior Research Only Partially Explains Historical Variations in Veterans' Unemployment Rates
Much prior research on veterans in the labor market focused on the aftermath of the Great Recession. During that recession, veterans overall had lower unemployment rates than their nonveteran counterparts, but new veterans—those who had served in the post-9/11 era—were the exception (Faberman and Foster, 2013). For recent veterans, unemployment rates peaked at 13.9 percent, compared with 9.2 percent for nonveterans and 7.9 percent for older veterans (Faberman and Foster, 2013; Heaton and Krull, 2012). By 2017, the gap for new veterans had narrowed but had not disappeared (Faberman and Haasl, 2018).
Nonetheless, veterans with jobs tended to earn more than nonveterans, and this was true even in the years prior to the Great Recession (Humensky et al., 2013). As of 2016, new veterans earned 16 percent more than nonveterans (Faberman and Haasl, 2018). This earnings gap was uneven, however: Veterans with a high school diploma outearned their peers, but those with some college did not (Kleykamp, 2013).
To develop effective policies and programs to assist future veterans in their job transitions, it is critical to identify the reasons for veteran-nonveteran employment and earnings gaps. Two major explanations have been proposed—demographic differences between veterans and nonveterans and a mismatch between military skills acquired and the skills required for civilian jobs—but neither offers a complete explanation.
Military-to-Civilian Transitions Pose Unique Challenges for New Veterans, but the Research on Veterans' Employment Transitions Is Fairly Recent
Matching veterans' skills to civilian labor market needs is a challenge because some military skill sets—particularly in combat arms and infantry—do not have natural civilian analogues. Indeed, recently released data from the Army show that infantry veterans have a harder time finding civilian employment (McEntarfer, 2020). Those who found jobs took one of two common paths: retail (a low-income industry) or professional services (a high-income industry). These patterns suggest that there might be room to improve earnings for both new veterans and already employed veterans by better targeting their skills to higher-earning occupations.
Industry and occupation do not reflect all the skills required for a particular job. "Hard" skills, such as the ability to use a particular tool, might be required to perform a job properly. But surveys of employers have revealed that they also value "soft skills" that veterans tend to possess, such as leadership, diligence, and tolerance for stress (Hall et al., 2014). However, there have been no systematic studies of how soft skills contribute to or mitigate job mismatch among veterans (Schulker, 2017).
Despite the lack of consensus regarding the extent and importance of skill mismatch, it is thought to be a major ongoing barrier in veterans' job searches, and several resources have been developed to assist veterans in marketing their skills after they leave the military (Bradbard and Maury, 2021). For example, the U.S. Department of Labor's My Next Move site has a page specifically for veterans that provides specific skill breakdowns by military occupation code to assist new veterans in identifying civilian jobs that use the same skills (U.S. Department of Labor, 2022).
A lesson from the Great Recession was that new veterans had a difficult time finding civilian employment, but those who did find jobs generally received good pay. It is clear that there is no single explanation for these trends. More research would help shed more light on why veterans and nonveterans—and new veterans and older veterans—have such different experiences.
Two Recent Recessions Show Very Different Patterns for Veterans' Earnings and Employment, Making It Difficult to Forecast Future Trends
Not all lessons from the Great Recession were relevant to the economic downturn associated with the COVID-19 pandemic. We extended earlier work comparing new veterans' and nonveterans' unemployment rates and earnings through mid-2022, using data from the U.S. Census Bureau's Current Population Survey (CPS) (Flood et al, 2022; Ruggles et al., 2022). The CPS tracks labor market trends and is the same dataset used by most prior studies. The survey is representative of the general population at both the national and state levels and captures data on 60,000 households over a period of 16 months (U.S. Census Bureau, 2019).
We used the months just prior to each recession as a benchmark: January 2020 for the pandemic recession and November 2007 for the Great Recession. This allowed us to analyze which subgroups were most vulnerable to the eventual economic downturn and why. Table A.1 in the appendix describes the characteristics of the CPS sample as of each date. The table illustrates patterns documented in prior research: A greater proportion of veterans are men, White, and have at least a high school diploma. Veterans are also older than nonveterans, on average.
Furthermore, the data also shows that the characteristics of veterans changed in the 13 years between the two recessions. Women, Black, and Hispanic veterans now make up a larger share of the veteran population, and veterans are now more likely to have a college or graduate degree. These changes are due entirely to new cohorts of post-9/11 service members who have separated from the military since the Great Recession.
Figure 1 shows unemployment rates before and during each recession. The top portion of the figure echoes prior research: During the Great Recession, veterans as a whole had lower unemployment rates than nonveterans, but new veterans had higher unemployment rates. That was true even in the year leading up to the recession. (We note, however, that the line for new veterans is noisier than the others because that sample size is much smaller.)
The lower portion of the figure shows that the opposite was true during the COVID-19 pandemic. In the year leading up to the pandemic, new veterans had unemployment rates that were comparable to those of nonveterans. After unemployment spiked in March 2020, new veterans' unemployment rates did not rise as high as nonveterans' rates. The unemployment rate for nonveterans peaked at 14.5 percent, compared with 12.1 percent for all veterans and 12.9 percent for new veterans in April 2020. As the economy recovered over the next two years, veterans' unemployment rates generally remained lower through the summer of 2022.
Figure 1. Unemployment Patterns Before and During the Great Recession and COVID-19 Pandemic
Great Recession
| Month | All veterans | Nonveterans | Post-9/11 veterans |
|---|---|---|---|
| Jan 2006 | 5% | 5% | 9% |
| Feb 2006 | 4% | 5% | 7% |
| Mar 2006 | 4% | 5% | 7% |
| Apr 2006 | 4% | 4% | 6% |
| May 2006 | 3% | 4% | 5% |
| Jun 2006 | 3% | 5% | 7% |
| Jul 2006 | 4% | 5% | 7% |
| Aug 2006 | 3% | 5% | 6% |
| Sep 2006 | 3% | 4% | 4% |
| Oct 2006 | 4% | 4% | 7% |
| Nov 2006 | 4% | 4% | 7% |
| Dec 2006 | 4% | 4% | 6% |
| Jan 2007 | 4% | 5% | 8% |
| Feb 2007 | 4% | 5% | 6% |
| Mar 2007 | 4% | 4% | 4% |
| Apr 2007 | 4% | 4% | 4% |
| May 2007 | 3% | 4% | 5% |
| Jun 2007 | 3% | 4% | 8% |
| Jul 2007 | 4% | 5% | 5% |
| Aug 2007 | 3% | 5% | 5% |
| Sep 2007 | 3% | 4% | 6% |
| Oct 2007 | 3% | 4% | 5% |
| Nov 2007 | 4% | 4% | 7% |
| Dec 2007 | 5% | 5% | 11% |
| Jan 2008 | 5% | 5% | 8% |
| Feb 2008 | 4% | 5% | 8% |
| Mar 2008 | 4% | 5% | 7% |
| Apr 2008 | 4% | 5% | 6% |
| May 2008 | 4% | 5% | 9% |
| Jun 2008 | 4% | 5% | 10% |
| Jul 2008 | 4% | 6% | 8% |
| Aug 2008 | 4% | 6% | 5% |
| Sep 2008 | 5% | 6% | 8% |
| Oct 2008 | 5% | 6% | 8% |
| Nov 2008 | 5% | 6% | 6% |
| Dec 2008 | 7% | 7% | 10% |
| Jan 2009 | 7% | 8% | 10% |
| Feb 2009 | 8% | 9% | 13% |
| Mar 2009 | 9% | 9% | 11% |
| Apr 2009 | 8% | 9% | 11% |
| May 2009 | 8% | 9% | 12% |
| Jun 2009 | 8% | 10% | 10% |
| Jul 2009 | 8% | 10% | 10% |
| Aug 2009 | 7% | 9% | 12% |
| Sep 2009 | 8% | 9% | 11% |
| Oct 2009 | 8% | 9% | 13% |
| Nov 2009 | 8% | 9% | 11% |
| Dec 2009 | 8% | 10% | 9% |
COVID-19 Pandemic
| Month | All veterans | Nonveterans | Post-9/11 veterans |
|---|---|---|---|
| Jan 2019 | 4% | 4% | 4% |
| Feb 2019 | 3% | 4% | 4% |
| Mar 2019 | 3% | 4% | 3% |
| Apr 2019 | 2% | 3% | 2% |
| May 2019 | 3% | 3% | 3% |
| Jun 2019 | 3% | 4% | 4% |
| Jul 2019 | 3% | 4% | 4% |
| Aug 2019 | 4% | 4% | 4% |
| Sep 2019 | 3% | 3% | 4% |
| Oct 2019 | 3% | 3% | 3% |
| Nov 2019 | 3% | 3% | 5% |
| Dec 2019 | 3% | 3% | 3% |
| Jan 2020 | 3% | 4% | 5% |
| Feb 2020 | 4% | 4% | 5% |
| Mar 2020 | 4% | 4% | 4% |
| Apr 2020 | 12% | 14% | 13% |
| May 2020 | 9% | 13% | 10% |
| Jun 2020 | 9% | 11% | 10% |
| Jul 2020 | 8% | 10% | 7% |
| Aug 2020 | 6% | 8% | 7% |
| Sep 2020 | 6% | 8% | 7% |
| Oct 2020 | 5% | 7% | 7% |
| Nov 2020 | 6% | 6% | 7% |
| Dec 2020 | 5% | 6% | 5% |
| Jan 2021 | 5% | 7% | 7% |
| Feb 2021 | 5% | 7% | 6% |
| Mar 2021 | 5% | 6% | 6% |
| Apr 2021 | 5% | 6% | 5% |
| May 2021 | 4% | 6% | 4% |
| Jun 2021 | 5% | 6% | 5% |
| Jul 2021 | 4% | 6% | 4% |
| Aug 2021 | 4% | 5% | 3% |
| Sep 2021 | 4% | 5% | 3% |
| Oct 2021 | 4% | 4% | 4% |
| Nov 2021 | 4% | 4% | 5% |
| Dec 2021 | 3% | 4% | 5% |
| Jan 2022 | 4% | 4% | 5% |
| Feb 2022 | 3% | 4% | 3% |
| Mar 2022 | 2% | 4% | 3% |
| Apr 2022 | 3% | 3% | 4% |
| May 2022 | 3% | 3% | 3% |
| Jun 2022 | 3% | 4% | 3% |
| Jul 2022 | 3% | 4% | 4% |
| Aug 2022 | 2% | 4% | 2% |
| Sep 2022 | 3% | 3% | 2% |
SOURCE: Calculated from CPS data (Flood et al., 2022; Ruggles et al., 2022).
NOTE: Unemployment rates are calculated for individuals age 18 and older and are not seasonally adjusted.
These patterns continued through the end of 2022, although the unemployment gap narrowed. According to the U.S. Bureau of Labor Statistics (BLS), post-9/11 veterans still had a 7-percent lower unemployment rate than nonveterans as of December 2022 (BLS, 2023). New veterans also participated in the labor force at substantially higher rates: 80.2 percent, compared with 64.5 percent for nonveterans.
The earnings differential between veterans and nonveterans, unlike the unemployment rate, remained largely consistent between the two recessions. Veterans' earnings (among those who worked full time) remained roughly 20-percent higher than nonveterans' earnings through both the Great Recession and the COVID-19 pandemic. This suggests that veterans who stayed employed through these crises consistently brought skills that were highly valued. The primary difference between the two recessions was that average earnings declined after the Great Recession—and for veterans more so than for nonveterans. But during the pandemic, earnings rose rather than declined, partly because lower-earning workers were more likely to have lost their jobs (Kochhar and Bennett, 2021).
In accordance with prior research, we examined whether differences in demographic characteristics explain differences in labor market outcomes for veterans and nonveterans. Age and marital status can explain the differences, but that is because veterans tend to be older than nonveterans. As noted above, younger veterans have lower unemployment rates than nonveterans of the same age. This all suggests that we must seek non-demographic factors that can explain the labor market performance of veterans.
Veteran-Heavy Industries Were Disproportionately Affected by the Great Recession but Not the Pandemic
What explains the different patterns in new veterans' unemployment rates during the Great Recession versus the pandemic? It may be partly attributable to the industries in which veterans and nonveterans worked. Veterans tended to work in industries that were relatively insulated from the pandemic but not from the Great Recession.
Table 1 shows the five most common industries in which veterans and nonveterans worked just prior to the start of the Great Recession (upper panel) and the pandemic (lower panel). Just before the Great Recession hit (August–November 2007), three of the top five industries for veterans and nonveterans were the same: education and health services, professional and business services, and manufacturing. By 2019, just before the COVID-19 pandemic (October 2019–January 2020), the same three industries plus retail accounted for four of the top five industries for both groups.
Table 1. Top Public- and Private-Sector Industries for Veterans and Nonveterans
August–November 2007
| Rank | Veterans | Nonveterans | ||
|---|---|---|---|---|
| Industry | Share of Total Veteran Employment (%) | Industry | Share of Total Nonveteran Employment (%) | |
| 1 | Manufacturing | 16.1 | Education and health services | 23.5 |
| 2 | Education and health services | 12.8 | Manufacturing | 11.9 |
| 3 | Public administration | 10.8 | Retail trade | 11.3 |
| 4 | Professional and business services | 10.4 | Professional and business services | 9.7 |
| 5 | Transportation and warehousing | 10.2 | Leisure and hospitality | 8.4 |
October 2019–January 2020
| Rank | Veterans | Nonveterans | ||
|---|---|---|---|---|
| Industry | Share of Total Veteran Employment (%) | Industry | Share of Total Nonveteran Employment (%) | |
| 1 | Education and health services | 14.8 | Education and health services | 25.2 |
| 2 | Public administration | 14.6 | Professional and business services | 11.3 |
| 3 | Professional and business services | 12.8 | Retail trade | 10.7 |
| 4 | Manufacturing | 12.7 | Manufacturing | 10.4 |
| 5 | Retail trade | 8.9 | Leisure and hospitality | 8.9 |
SOURCE: CPS data (Flood et al., 2022; Ruggles et al., 2022).
NOTE: Statistics are based on individuals age 18 and older who were employed in the private or public sector at the time of the survey.
An important difference between veterans and nonveterans is the fifth industry rounding out each group's top 5 at the start of the pandemic: public administration for veterans and leisure and hospitality for nonveterans. This difference is important because leisure and hospitality was substantially more affected by the pandemic than public administration. Thus, veterans happened to be less exposed to the biggest declines in employment.
Figure 2 shows how each industry's employment level changed in the wake of the Great Recession and COVID-19 pandemic. The figure shows total employment in each industry, according to the Quarterly Census of Employment and Wages (QCEW) (BLS, 2022c). The QCEW is a near-full count of employment across all sectors in the United States, collecting data on upwards of 95 percent of all jobs that are covered under unemployment insurance (BLS, 2022b). The figure shows employment in each of the industries listed in Table 1, indexed to pre-pandemic employment levels.
Figure 2. Employment Levels in Top Veteran and Nonveteran Industries
Great Recession
Employment level measured relative to November 2007
| Month | Manufacturing | Education and health services | Retail trade | Professional and business services | Leisure and hospitality | Public administration |
|---|---|---|---|---|---|---|
| Jan 2006 | 102 | 94 | 95 | 93 | 93 | 97 |
| Feb 2006 | 102 | 96 | 93 | 94 | 94 | 97 |
| Mar 2006 | 103 | 96 | 94 | 95 | 96 | 98 |
| Apr 2006 | 103 | 96 | 94 | 96 | 98 | 98 |
| May 2006 | 103 | 96 | 95 | 96 | 100 | 99 |
| Jun 2006 | 104 | 94 | 96 | 98 | 103 | 101 |
| Jul 2006 | 103 | 87 | 95 | 97 | 103 | 101 |
| Aug 2006 | 103 | 88 | 96 | 98 | 103 | 101 |
| Sep 2006 | 103 | 95 | 95 | 98 | 101 | 99 |
| Oct 2006 | 102 | 97 | 96 | 98 | 99 | 99 |
| Nov 2006 | 102 | 98 | 99 | 98 | 98 | 99 |
| Dec 2006 | 102 | 98 | 101 | 98 | 98 | 98 |
| Jan 2007 | 101 | 96 | 96 | 96 | 95 | 98 |
| Feb 2007 | 101 | 98 | 94 | 96 | 96 | 98 |
| Mar 2007 | 101 | 98 | 95 | 97 | 98 | 98 |
| Apr 2007 | 101 | 98 | 95 | 98 | 100 | 99 |
| May 2007 | 101 | 99 | 96 | 99 | 103 | 100 |
| Jun 2007 | 101 | 97 | 97 | 100 | 106 | 102 |
| Jul 2007 | 101 | 89 | 97 | 99 | 106 | 102 |
| Aug 2007 | 101 | 91 | 97 | 100 | 106 | 102 |
| Sep 2007 | 101 | 97 | 96 | 100 | 103 | 100 |
| Oct 2007 | 100 | 99 | 97 | 100 | 101 | 100 |
| Nov 2007 | 100 | 100 | 100 | 100 | 100 | 100 |
| Dec 2007 (recession) | 100 | 100 | 101 | 100 | 100 | 100 |
| Jan 2008 (recession) | 99 | 99 | 96 | 97 | 97 | 100 |
| Feb 2008 (recession) | 99 | 100 | 95 | 97 | 98 | 100 |
| Mar 2008 (recession) | 98 | 101 | 95 | 98 | 100 | 100 |
| Apr 2008 (recession) | 98 | 101 | 95 | 99 | 102 | 100 |
| May 2008 (recession) | 98 | 101 | 95 | 99 | 104 | 101 |
| Jun 2008 (recession) | 99 | 99 | 96 | 99 | 106 | 103 |
| Jul 2008 (recession) | 98 | 91 | 95 | 99 | 106 | 104 |
| Aug 2008 (recession) | 98 | 93 | 95 | 99 | 106 | 104 |
| Sep 2008 (recession) | 97 | 99 | 95 | 98 | 103 | 102 |
| Oct 2008 (recession) | 96 | 101 | 95 | 98 | 101 | 102 |
| Nov 2008 (recession) | 95 | 102 | 96 | 97 | 99 | 102 |
| Dec 2008 (recession) | 94 | 102 | 97 | 96 | 98 | 102 |
| Jan 2009 (recession) | 91 | 101 | 92 | 92 | 95 | 101 |
| Feb 2009 (recession) | 89 | 102 | 90 | 92 | 95 | 101 |
| Mar 2009 (recession) | 88 | 102 | 90 | 91 | 97 | 101 |
| Apr 2009 (recession) | 87 | 102 | 89 | 91 | 99 | 103 |
| May 2009 (recession) | 86 | 102 | 90 | 91 | 101 | 103 |
| Jun 2009 (recession) | 85 | 100 | 91 | 91 | 103 | 104 |
| Jul 2009 | 85 | 93 | 90 | 91 | 103 | 105 |
| Aug 2009 | 85 | 94 | 90 | 91 | 103 | 104 |
| Sep 2009 | 85 | 100 | 90 | 90 | 100 | 102 |
| Oct 2009 | 84 | 103 | 90 | 91 | 98 | 101 |
| Nov 2009 | 84 | 103 | 93 | 91 | 96 | 101 |
| Dec 2009 | 84 | 103 | 94 | 91 | 96 | 101 |
COVID-19 Pandemic
Employment level measured relative to January 2020
| Month | Manufacturing | Education and health services | Retail trade | Professional and business services | Leisure and hospitality | Public administration |
|---|---|---|---|---|---|---|
| Jan 2019 | 100 | 98 | 101 | 99 | 98 | 99 |
| Feb 2019 | 101 | 99 | 100 | 99 | 99 | 99 |
| Mar 2019 | 101 | 99 | 100 | 99 | 101 | 99 |
| Apr 2019 | 101 | 100 | 100 | 101 | 103 | 100 |
| May 2019 | 101 | 100 | 100 | 101 | 105 | 101 |
| Jun 2019 | 102 | 98 | 101 | 102 | 107 | 103 |
| Jul 2019 | 101 | 92 | 101 | 102 | 108 | 103 |
| Aug 2019 | 101 | 94 | 100 | 102 | 107 | 103 |
| Sep 2019 | 101 | 99 | 100 | 102 | 104 | 101 |
| Oct 2019 | 100 | 100 | 101 | 102 | 103 | 101 |
| Nov 2019 | 101 | 101 | 104 | 103 | 102 | 101 |
| Dec 2019 | 101 | 101 | 104 | 102 | 102 | 100 |
| Jan 2020 | 100 | 100 | 100 | 100 | 100 | 100 |
| Feb 2020 (recession) | 100 | 101 | 99 | 101 | 101 | 100 |
| Mar 2020 (recession) | 100 | 101 | 99 | 100 | 99 | 101 |
| Apr 2020 (recession) | 88 | 92 | 83 | 91 | 55 | 99 |
| May 2020 | 90 | 92 | 87 | 92 | 62 | 99 |
| Jun 2020 | 94 | 91 | 93 | 94 | 74 | 100 |
| Jul 2020 | 95 | 87 | 95 | 95 | 79 | 101 |
| Aug 2020 | 95 | 90 | 96 | 96 | 80 | 104 |
| Sep 2020 | 95 | 94 | 96 | 96 | 80 | 103 |
| Oct 2020 | 95 | 96 | 98 | 98 | 81 | 101 |
| Nov 2020 | 95 | 96 | 100 | 99 | 80 | 100 |
| Dec 2020 | 96 | 96 | 101 | 99 | 77 | 100 |
| Jan 2021 | 96 | 95 | 98 | 97 | 75 | 98 |
| Feb 2021 | 96 | 96 | 97 | 98 | 78 | 98 |
| Mar 2021 | 96 | 96 | 97 | 99 | 81 | 98 |
| Apr 2021 | 96 | 97 | 97 | 100 | 85 | 99 |
| May 2021 | 96 | 97 | 98 | 101 | 89 | 100 |
| Jun 2021 | 97 | 95 | 99 | 101 | 93 | 101 |
| Jul 2021 | 98 | 90 | 99 | 102 | 96 | 102 |
| Aug 2021 | 98 | 92 | 99 | 102 | 96 | 101 |
| Sep 2021 | 97 | 96 | 98 | 102 | 94 | 100 |
| Oct 2021 | 98 | 98 | 100 | 105 | 94 | 99 |
| Nov 2021 | 98 | 98 | 103 | 105 | 93 | 99 |
| Dec 2021 | 99 | 98 | 104 | 105 | 94 | 99 |
SOURCE: BLS, 2022c.
NOTE: Certain industries have annual cycles of employment, even in normal times, and those are reflected in the patterns for the Great Recession. For example, total employment in education and health services dips during the summer months (when school is out of session), whereas it rises in leisure and hospitality. We did not see these normal cycles in summer 2020, during the pandemic. Gray shading indicates the official dates of each recession, according to the National Bureau of Economic Research.
As Figure 2 shows, by 2009 the effects of the Great Recession had become clear, with sustained drops in employment in manufacturing, professional and business services, and retail. As Table 1 showed, veterans were more likely than nonveterans to be exposed to declines in manufacturing. Professional and business services also employed a slightly larger share of veterans than nonveterans, although nonveterans were disproportionately exposed to the decline in retail. When the pandemic began in March 2020, the retail and leisure and hospitality industries saw the largest immediate drops in employment. Nonveterans were most likely to be working in those industries. In contrast, public administration, which disproportionately employs veterans, saw virtually no change in employment.
Together, Table 1 and Figure 2 show that veterans' relative labor market performance can be partially explained by the jobs they chose. Veterans tended to be overexposed to the effects of the Great Recession but insulated from the economic shocks of the pandemic. These trends highlight the challenge of preparing for recessions and other economic crises and how they might affect veterans' employment opportunities and future earnings.
Can Veterans and Veteran-Serving Organizations Prepare for the Next Recession? Directions for Future Research
The Great Recession and the COVID-19 pandemic had different effects on new veterans and nonveterans. The two groups will likely weather the next crisis in different ways too. But will the next recession look more like the Great Recession or the pandemic? And what can current service members, veteran-serving organizations, and policymakers do to prepare?
The Next Recession Might Be Inflation-Driven, Like the Recession of the Early 1980s
Although unemployment did not rise quite as high for veterans as for nonveterans during the pandemic, it would be prudent to assume that this pattern is an anomaly rather than a new rule. The labor market patterns and underlying causes of the pandemic recession were unusual compared with earlier recessions: It was caused by a public health emergency, not by underlying economic forces. That led to an unusually large and sudden contraction in economic activity coupled with a relatively fast recovery (Wheelock, 2020). The actual recession lasted just two months, the shortest in U.S. history (Cox, 2021). Asset prices (such as home prices), the stock market, and GDP growth recovered unusually quickly. In addition, the unemployment rate dropped to pre-pandemic levels faster than expected, and employment rates for young workers showed fewer signs of long-term effects than has historically been the case (Forsythe, 2022). However, employment levels have not fully recovered for all groups (especially women), and data suggest that many workers have left the labor force altogether (Center on Budget and Policy Priorities, 2023).
The unusual pandemic recession has been followed by an equally unusual combination of new economic forces. Inflation has been at its highest in nearly 40 years, affecting the cost of living (BLS, 2022b). Rising interest rates (intended to rein in inflation) and the war in Ukraine have increased geopolitical instability, and another global recession looks increasingly likely (World Bank, 2022). Former Treasury Secretary Larry Summers described the outlook as the most "complex a set of macroeconomic challenges as at any time in 75 years" (Summers, 2022), though it is not necessarily the case that high inflation leads to a recession: Despite high inflation in 2022 and 2023, the economy is not showing signs of recession.
Historically, inflation-driven recessions, such as those in the 1970s and 1980s, have been shallower than other recessions in terms of declines in output (Shalett, 2022). Major banks predict that the next recession will be similar (Bhattarai, 2022). In this respect, the recession of the early 1980s—when the Federal Reserve raised interest rates to counter persistent inflation—might offer the best benchmark. Although that recession was short, it was also painful for workers: Unemployment reached double digits, and a broader swath of industries were affected than in the Great Recession or the pandemic: Manufacturing, services, the public sector, transportation, and retail all saw large declines in employment (Urquhart and Hewson, 1983).
The lesson is that relatively pandemic-immune industries may not be insulated from the next recession. The patterns that held in the wake of the Great Recession did not continue into the pandemic recession and the causes of the pandemic recession are quickly fading into history. The upshot is that veterans and the organizations and policies that support them must constantly adapt as the economy changes and labor market opportunities evolve.
Employment Projections Provide Guidance on Future Job Opportunities
For veterans entering the job market in the next decade, it may be prudent to consider projected growth when deciding where to live and what industry to enter. BLS creates employment projections based on longer-term economic trends showing how different industries are expected to grow or shrink ten years out (BLS, 2022a).
Figure 3 and Table A.2 in the appendix show projections for specific industries. Of the current top five veteran-employing industries, BLS projects that the number of jobs in manufacturing will decline slightly over the next ten years. Veterans in the Midwest and Pacific Northwest, where manufacturing is currently the top veteran-employing industry, will be most exposed to this negative growth.
Figure 3. Projected Employment Growth, 2021–2031
| Industry | Growth (%) |
|---|---|
| Construction | 2.8% |
| Education and health services | 12.9% |
| Financial activities | 3.8% |
| Information | 7.4% |
| Leisure and hospitality | 13.6% |
| Manufacturing | −1.1% |
| Natural resources and mining | 2.9% |
| Professional and business services | 7.3% |
| Public administration | 1.8% |
| Retail trade | −2.2% |
| Transportation and warehousing | 7.7% |
| Utilities | −6.4% |
| Wholesale trade | 2.4% |
| All other (including unknown) | 8.6% |
SOURCE: BLS, 2022a.
Conversely, education and health services and leisure and hospitality are projected to grow by double digits. Should veterans increasingly enter industries with more growth potential, the top veteran-employing industries could shift in ways that could make veterans more resilient overall to the next downturn.
Research Could Support Veterans' Transitions to the Civilian Labor Market
Veteran transition programs can help match newly separated service members to civilian careers with good long-term prospects. RAND research has resulted in a more granular and comprehensive list of military-civilian job skill matches (Wenger et al., 2017), and the U.S. Department of Labor's My Next Move for Veterans has adopted these military-specific skill matches. Similar research could inform the creation of additional datasets on location-specific industries, wages, or employment projections.
There are other opportunities for research to guide improvements to these programs. For example, better data could help programs better advise veterans on their location-specific employment prospects. Veterans not only have the opportunity to choose a new career path, but many also have a choice of where to live for the first time since they joined the military. Future research should include a detailed assessment of the historical patterns that we've highlighted and the best data on employment projections, exploring how industry composition and the consequences of economic downturns differ by location and whether these factors explain differences in veterans' labor market outcomes. A related question is how new veterans choose where to live after separation and the extent to which job opportunities factor into that decision. This is important because location affects more than just employment opportunities: Unemployment Compensation for Ex-Servicemembers program eligibility and benefits depend on the state in which a newly separated veteran lives, not the state in which they last served (U.S. Department of Labor, undated).
Another important consideration is the ever-changing demographic profile of veterans. This is a function of both who joins the military and who decides to separate at a given point in time. Pew Research Center (Schaeffer, 2021) projects that, by mid-century, the fraction of women veterans will increase and veterans as a whole will become slightly younger. But historical retention patterns indicate that service members will be more likely to remain in the military if there is another recession (Borgschulte and Martorell, 2018)—something that the military can encourage by offering selective reenlistment bonuses and other incentives. Similarly, today's difficult recruiting environment now could result in increased incentives to remain in the military and thus fewer service members separating. For example, the Air Force temporarily expanded the number of occupations eligible for selective retention bonuses to compete with a tight civilian labor market (Air Force Recruiting Service, 2022). Demographic projections require constant revision in light of such conditions to provide the best guidance for veteran-serving organizations and policymakers regarding who will be separating in the future.
Finally, research must account for what is perhaps the greatest unknown of all: the future. Economic projections depend on many assumptions; macroeconomic and geopolitical factors change so rapidly that these projections can fall rapidly out of date. Major short-run uncertainties include the war in Ukraine and the Federal Reserve's response to inflation. In the longer term, President Biden's "Buy American" executive order could reverse some of the projected decline in manufacturing (White House, 2022). In the even longer term, major shocks can be nearly impossible to predict, as the COVID-19 pandemic demonstrated.
Appendix
Table A.1 presents the demographic characteristics of the U.S. nonveteran and veteran populations at the start of the COVID-19 pandemic and Great Recession, supplementing our discussion of how the demographics of these populations could explain variations in their earnings and employment. Table A.2 shows past and projected U.S. labor market growth by industry, with an emphasis on industries that employ a significant share of veterans.
Table A.1. Descriptive Statistics of the Current Population Survey Sample Just Prior to the COVID-19 Pandemic and Great Recession
| Demographic | COVID-19 Pandemic (January 2020) | Great Recession (November 2007) | ||
|---|---|---|---|---|
| Nonveterans | Veterans | Nonveterans | Veterans | |
| Sex | ||||
| Male | 51.0% | 87.1% | 50.4% | 92.1% |
| Female | 49.0% | 12.9% | 49.6% | 7.9% |
| Race and ethnicity | ||||
| White, non-Hispanic | 60.8% | 70.5% | 67.4% | 79.0% |
| Black, non-Hispanic | 11.7% | 14.0% | 10.9% | 11.3% |
| Asian, non-Hispanic | 6.4% | 1.8% | 4.8% | 1.6% |
| All other, non-Hispanic | 2.6% | 3.3% | 1.9% | 1.8% |
| Hispanic | 18.5% | 10.4% | 14.9% | 6.2% |
| Marital status | ||||
| Married | 53.3% | 66.8% | 56.3% | 70.2% |
| Separated, widowed, or divorced | 13.3% | 19.9% | 14.7% | 18.4% |
| Never married | 33.4% | 13.3% | 29.0% | 11.5% |
| Education | ||||
| Less than high school | 7.4% | 1.8% | 10.3% | 3.4% |
| High school or equivalent | 26.2% | 25.4% | 30.2% | 31.2% |
| Some college | 27.1% | 35.9% | 28.5% | 36.6% |
| Bachelor's degree | 25.2% | 21.8% | 20.7% | 18.0% |
| Graduate or professional degree | 14.1% | 15.1% | 10.3% | 10.7% |
| Family size | ||||
| 1 (no dependents) | 16.8% | 17.8% | 17.2% | 17.5% |
| 2 to 4 | 68.3% | 72.4% | 67.7% | 73.7% |
| More than 4 | 14.8% | 9.8% | 15.1% | 8.8% |
| Age (mean) | 42 | 52 | 40 | 51 |
SOURCE: Calculated from November 2007 and January 2020 CPS data (Flood et al., 2022; Ruggles et al., 2022).
NOTE: Statistics are based on individuals age 18 and older. Statistics for nonveterans exclude individuals who are currently serving in the military.
Table A.2. BLS Employment Projections
| Industry | Employment (millions) | Employment Growth (%) | |||
|---|---|---|---|---|---|
| 2011 | 2021 | 2031 | 2011–2021 | 2021–2031 | |
| Construction | 5.533 | 7.413 | 7.618 | 34.0 | 2.8 |
| Education and health services | 20.318 | 23.673 | 26.720 | 16.5 | 12.9 |
| Financial activities | 7.697 | 8.777 | 9.113 | 14.0 | 3.8 |
| Information | 2.673 | 2.831 | 3.041 | 5.9 | 7.4 |
| Leisure and hospitality | 13.353 | 14.101 | 16.024 | 5.6 | 13.6 |
| Manufacturing | 11.727 | 12.347 | 12.207 | 5.3 | –1.1 |
| Natural resources and mining | 2.887 | 2.704 | 2.784 | –6.3 | 2.9 |
| Professional and business services | 17.389 | 21.250 | 22.799 | 22.2 | 7.3 |
| Public administration | 14.101 | 14.088 | 14.340 | –0.1 | 1.8 |
| Retail trade | 14.674 | 15.396 | 15.063 | 4.9 | –2.2 |
| Transportation and warehousing | 4.289 | 6.092 | 6.559 | 42.0 | 7.7 |
| Utilities | 0.553 | 0.541 | 0.511 | –2.1 | –6.4 |
| Wholesale trade | 5.475. | 5.678 | 5.814 | 3.7 | 2.4 |
| All other (including unknown) | 6.083 | 6.114 | 6.641 | 0.5 | 8.6 |
SOURCE: BLS employment projections (BLS, 2022b).
NOTE: Industries in bold are those in the top 5 for veteran employment in Table 1.
References
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- BLS—See U.S. Bureau of Labor Statistics.
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This Perspective is part of the "Veterans' Issues in Focus" series. Policy research has an important role to play in supporting veterans as they transition to life after military service. This shift can be challenging—from securing job opportunities and housing to coping with trauma and disability. Researchers at the RAND Epstein Family Veterans Policy Research Institute routinely assess the latest data on critical issues affecting veterans, gaps in the knowledge base, and opportunities for policy action.
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Format:Schwam, Daniel and James V. Marrone, Veterans' Employment During Recessions: Veterans' Issues in Focus. Santa Monica, CA: RAND Corporation, 2023. https://www.rand.org/pubs/perspectives/PEA1363-7.html.
Schwam, Daniel and James V. Marrone, Veterans' Employment During Recessions: Veterans' Issues in Focus, RAND Corporation, PE-A1363-7, March 2023. As of June 1, 2023: https://www.rand.org/pubs/perspectives/PEA1363-7.html