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The Labor Market Earnings of Veterans: Is Military Experience More or Less Valuable than Civilian Experience?

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Abstract

We assess the labor market experiences and earnings of military veterans, focusing on three major outcomes, among others, controlling for a wide array of demographic characteristics and industry and occupational fixed effects. First, we find that male and female veterans receive civilian earnings nearly equivalent to nonveteran men and women. This finding implies that military experience is valued in the labor market similarly to foregone civilian experience. Second, veterans are clustered in occupations with somewhat lower than average employment and real earnings growth, and in metropolitan areas with lower levels and growth of real GDP per capita. Third, veterans experience lower returns to formal educational investments (e.g., college) than do nonveterans. Veterans realize earnings gains from professional licenses, but their returns are lower than for nonveterans. These gains are concentrated among science, technology, engineering, and math (STEM) jobs, suggesting that veterans could help meet the growing demand for tech talent and artificial intelligence skills.

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Notes

  1. Angrist (1990) and Angrist et al. (2011) provide analysis of veteran/nonveteran earnings differences for those exposed to the draft lottery toward the end of the Vietnam War. Prior analyses on Vietnam-era veterans and nonveterans, as well as for earlier periods, include Villemez and Kasarda (1976), Little and Fredland (1979), De Tray (1982); Berger and Hirsch (1983, 1985), Schwartz (1986), Goldberg and Warner (1987), Mangum and Ball (1989), Angrist and Krueger (1994), and Angrist (1998). Relatively recent analyses include Hirsch and Mehay (2003), Davila and Mora (2012), Card and Cardoso (2012), Faberman and Foster (2013), Routan (2014), Asali (2019), and Tan (2020). Some of these analyses can reasonably claim that their earnings gap estimates are causal; most cannot.

  2. The labor force participation rate among veterans in 2018 was 49%, as compared to 66% among nonveterans. This difference reflects the older average age of veterans than nonveterans. Participation rates are roughly equivalent for veterans and nonveterans when compared within narrow age groups (https://www.bls.gov/news.release/pdf/vet.pdf, Table 2).

  3. Such a conclusion is not unique to recent years. At least one recent paper examines military service during World War I (Tan 2020) and concludes that there was little evidence of a causal relationship between wartime service and subsequent economic outcomes. That said, a recent paper by Gabriel (2020) finds that World War I veterans observed in Census data from 1930, 1940, and 1950 were employed in occupations that provided higher pay and greater upward mobility than did occupations in which nonveterans were employed. Similar evidence is found for World War II, in which there was nearly universal service among men fit for duty (Angrist and Krueger 1994). Men unable to serve in World War II tended to earn less than did their World War II veteran counterparts.

  4. With the exception of the OES data on employment and real wages and the Bureau of Economic Analysis (BEA) data on real per capita GDP, all data files were accessed from the Integrated Public Use Microdata Series (IPUMS) at the Minnesota Population Center.

  5. Throughout the paper we treat the log differential as the percentage differential, albeit one with an intermediate base. The standard conversion from a log differential to an arithmetic percentage is [exp(β)-1]100, where β is the log gap. The 0.123 veteran coefficient implies a 13.1 percent arithmetic differential. Wage gap estimates with controls are far below 0.123; hence there is a minimal difference between the log gaps and the arithmetic percentages.

  6. Credentials matter in the larger labor market. Deming et al. (2016) provide results from an experimental study in which fictitious resumes were sent to real vacancy postings. Among their findings were that applicants listing business degrees from for-profit colleges had substantially lower callback than from applicants from nonselective public institutions. An exception was that in health jobs, for-profit credentials coupled with a government occupational license did not have a negative signal.

  7. Our analysis focuses exclusively on those employed. There have been considerable reductions in labor force participation and high rates of institutionalized black males (Hirsch and Winters 2014; Bayer and Charles 2018). If one were to account for African Americans out of the labor force and institutionalized (i.e. zero earners), we would see a larger left tail with respect to skill, thus observing even stronger positive selection by the military.

  8. As seen above, we infer that there is positive selection into the military for both black and Hispanic veterans. In a recent paper from Hamermesh et al. (forthcoming) using time-use data (i.e., the ATUS), the authors measure racial and ethnic differences in “non-work” time during paid time work hours. Both black and Hispanic workers are found to have somewhat higher levels of “non-work” during paid work hours. These differences in “non-work” time on the job explain a relatively small share of the overall racial and Hispanic wage gaps. The authors note, however, that among male veterans, there were no difference in “nonwork” hours between black veterans and white workers, nor any differences in nonwork among Hispanic veterans and white workers in the ATUS samples. In short, the racial and ethnic differences in “nonwork” found by the authors is fully driven by nonveterans. Time-use evidence in this study reinforces our conclusion that there is positive selection into the military among black and Hispanic men.

  9. The share of veterans in rural areas is higher than in CPS-designated metro areas. Likewise, controlling for standard demographics, we find that male veterans are 6.4 percentage points less likely to live in metro areas with over 1 million people than their nonveteran male counterparts.

  10. Mehay and Hirsch (1996, Appendix) provide supplementary analysis of female veterans using the 1989–1993 CPS. For birth cohorts of women between 1955 and 1973, they find wage ratios of female veterans to nonveterans to be very close to 1.0. For much earlier cohorts of women, the civilian earnings of female veterans substantially exceeded the earnings of nonveteran women, but the differences were fully accounted for by standard worker attributes (schooling, age, etc.).

  11. The CPS earnings files from IPUMS do not include allocation (imputation) flags for the early years in our sample.

  12. Our results are robust to the base year we use, but we choose to use 2002 as our starting point since it is after the technology boom and bust and before the run-up to the sub-prime mortgage crisis.

  13. https://comptroller.defense.gov/Portals/45/Documents/defbudget/fy2020/FY20_Green_Book.pdf

  14. The military has been concerned that many of its soldiers are not well prepared to transition to IT and other rapidly growing civilian occupations. They have supported recent studies guiding veterans toward civilian occupations that utilize and require job skills similar to their military occupations (see Wenger et al. 2017).

  15. We would use 2018 data on real per capita GDP to match our real wage and employment data, but it is not available at the time of our release of this paper.

  16. As seen in column 2 of both Tables 4 and 5 (as compared to columns 3 and 4), the estimated earnings licensing advantage is more than 2 percentage points higher absent controls for detailed industry and occupation.

  17. Based on calculations from the 2018 CPS, 48.8% of public workers are local government workers, 33.6% state workers, 14.6% non-postal federal, and 3.0% postal service. These public workers account for 15.1% of all wage and salary workers.

  18. Based on the CPS, 33.9 percent of public sector workers were union members in 2018, as compared to 6.4 percent in the private sector (https://www.bls.gov/news.release/pdf/vet.pdf, Table 3). Roughly half of all union members are public sector workers.

  19. The obvious exception are military veterans injured either in combat or in other on-the-job military activities.

References

  • Acemoglu D, Autor D (2012) What does human capital do? a review of Goldin and Katz’s the race between education and technology. J Econ Lit 50(2):426–463

    Article  Google Scholar 

  • Angrist JD (1990) Lifetime earnings and the Vietnam era draft lottery: evidence from social security administrative records. Am Econ Rev 80(3):313–336

    Google Scholar 

  • Angrist JD (1998) Estimating the labor market impact of voluntary military service using social security data on military applicants. Econometrica 66(2):249–288

    Article  Google Scholar 

  • Angrist JD, Chen SH, Song J (2011) Long-term consequences of Vietnam-era conscription: new estimates using social security data. Am Econ Rev Pap Proc 101(3):334–338

    Article  Google Scholar 

  • Angrist JD, Krueger AB (1994) Why do World War II veterans earn more than nonveterans? J Law Econ 12(1):74–97

    Google Scholar 

  • Asali M (2019) Compulsory military service and future earnings: evidence from a natural experiment. Def Peace Econ 309(4):402–420. https://EconPapers.repec.org/RePEc:taf:defpea:v:30:y:2019:i:4:p:402-420

  • Autor, DH (2019) Work of the past, work of the future. American economic review: papers and proceedings 109, Richard T. Ely Lecture, 1–32

  • Autor DH, Dorn D (2013) The growth of low skill service jobs and the polarization of the U.S. labor market. Am Econ Rev 103(5):1553–1597

    Article  Google Scholar 

  • Autor DH, Levy F, Murnane RJ (2003) The skill content of recent technological change: an empirical exploration. Quart J Econ 118(4):1279–1333

    Article  Google Scholar 

  • Bayer P, Charles KK (2018) Divergent paths: a new perspective on earnings differences between black and white men since 1940. Quart J Econ 133(3):1459–1501

    Article  Google Scholar 

  • Berger MC, Hirsch BT (1983) The civilian earnings experience of Vietnam- era veterans. J Hum Resour 18(4):455–479

    Article  Google Scholar 

  • Berger MC, Hirsch BT (1985) Veteran status as a screening device during the Vietnam era. Soc Sci Q 66(1):79–89

    Google Scholar 

  • Bingley P, Lundborg P, Lyk-Jensen SV (2020) The opportunity costs of mandatory military service: evidence from a draft lottery. J Law Econ 38(1):39–66

    Google Scholar 

  • Bollinger CR, Hirsch BT (2006) Match bias from earnings imputation in the Current Population Survey: the case of imperfect matching. J Law Econ 24(3):483–519

    Google Scholar 

  • Card D, Cardosa AR (2012) Can compulsory military service raise civilian wages? evidence from the peacetime draft in Portugal. Am Econ J Appl Econ 4(4):57–93

    Article  Google Scholar 

  • Cellini SR, Goldin C (2014) Does federal student aid raise tuition? new evidence on for-profit colleges. Am Econ J Econ Pol 6(4):174–206

    Article  Google Scholar 

  • Cellini SR, Turner N (2019) Gainfully employed? assessing the employment and earnings of for-profit college students using administrative data. J Hum Resour 54(2):342–370

    Article  Google Scholar 

  • Davila A, Mora MT (2012) Terrorism and patriotism: on the earnings of US veterans following September 11, 2001. Am Econ Rev Pap Proc 102(3):261–266

    Article  Google Scholar 

  • De Tray DN (1982) Veteran status as a screening device. Am Econ Rev 72(1):133–142

    Google Scholar 

  • Deming DJ, Goldin C, Katz LF (2012) The for-profit postsecondary school sector: nimble critters or agile predators J Econ Perspect 26(1):139–164

    Article  Google Scholar 

  • Deming DJ, Yuchtman N, Abulafi A, Goldin C, Katz LF (2016) The value of post-secondary credentials in the labor market: an experimental study. Am Econ Rev 106(3):778–806

    Article  Google Scholar 

  • Dever M (2019) With historic number of women in uniform, the vet community is about to change Military.com, March 11. https://www.military.com/daily-news/2019/03/11/historic-number-women-uniform-vet-community-about-change.html. Accessed Apr 2020

  • Eggleston J Holder KA (2017) The wealth of veterans,” U.S. Census Bureau, Current Population reports, P70–1, 2017: 70–151, Washington, DC. https://www.census.gov/library/publications/2017/demo/p70-151.html. Accessed Apr 2020

  • Faberman RJ, Foster T (2013) Unemployment among recent veterans during the great recession, economic perspectives, federal reserve bank of Chicago, 1Q/2013: 1-13

  • Gabriel PE (2020) An empirical examination of the occupational attainment of American veterans of World War I. Soc Sci Q 101(3):1009–1017

    Article  Google Scholar 

  • Gallipoli G, Makridis CA (2018) Structural transformation and the rise of information technology. J Monet Econ 97(C):91–110

    Article  Google Scholar 

  • Gittleman M, Klee MA, Kleiner MM (2018) Analyzing the labor market outcomes of occupational licensing. Ind Relat 57(1):57–100

    Article  Google Scholar 

  • Goldberg MS, Warner J (1987) Military experience, civilian experience, and the earnings of veterans. J Hum Resour 22(1):61–81

    Article  Google Scholar 

  • Goos M, Manning A, Salomons A (2009) Job polarization in Europe. Am Econ Rev Pap Proc 99(2):58–63

    Article  Google Scholar 

  • Hamermesh DS, Genadek KR, Burda MC (Forthcoming) Racial/ethnic differences in non-work at work. Ind Labor Relat Rev 1–21. https://doi.org/10.1177/0019793919891429

  • Hirsch BT, Macpherson DA (2019) Union membership and earnings data book, compilations from the Current Population Survey: 2019 Ed., Bloomberg BNA

  • Hirsch BT, Mehay SL (2003) Evaluating the labor market performance of veterans using a matched comparison group design. J Hum Resour 38(3):673–700

    Article  Google Scholar 

  • Hirsch BT, Schumacher EJ (2004) Match bias in wage gap estimates due to earnings imputation. J Law Econ 22(3):689–722

    Google Scholar 

  • Hirsch BT, Winters JV (2014) An anatomy of racial and ethnic trends in male earnings. Rev Income Wealth 60(4):930–947

    Google Scholar 

  • Kirkeboen LJ, Leuven E, Mogstad M (2016) Field of study, earnings, and self-selection. Quart J Econ 131(3):1057–1111

    Article  Google Scholar 

  • Lewis GB, Pathak R (2014) The employment of veterans in state and local government service, public management & policy faculty publications, 11, Georgia State Univ. https://scholarworks.gsu.edu/pmap_facpubs/11. Accessed Apr 2020

  • Little RD, Fredland JE (1979) Veteran status, earnings, and race: some long term results. Armed Forces Soc 5(2):244–260

    Article  Google Scholar 

  • Mangum SL, Ball DE (1989) The transferability of military-provided occupational training in the post-draft era. Ind Labor Relat Rev 42(2):230–245

    Article  Google Scholar 

  • Makridis CA (2021) (Why) is there a public/private pay gap? J Gov Econ 1

  • Martorell P, Miller T, Daugherty L, Borgschulte M (2013) Effects of military service on earnings and education revisited: variation by service duration, occupation, and civilian unemployment. RAND Corporation, Research Report 342

  • Mehay SL, Hirsch BT (1996) The post-military earnings of female veterans. Ind Relat 35(2):197–217

    Article  Google Scholar 

  • Routan PW (2014) The effect of 21st century military service on civilian labor and educational outcomes. J Lab Res 35(1):15–38

    Article  Google Scholar 

  • Steinhauer J (2020) Veterans are working, but not in jobs that match their advanced training. New York Times, Updated 3/16. https://www.nytimes.com/2020/03/07/us/politics/veterans-jobs-employment.html. Accessed Apr 2020

  • Tan HR (2020) Did military service during World War I affect the economic status of American veterans? Explor Econ Hist 75(1): Article 101301

  • Schwartz S (1986) The relative earnings of Vietnam and Korean-era veterans. Ind Labor Relat Rev 39(4):564–572

    Article  Google Scholar 

  • Spence M (1973) Job market signaling. Quart J Econ 87(3):355–374

    Article  Google Scholar 

  • U.S. Bureau of Labor Statistics (2019) Employment situation of veterans—2018, USDL-19–0451, March 21

  • U.S. Congressional Budget Office (2017) Labor force experiences of recent veterans, May. https://www.cbo.gov/system/files/115th-congress-2017-2018/reports/52418-laborforceveterans_0.pdf. Accessed Apr 2020

  • Villemez WJ, Kasarda JD (1976) Veteran status and socioeconomic attainment. Armed Forces Soc 2:407–420

    Article  Google Scholar 

  • Wenger, JB, et al (2017) Helping soldiers leverage army knowledge, skills, and abilities in civilian jobs, RAND Corporation, Research Report 1719-A

  • Zivin K, Bohnert ASB, Mezuk B, Ilgen MA, Welsh D, Ratliff S, Miller EM, Valenstein M, Kilbourne AM (2011) Employment status of patients in the VA health system: implications for mental health services. Psychiatr Serv 62(1):35–38

    Article  Google Scholar 

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Authors and Affiliations

  1. National Artificial Intelligence Institute at the Department of Veterans Affairs, 810 Vermont Ave NW, Washington, DC, 20420, USA

    Christos A. Makridis

  2. Stanford Digital Economy Lab, Stanford University, Stanford, CA, USA

    Christos A. Makridis

  3. Department of Economics, Andrew Young School of Policy Studies, Georgia State University, Atlanta, GA, USA

    Barry T. Hirsch

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Correspondence to Christos A. Makridis.

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Makridis, C.A., Hirsch, B.T. The Labor Market Earnings of Veterans: Is Military Experience More or Less Valuable than Civilian Experience?. J Labor Res 42, 303–333 (2021). https://doi.org/10.1007/s12122-021-09321-y

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