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ABSTRACT
We test two sets of alternative hypotheses about the demographic composition of the U.S. armed forces. We analyse individual-level data of two national representative samples covering the period 1979–2008. We find that, in contrast to the accepted wisdom, the U.S. military no longer primarily recruits individuals from the most disadvantaged socio-economic backgrounds. Technological, tactical, operational and doctrinal changes have led to a change in the demand for personnel. As a result, on different metrics such as family income and family wealth as well as cognitive abilities, military personnel are on average like the average American citizen or slightly better.
Acknowledgements
The authors would like to thank the participants to the presentations at MPSA 2016 and APSA 2016, and in particular Katryn Boehlefeld, Jon Caverley, Keith Carter, Kate Cronin-Furman, Fiona Cunningham, Erica De Bruin, Thomas Michael Dolan, Michal Ben-Josef Hirsch, Mathias Frendem, Erik Gartzke, Payam Ghalehdar, Hein Goemans, Kelly Greenhill, Jeffrey Karam, Nadiya Kostyuk, Max Margulies, Reid Pauly, Kate Perry, Bruce Russett, Nina Silove, Jennifer Spindel, Nathan Toronto, Amy Zegart and Ketian Zhang for helpful feedbacks. Anne Sartori, Stephen Biddle, Pietro Biroli, Stephen Nelson, Josh Shifrinson, Hendrik Spruyt and Bill Wohlforth provided very helpful feedbacks at different stages of this project.
Disclosure statement
No potential conflict of interest was reported by the authors.
Supplemental data
Supplemental data for this article can be accessed here.
Notes
1 Noam Chomsky, Understanding Power: The Indispensable Chomsky (London, UK: Vintage Books 2003), 36.
2 Nicholas Kristof, ‘Profiting from a child’s illiteracy’, New York Times, 7 Dec. 2012.
3 Matt Kennard, ‘The modern US army: unfit for service’? The Guardian, 31 Aug. 2012.
4 Douglas L. Kriner and Frances X. Shen, The Casualty Gap: The Causes and Consequences of American Wartime Inequalities (Oxford, UK: Oxford University Press 2010).
5 Adam Dean, ‘NAFTA’s Army: Free Trade and US Military Enlistment’, International Studies Quarterly 62/4 (Dec. 2018), 845–85.
6 Thomas E. Ricks, ‘The widening gap between the military and society’, The Atlantic, 1997, pp. 66–76; Eliot A. Cohen, ‘Twilight of the Citizen-Soldier’, Parameters 31 (Summer 2001), 23–28; Charles Moskos, ‘What Ails the All-Volunteer Force: An Institutional Perspective’, Parameters 31 (Summer 2001), 29–47.
7 This is true for democratic and non-democratic governments. See, for example, Edward N. Luttwak, Strategy: The Logic of War and Peace (Belknap Press of Harvard University Press 1987), 72; Gil Meron, How Democracies Lose Small Wars (Cambridge: Cambridge University Press 2003). On how inequality in serving and in dying affects public support, see Christopher Gelpi, Peter Feaver, and Jason Reifler, Paying the Human Costs of War: American Public Opinion and Casualties in Military Conflicts (Princeton, NJ: Princeton University Press 2009). For instance, Kriner and Shen have shown that, ‘Americans are less willing to accept casualties in future military endeavors when informed that the costs of war fall disproportionately on the shoulders of a disadvantaged few’. Douglas L. Kriner and Frances X. Shen, ‘Reassessing American Casualty Sensitivity The Mediating Influence of Inequality’, Journal of Conflict Resolution 58/7 (2013), 2.
8 Samuel P. Huntington, The Soldier and the State: The Theory and Politics of Civil-military Relations (Cambridge, MA: The Belknap Press of Harvard University Press 1957).
9 Morris Janowitz, ‘The All Volunteer Military as a Socio-Political Problem’, Social Problems 22/3 (1975), 432–449.
10 See, for example, Stephen Biddle and Stephen Long, ‘Democracy and Military Effectiveness: A Deeper Look’, Journal of Conflict Resolution 48/4 (Aug. 2004), 525–46.
11 This hypothesis was implicit in several studies of the 1980s which concluded, ‘that improvements in technology can readily compensate for lack of manpower quality’. See Juri Toomepuu, Costs and Benefits of Quality Soldiers: A Critical Review of the CBO Report, Quality Soldiers: Costs of Manning the Active Army (Fort Sheridan IL: U.S. Army Recruiting Command 1986), 6.
12 See, for example, David Card and John E. DiNardo, ‘Skill‐Biased Technological Change and Rising Wage Inequality: Some Problems and Puzzles’, Journal of Labor Economics 20/4 (Oct. 2002), 733–783; David H. Autor, Frank Levy and Richard J. Murnane, ‘The Skill Content of Recent Technological Change: An Empirical Exploration’, The Quarterly Journal of Economics 118/4 (Nov. 2003), 1279–1333; Francesco Caselli, ‘Technological Revolutions’, American Economic Review 89/1 (Mar. 1999), 78–102.
13 Socio-economic inequality in the USA has increased dramatically over the past decades: while in the 1950s, the richest 1% earned about 10% of U.S. total income, by 2010 the share had more than doubled to 23.5%. See Thomas Piketty, Capital in the Twenty-Fist Century (Cambridge MA: Belknap Press 2014).
14 Kriner and Shen, The Casualty Gap; Jonathan D. Caverley, Democratic Militarism: Voting, Wealth and War (Cambridge, UK: Cambridge University Press 2014); Lindsay P. Cohn, ‘Who Will Serve: Labor Markets and Military Personnel Policy’, Res Militaris 3/2 (2013), 1–26; Lindsay P. Cohn and Nathan W. Toronto, ‘Markets and Manpower: The Political Economy of Compulsory Military Service’, Armed Forces & Society 43/3 (July 2017), 436–458; Pany Poutvaar and Andreas Wagener, ‘To Draft or Not to Draft? Inefficiency, Generational Incidence, and Political Economy of Military Conscription’, European Journal of Political Economy 23/4 (Dec. 2007), 975–987; Yagil Levy, ‘Militarizing Inequality: A Conceptual Framework’, Theory and Society 27/6 (1997), 873–904; and Yagil Levy, ‘Soldiers as Labourers: A Theoretical Model’, Theory and Society 36/2 (2007), 187–208.
15 For works that focus on the substitution effect between capital and labour, see, for example, Jonathan D. Caverley, Democratic Militarism: Voting, Wealth and War (Cambridge UK: Cambridge University Press 2014); and Amy Zegart, ‘Cheap fights, credible threats: The future of Armed Drones and Coercion’, Journal of Strategic Studies (2018). For a discussion of complementation effects, see for example Ajay Agrawal, Avi Goldfarb, and Joshua Gans, Prediction Machines: The Simple Economics of Artificial Intelligence (Cambridg MA: Harvard Business School Press 2018).
16 For a discussion on the challenges of imitating the most advanced U.S. weapon systems, see Andrea Gilli and Mauro Gilli, ‘Why China Has Not Caught Up Yet: Military-Technological Superiority and the Limits of Imitation, Reverse Engineering, and Cyber Espionage’, International Security 43/3 (Winter 2018/19), 141–189.
17 For a discussion, see, for example, Stephen Biddle and Robert Zirkle, ‘Technology, Civil-Military Relations, and Warfare in the Developing World’, Journal of Strategic Studies 19/2 (June 1996), 171–212; Christopher S. Parker, ‘New Weapons for Old Problems: Conventional Proliferation and Military Effectiveness in Developing States’, International Security 23/4 (Spring 1999), 119–147; Stephen D. Biddle, Military Power: Explaining Victory and Defeat in Modern Combat (Princeton NJ: Princeton University Press 2004); and Michael C. Horowitz, The Diffusion of Military Power: Causes and Consequences for International Politics (Princeton NJ: Princeton University press 2010).
18 Albert B. Moore, Conscription and Conflict in the Confederacy (New York, NY: Hillary House 1924). For an empirical investigation, see Andrew B. Hall, Connor Huff and Shiro Kuriwaki, ‘Wealth, Slave Ownership, and Fighting for the Confederacy: An Empirical Study of the American Civil War’, American Political Science Review (forthcoming).
19 O. M. W. Sprague, ‘The Conscription of Income a Sound Basis for War Finance’, Economic Journal 27/105 (1917), 1–17; Eric Bradner, ‘Beto O’Rourke proposes “war tax” as part of veterans’ plan’, CNN, 24 June 2019.
20 Bernard D. Rostker, I Want You! The Evolution of the All-Volunteer Force (Santa Monica CA: RAND Corporation 2006).
21 David Cortright, ‘Economic Conscription’, Society 12/4 (May–June 1975), 43–47; and Jorge Mariscal, ‘The Poverty Draft: Do Military Recruiters Dis-proportionately Target Communities of Color and the Poor’? Sojourners Magazine (June 2007).
22 Martin Binkin, et al., Black and the Military (Washington, DC: Brookings Institution 1982); Kriner and Shen, The Casualty Gap; Alair MacLean and Nicholas. L. Parsons, ‘Unequal Risk: Combat Occupation in the Volunteer Military’, Sociological Perspectives 43/3 (2010), 347–72.
23 Democratic Leadership Council, Citizenship and National Service: A Blueprint for Civic Enterprise. (Washington DC: Democratic Leadership Council 1988).
24 Charles Rangel, Representative Rangel Remarks at the National Press Club, Washington DC (15 Apr. 2004).Cited in Edward Epstein, ‘Draft Unlikely Soon but Hot Topic Now’, San Francisco Gate, 2 May 2004.
25 Michael Massing, ‘The Volunteer Army: Who Fights and Why’? The New York Review of Books, 3 Apr. 2008.
26 Fred Barbash, ‘Teacher who called military “lowest of our low” explains himself – with little success’, The Washington Post, 14 Feb. 2018.
27 Larry DeBoer and B. Wade Brorsen, ‘The Demand for and Supply of Military Labor’, Southern Economic Journal 55/4 (1989), 853–69.
28 Charles C. Moskos Jr., The American Enlisted Man: The Rank and File in Today’s Military (New York: Basic Books 1970), 171; Seung-Whan Choi and Patrick James, ‘No Professional Soldiers, No Militarized Interstate Disputes? A New Question for Neo-Kantianism’, Journal of Conflict Resolution 47/6 (Dec. 2003), 796–816.
29 Cohen, ‘Twilight’, 24.
30 Joseph Paul Vasquez, III, ‘Shouldering the Soldiering: Democracy, Conscription, and Military Casualties’, Journal of Conflict Resolution 49/6 (Dec. 2005), 852.
31 Andrew J. Bacevich, The Limits of Power: The End of American Exceptionalism (New York NY: Metropolitan Books/Henry Holt & Company), 140.
32 Caverley, Democratic Militarism, 33.
33 Kriner and Shen, Casualty Gap.
34 Curtis J. Simon and John T. Warner, ‘Managing the All-Volunteer Force in a Time of War’, The Economics of Peace & Security Journal 2/1 (2007), 20–29; Kriner and Shen, Casualty Gap; Dean, ‘NAFTA’s Army’.
35 David A. Freedman, ‘The Ecological Fallacy’, Prepared for the International Encyclopedia of the Social & Behavioral Sciences Technical Report, No. 549, 15 Oct. 1999.
36 Department of Defence, Population Representation in the Military Services, Fiscal Year 1999 (Washington, DC: Office of the Assistant Secretary of Defense 2000) Ch. 7.
37 Department of Defense, Population Representation.
38 See Appendix A in supplementary material for a more thorough discussion of the limitations of this methodology, available at https://css.ethz.ch/content/dam/ethz/special-interest/gess/cis/center-for-securities-studies/pdfs/AGGS.pdf.
39 Kriner and Shen, The Casualty Gap, 40–58.
40 Tim Kane, ‘Who Bears the Burden? Demographic Characteristics of U.S. Military Recruits Before and After 9/11’, Center for Data Analysis Report, 05–08 (Washington, DC: Heritage Foundation 2005). See also Diana S. Lien, et al., An Investigation of FY10 and FY11 Enlisted Accessions’ Socioeconomic Characteristics (Arlington, VA: Center for Naval Analyses 2012).
41 Eric J. Fredland and Roger D. Little, Socioeconomic Characteristics of the All Volunteer Force: Evidence from the National Longitudinal Survey, 1979 (Annapolis MD: U.S. Naval Academy 1982); see also Ghislaine Boulanger, ‘Who Goes to War’? in Arthur Egendorf, et al. (eds.), Legacies of Vietnam: Comparative Adjustment of Veterans and Their Peers, Vol. 4 (Washington DC: U.S. Government Printing Office 1981), 494–515. We will separately analyse the NLSY79 data in this article and confirm that individuals who joined the military in the 1980s are more likely to come from lower socio-economic backgrounds.
42 Richard N. Cooper, Military Manpower and the All Volunteer Force (Santa Monica CA: RAND Corporation 1977); Richard L. Fernandez, Social Representation in the U.S. Military (Washington, DC: Congressional Budget Office 1989); DeBoer and Brorsen, ‘The Demand for and Supply of Military Labor’; Jay D. Teachman, et al., ‘The Selectivity of Military Enlistment’, Journal of Political and Military Sociology 21/2 (1993), 287–309; Cynthia Gimbel and Alan Booth, ‘Who Fought in Vietnam’, Social Forces 74/4 (1996), 1137–1157; Amy Lutz, ‘Who Joins the Military? A Look at Race, Class, and Immigration Status’, Journal of Political and Military Sociology 36/2 (2008), 167–188; MacLean and Parsons, ‘Unequal Risk’; Glen H. Elder, et al., ‘Pathways to the All‐Volunteer Military’, Social Science Quarterly 91/2 (June 2010), 455–475.
43 Department of Defense, Population Representation.
44 Idem.
45 Kriner and Shen, The Casualty Gap, 58–66, 74–79.
46 Christopher Bellamy, The Evolution of Modern Land Warfare: Theory and Practice (Abington: Routledge 1990), 80–120.
47 Gimbel and Booth, ‘Who Fought in Vietnam’.
48 Jonathan M. House, Toward Combined Arms Warfare: A Survey of Twentieth Century Tactics, Doctrine, and Organization (Ft. Leavenworth, KS: U.S. Army Combat Studies Institute. 1984); Thomas G. Mahnken, Technology and the American Way of War Since 1945 (New York NY: Columbia University Press 2008); The Congressional Budget Office, The All- Volunteer Military: Issues and Performance (Washington DC: The Congress of the United States July 2007).
49 Heidi Golding and Adebayo Adedeji, The All-Volunteer Military: Issues and Performance (Washington, DC: Congressional Budget Office 2008), 13–19; Christopher Tuck, Understanding Land Warfare (London: Routledge 2014), 55–76; Anthony King, The Combat Soldier Infantry Tactics and Cohesion in the Twentieth and Twenty-First Centuries (Oxford: Oxford University Press 2013), 24–39, 62–97; Lutz, ‘Who Joins the Military’; Amy Lutz, ‘Who Joins the Military in the Post-9/11 Era? A Look at Class, Race and Immigrant Generation’. Working Paper (2016).
50 See, for example, Martin Binkin, Military Technology and Defense Manpower (Washington, DC: The Brookings Institution 1986); Toomepuu, Costs and Benefits of Quality Soldiers, 1–2, 6–7; Todd S. Sechser and Elizabeth N. Saunders, ‘The Army You Have: The Determinants of Military Mechanization, 1979–2001’, International Studies Quarterly 54/2 (June 2010), 481–511; Tanisha M. Fazal, ‘Dead Wrong?: Battle Deaths, Military Medicine, and Exaggerated Reports of War’s Demise’, International Security 39/1 (Summer 2014), 95–125.
51 Barry R. Posen, ‘The Command of the Commons: The Military Foundation of American Hegemony’, International Security 28/1 (Summer 2003), 32–36; Brian A. Jackson, et al., Evaluating Novel Threats to the Homeland Unmanned Aerial Vehicles and Cruise Missiles (Santa Monica, CA: RAND Corporation 2008).
52 Janina Dill, Legitimate Targets? Social Construction, International Law and US Bombing (Cambridge: Cambridge University Press 2014).
53 Beth J. Asch. and James Hosek, Looking to the Future: What Does Transformation Mean for Military Manpower and Personnel Policy? (Santa Monica CA: RAND Corporation 2004); Arthur K. Cebrowski and John H. Garstka, ‘Network-Centric Warfare: Its Origin and Future’, Proceedings 124/1/1/139 (January 1998); Douglas A. Macgregor, Transformation Under Fire: Revolutionizing How America Fights (Westport CT: Praeger 2003).
54 Terry Pierce, Warfighting and Disruptive Technologies: Disguising Innovation (New York: Routledge 2004); Norman Friedman, The U.S. Maritime Strategy (London, Jane’s Information Group 1988).
55 Benjamin S. Lambeth, The Transformation of American Air Power (Ithaca NY: Cornell University Press 2000); Macgregor, Transformation Under Fire.
56 David Mowery, ‘Military R&D and Innovation’, in Bronwyn H. Hall and Nathan Rosenberg (eds.), Handbook of the Economics of Innovation, Vol. 2 (New York NY: Elsevier 2010), 1230; Michael R. Rip and James M. Hasik, The Precision Revolution: GPS and the Future of Aerial Warfare (Annapolis MD: Naval Institute Press 2002); Barry D. Watts, The Evolution of Precision Strike (Washington DC: Centre for Strategic and Budgetary Assessments 2013).
57 Mahnken, Technology and the American Way of War; Caverley, Democratic Militarism; Owen R. Cote, Jr., ‘The Personnel Needs of the Future Force’, in Cindy Williams (ed.), Filling the Ranks: Transforming the U.S. Military Personnel System (Cambridge, MA: M.I.T. Press 2003), 55–68; and Jon R. Lindsay, ‘Reinventing the Revolution: Technological Visions, Counterinsurgent Criticism, and the Rise of Special Operations’. Journal of Strategic Studies 36/3 (2013), 422–53.
58 Mahnken, Technology; Department of Defense, Population Representation; Massimiliano Gaetano Onorato, Kenneth Scheve, and David Stasavage, ‘Technology and the Era of the Mass Army’, The Journal of Economic History 74/2 (2014), 449–81.
59 We borrow the term ‘non-cognitive skills’ from Nobel Prize-laureate James Heckman and co-authors, among others. Non-cognitive skills refer are the set of attitudes, behaviours, and strategies such as motivation, self-discipline, perseverance, and self-control that facilitate academic and professional success. See James Heckman, ‘The Economics of Inequality: The Value of Early Childhood Education’, American Educator 35/11 (2011), 31–47; and James Heckman, et al., ‘Understanding the Mechanisms through Which an Influential Early Childhood Program Boosted Adult Outcomes’, American Economic Review 103/16 (2013), 2052–86.
60 Under some circumstances, technological change can lower the requirements for those who employ, as was the case for example the introduction of mass production, which permitted unskilled individuals to contribute to the manufacturing of products that, until then, had been produced by skilled artisans and craftsmen. Shoshana Zuboff, In the Age of the Smart Machine: The Future of Work and Power (New York NY: Basic Books 1988), 41–44; and Caselli, ‘Technological Revolutions’. We argue, however, that the opposite change has taken place. The military transformation the U.S. has gone through over the past decades is similar to the one that has taken place in industrial production. While until the mid 20th century, companies employed a large number of unskilled workers to perform relatively simple tasks, the growing sophistication of modern industrial products, such as cars and airplanes, as well as of manufacturing processes has progressively required increasingly skilled, trained and specialised workers.
61 Jeanne Brooks-Gunn and Greg J. Duncan, ‘The Effects of Poverty on Children’, The Future of Children 7/2 (1997), 55–71; Frances Campbell, et al. ‘Early Childhood Investments Substantially Boost Adult Health’, Science 343/6178 (2014), 1478–148; Kimberly G. Noble, et al. ‘Family Income, Parental Education and Brain Structure in Children and Adolescents’, Nature Neuroscience 18/5 (2015), 773–8.
62 For a summary and criticism of this perspective, see Toomepuu, Costs and Benefits of Quality Soldiers, 6.
63 Matthew Ronglie, ‘Deciphering the Fall and Rise in the Net Capital Share: Accumulation or Scarcity’? Brookings Papers on Economic Activity (Washington, DC: Brookings Institution Spring 2015).
64 Elder, et al., Pathways to the All-Volunteer Military; Bacevich, The Limits.
65 Stephen A. Petrill, et al., ‘Genetic and Environmental Contributions to General Cognitive Ability Through the First 16 Years of Life’, Developmental Psychology 40/5 (2004), 805–812; Celia Beckett, et al., ‘Do the Effects of Early Severe Deprivation on Cognition Persist into Early Adolescence? Findings from the English and Romanian Adoptees Study’, Child Development 77/3 (2006), 696–711; Campbell, et al. ‘Early Childhood Investments’; and Noble, et al., ‘Family Income’.
66 Greg J. Duncan and Katherine A. Magnuson, ‘Can Family Socioeconomic Resources Account for Racial and Ethnic Test Score Gaps’? The Future of Children15/1: School Readiness: Closing Racial and Ethnic Gaps (Spring 2005), 35–54; Gordon B. Dahl and Lance Lochner, ‘The Impact of Family Income on Child Achievement: Evidence from the Earned Income Tax Credit’, American Economic Review 102/5 (August 2011), 1927–56; Noble, et al., ‘Family Income’. Standardised tests have come under increasing criticism over the past years. Some have pointed out that the correlation between scores in standardised tests and socio-economic factors reflects the inequality in access to good teachers, schools and tutoring. According to this view, socio-economic factors do not lead to differences in cognitive abilities but to a difference in assessed cognitive abilities – in other words, they introduce a downward bias in test scores for those individuals from poorer backgrounds. It is beyond the scope of this article to assess the merit of each position. For the sake of our article, these two arguments point in the same direction, but for different reasons, and thus they do not affect our results. For simplicity, we take the results of standardised scores at face value. We leave to others to study this aspect more in depth.
67 Harvey M. Sapolsky, Eugene Gholz and Caitlin Talmadge, U.S. Defense Politics: The Origins of Security Policy (Oxon: Routledge 2008), 27–42; Tuck, Understanding Land Warfare, 42–76.
68 Jess Benhabib and Mark M. Spiegel, ‘The Role of Human Capital in Economic Development: Evidence from Aggregate Cross-Country Data’. Journal of Monetary Economics34/1 (1994), 143–173; Daron Acemoglu and David Autor, ‘Skills, Tasks and Technologies: Implications for Employment and Earnings’, Handbook of Labor Economics 4 (2011), 1043–1171; David Author, Lawrence F. Katz, and Alan B. Krueger, ‘Computing Inequality: Have Computers Changed the Labor Market’? The Quarterly Journal of Economics 113/4 (November 1998), 1169–1213; Steven M. Kosiak, Strategy for the Long Haul: Military Manpower for the Long Haul (Washington, DC: Center for Strategic and Budgetary Assessments 2008), 8; Golding and Adedeji. The All-Volunteer, 13–14; Biddle and Long, ‘Democracy and Military Effectiveness’.
69 Golding and Adedeji, The All-Volunteer, 13–19; and Kosiak; Strategy for the Long Haul, 8.
70 Golding and Adedeji, The All-Volunteer, 13–14; and Kosiak; Strategy for the Long Haul, 8.
71 Steven A. Fino, Tiger Check: Automating the U.S. Air Force Fighter Pilot in Air-to-Air Combat, 1950–1980 (Baltimore MD: Johns Hopkins University Press 2017), 15 and 262; and Michael G. Mattock et al., The Relative Cost-Effectiveness of Retaining Versus Accessing Air Force Pilots (Santa Monica CA: RAND Corporation 2019).
72 See, for example, Williams, Filling the Ranks; and Curtis Gilroy and Cindy Williams, Service to Country: Personnel Policy and the Transformation of Western Militaries (Cambridge MA: MIT Press 2007).
73 Kosiak, Strategy for the Long Haul, 8; Golding and Adedeji. The All-Volunteer, 13–14; Biddle and Long, ‘Democracy and Military Effectiveness’; Robert Martinage, Towards a New Offset Strategy: Exploiting U.S. Long-Term Advantages to Restore U.S. Global Power Projection Capability (Washington DC: Centre for Strategic and Budgetary Assessment 2014); Tuck, Understanding, 55–76; King, The Combat Soldier, 24–39, 62–97; Lutz, ‘Who Joins the Military in the Post-9/11 Era’?.
74 Gilroy and Williams, Service to Country.
75 See, for example, David Kilcullen, The Accidental Guerrilla: Fighting Small Wars in the Midst of a Big One (New York NY: Oxford University Press 2009).
76 Mahnken, Technology, Kosiak, Strategy for the Long Haul; Sapolsky, Gholz and Talmadge, US Defence Politics, 27–42; Lindsay, ‘Reinventing the Revolution’. On the demographic composition of Special Forces, see Appendix C in supplementary material.
77 In the early phase of the war in Afghanistan, for instance, an entire US Navy SEAL team was exterminated when, by changing the batteries of its laser pointer, the user called for close-air support over and mistakenly provided the geospatial coordinates of his own position rather than of the intended target. James Hasik, Arms and Innovation: Entrepreneurship and Alliances in the Twenty- First Century Defense Industry (Chicago IL: University of Chicago 2008), 70.
78 Andrea Gilli and Mauro Gilli, ‘The Diffusion of Drone Warfare? Industrial, Infrastructural, and Organizational Constraints’, Security Studies 25/1 (Winter 2016), 50–84.
79 Brooks-Gunn and Duncan, ‘The Effects of Poverty’; Campbell, et al., ‘Early Childhood Investments’; and Noble, et al., ‘Family Income’; and Randall K. Q. Akee, et al., ‘Parents’ Incomes and Children’s Outcomes: A Quasi-Experiment’, American Economic Journal: Applied Economics 2/1 (2010), 86–115.
80 Petrill, et al., ‘Genetic and Environmental’; M. J. Farah, et al., ‘Childhood poverty: Specific associations with neurocognitive development’, Brain Research, 1110 19/1 (2006), 166–174; Beckett, et al., ‘Do the Effects of Early’; Dahl and Lance Lochner, ‘The Impact of Family Income on Child Achievement’; Hair, et al., ‘Association of Child Poverty, Brain Development, and Academic Achievement’; Noble, et al., ‘Family Income’.
81 Campbell, et al., ‘Early Childhood Investments,; and Noble, et al., ‘Family Income’.
82 See, for example, Guilherme Lichand, et al., ‘The Psychological Effects of Poverty on Investments in Children’s Human Capital’, Working Paper, https://www.econ.uzh.ch/dam/jcr:e677acab-0a12-4129-b535-4671646a47fd/PsychologyPoverty_Parenting.pdf.
83 Heckman, ‘The Economics of Inequality’; Heckman, Pinto and Savelyev, ‘Understanding’; and Joan L. Luby, ‘Poverty’s Most Insidious Damage: The Developing Brain’, JAMA Pediatrics 169/9 (September 2015), 810–811.
84 Pearl L. H. Mok, et al., ‘Family Income Inequalities and Trajectories Through Childhood and Self-harm and Violence in Young Adults: a Population-based, Nested Case-Control Study’, Lancet Public Health 10/3 (Oct. 2010), 498–507.
85 Brooks-Gunn and Duncan, ‘The Effects of Poverty’; Barbara L. Thompson, et al., ‘Prenatal exposure to drugs: effects on brain development and implications for policy and education’. Nature Reviews. Neuroscience 10/4 (2009), 303–312; Noble, et al., ‘Family Income’.
86 Sherry A. Tanumihardjo, et al., ‘Poverty, Obesity, and Malnutrition: An International Perspective Recognizing the Paradox’, Journal of the American Dietetic Association107/11 (2007), 1966–1972. This topic has entered the public discourse in the USA over the past decade, with increased attention towards inequality of opportunity between the richest and the poorest communities – with the introduction of an ‘adversity score’ in the Standardised Admission Test (SAT) being one step to take this aspect into consideration.
87 This should be the case because the U.S. military is interested in highly capable and highly motivated individuals (rather than in individuals who see the armed forces as career of last resort); because individuals coming from the poorest and least privileged segments of American society are less likely to meet the standards of the U.S. military; and hence because screening mechanisms are at play.
88 Jeffrey A. Kentor, et al., ‘The “New” Military and Income Inequality: A Cross National analysis’. Social Science Research 41/3 (2012), 514.
89 The population weights are provided by the U.S. Bureau of Labor Statistics, and are intended to allow researchers to calculate figures such as average income or percentage of people of Hispanic origin that are representative of the U.S. population rather than the sample of individuals included in the survey.
90 All results remain the same, and are often reinforced, if we include the National Guard in our sample. We thus reported the most conservative findings. The only exception is being born in the US. If we include the national guardsmen in the sample, we find that being born in the US has a positive effect on the probability of joining the military.
91 The NLSY79 data do not include wealth measures until 1985 hence we are not able to measure family wealth while the survey respondent is still living within its original family unit.
92 The long right tail of the wealth distribution explains the large difference in absolute values between the lower and upper boundaries of the 3rd and 4th quintiles. This finding is consistent with the large literature in economics measuring the inequality of wealth distribution in USA. See, for example, Piketty, Capital in the Twenty-Fist Century.
93 Fredland and Little, Socioeconomic Characteristics of the All Volunteer Force; MacLean and Parsons, ‘Unequal Risk’; and Lutz, ‘Who Joins the Military? A Look at Race’.
94 Kane ‘Who Bears the Burden’?; Lutz ‘Who Joins the Military in the Post-9/11 Era’?. We discuss Lutz findings more in depth in the robustness tests section.
95 This measure is generated by the NLS team combining scores in the Mathematical Knowledge (MK), Arithmetic Reasoning (AR), Word Knowledge (WK), and Paragraph Comprehension (PC) sections of the ASVAB, and adjusts for differences in age among the individuals at the time of the test. The formula is similar to the Armed Forces Qualification Test (AFQT) score generated by the Department of Defense for the NLSY79 cohort. This variable, however, reflects work done by the NLS programme staff and is not generated, nor endorsed, by the DoD.
96 The average AFQT score increased from the 53rd percentile in 1978 to the 59th percentile in 1998. In fact, ‘high-quality recruits’ (i.e., those who, according to the DoD, ‘have both graduated 965 from high school and score above the median on the AFQT’) increased from some 28% in 1977 to more than 60% in 1990 and throughout the 1990s remained between the range 55% and 65%. See respectively, John T. Warner and Beth J. Asch, ‘The Record and Prospects of the All-Volunteer Military in the United States’, Journal of Economic Perspectives 15/2 (2001), 169–192; and Kosiak, A Strategy for the Long Haul, 16.
97 Charles C. Moskos Jr. and John S. Butler, All That We Can Be: Black Leadership And Racial Integration The Army Way (New York NY: Basic Books 1997).
98 Fredland and Little, Socioeconomic Characteristics of the All Volunteer Force.
99 This result is consistent with numbers provided by the Department of Defense: in 2011 the group accounted for 15 percent of the civilian population aged 18–24, and 16 percent of recruits. Similarly, Hispanics constituted 19 percent of the civilian population and 17 percent of recruits (DoD 2011).
100 Kriner and Shen state explicitly that, according to their findings, African American communities suffered disproportionately low casualty rates in Iraq. Yet, this finding is inconsistent with their argument that the poor are more likely to join the military, an aspect that they fail to explain.
101 Family income and family wealth are scaled so that the coefficients in the regressions can be interpreted as the effect of a $100,000 increase in income (or wealth) on the probability of joining the military. The AFQT percentile measure is scaled so that the coefficient in the regression can be interpreted as the effect of a 10 point increase in AFQT percentile on the probability of joining the military.
102 Includes Texas, Oklahoma, Arkansas, Louisiana, Mississippi, Tennessee, Alabama, Kentucky, Georgia, Florida, South Carolina, North Carolina, West Virginia, Virginia, Maryland, DC, and Delaware. Department of Defense data shows an over-representation for the south of 20% compared to the national average 2006–2011.
103 Includes Illinois, Indiana, Iowa Kansas, Michigan, Minnesota, Missouri, Nebraska, Ohio, North Dakota, South Dakota, and Wisconsin.
104 Includes Washington, Oregon, California, Idaho, Nevada, Arizona, Utah, Montana, Wyoming, Colorado, and New Mexico.
105 Bacevich, The Limits, 140.
106 Note that for individuals in the 75th percentile of the skills distribution the marginal effect from cognitive skills is positive but very close to zero for family incomes between $120,000 and $165,000.
107 Mahnken, Technology, 7.
108 Mahnken, Technology, 7.
109 In Appendix D in supplementary material we provide a breakdown for each individual service, including also Air Force and Navy.
110 See, for example, Lizette Alvarez, ‘Army Giving More Waivers in Recruiting’, The New York Times, 14 Feb. 2007.
111 Officers are defined in the NLSY97 as those with a military pay grade at or above 10.
112 We excluded from the sample individuals who joined the military in 2002 or after. In our sample, however, 60% of individuals who joined the military did so in 2002 or later. This is driven by ageing: in 1998 only 35% of the sample was 17 or older; in 2000 75% of the sample was 17 or older. As the individuals in the sample get older, we would expect more of them to join the military. We have investigated the extent to which ageing might be confounding the effect of 9/11 and concluded that, controlling for age, a ‘9/11 effect’ is not driving our results. These results are reported in Appendix D in supplementary material.
113 Lutz, ‘Who Joins the Military? A Look at Race’; and Lutz, ‘Who Joins the Military in the Post-9/11 Era’?.
114 Lutz, ‘Who Joins the Military in the Post-9/11 Era’? Lutz adds, however, that ‘there is some evidence that those who join are somewhat disadvantaged to those who join. Those who serve in the military tend to come from public schools and have significantly lower grade point averages’.
115 Beth J. Asch, C. Christine Fair and M. Rebecca Kilburn, An Assessment of Recent Proposals to Improve the Montgomery GI Bill (Santa Monica CA: RAND Corporation 2000).
116 The GI Bill has coincided with the financial crisis and the resulting increase in unemployment, therefore it is difficult to properly assess its effect. Yet, combining different methods and data, A RAND report reached the conclusion summarised in the text. See Jennie W. Wenger, et al., Are Current Military Education Benefits Efficient and Effective for the Services? (Santa Monica CA: RAND Corporation 2017).
117 During the years of the Iraq war, these bonuses (especially for the Army) aimed at compensating the drop in applications. For an analysis, see Beth J. Asch, Paul Heaton, James Hosek, Francisco Martorell, Curtis Simon, John T. Warner, Cash Incentives and Military Enlistment, Attrition, and Reenlistment (Santa Monica CA: RAND Corporation 2010).
118 James Hosek, Beth J. Asch, Michael G. Mattock, Troy D. Smith, Military and Civilian Pay Levels, Trends, and Recruit Quality (Santa Monica CA: RAND Corporation 2018), 18–19, 37, 40–41.
119 Department of Defense, Population Representation.
120 E.g., Vasquez, ‘Shouldering’.
121 See, for example, Stephen D. Biddle, Afghanistan and the Future of Warfare: Implications for Army and Defense Policy (Carlisle, Pa.: Strategic Studies Institute, U.S. Army War College 2002); Biddle, Military Power; Stephen D. Biddle, ‘Speed kills? Reassessing the Role of Speed, Precision, and Situation Awareness in the Fall of Saddam’, Journal of Strategic Studies 30/1 (2007), 3–46.
122 See, for example, Mattock, et al., The Relative Cost-Effectiveness of Retaining Versus Accessing Air Force Pilots.
123 Heckman, ‘The Economics of Inequality’; Heckman, Pinto and Savelyev, ‘Understanding’; and Luby, ‘Poverty’s Most Insidious Damage’.
124 Elsa B. Kania, ‘Great Power Rivalry Is Also a War For Talent’, DefenseOne, 22 Apr. 2019.
125 Peter Wood, ‘PLA Attempts to Attract Higher-Quality Recruits’, ChinaBrief 17/12 (September 2017), 1-3.
Additional information
Notes on contributors
Andrea Asoni
Andrea Asoni is an associate principal at Charles River Associates; he holds a PhD in Economics from the University of Chicago. The views presented here are his own and do not necessarily reflect those of CRA or any CRA employee.
Andrea Gilli
Andrea Gilli is a Senior Researcher at NATO Defence College; he holds a PhD in Social and Political Sciences from the European University Institute. The views expressed here are his own do not represent those of NATO or of the NATO Defence College.
Mauro Gilli
Mauro Gilli is a Senior Researcher at the Center for Security Studies of the Swiss Federal Institute of Technology in Zurich, Switzerland (ETH-Zurich). He holds a PhD in Political Science from Northwestern University.
Tino Sanandaji
Tino Sanandaji is a Researcher at the Institute for Economic and Business History Research of the Stockholm School of Economics; he holds a PhD from the Harris School of Public Policy of the University of Chicago.