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The Effect of 21st Century Military Service on Civilian Labor and Educational Outcomes

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Abstract

I estimate the effect of military service during the Afghanistan and Iraq wars on civilian labor and educational outcomes using several empirical methodologies including sibling fixed effects and propensity score matching. Since military occupations and training have changed significantly in the past few decades, these effects may be different than those found in previous studies on veterans of earlier theaters. I find that veteran status increases civilian wages by approximately ten percent for minorities but has little or no effect on whites in this regard. Veterans of all demographic groups are found to be equally employable and equally as satisfied with their civilian occupation as non-veterans. For females and minorities, veteran status substantially increases the likelihood one attempts college. These veterans are found to be more apt to pursue and obtain a two year (associate’s) degree instead of a four year (bachelor’s) degree. Lastly, I find mixed evidence that veteran status increases the likelihood of public sector employment.

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Notes

  1. As of January 31, 2013, there were 1,429,995 active duty personnel in the U.S. armed forces with an additional 850,880 personnel in the reserves (U.S. Department of Defense 2013).

  2. For clarification, my treatment samples only include those individuals who served on active duty, not in the reserves, during the wars in Afghanistan and/or Iraq.

  3. Among the methodologies used are comparisons of summary statistics (e.g., Villemez and Kasarda 1976), ordinary least squares (e.g., Fredland and Little 1980; Bryant and Wilhite 1990), fixed effects (e.g., Teachman 2004), instrumental variables (e.g., Angrist 1990; Angrist and Krueger 1994; Teachman and Call 1996) and matching techniques (Hirsch and Mehay 2003; Angrist 1998).

  4. The R package twang (Toolkit for Weighting and Analysis of Nonequivalent Groups) was used to calculate the propensity scores in the models presented here. All models were also re-estimated using propensity scores obtained from logistic regression (as a robustness check) and similar results were found.

  5. For a more detailed analysis of these weights, I direct the reader to Wooldridge (2002), Hirano and Imbens (2001), and McCaffrey et al. (2004).

  6. In the interest of full disclosure, all tables relate veteran sample sizes.

  7. In a supplemental analysis, I also use data from the CPS July 2010 Veterans Supplement. See Section “Discussion and Conclusions”.

  8. Raw NLSY97 data suggests that Iraq and Afghan veterans fared equally as well as non-veterans during the recession in terms of wages and weeks worked. For example, veterans and non-veterans worked on average36.0 and 37.7 weeks and earned an hourly wage of $20.12 and $21.62 during 2008, respectively. These differences are not statistically different with respective p-values from t-tests of mean equality being 0.136 and 0.795. Wages and weeks worked for 2009 were also not statistically different across veteran status.

  9. In the original data, this variable is coded in descending order (where 1 represents extremely satisfied and 5 extremely dissatisfied). I recode the variable in ascending order for ease of interpretation.

  10. In my secondary data (presented in Section “Discussion and Conclusions”), however, I do find statistically-significant differences regarding public sector employment as well as suggestive results that veteran status is causing these differences.

  11. Several previous studies (e.g., Brien 1997 and DaVanzo and Rahman 1993) have noted that whites tend to marry at younger ages.

  12. In the whites-only sub-sample, individuals are effectively exactly matched on race. Thus, race variables are not used as controls or in the matching procedure but were used in the minorities analysis as this sample contains multiple races. Similarly, in the within-gender analysis, the two samples are exactly matched on gender.

  13. In her study of childhood residences, Haurin (1992) finds that maternal age when the child is born is associated with several of the child’s young adult outcomes such as the likelihood of high school completion, teen pregnancy, and serious illegal activities.

  14. Eighteen is the youngest age one typically enlists in the armed forces. Technically, one may enlist in the armed forces at 17 years of age with parental consent. However, few volunteers are 17 years of age.

  15. Various types of exercise are staples of military training. Youths who already exercise regularly will be better prepared for military training. Youths that enjoy frequent exercise may be more likely to enlist. Unlike height, weight, and health status, exercise habit data was not collected every survey year. I use the data available to construct a measure of exercise for the year closest to, but not over, 18 years of age.

  16. Also unfortunately, missingness was too high to investigate veteran wages using this data and the survey did not collect information on job satisfaction or number or jobs.

  17. The controls used in these models are listed in the Table 7 notes.

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Acknowledgments

I thank Joachim Zietz, Mark F. Owens, Charles L. Baum II, Adam D. Rennhoff, Christian Brown, Karen Mulligan, Carolyn M. Wolff, and two anonymous referees for their insight and suggestions.

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Correspondence to P. Wesley Routon.

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Routon, P.W. The Effect of 21st Century Military Service on Civilian Labor and Educational Outcomes. J Labor Res 35, 15–38 (2014). https://doi.org/10.1007/s12122-013-9170-4

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