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Does the military turn men into criminals? New evidence from Australia’s conscription lotteries


In this paper, we estimate the effect of military service on the perpetration of crime. Several hypothesized links exist between service and crime, but recent quasi-experimental studies on this subject have produced mixed results. Our contribution to this literature uses Australia’s Vietnam era conscription lotteries for identification along with criminal court data from Australia’s three largest states. We find no evidence that military service increases or decreases crime in any category. In our preferred specification, the 95 % confidence interval rules out positive (negative) effects larger than 11 % (10 %) relative to the mean crime rate.

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  1. See also Paloyo et al. (2010) for an analysis of the effect of military bases on local crime rates.

  2. A 16th birth cohort also was subjected to a National Service lottery in September 1972. However, the conscription system was abolished before they were due to be called up. Thus, we ignore the 16th cohort.

  3. One interesting aspect of the Australian veterans’ benefits system is that the reduced incentive to engage in formal work is fully compensated by generous pensions. Very large negative employment effects are accompanied by a zero average effect on income (Siminski and Ville 2012; Siminski 2013). Thus, veterans have much more free time to potentially allocate to illegal activity. But any such illegal activity is not motivated by poverty.

  4. Veterans’ compensation may also affect crime negatively if payment eligibility is affected by criminal convictions. In Australia, disability compensation payments are unaffected by criminal convictions. Veterans’ income support (including the service pension), however, is not paid while a person is imprisoned, similarly to related civilian pensions.

  5. In 1971, the full-time component was reduced to 18 months, with the army-reserve period raised to 3.5 years. In December 1972, all requirements of conscripts were cancelled by a new government.

  6. The “ballot outcome” is the outcome of the relevant conscription lottery drawing. A man is considered to be “balloted-in” if his DOB was drawn in the ballot held for his birth cohort, and “balloted-out” otherwise. Being “balloted-in” is referred to as “draft eligible” in the American literature.

  7. Using just-identified models, the standard errors of the key estimates are approximately 5 % (1 %) larger for the 15-cohort (3-cohort) specification.

  8. We think this is likely to be only a minor threat to validity. The incarceration rate of Australian men in these age groups is 0.23 % (ABS 2013), almost five times lower than in the USA (Guerino et al. 2012). Further, such a dynamic requires the existence of short-run effects. As we have discussed, the international literature on the crime effects of service has produced mixed results, and there is no data on short-run effects for Australia.

  9. While crime rates are highest at younger ages, the types of crimes committed by males do not differ greatly by age, at least not for offenses that are brought to court. The largest differences are between males under age 20 and over 20 (see for example ABS 2014: Table 5). However, middle-aged male defendants are somewhat less likely to be tried for robbery, unlawful entry, theft, property damage, or public order offenses and more likely to be tried for traffic/vehicle offenses and sexual assault.

  10. A case is a set of one or more offenses heard on the same date for the same defendant. Our results are not sensitive to analyzing offenses rather than cases, but they are less precise because the distribution of the number of offenses within cases is highly skewed.

  11. The ASOC codes for drunk driving offenses are 411 and 1431. Property offenses have four-digit ASOC codes ranging from 0600 to 1030. They include robbery, extortion and related offenses; unlawful entry with intent/burglary, break, and enter; theft and related offenses; fraud, deception, and related offenses; and illicit drug offenses (excluding possession, use, or miscellaneous drug offenses).

  12. The coefficients on the instruments are smaller than those previously reported (for example in Siminski 2013), which reflects the inclusion of recent migrants in the data here.

  13. The estimates from the just-identified specifications are similar to those from the overidentified specifications but are slightly less precise.

  14. The violent crime effects that Lindo and Stoecker (2014) find are statistically significant only for periods soon after military service. Similar to our results, their estimates for later periods are statistically insignificant.


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We are grateful to two anonymous referees, Joshua Angrist, William N. Evans, Jason M. Lindo, Alfredo R. Paloyo, Joan R. Rodgers and seminar participants at the Melbourne Institute of Applied Economic and Social Research, the University of Technology Sydney, the University of Queensland, the University of Tasmania, and the University of Wollongong for discussions and comments. We thank Daniel Thomason for excellent research assistance. For criminal court data, we are grateful to NSW BOCSAR, the Queensland Department of Justice and Attorney-General, and the Victorian Department of Justice. We acknowledge grant support from the Australian Research Council (LP100100417 and DE120101642) and the Department of Veterans’ Affairs. The views expressed in this paper are the authors’ alone, as are any errors of fact or omission.

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Correspondence to Peter Siminski.

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Responsible editor: Erdal Tekin



Table 5 2SLS estimates for alternate categories of crime: all 15 birth cohorts (models with two endogenous variables)

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Siminski, P., Ville, S. & Paull, A. Does the military turn men into criminals? New evidence from Australia’s conscription lotteries. J Popul Econ 29, 197–218 (2016).

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  • Crime
  • Military service
  • Australia

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  • I12
  • J45