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Random effects meta analysis of military recruiting

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  • Sohn, S. Y.

Abstract

The success of the US military recruiting depends not only on recruiting efforts but also on the labor market conditions. In this paper we review the econometric literature that examined the effects of marketing as well as recruiting effort on high quality enlistment contracts in the 1980s. A random-effects meta analysis is used to examine the systematic variation across studies of advertising, recruiter effort, and unemployment rate elasticities. The result of a meta analysis indicates that (1) the estimated effect of unemployment rate on military recruiting does not vary significantly over several military recruiting studies; (2) the average elasticity of high quality contract with respect to unemployment rate is estimated as 0.48; (3) elasticities of high quality contract with respect to advertising and recruiter forces are influenced by individual study characteristics; (4) although the Army recruiter elasticity (0.43) turns out to be higher than advertising elasticity (0.15), Army advertising appears to cost slightly less than recruiter forces on average when an additional contract is needed. However, this cost difference is not significant.

Suggested Citation

  • Sohn, S. Y., 1996. "Random effects meta analysis of military recruiting," Omega, Elsevier, vol. 24(2), pages 141-151, April.
    • Handle: RePEc:eee:jomega:v:24:y:1996:i:2:p:141-151
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    1. Kostiuk, Peter F & Follmann, Dean A, 1989. "Learning Curves, Personal Characteristics, and Job Performance," Journal of Labor Economics, University of Chicago Press, vol. 7(2), pages 129-146, April.
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    4. C. A. Knox Lovell & Richard C. Morey, 1991. "The Allocation of Consumer Incentives to Meet Simultaneous Sales Quotas: An Application to U.S. Army Recruiting," Management Science, INFORMS, vol. 37(3), pages 350-367, March.
    5. Cyril E. Kearl & David K. Horne & Curtis L. Gilroy, 1990. "Army Recruiting In A Changing Environment," Contemporary Economic Policy, Western Economic Association International, vol. 8(4), pages 68-78, October.
    6. Riddington, GL, 1993. "Time varying coefficient models and their forecasting performance," Omega, Elsevier, vol. 21(5), pages 573-583, September.
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    Cited by:

    1. So Young Sohn, 2000. "Multivariate meta analysis with potentially correlated marketing study results," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(6), pages 500-510, September.
    2. S Y Sohn & H Choi, 2006. "Random effects logistic regression model for data envelopment analysis with correlated decision making units," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(5), pages 552-560, May.
    3. Sohn, So Young & Kim, Hong Sik, 2007. "Random effects logistic regression model for default prediction of technology credit guarantee fund," European Journal of Operational Research, Elsevier, vol. 183(1), pages 472-478, November.

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