This review of the literature has attempted to capture the most relevant reserve studies to date. Now, more than ever before, reserve studies are becoming a high priority since the Iraq and Afghanistan conflicts have demanded so much reserve force support over the past 10 years. This brief literature review has provided a basis for the central themes that are essential to reserve behavior. It also marks the clear distinction of how
19 Armed Forces Qualification Test (AFQT) is an aptitude test which generates a composite of four core written tests given to new military recruits which measure knowledge across a group of typical high school- level academic disciplines. Scores are categorized into groups which indicate high quality and low quality recruits. AFQT categories 1-3A are considered high-quality recruits and AFQT categories 3B and below are considered low-quality.
and why certain techniques of attrition and retention focused studies are used and why.
Several conclusions can be made from this review.
A total force perspective should be utilized when studying reserve behavior.
Deployment tempo has significant effects on whether a reservist continues service inside their contract, and longer periods of activation also result in higher loss rates.
Enlisted members make up the preponderance of reserve deployments.
Mobilization characteristics are relevant to consider given the potential expectation to deploy outside the continental U.S. (CONUS) post-9/11. Current evidence supports that those who do not get deployed overseas have higher incidents of loss rate behavior.
Monetary and educational incentives and their effect on MCR retention should be considered. Studies suggest that offering more bonus options for reenlistment to include both higher monetary bonus payout, as well as, more bonus programs available for reservists to use, may help increase reserve continuation.
Comprehensively, several common relationships exist to include: demographics, education–level, paygrade, length of military service, geographic location, local economic conditions, fiscal year effects, and occupational specialties.
Intangible factors such as spousal and employer attitudes toward service, dissatisfaction with specific units, morale, leadership, and poor unit cohesion are relevant to consider when studying reserve retention and very difficult to measure using multivariate econometric models, which rely solely on observational data.
Valid model choice and statistical approach is crucial in estimating the effects of attrition, retention, or continuation. Continuation rate models seem to provide a better approach for examining reserve specific retention behaviors verses standard retention approaches.
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III. THEORETICAL MODELS OF RETENTION
The following sections consider theoretical models from an economic perspective.
Each model will be reviewed for its relevance to the retention behavior of reservists.
Section A will analyze the Annualized Cost of Leaving (ACOL) model, which considers the net monetary returns to continued military service. Section B will present the Expected Utility of Deployment model, which considers the monetary effects combined with the probability of deployment duration. Section C will consider Moonlighting Theory as an explanation for reserve behavior.
A. ANNUALIZED COST OF LEAVING
The Annualized Cost of Leaving (ACOL) model brings into consideration an individual’s civilian earnings versus military earnings and the expected decrease in earnings as a result of leaving. Additionally, it considers unemployment rates and net preference for civilian versus military life. A notable aspect of the ACOL model is that it accounts for the number of years previously spent in the military and, therefore, loss of time and experience needed for civilian employment. Hansen and Wenger (2005) summarized the ACOL model, which predicts that an individual will continue serving for y additional time so long as the following holds true:
t = Years of Previous Military Service y = Years of Service Beyond Present
Mi = Expected Military Compensation for the i-th Year of Service Ci = Expected Civilian Compensation for the i-th Year of Service
τ = Individual Relative Preference for Civilian vs. Military Employment As can be seen from the model, an individual’s “taste” for civilian employment is considered in the model as a negative factor in military continuation and is combined with their expected civilian earnings for the given year. In contrast, the expected military compensation is a positive factor in military continuation. The ACOL model predicts that an individual will remain in service so long as the individual’s benefits from military employment exceed those benefits yielded by civilian employment, where net benefits incorporate the individual’s taste for each occupational option.
Over the time covered in this specific study, unemployment rates and possible monetary benefits of deploying could increase an individual’s likelihood of military continuation based on the ACOL model. For example, if a reservist is unemployed or facing static civilian earnings for the future year, or some future period, there is a stronger probability of continuation.
During the Overlap-9/11 time period, it is hypothesized that the expectation of deployment is undetermined and therefore the “taste” for military employment may not be as strong of a factor. In comparison, for the Post-9/11 period, it is hypothesized that deployment constitutes a strong expectation and therefore the “taste” for military employment has become very specific. Consequently, the effect of τ could have increased during the Post-9/11 period.
In summary, the ACOL model helps describe the net expectation of a reservist’s continuation as based on their expected monetary benefits and the individual’s tastes for military and civilian employment. This model helps provide a foundation for specifying the multivariate models that will be estimated in this study.