Using Survivor Functions to Estimate Occupation-Specific Bonus Effects

by Daniel F. Kohler

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This study reports on the development of a new type of model for estimating the effect of reenlistment bonuses on retention in the armed forces. The new model, based on estimating a survivor function, presents two major improvements over the way in which bonus effects have traditionally been analyzed: (1) lag and lead effects of bonuses can be identified, and (2) bonus effects can be estimated for individual specialties. Past analyses of survivor functions were used to explain retention behavior over time for one specific cohort. In this report, the approach is modified to allow analysis of several cohorts simultaneously, and to permit differential influences of some variables, most notably reenlistment bonuses paid at the first expiration of term of service, on different segments of the survivor function. This study substantiates the finding that bonus-induced reenlistees have lower reenlistment rates at the second reenlistment point. It also shows, however, that the expectation of a bonus tends to reduce attrition toward the end of the first term, leading to more individuals reaching the first reenlistment point.

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