Empirical Biases and Some Remedies in Estimating the Effects of Selective Reenlistment Bonuses on Reenlistment Rates

Researchers have, for decades, been attempting to estimate the effects of Selective Reenlistment Bonuses (SRBs) on the probability of reenlistment for the military services. SRBs are targeted to specific military occupations for which reenlistment rates are lower (or expected to be lower) than what is needed. This article first identifies four primary sources of biases affecting these models: reverse causality from supply shifts (a negative bias), the endogeneity of the decision point causing coded SRBs to be higher for reenlisters than leavers (a positive bias), measurement error (a likely negative bias), and excess supply preventing the full effect of an SRB change to materialize (a positive or negative bias). The report proceeds to develop a model that attempts to address the first two biases. With U.S. Navy data from FY2001-FY2008, I examine the extent to which these two biases are affecting the estimated SRB effects. Despite these corrections, the difficulty of addressing the other biases calls into doubt studies that examine the effects of retention bonuses or even the effects of the structure of military pay in general.     

Workplace goals and output quality: evidence from time-constrained recruiting goals in the US navy

This paper examines how workplace goals affect the quality of worker output, using data from the recruiting command of the US Navy. Recruiting stations and recruiters are assigned monthly goals for the quantity of new recruits that may create an unintended incentive to sacrifice quality, especially towards the end of the month. Using data on the universe of Navy recruits from FY1998 to 2010, we find significant reductions in the quality of recruits towards the end of the contracting month, both in terms of pre-existing quality of recruits and in medium-term outcomes that reflect the quality of the job match.     

British Strategy and the Struggle with France 1793–1815

This article examines the various constraints under which the conduct of British strategy operated during the French Wars – examples include its political and geographical situation, its far-flung colonial interests and its limited military resources and its need to maintain a strong alliance system in continental Europe – and shows how the direction that it took closely mirrored a variety of campaigns in the eighteenth century. That said, the position in which Britain found herself in the struggle against the French Revolution and Napoleon was frequently contradictory, and it is no coincidence that it was some time before the ideal combination of strategies was found that marked the period 1808–14. The fact that the difficulties involved were overcome said a great deal for the underlying strength of the British state.     

The Impact of the Unemployment Rate on Attrition of First-Term Enlistees

This study examines the effects of home-state unemployment rates on attrition behavior of Navy enlistees for successive career windows during the first term of service: the first 6?months, the second 6?months, the second year, and the third year of service. The results indicate that attrition is negatively associated with changes in the local unemployment rate during the first three career windows covering two years of service. However, after two years of service, the estimated effect of the unemployment rate becomes insignificant for most groups of sailors. This is likely because sailors with the poorest job matches are sorted out early in the first term of service.     

Algorithm to solve a chance‐constrained network capacity design problem with stochastic demands and finite support

We consider the problem of determining the capacity to assign to each arc in a given network, subject to uncertainty in the supply and/or demand of each node. This design problem underlies many real‐world applications, such as the design of power transmission and telecommunications networks. We first consider the case where a set of supply/demand scenarios are provided, and we must determine the minimum‐cost set of arc capacities such that a feasible flow exists for each scenario. We briefly review existing theoretical approaches to solving this problem and explore implementation strategies to reduce run times. With this as a foundation, our primary focus is on a chance‐constrained version of the problem in which α% of the scenarios must be feasible under the chosen capacity, where α is a user‐defined parameter and the specific scenarios to be satisfied are not predetermined. We describe an algorithm which utilizes a separation routine for identifying violated cut‐sets which can solve the problem to optimality, and we present computational results. We also present a novel greedy algorithm, our primary contribution, which can be used to solve for a high quality heuristic solution. We present computational analysis to evaluate the performance of our proposed approaches. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 236–246, 2016