| A persistent problem for the Navy has been the uneven inflow of recruits over the course of the year. Accessions are much higher in the summer months than the rest of the year. This uneven flow of new recruits into basic training facilities imposes several negative effects on the Navy, such as the inability to fill key personnel billets when shortages occur in certain seasonal periods. One of the attempts by the Navy to smooth the flow of recruits into the training pipeline is to implement a program called Targeted Enlistment Bonus (EB). The bonus amount is allocated inversely proportional to the popularity of seasons, and thus provides an incentive for recruits to access in the off-peak seasons. But the effect of EB is complicated by another major form of enlistment incentive, the Navy College Fund (NCF). The Navy College is constant across all season (in the sample), so those who choose it are not enticed to access in the off-peak season. This dissertation analyzes the effectiveness of the EB program and behavior of recruits, and estimates the EB allocations that yield a level-loading of accessions. It applies two discrete choice models, the Multinomial Conditional Logit Model and the Nested Multinomial Logit Model, to the Delayed Entry Program (DEP), using sample data on recruits who select the nuclear rating over the time period 1994 to 1996. The estimated coefficients can be used to predict aggregate accession probabilities as well as serve as a means to set the enlistment incentive that achieves a desirable accession pattern. |
