Army Reserve Enlisted Aggregate Flow Model

摘要

Recent world events have affected the rates at which the United States Army Reserve (USAR) recruits and retains enlisted members. As these rates fluctuate, it becomes difficult for the USAR to forecast its recruiting requirements. This thesis describes a statistical model and an associated software tool designed to provide precise forecasts of aggregate USAR enlisted personnel trends. In particular, the tool can assist in forecasting specific USAR enlisted end strength requirements using aggregate accession, retention and attrition rates. Entitled the Army Reserve Enlisted Aggregate Flow Model (AREAFM), the tool uses a Markov Growth Model and, for the purposes of this thesis, it is standardized using fiscal year 2001 (FY01) through FY03 data and validated with FY04 data. The AREAFM is intended for annual use in forecasting the number of enlisted accessions required to achieve USAR end strength. The model can also be used to evaluate how adjustments in accession, promotion and attrition rates, perhaps as the result of changes in USAR manpower policies or current events, might affect the assigned strength.