A multivariate times series analysis of US Army recruiting
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Authors
Burger, Eric C.
Subjects
Advisors
Buttrey, Samuel E.
Date of Issue
2000-06
Date
June, 2000
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
The United States Army Recruiting Command requires tools to quantify the impact of factors in the recruiting environment, identify differences in the recruiting processes across its five regional subordinate units, and measure the effectiveness of its policies and resource expenditures. This thesis examines recruiting data for the "high-quality" male demographic from July 1992 to September 1997. It uses multivariate time series analysis to predict the number of enlistment contracts signed in a month as a function of fifteen exogenous and endogenous factors plus monthly indicators. A stepwise recursion using bootstrap simulation is developed to identify significant factors in the multivariate time series. The significant factors in the reduced models are compared to those contained in models developed in previous studies. The models are also used to create nine- month projections of recruiting production, which are compared to known production figures from test set data to determine forecast accuracy. The results of this research support the intuition that the influential factors differ by region. The stepwise model reduction recursion using bootstrap simulation offers potential for further refinement and application.
Type
Thesis
Description
Series/Report No
Department
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
xviii, 91 p.:map;28 cm.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.