An Analysis of the Effect of Using Lump Sum Payments for the U. S. Marine Corps Selective Reenlistment Bonus Program

Abstract

This thesis examines the estimated effects on enlisted retention in the Marine Corps of changing the Selective Reenlistment Bonus (SRB) payment method to lump sum. The thesis surveys the literature on personal discount rates (PDR) and on models of enlisted retention. The thesis analyzes the potential effect of the payment method on retention of Zone A eligible personnel using a range of PDRs and retention elasticities estimated by the Center for Naval Analyses. The NPV of a lump sum payment was compared to that of the current payment method using the actual SRB multiples for each USMC Occupational Field. The results indicate Zone A first-term Marine retention will increase between 6.8 percent and 11.7 percent if the SRB payment were made in lump sum. The effect of switching to a lump sum payment was also analyzed using the Annualized Cost of Leaving (ACOL) model. The ACOL model estimates reinforced the estimates predicted by this thesis. Finally, a Monte Carlo simulation was run in Microsoft Excel to estimate the probabilities of attaining a given number of Marines across all Occupational Fields. The Monte Carlo simulation runs show an increased probability of obtaining a given number of first-term Marines by changing the SRB payment method to lump sum.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2000
Accession Number
ADA377395

Entities

People

  • David L. Ross

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Basic Programming Language
  • Business Administration
  • Computer Programs
  • Congress
  • Economic Analysis
  • Employment
  • Enlisted Personnel
  • Management Personnel
  • Military Personnel
  • Monte Carlo Method
  • Organizational Structure
  • Simulations
  • Spreadsheet Software
  • Surveys
  • United States
  • Warfare

Readers

  • Computational Modeling and Simulation
  • Government Contracting/Procurement.
  • Naval Personnel Management