Estimating Dynamic Models of Quit Behavior: The Case of Military Reenlistment.

Abstract

We estimate the effect of financial incentives for reenlistment on military retention rates using a stochastic dynamic programming model. We show that the computational burden of the model is relatively low even when estimated on panel data with unobserved heterogeneity. The estimates of the model show strong effects of military compensation, especially of retirement pay, on retention rates. We also compare our model with simpler-to-compute models and find that all give approximately the same fit but that our dynamic programming model gives more plausible predictions of policy measures that affect military and civilian compensation at future dates. We use our model to simulate the effect of recent changes by the military aimed at reducing reenlistment rates.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1993
Accession Number
ADA361127

Entities

People

  • Robert Moffitt
  • Thomas Dayka

Organizations

  • United States Military Academy

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Compensation
  • Computer Programming
  • Databases
  • Dynamic Programming
  • Enlisted Personnel
  • Heterogeneity
  • Management Personnel
  • Military Personnel
  • Operations Research
  • Organizational Structure
  • Personnel Management
  • Personnel Retention
  • Probability
  • Recruiting
  • Reenlistment
  • Simulations
  • United States Military Academy

Fields of Study

  • Mathematics

Readers

  • Computational Modeling and Simulation
  • Naval Personnel Management