An Analysis of the Effects of Military Service on Retirees' Civilian Earnings

Abstract

This thesis analyzes differences in earnings between U.S. military retired veterans and non-retired veterans with similar demographic characteristics. Using data from the 1987 National Survey of Veterans (SOVIII) Files, the analysis first examines the frequency distribution of the explanatory variables. It then employs Heckman's two stage regression technique to correct for the selectivity bias that distorts the estimates obtained using Ordinary Least Squares. A log-earnings model is specified based on human capital theory. The intent of the model is to measure the effects of retired versus non-retired veteran status on the post-service earnings of male veterans. The findings reveal a statistically significant loss of post-service income incurred by male retired veterans. It was also determined, however, that increases in education had a statistically significant effect on earnings for both retired and non- retired veterans. Applying the results of this U.S. study to the Republic of China (R.O.C.), it is recommended that the R.O.C. Armed Forces conduct a study to determine whether a similar post-retirement earnings deficit applies. If such an effect exists, policies might be developed to compensate for this effect, thereby contributing to obtaining the most highly qualified members of the career military. Military retired veterans, SOVIII, Selectivity bias correction.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1993
Accession Number
ADA277292

Entities

People

  • Tsung-ying Wang

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Data Analysis
  • Data Science
  • Data Sets
  • Databases
  • Descriptive Analytics
  • Education
  • Employment
  • Enlisted Personnel
  • Factor Analysis
  • Information Science
  • Military Education
  • Military Personnel
  • Military Training
  • Regression Analysis
  • Statistics
  • Students
  • Surveys

Readers

  • Naval Personnel Management
  • Regression Analysis.
  • Rehabilitation and Prosthetic Care for Military Service Members and Veterans with Limb Loss or Disability.