Abstract
To prevent discrimination, the U.S. Navy enlisted-personnel promotion process relies primarily on objective measures. However, it also uses the subjective opinion of a sailor’s superior. The Navy’s promotion and retention process involves two successive decisions: The Navy decides whether to promote an individual, and conditional on that decision, the sailor decides whether to stay. Using estimates of these correlated decision-making processes, we find that during 1997–2008, Blacks and Hispanics were less likely to be promoted than Whites, especially during wartime. The Navy’s decision-making affects Blacks’ differential promotion rates by twice as much as differences in the groups’ characteristics. However, Nonwhite retention probabilities, even when not promoted, are higher than for Whites, in part because they have fewer opportunities in the civilian market. Females have lower promotion rates than males and slightly lower retention rates during wartime.
Highlights
Can the U.S Navy prevent the race- and sex-based glass ceilings that are rife in civilian labor markets? To combat such discrimination, the U.S Navy has instituted formal job evaluations for its enlisted personnel [1]
One factor is subjective: an evaluation by the sailor’s superior. Does this one subjective factor result in promotion rates that vary by race, ethnicity, or sex? If the Navy’s formal, primarily objective, system works, it can provide a model for other employers
To investigate whether promotion and retention rates vary by race, ethnicity, and gender, we present the first consistently estimated promotion and retention model
Summary
Can the U.S Navy prevent the race- and sex-based glass ceilings that are rife in civilian labor markets? To combat such discrimination, the U.S Navy has instituted formal job evaluations for its enlisted personnel [1]. The Navy bases promotions to ranks E4 through E7 on an individual’s Final Multiple score, a pay grade-specific value for each individual in each promotion period. The two equations contain some common demographic variables Variables in both equations include: a sailor’s Armed Forces Qualifications Test (AFQT) percentile score; education variables; whether a sailor is currently on sea duty, a separate dummy variable for each current pay grade, E4, E5, and E6; race-ethnicity and sex dummies; and time dummies. The S1 Appendix provide a detailed data dictionary and a further discussion on the data and model used
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