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Racial/Ethnic Pay Disparities among Registered Nurses (RNs) in U.S. Hospitals: An Econometric Regression Decomposition

Keywords: Regression decomposition; racial/ethnic wage disparities; minority RNs.

Objective: To detect the presence of racial and ethnic pay disparities between minority and white hospital RNs using a national sample.

Data Sources/Study Setting: The National Sample Survey of Registered Nurses, 2008, which is representative at both the state and national level.

Study Design: Cross-sectional data were analyzed using multivariate regression and regression decomposition. Differences between groups were decomposed into differences in the possession of characteristics and differences in the value of the same characteristic between different groups, the latter being a commonly used measure of wage discrimination.

Data Collection/Extraction Methods: As the majority of minority hospital RNs are employed within the most densely populated (central) counties of metropolitan statistical areas (MSAs), only hospital RNs employed in the central counties of MSAs were selected.

Principal Findings: Regression decomposition found that black and Hispanic RNs earned less than whites and Asians, while Asian RNs earned more than white RNs. The majority of pay variation between white RNs, versus Asian, black, or Hispanic RNs was due to unexplained differences in the value of the same characteristic between groups.

Conclusions: Differences in earnings between underrepresented and overrepresented hospital RNs is suggestive of discrimination.

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