Document Type
Capstone Project
Publication Date
5-21-2026
Publication Title
UNLV Undergraduate Economics Working Paper Series
Publisher
University of Nevada, Las Vegas
Publisher Location
Las Vegas (Nev.)
Volume
3
Issue
1
First page number:
1
Last page number:
14
Abstract
This study analyzes the gender wage gap in metropolitan versus rural areas using U.S. hourly wage data from the Bureau of Labor Statistics (BLS), for the period 2010-2025. The analysis uses regressions on a semi-log wage model and Blinder-Oaxaca decompositions to compare the gaps and separate the effects attributable to explained (endowment) differences from those attributable to unexplained (coefficient) differences. The semi-log wage model reveals a percentage wage decrease for females of approximately 17.4% in rural areas and 9.9% in metropolitan areas. The Blinder-Oaxaca decompositions further indicate that the unexplained (coefficient) component of the gap is substantially larger in rural areas than in metropolitan areas, while the explained (endowment) component is similar across the two areas. In conclusion, the gender wage gap persists in both rural and metropolitan areas and is more pronounced in rural areas—a pattern consistent with, though not direct proof of, greater wage discrimination in rural labor markets.
Keywords
Gender wage gap; rural areas; metropolitan areas; hourly wage; labor market discrimination
Disciplines
Benefits and Compensation | Economics | Labor Relations | Management Sciences and Quantitative Methods
File Format
File Size
306 KB
Language
English
Rights
IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/
Repository Citation
Gonzalez, A.,
Montano, M.,
Sacks, B.,
Williams, J.
(2026).
Do Rural Areas Gender-Discriminate Wages More than Metropolitan Areas?.
UNLV Undergraduate Economics Working Paper Series, 3(1),
1-14.
Available at:
http://dx.doi.org/10.34917/40601195
Included in
Benefits and Compensation Commons, Economics Commons, Labor Relations Commons, Management Sciences and Quantitative Methods Commons