Measuring links between labor monopsony and the gender pay gap in Brazil

Measuring links between labor monopsony and the gender pay gap in Brazil This paper focuses on gender differences in job mobility and earnings for workers in Brazil. Monopsony theory suggests a link between the wage elasticity of labor supply and wage penalties. Should one group of workers be less elastic in their supply choices, that group is predicted to earn less than others. To measure wage elasticity, I estimate a hazard model on voluntary job separations using the RAIS, a linked employer-employee dataset that captures formal-sector workers’ job durations over time. Four models are specified and point to significant gender differences. Across the models, male elasticity ranges from 1.638 to 2.175 while female elasticity ranges from 1.22 to 1.502. The female wage penalty predicted by these elasticity differences ranges from 11.4 to 20.5%, compared to an actual gender wage difference of 16.4%. Results of higher male elasticity are robust to the use of a more parsimonious specification, a discrete-time approach, the use of job spell data for a single year, and disaggregation by region. I extend the model through decomposition methods to help clarify the association between earnings, job separations, and elasticity. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png IZA Journal of Migration Springer Journals

Measuring links between labor monopsony and the gender pay gap in Brazil

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Publisher
Springer Berlin Heidelberg
Copyright
Copyright © 2017 by The Author(s)
Subject
Economics; Population Economics; Labor Economics; Migration; Demography
eISSN
2520-1786
D.O.I.
10.1186/s40176-017-0099-x
Publisher site
See Article on Publisher Site

Abstract

This paper focuses on gender differences in job mobility and earnings for workers in Brazil. Monopsony theory suggests a link between the wage elasticity of labor supply and wage penalties. Should one group of workers be less elastic in their supply choices, that group is predicted to earn less than others. To measure wage elasticity, I estimate a hazard model on voluntary job separations using the RAIS, a linked employer-employee dataset that captures formal-sector workers’ job durations over time. Four models are specified and point to significant gender differences. Across the models, male elasticity ranges from 1.638 to 2.175 while female elasticity ranges from 1.22 to 1.502. The female wage penalty predicted by these elasticity differences ranges from 11.4 to 20.5%, compared to an actual gender wage difference of 16.4%. Results of higher male elasticity are robust to the use of a more parsimonious specification, a discrete-time approach, the use of job spell data for a single year, and disaggregation by region. I extend the model through decomposition methods to help clarify the association between earnings, job separations, and elasticity.

Journal

IZA Journal of MigrationSpringer Journals

Published: Aug 10, 2017

References

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