Selection Into Employment and the Gender Wage Gap Across the Distribution and Over Time

36 Pages Posted: 14 Jan 2020

See all articles by Patricia Gallego-Granados

Patricia Gallego-Granados

German Institute for Economic Research (DIW Berlin)

Katharina Wrohlich

DIW Berlin, German Institute for Economic Research

Multiple version iconThere are 2 versions of this paper

Date Written: January 2020

Abstract

Using quantile regression methods, this paper analyses the gender wage gap across the wage distribution and over time (1990-2014), while controlling for changing sample selection into full-time employment. Our findings show that the selection-corrected gender wage gap is much larger than the one observed in the data, which is mainly due to large positive selection of women into fulltime employment. However, we show that selection-corrected wages of male and female workers at the lower half of the distribution have moderately converged over time. The reason for this development have been changes in the composition of the male full-time employment force over time, which in spite of the rather constant male full-time employment rate, have given place to a small but rising selection bias in male observed wages. In the upper half of the wage distribution, however, neither the observed nor the selection-corrected gender wage gap has narrowed over time.

Keywords: Gender wage gap, quantile regression, selection into employment

JEL Classification: J31, J21

Suggested Citation

Gallego-Granados, Patricia and Wrohlich, Katharina, Selection Into Employment and the Gender Wage Gap Across the Distribution and Over Time (January 2020). DIW Berlin Discussion Paper No. 1838. Available at SSRN: https://ssrn.com/abstract=3518323 or http://dx.doi.org/10.2139/ssrn.3518323

Patricia Gallego-Granados

German Institute for Economic Research (DIW Berlin) ( email )

Mohrenstra├če 58
Berlin, 10117
Germany

Katharina Wrohlich (Contact Author)

DIW Berlin, German Institute for Economic Research ( email )

Mohrenstra├če 58
Berlin, 10117
Germany

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