Labor market sorting on personality traits and the gender wage gap

ABSTRACT

Gender sorting in the labor market can explain a major part of the gender wage gap. This paper documents the association between the gender wage gap and labor market sorting into jobs characterized by their requirements to personality traits. Two thirds of the Danish gender wage gap from 2008 to 2015 explained by occupational sorting can be explained by characterizing occupations by their requirements to personality traits. This amounts to around a quarter of the gender wage gap explained by these nonpecuniary occupational characteristics. In particular, men are awarded for working in jobs that require higher levels of disagreeableness

KEYWORDS:

• Gender pay gap
• labor market sorting
• personality traits
• nonpecuniary occupational characteristics

JEL CLASSIFICATION:

• J31
• J16

Acknowledgments

I gratefully acknowledge support from The Danish Council for Independent Research - Social Sciences, grant DFF 1327-00119B. The usual disclaimer applies.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

¹ I use version 23.0 of the O*NET database, constructed by the U.S. Department of Labor. The dataset is based on a mixture of survey information from job incumbents and expert assessments. It consists of ratings of a variety of occupational attributes, which are important for job performance. Occupations are described by the skills and knowledge required, how the work is performed, and typical work settings. See Peterson et al. (2001) and https://www.onetcenter.org/overview.html for documentation.

² The results in this paper should be interpreted as evidence of gender sorting on job characteristics and not as gender sorting on individual traits. The measures of job requirements on personality traits are related to individual traits to the extent that the labor market matches skill bundles of workers to occupational skill requirements. Guvenen et al. (Forthcoming) provides evidence that worker-firm skill matches are often not observed in the data.

³ Imputing missing occupational codes based on workplace, education, and age do not affect the conclusions.

⁴ See Table 1 for the list of controls.

Additional information

Funding

This work was supported by the Samfund og Erhverv, Det Frie Forskningsråd [DFF 1327-00119B].