Identifying and Overcoming Gender Barriers in Tech: A Field Experiment on Inaccurate Statistical Discrimination

Jan Feld, Edwin Ip, Andreas Leibbrandt and Joseph Vecci
Additional contact information
Edwin Ip: Department of Economics, University of Exeter
Joseph Vecci: Department of Economics, University of Gothenburg

No 2205, Discussion Papers from University of Exeter, Department of Economics

Abstract: Women are significantly underrepresented in the technology sector. We design a field experiment to identify statistical discrimination in job applicant assessments and test treatments to help improve hiring of the best applicants. In our experiment, we measure the programming skills of job applicants for a programming job. Then, we recruit a sample of employers consisting of human resource and tech professionals and incentivize them to assess the performance of these applicants based on their resumes. We find evidence consistent with inaccurate statistical discrimination: while there are no significant gender differences in performance, employers believe that female programmers perform worse than male programmers. This belief is strongest among female employers, who are more prone to selection neglect than male employers. We also find experimental evidence that statistical discrimination can be mitigated. In two treatments, in which we provide assessors with additional information on the applicants' aptitude or personality, we find no gender differences in the perceived applicant performance. Together, these findings show the malleability of statistical discrimination and provide levers to improve hiring and reduce gender imbalance.

Keywords: inaccurate beliefs; discrimination; gender; field experiment (search for similar items in EconPapers)
JEL-codes: C93 D90 J71 (search for similar items in EconPapers)
Date: 2022-09-16
New Economics Papers: this item is included in nep-exp, nep-gen, nep-hrm and nep-lma
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://exetereconomics.github.io/RePEc/dpapers/DP2205.pdf (application/pdf)

Related works:
Working Paper: Identifying and Overcoming Gender Barriers in Tech: A Field Experiment on Inaccurate Statistical Discrimination (2022)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:exe:wpaper:2205

Access Statistics for this paper

More papers in Discussion Papers from University of Exeter, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Sebastian Kripfganz ().