Missing Women in Tech: The Labor Market for Highly Skilled Software Engineers

Abstract

This paper examines the behavior of job seekers and recruiters in the labor market for software engineers. I obtained data from a recruiting platform where individuals can self-report their computer programming skills and recruiters can message individuals they wish to contact about job opportunities. I augment this data set with measures of each individual’s previous programming experience based on analysis of actual computer source code they wrote and shared within the open-source software community. This novel data set reveals that candidates’ self-reported technical skills are quantitatively important predictors of recruiter interest. Consistent with social psychology and behavioral economics studies, I also find female programmers with previous experience in a programming language are 11.07% less likely than their male counterparts to self-report knowledge of that programming language on their resume. Despite public pronouncements, however, recruiters do not appear more inclined toward recruiting female candidates who self-report knowing programming languages. Indeed, recruiters are predicted to be 6.47% less likely to express interest in a female candidate than a male candidate with comparable observable qualifications even if those qualifications are very strong. Ultimately, a gender gap in the self-reporting of skills on resumes exists; but recruiters do not appear to be adjusting their response to such signals in ways that could increase the representation of women among software engineering recruits. This paper was accepted by Yan Chen, behavioral economics and decision analysis.

The Gender Gap in Self-Promotion

“…Given that individuals typically communicate their performance and ability to others in subjective terms (e.g., asserting that they are "good" at math) rather than in more precise terms (e.g., asserting that they fall in the 90th percentile of math ability according to some observable metric), one may be particularly concerned about a gender gap in self-promotion that relates to such subjective descriptions. Indeed, prior work shows that women are less likely to report being "proficient" or "skilled" in programming languages on their resumes (Murciano-Goroff, 2021), are less likely to use "positive" words in their titles and abstracts for papers on clinical research (Lerchenmueller, Sorenson and Jena, 2019), and are more likely to use narrow topic-specific-rather than broad-words in their research grant proposals (Kolev, Fuentes-Medel and Murray, 2019). 1 However, research on self-promotion that relates to how individuals subjectively communicate their performance and ability-the ubiquitous type of self-promotion that we focus on in this paper-faces three distinct challenges.…”

Salary History and Employer Demand: Evidence from a Two-Sided Audit

“…We show that these are not only interpreted as a signal of candidate quality, but also as signals about the competitive landscape. In short, 3 Other examples include the propensity to apply for a job given the number of other applicants (Gee, 2019), the choice to disclose skills (Murciano-Goroff, 2017), the decision to reapply to an employer following a rejection (Brands and Fernandez-Mateo, 2017), and the choice to negotiate wages (Laschever and Babcock, 2003;Biasi and Sarsons, 2020).…”

“… Exley et al (2020) similarly studies negotiation costs by gender, including indirect costs of unsuccessful negotiations.5 Murciano-Goroff (2017) says that evidence about anticipation is "lacking" (p. 3). The most closely related papers regarding anticipation areReuben et al (2014),Exley and Kessler (2019) andMurciano- Goroff (2017). These papers report limited evidence of anticipation using laboratory(Reuben et al, 2014), online subject pools (Exley and Kessler, 2019), and observational (Murciano-Goroff, 2017) designs.…”

The Gender Gap in Tech & Competitive Work Environments? Field Experimental Evidence from an Internet-of-Things Product Development Platform

“…To date, there has been considerably less scholarly attention-and particularly systematic empirical research-devoted to gender gaps in the tech sector 1 -this, despite the economic importance of this sector and conspicuous coverage of gender and tech in the popular media (e.g., Chang, 2018). (For exceptions, see : Fernandez & Campero, 2017;Lambrecht & Tucker, 2018;Murciano-Goroff, 2018;Wynn & Correll, 2017. ) Gaining more empirically-grounded understanding of explanations for the gender gap in tech might point to effective interventions-and perhaps then also means of moderating the "leaky pipeline" of native-born technical workers (US BLS, 2017).…”