Economists have long explored the social phenomenon known as homophily, or the tendency to associate with those who share similar traits, even if such an inclination is costly. Like attracts like, it seems, but is that always the case? Gary Becker’s seminal 1957 book, The Economics of Discrimination, laid the groundwork for thinking about this phenomenon by developing theories of taste-based discrimination. However, even after decades of research, important questions remain.
This paper studies whether homophily by gender is driven by preferences for shared traits within the context of mentorship, a setting where—unlike hiring or lending or renting—explicitly using race, gender, and nationality to determine matches is common, encouraged, and even considered best practice. Among the top 50 US News college/universities, all but two host a mentorship program designed specifically for women in STEM fields, and 80% of the programs match students with a same-gender mentor. Do mentees value same-gender mentors? Or does demand for same-gender mentors arise from a lack of information on mentor quality?
Using novel administrative data from an online college students/alumni mentoring platform serving eight colleges and universities, the authors find the following:
These findings are consistent with taste-based discrimination, that is, female students incurring a cost to access a female mentor. But what if researchers cannot control for all mentor attributes used in students’ decisions? Students, for example, could use information outside of the mentoring platform to decide whom to contact, leading to omitted variable bias. To address this, the authors designed a survey that incentivizes truthful responses, and they find the following:
The authors then investigate whether female students’ preference for female mentors reflects taste-based discrimination, which could arise from female students’ affinity for interacting with women, or from valuing an attribute that only female mentors possess, to find:
This work has several important implications, including regarding employee recruitment initiatives, service-provider matching, and doctor-patient matching that commonly use shared traits as a coarse proxy for match quality. These efforts may be well-intentioned, but they could also lead to efficiency losses relative to those that incorporate information on valued traits into the matching process.