Benjamín Villena, with fellow researcher Sekyu Choi of the University of Bristol, are studying gender differences in preferences over jobs.

By defining consideration sets of job ads for applicants using a traditional network formulation, several dimensions of jobs are documented, which attract, on average, females more than males, such as female-wanted, remote work, inclusive policies, and minority recruiting. In contrast, job complexity (measured as the content of adjectives in the ad text) deters female applications more than males'. Background similarity between workers' last/current occupation and job ad title also spur applicants but do less for females. These preferences are also related for inclusivity (and other dimensions) to gender gaps in what job seekers expect to earn in narrowly defined labor markets and show that, while all individuals with higher wage expectations prefer inclusive policies, this is stronger for women. Finally, a social-interaction effects model also allows to estimate that applicants prefer jobs with fewer expected applications, a notably more significant effect for females.