UC Berkeley

This dissertation investigates key aspects of the gender wage gap in the U.S.The first chapter studies whether there is a gender \ask gap", that is whether women with similar resume to men's ask for lower wages. This analysis relies on the innovative recruitment process of an online recruitment platform for full-time engineering jobs in the United States. To use the platform, job candidates must post their resume information as well as an ask salary, stating how much they want to make in their next job. Using data on more than 120,000 candidates over several years, I first document a 7.2% raw ask gap on the platform. After controlling for all the candidates' resume characteristics, the ask gap is 3.3%. In other words, women with resumes comparable to those of men ask for 3.3% less. The second chapter investigates the relationship between the gender ask gap and the gender wage gap. In this chapter, I leverage the fact that, on the recruitment platform, firms apply to candidates by offering them a bid salary, solely based on the candidate's resume and ask salary. Additionally, if the candidate is hired, a final salary is recorded. Using data on more than 510,000 bids, I find a raw bid gap on the platform of 3.4%. Adjusting for candidates' resume characteristics but excluding their ask salary leaves a 2.4% residual bid gap. When candidates' ask salaries are included as a control, this residual bid gap disappears. In other words, while resume characteristics can only reduce the bid gap by 30%, gender differences in ask salaries can essentially explain 100% of the bid gap. For the sub-sample of 8,333 hired candidates, gender differences in ask salaries explain nearly all of the gap in final offers. In particular, while conditioning on resume characteristics only narrows the final offer gap to 1.8%, adding the ask salary to the controls yields an insignificant final offer gap of -0.5%. I find no evidence of discrimination against women at the extensive margin. In fact, conditional on their resume characteristics, women get slightly more bids than men and, conditional on interviewing, women are just as likely as men to get a final offer. The third chapter estimates the market-level effects of an increase in women's ask salaries, leveraging an unanticipated feature change on the platform. In mid-2018, Hired.com abruptly changed the way that some candidates were prompted to provide their ask salary. From the first year of the data to mid-2018, candidates stated their ask salary by filling out an empty text box. Starting in mid-2018, the answer box for San Francisco software engineers was pre filled with the median bid salary over the past 12 months for the candidate's combination of desired location, job title, and experience. In effect, this change gave candidates information on the typical offers received by similar candidates on the platform and provided them with an anchor to benchmark their own ask salary. Using an interrupted time series design, I show that the new framing of the ask salary elicitation eliminated the ask gap and rendered the bid gap insignificant. These results are mostly driven by women asking for higher salaries after the reform. Further, I find no discernable impact on the number of bids that women received or the time it took women to receive their first bid, suggesting that women had effectively been leaving money on the table.