ABSTRACT Research shows that, holding qualifications equal, women are less willing than men to apply for certain high-paying jobs. I experimentally investigate whether the “gender application gap” for high-paying jobs depends on the presence or magnitude of application costs. I randomly vary the cost of applying for such a job: subjects in an online stylized labor market experiment face no marginal cost, pay a fee, or write a cover letter. Men are significantly more likely than equally qualified women to apply for a job only when the marginal cost of applying is zero. This arises from gender differences in self-selection: women prefer not to apply when unskilled regardless of costs, whereas unskilled men drop out only when tangible costs are introduced. Women face a higher intangible cost from applying for a job they’re likely to perform poorly at, especially if the job is in a stereotypically “male-typed” domain. While fees modestly increase women's share of hires through applicant self-selection, cover letters reduce women's share of hires and appear to bias recruiters against women applicants.

ABSTRACT Conventional wisdom states that women are less willing than men to apply for a job for which they feel only partly qualified. Is this due to gender differences in anticipated returns to meeting or exceeding the desired level of qualification for a job? In a series of studies, I investigate whether men and women rate more and less qualified candidates’ chances of being hired differently. In the lab, I elicit beliefs about callback and offer likelihood by having subjects “bet” on the outcomes of other applicants' job searches. In a stylized online labor market experiment, I observe subjects' job application decisions and elicit beliefs regarding how qualified they will appear to a recruiter. Across studies, I find that women anticipate the same or greater returns than men to moving from "not at all'' to "somewhat'' qualified for a position, but the same or lower returns to moving from "somewhat'' to fully or "highly'' qualified. Controlling for gender differences in willingness to rate one's own or others' resumes as qualified does not change the pattern of results. Consistent with these findings, women in my experiment do not differ from men in how likely they are to apply if they fulfill some, but not all, of the listed qualifications in a job posting.

ABSTRACT When workers from underrepresented groups choose not to take on more challenging, higher-paying work, income gaps arise. Bias affects how employers interpret negative productivity signals from workers, such as mistakes made on the job. Thus, workers may rationally avoid transitioning into jobs in which they would face discriminatory consequences for making mistakes, even if their overall productivity is expected to be high. Simultaneously, variation in behavioral traits such as risk aversion or other-regarding preferences have also been shown to influence group differences in job choice. Do workers from underrepresented groups take disproportionate action to avoid failure on the job, such as not taking on “higher risk, higher reward” work? If so, what proportion of any resultant gaps in job choice is due to anticipated discrimination? In a stylized online labor market experiment, we randomly vary the potential consequences for failure on the job and the ability of employers to discriminate, and observe how this affects minority workers' willingness to take on more challenging work. In a follow-up field study, we test whether extending the "probationary" period for new workers could help attract a more diverse group of qualified applicants for a job.

ABSTRACT In order to be classified as unemployed, one must not only be out of work but also actively looking for a new job. Household surveys that collect employment status differ in their implicit assumption of whether respondents understand what it means to "actively" look for work, and also differ in the unemployment estimates they produce. Evidence from historical survey redesigns suggests that how exactly a survey asks about job search affects the share of the non-employed who are classified as unemployed, but the role of design cannot be fully disentangled in observational data from the role of differences in other survey features, such as sampling frame or response mode. In this paper, we estimate the causal impact of search question design on unemployment measurement by randomly varying the questions used to measure active job search within a single online federal survey. We find differences in active search rates -- and thereby in unweighted "unemployment" rates -- by approach. Giving respondents additional instructions on what counts as “actively” looking for work produces comparable results to simply asking respondents to report all their search activities, suggesting a potential lower-burden alternative for surveys looking to capture a CPS-style unemployment concept with fewer questions.

ABSTRACT Increasingly, international trade policy analysis explores the economic effects of changes in ad-valorem tariffs or equivalent nontariff measures on vertically integrated markets for which high quality data are unavailable. Standard Constant Elasticity of Substitution (CES) Armington models fail to account for either vertical linkages or parameter uncertainty. Here, we introduce a vertically integrated, nested two-sector Armington model that incorporates uncertainty in the estimates of Armington elasticities through Monte Carlo simulation. As an illustrative case, we model the effects of changes in country of origin labeling (COOL) rules on the market shares of cattle in the U.S. beef market. By accounting for parameter uncertainty in this way, we are able to estimate the distribution of potential effects of repealing mandatory COOL. Ultimately, we predict that, in all but the most extreme cases, Mexico and Canada would not gain as much market share from the repeal of mandatory COOL as they claim in their World Trade Organization (WTO) filings against the regulation.