Kevin Bryan

Abstract

Do good startups have difficulty hiring because workers find it hard to evaluate their quality? We recruit 26 science-based startups making an early business hire to use a custom job board, and invite roughly 20,000 business school alumni to apply. The job board randomizes at the applicant level to show coarse expert ratings of all startups' science quality, business model quality, both, or neither: we induce a market-level shift in the precision of information. Making this information visible strongly reallocates applications toward higher quality firms: applications rise 12-31% to firms where positive information was shown, and fall 9-24% when negative information is shown. Stated another way, firms with above average quality along both dimensions see 11% more applications than those with below average quality in the control, but 89% more when workers receive coarse information about business and science quality. Incentivized surveys indicate that worker beliefs about positive growth outcomes for startups are affected by both information dimensions.