Abstract
We analyze the underlying source of gender differences in earnings estimates on a crowdsourcing platform, Estimize, to understand the mechanisms driving analyst ability. Estimates made by females are more accurate than those made by males. This outperformance is not consistent with explanations based on females’ innate ability to process information, females utilizing more up-to-date information, superior stock selection among females, copycat estimates, gender bias, or survivorship bias. Instead, our evidence is consistent with females learning more quickly through making estimates, leading to their outperformance.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
