Key Takeaways
Representative samples make it hard to separate women's preferences from constraints because they mix in part-time and weakly attached workers. Using a panel of over 3,400 GMAT registrants from the 1990s — career-motivated men and women with comparable ambition and prior investment in business human capital — we examine how cognitive ability, non-cognitive traits, stated job-attribute preferences, and "skill balance" relate to self-employment participation and earnings, estimated separately by gender.
The traits associated with entering self-employment differ from those associated with succeeding in it, and the patterns differ by gender. Non-cognitive traits and balanced skills predict women's participation, but quantitative skills predict their self-employment earnings. Work-life balance and job-characteristic preferences predict men's participation, but balanced non-cognitive traits predict their earnings. In traditional employment, the same traits raise earnings for both groups — the divergence is specific to self-employment.