Abstract
How much of the gender wage gap can be attributed to statistical discrimination? Applying an employer learning model and Instrumental Variable (IV) estimation strategy to Japanese panel data, I examine how women's generally weak labor force attachment affects wages when employers cannot easily observe an individual's labor force intentions. To overcome endogeneity issues, I use survey information on individual workers' intentions to continue working after having children and Japanese panel data with exogenous variation in average quit rates for female workers. I find that the extent of statistical discrimination is greatest for young age cohorts, ages 24 to 35, and that it diminishes for older cohorts. I also find that if employers could observe an individual's labor force intentions, the gender wage gap could be reduced from 17% to 5% for workers aged 24 to 29.