Employer Learning, Statistical Discrimination and Occupational Attainment
构建模型分析雇主学习和统计歧视如何影响初始就业率、工资和职业类型，以及整个职业生涯中的工资增长和职业变化，发现市场可能因早期低技能工作而延迟识别高技能工人。
I examine the implications of employer learning and statistical discrimination for initial employment rates, wages, and occupational attainment and for wage growth and occupational change over a career using a model in which the sensitivity of productivity to worker skill is increasing in the skill requirements of the job and in which employers learn about worker skill more rapidly in high skill jobs. I show that statistical discrimination influences initial employment rates, wage levels and job type, and that employers' initial estimate of productivity influences wage growth even in an environment in which access to training is not an issue. The implication is that the market may be slow to learn that a worker is highly skilled if worker's best early job opportunity given the information available to employers is a low skill level job that reveals little about the worker's talent.