Changing Income Risk across the US Skill Distribution: Evidence from a Generalized Kalman Filter
结合卡尔曼滤波和EM算法，估计每个个体每时点的持久和暂时收入，发现自1980年代以来持久收入风险上升12.5%，失业疤痕效应翻倍，且上升集中在高技能工人，与技术采用相关。
For whom has earnings risk changed, and why? We answer these questions by combining the Kalman filter and EM algorithm to estimate persistent and temporary earnings for every individual at every point in time. We apply our method to administrative earnings linked with survey data. We show that since the 1980s, persistent earnings risk rose by 12.5 percent for both employed and unemployed workers and the scarring effects of unemployment doubled. At the same time, temporary earnings risk declined. Using education and occupation codes, we show that rising persistent earnings risk is concentrated among high-skill workers and related to technology adoption.