What Do Data on Millions of U.S. Workers Reveal About Lifecycle Earnings Dynamics?
中文摘要
我们利用覆盖数百万美国劳动者的面板数据，研究男性个体在整个生命周期中的收入动态。首先，使用非参数方法，我们表明收入变动的分布表现出对对数正态性的大幅偏离，例如负偏度和极高的峰度。此外，这些非正态性的程度随年龄和收入水平显著变化，在50岁左右以及收入分布的第70至第90百分位之间达到峰值。其次，我们估计了非参数脉冲响应函数，并发现了重要的不对称性：高收入个体的正向变动相当短暂，而负向变动则非常持久；对低收入个体而言恰好相反。第三，我们转向长期结果，发现在25岁至55岁之间，收入的累积增长率和个体未就业的总年数存在显著的异质性。最后，通过以这些丰富的矩条件为目标，我们估计了从简单到复杂的各种收入随机过程。我们偏好的设定对持久性成分和暂时性成分均采用了正态混合新息，并包含了状态依赖的长期未就业冲击，其实现概率随年龄和收入而变化。
Abstract
We study individual male earnings dynamics over the life cycle using panel data on millions of U.S. workers. Using nonparametric methods, we first show that the distribution of earnings changes exhibits substantial deviations from lognormality, such as negative skewness and very high kurtosis. Further, the extent of these nonnormalities varies significantly with age and earnings level, peaking around age 50 and between the 70th and 90th percentiles of the earnings distribution. Second, we estimate nonparametric impulse response functions and find important asymmetries: Positive changes for high‐income individuals are quite transitory, whereas negative ones are very persistent; the opposite is true for low‐income individuals. Third, we turn to long‐run outcomes and find substantial heterogeneity in the cumulative growth rates of earnings and the total number of years individuals spend nonemployed between ages 25 and 55. Finally, by targeting these rich sets of moments, we estimate stochastic processes for earnings that range from the simple to the complex. Our preferred specification features normal mixture innovations to both persistent and transitory components and includes state‐dependent long‐term nonemployment shocks with a realization probability that varies with age and earnings.