We study the evolution of individual labor earnings over the life cycle using a large panel data set of earnings histories drawn from U.S. administrative records. Using fully nonparametric methods, our analysis reaches two broad conclusions. First, earnings shocks display substantial deviations...

This paper studies the cyclical nature of individual income risk using a confidential dataset from the U.S. Social Security Administration, which contains (uncapped) earnings histories for millions of individuals. The base sample is a nationally representative panel containing 10 percent of all...

We study the determinants of lifetime earnings (LE) inequality in the United States, for which differences in lifetime earnings growth are key. Using administrative data and focusing on the roles of job ladder dynamics and on-the-job learning, we document that:1) lower LE workers change jobs...

We study the determinants of lifetime earnings (LE) inequality in the United States, for which differences in lifetime earnings growth are key. Using administrative data and focusing on the roles of job ladder dynamics and on-the-job learning, we document that 1) lower LE workers change jobs...

We study the determinants of lifetime earnings (LE) inequality in the U.S. by focusing on job ladder dynamics and on-the-job learning as sources of wage growth. Using administrative data, we document that i) lower LE workers change jobs more often, which is mainly driven by nonemployment; ii)...

Recent empirical studies document that the distribution of earnings changes displays substantial deviations from lognormality: in particular, earnings changes are negatively skewed with extremely high kurtosis (long and thick tails), and these non-Gaussian features vary substantially both over...