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 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...

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 individual 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....

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)...

Using panel data on individual earnings histories from 1957 to 2013, we document empirical facts about the distribution of lifetime earnings in the United States. First, from the cohort that entered the labor market in 1957 to the cohort that entered in 1983, median lifetime earnings of men...

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...