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.

Drawing on administrative data from the Social Security Administration, we find that individuals that go through a long period of non-employment suffer large and long-term earnings losses (around 35-40 percent) compared to individuals with similar age and previous earnings histories. Importantly, these differences depend on past earnings, and are largest at the bottom and top of the earnings distribution. Focusing on workers that are employed 10 years after a period of long-term non-employment, we find much smaller earnings losses (8-10 percent). Furthermore, the large earnings losses of low-income individuals are almost entirely due to employment effects.

We propose a simple explanation for the long-run decline in the US start-up rate. It originates from a slowdown in labor supply growth since the late 1970s, largely predetermined by demographics. This channel can explain roughly half of the decline and why incumbent firm survival and average growth over the life cycle have changed little. We show these results in a standard model of firm dynamics and test the mechanism using cross-state variation in labor supply growth. Finally, we show that a longer entry rate series imputed using historical establishment tabulations rises over the 1960s–1970s period of accelerating labor force growth.

We develop a method to jointly measure the response of worker search effort (micro effect) and vacancy creation (macro effect) to changes in the duration of unemployment insurance (UI) benefits. To implement this approach, we exploit an unexpected cut in UI durations in Missouri and provide quasi-experimental evidence on the effect of UI on the labor market. In our baseline specification, the data indicate that the cut in Missouri increased job-finding rates by 12% by raising firm vacancy creation and the search effort of unemployed workers. Both channels contribute roughly equally to the total effect.

The U.S. economy has been going through a striking structural transformation--the secular reallocation of employment across sectors--over the past several decades. We propose a decomposition framework to assess the contributions of various margins of firm dynamics to this shift. Using firm-level data, we find that at least 50 percent of the adjustment has been taking place along the entry margin, due to sectors receiving different shares of startup employment than their employment shares. The rest is mostly due to life cycle differences across sectors. Declining overall entry has a small but growing effect of dampening structural transformation.

We investigate the importance of job-to-job (JJ) transitions for cyclical wage dynamics. By exploiting cross-state variation, we find that wage growth is tightly linked to variation in the JJ transition probability, and conditional on this, the job finding probability of the unemployed has no explanatory power. We investigate the robustness of our results to several caveats and find the result to hold. Finally, we discuss the implications of our findings for competing theories of wage dynamics.