ABSTRACT We study the financial and labor market impacts of bad credit reports. Using difference‐in‐differences variation from the staggered removal of bankruptcy flags, we show that bankruptcy flag removal leads to economically large increases in credit limits and borrowing. Using administrative tax records linked to personal bankruptcy records, we estimate economically small effects of flag removal on employment and earnings outcomes. We rationalize these contrasting results by showing that, conditional on basic observables, “hidden” bankruptcy flags are strongly correlated with adverse credit market outcomes but have no predictive power for measures of job performance.

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.

Abstract We analyze the effect of exposure to international trade on earnings and employment of U.S. workers from 1992 through 2007 by exploiting industry shocks to import competition stemming from China’s spectacular rise as a manufacturing exporter paired with longitudinal data on individual earnings by employer spanning close to two decades. Individuals who in 1991 worked in manufacturing industries that experienced high subsequent import growth garner lower cumulative earnings, face elevated risk of obtaining public disability benefits, and spend less time working for their initial employers, less time in their initial two-digit manufacturing industries, and more time working elsewhere in manufacturing and outside of manufacturing. Earnings losses are larger for individuals with low initial wages, low initial tenure, and low attachment to the labor force. Low-wage workers churn primarily among manufacturing sectors, where they are repeatedly exposed to subsequent trade shocks. High-wage workers are better able to move across employers with minimal earnings losses and are more likely to move out of manufacturing conditional on separation. These findings reveal that import shocks impose substantial labor adjustment costs that are highly unevenly distributed across workers according to their skill levels and conditions of employment in the pre-shock period.

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.

In 2008, a group of uninsured low-income adults in Oregon was selected by lottery for the chance to apply for Medicaid. Using this randomized design and 2009 administrative data, we find no significant effect of Medicaid on employment or earnings. Our 95 percent confidence intervals allow us to reject that Medicaid causes a decline in employment of more than 4.4 percentage points, or an increase of more than 1.2 percentage points. Medicaid increases food stamps receipt, but has little, if any, impact on receipt of other measured government benefits, including SSDI.

Abstract We use a massive, matched employer-employee database for the United States to analyze the contribution of firms to the rise in earnings inequality from 1978 to 2013. We find that one-third of the rise in the variance of (log) earnings occurred within firms, whereas two-thirds of the rise occurred due to a rise in the dispersion of average earnings between firms. However, this rising between-firm variance is not accounted for by the firms themselves but by a widening gap between firms in the composition of their workers. This compositional change can be split into two roughly equal parts: high-wage workers became increasingly likely to work in high-wage firms (i.e., sorting increased), and high-wage workers became increasingly likely to work with each other (i.e., segregation rose). In contrast, we do not find a rise in the variance of firm-specific pay once we control for the worker composition in firms. Finally, we find that two-thirds of the rise in the within-firm variance of earnings occurred within mega (10,000+ employee) firms, which saw a particularly large increase in the variance of earnings compared with smaller firms.