The magnitude of and heterogeneity in systematic earnings risk has important implications for various theories in macro, labor, and financial economics. Using administrative data, we document how the aggregate risk exposure of individual earnings to GDP and stock returns varies across gender, age, the worker's earnings level, and industry. Aggregate risk exposure is U-shaped with respect to the earnings level. In the middle of the earnings distribution, aggregate risk exposure is higher for males, younger workers, and construction and durable manufacturing. At the top of the earnings distribution, aggregate risk exposure is higher for older workers and finance.

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.