What Do Data on Millions of U.S. Workers Reveal About Life-Cycle Earnings Risk?

71 Pages Posted: 2 Feb 2015 Last revised: 8 Feb 2015

See all articles by Fatih Guvenen

Fatih Guvenen

University of Minnesota - Department of Economics; National Bureau of Economic Research (NBER)

Jae Song

U.S. Social Security Administration

Serdar Ozkan

University of Toronto

Fatih Karahan

Federal Reserve Bank of New York

Multiple version iconThere are 3 versions of this paper

Date Written: January 2015

Abstract

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 from lognormality---the standard assumption in the incomplete markets literature. In particular, earnings shocks display strong negative skewness and extremely high kurtosis---as high as 30 compared with 3 for a Gaussian distribution. The high kurtosis implies that in a given year, most individuals experience very small earnings shocks, and a small but non-negligible number experience very large shocks. Second, these statistical properties vary significantly both over the life cycle and with the earnings level of individuals. We also estimate impulse response functions of earnings shocks and find important asymmetries: positive shocks to high-income individuals are quite transitory, whereas negative shocks are very persistent; the opposite is true for low-income individuals. Finally, we use these rich sets of moments to estimate econometric processes with increasing generality to capture these salient features of earnings dynamics.

Suggested Citation

Guvenen, Fatih and Song, Jae and Ozkan, Serdar and Karahan, Fatih, What Do Data on Millions of U.S. Workers Reveal About Life-Cycle Earnings Risk? (January 2015). NBER Working Paper No. w20913. Available at SSRN: https://ssrn.com/abstract=2558965

Fatih Guvenen (Contact Author)

University of Minnesota - Department of Economics ( email )

Minneapolis, MN 55455
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Jae Song

U.S. Social Security Administration ( email )

Washington, DC 20254
United States
202-358-6403 (Phone)
202-358-6192 (Fax)

Serdar Ozkan

University of Toronto ( email )

Toronto, Ontario M5S 3G8
Canada

Fatih Karahan

Federal Reserve Bank of New York ( email )

33 Liberty Street
New York, NY 10045
United States

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