Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/120829 
Year of Publication: 
2015
Series/Report no.: 
Staff Report No. 710
Publisher: 
Federal Reserve Bank of New York, New York, NY
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 literature on incomplete markets. 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.
Subjects: 
earnings dynamics
life-cycle earnings risk
nonparametric estimation
kurtosis
skewness
non-Gaussian shocks
normal mixture
JEL: 
E24
J24
J31
Document Type: 
Working Paper

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