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The Distribution of Annual and Long-Run US Earnings, 1981-2004


Michael V. Leonesio


Social Security Administration - Office of Research, Evaluation and Statistics

Linda Del Bene


Social Security Administration - Office of Research, Evaluation and Statistics

February 4, 2011

Social Security Bulletin, Vol. 71, No. 1, pp. 17-33, 2011

Abstract:     
Numerous authors have presented evidence of increased dispersion in the distribution of annual earnings in the United States from the late 1970s through 2004 or later. However, the dispersion of long-run earnings measured over many years has received relatively little attention because of the limited availability of appropriate data. This article uses the Social Security Administration’s Continuous Work History Sample, which documents the earnings histories of 3.3 million workers, to examine changes in both the annual and the long-run distributions of earnings during 1981-2004 for men and women. For men, the results indicate an increase in long-run earnings inequality of roughly the same magnitude as the trend seen in annual earnings dispersion, but there has been very little increase in the dispersion of long-run earnings among women. If calculations are restricted to a sample of women who work every year of the observation period, a trend of increased earnings dispersion emerges, but much less so than that observed for men.

Number of Pages in PDF File: 17

Keywords: Earnings Distribution, Inequality

JEL Classification: D31, J3

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Date posted: February 12, 2011  

Suggested Citation

Leonesio, Michael V. and Del Bene, Linda, The Distribution of Annual and Long-Run US Earnings, 1981-2004 (February 4, 2011). Social Security Bulletin, Vol. 71, No. 1, pp. 17-33, 2011. Available at SSRN: http://ssrn.com/abstract=1760013

Contact Information

Michael V. Leonesio (Contact Author)
Social Security Administration - Office of Research, Evaluation and Statistics ( email )
Washington, DC
United States
Linda DelBene
Social Security Administration - Office of Research, Evaluation and Statistics ( email )
Washington, DC 20254
United States
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