Estimating Trends in U.S. Income Inequality Using the Current Population Survey
The Importance of Controlling for Censoring

Visiting Scholar Richard Burkhauser
Visiting Scholar Richard Burkhauser

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Abstract

Using internal and public use March Current Population Survey (CPS) data, we analyze trends in U.S. income inequality (1975-2004). We find that the upward trend in income inequality prior to 1993 significantly slowed thereafter once we control for top coding in the public use data and censoring in the internal data. Because both series do not capture trends at the very top of the income distribution, we use a multiple imputation approach in which values for censored observations are imputed using draws from a Generalized Beta distribution of the Second Kind (GB2) fitted to internal data. Doing so, we find income inequality trends similar to those derived from unadjusted internal data. Our trend results are generally robust to the choice of inequality index, whether Gini coefficient or other commonly-used indices. When we compare our best estimates of the income shares held by the richest tenth with those reported by Piketty and Saez (2003), our trends fairly closely match their trends, except for the top 1 percent of the distribution. Thus, we argue that if United States income inequality has been substantially increasing since 1993, such increases are confined to this very high income group.

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Richard Burkhauser is a visiting scholar at AEI. Shuaizhang Feng is an assistant professor of economics at the Shanghai University of Finance and Economics. Stephen P. Jenkins is a professor of economics at the University of Essex. Jeff Larrimore is a graduate student in economics at Cornell University.

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About the Author

 

Richard
Burkhauser
  • Richard Burkhauser's research focuses on how public policies affect the economic behavior and well-being of vulnerable populations, e.g., older persons, people with disabilities, and low-income households. He has published widely on these topics in journals of demography, economics, gerontology, as well as public policy.

  • Email: rvb1@cornell.edu

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