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Any opinions and conclusions expressed herein are those of the authors and do not necessarily represent the views of the U.S. Census Bureau. All results have been reviewed to ensure that no confidential information is disclosed. the referees, for their helpful comments and suggestions on earlier versions of this paper. Abstract Although most research on US income inequality trends is based on public-use March CPS data, a new wave of research using IRS tax return data reports substantially higher levels of inequality and faster growing trends for recent years. We show that these apparently inconsistent estimates are largely reconciled when the income distribution and inequality are defined in the same way. Using internal CPS data for 1967-2006, we show that estimates of top income shares based on internal CPS data for 1967-2006 are similar in many respects to the IRS data-based estimates reported by Piketty and Saez (2003). Our results imply that changes in US income inequality since 1993 are largely driven by changes in the share of the top 1 percent.

We analyze trends in US size-adjusted household income inequality between 1975 and 2004 using the most commonly used data source -the public use version of the March Current Population Survey. But, unlike most researchers, we also give substantial attention to the problems caused by the topcoding of each income source in the CPS data. Exploiting our access to Census Bureau internal CPS data, we examine estimates from data incorporating imputations for topcoded incomes derived from cell means and estimates from data multiplyimputed from parametric distribution models. Our analysis yields robust conclusions about inequality trends. The upward trend in US income inequality that began in the mid-1970s and increased in the 1980s slowed markedly after 1993.

Using the internal March CPS, we create and in this paper distribute to the larger research community a cell mean series that provides the mean of all income values above the topcode for any income source of any individual in the public use March CPS that has been topcoded since 1976. We also describe our construction of this series. When we use this series together with the public use March CPS, we closely match the yearly mean income levels and income inequalities of the U.S. population found using the internal March CPS data.

Researchers considering levels and trends in the resources available to the middle class traditionally measure the pre-tax cash income of either tax units or households. In this paper, we demonstrate that this choice carries significant implications for assessing income trends. Focusing on tax units rather than households greatly reduces measured growth in middle class income. Furthermore, excluding the effect of taxes and the value of in-kind benefits further reduces observed improvements in the resources of the middle class. Finally, we show how these distinctions change the observed distribution of benefits from the tax exclusion of employer provided health insurance.