Publication type
ISER Working Paper Series
Series Number
2009-27
Series
ISER Working Paper Series
Authors
Publication date
September 14, 2009
Summary:
The March Current Population Survey (CPS) public-use files have been the primary data source used to study income inequality trends in the USA. The consensus finding of research based on these data is that household income inequality increased substantially in the 1970s and 1980s, and continued to increase but at a much slower pace starting in the 1990s. The most notable alternative source for studying income inequality trends derives from tax return data. In their seminal paper, Piketty and Saez (Quarterly Journal of Economics, 2003) use data from Internal Revenue Service (IRS) Statistics of Income tax returns to analyze income inequality trends in the USA. Their paper was one of the first in a rapidly expanding literature that has used tax return data to examine income inequality trends around the world.
One of Piketty and Saez’s major contributions derives from being able to observe income inequality trends over a much longer period than previous researchers: tax return data are available for years well before any survey data on income was collected. However, their findings have also sparked debate about inequality trends over relatively short periods, and recent years in particular.
In contrast to research based on CPS data that finds income inequality slowing in the 1990s, Piketty and Saez (2003, 2008) find that the share of total income held by the very richest groups grew during the 1990s and, with the exception of the period from 2000-2002, continued to rise rapidly through the beginning of the 21st century as well. What explains the differences in inequality trends found by researchers using these two types of data?
One explanation is that there are deficiencies in one or both of these data sets that limit researchers’ abilities to observe the true trends in inequality. Critics of those using the public-use CPS to measure income inequality argue that topcoding and underreporting of top incomes restricts the survey’s ability to observe income changes for those at the top of the distribution. Using IRS data to measure income inequality also has potential limitations, however. Critics point out that tax filers have a financial incentive to report their income in ways that limit their tax liabilities and, as a result, filing behavior is sensitive to changes in the personal income tax rate. Yet another potential explanation for the differences in estimated inequality trends is that they result from differences in the definition of income and how its distribution is summarized rather than differences in the data sources themselves.
To date, no researchers have attempted to bridge the gap between the CPS- and IRS-based literatures to determine the extent to which the differences in inequality estimates emanating from these two literatures arise from differences in the ability of these two data sources to capture top incomes or from the application of different income constructs based on these data sources. In this paper, we do just that.
Using internal CPS data, we examine the trends in income inequality since 1967 using the inequality measures and income distribution definitions developed by Piketty and Saez (2003) and others using tax return data. Doing so, we are able to closely match their results. Our estimates of top income shares are nearly identical for groups in the richest tenth with the exception of the richest 1 percent, and our estimates of trends differ only slightly. Even for estimates of the share held by the top 1 percent, the two data sources are broadly in agreement about trends over much of the past 40 years. It is only during a six year period in the late 1990s that the trends diverge for reasons that are not easily explained by changes in the nature of the two data sources.
Subject
Notes
working paper
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