The Journal of Economic Inequality

, Volume 17, Issue 4, pp 443–459 | Cite as

The tail that wags: differences in effective right tail coverage and estimates of wealth inequality

  • Arthur B. KennickellEmail author


This paper focuses on the sensitivity of survey-based estimates of wealth inequality to the quality of the measurement of the upper tail of the distribution. Using data from the 2013 Survey of Consumer Finances (SCF), it develops a series of illustrative examples to highlight some of the problems in making comparisons of wealth inequality measures when there are specific defects in the measurement of the upper tail of the distribution. The results presented strongly indicate that in the absence of effective controls on the measurement of the upper tail of the wealth distribution, great caution should be the rule in the interpretation of most commonly used measures of wealth inequality from a given survey, comparison of such measures across the waves of the survey, and perhaps even more strongly, comparison across independently designed and managed surveys. A graphical decomposition of the 2013 SCF wealth distribution provides additional insight into the underlying cause of the sensitivity of the inequality measures. The paper concludes with a brief outline of a research program for improving the ability of surveys to provide more meaningful estimates of inequality measures.


Wealth distribution Survey response Estimation bias 


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I am grateful to participants and discussions in the ECB Household Finance and Consumption Network, Janet Gornick, Salvatore Morelli, and participants in the CUNY Stone Center 2017 conference Inequality by the Numbers for stimulating me to write this paper and for participants in the 2018 Paris School of Economics Workshop on Harmonization of Household Surveys, Fiscal Data and National Accounts. I am especially grateful to Laurie Maldonado for help in securing computing resources that made this work possible. I am solely responsible for any errors or omissions.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Stone Center, City University of New YorkNew YorkUSA

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