The impact of top incomes biases on the measurement of inequality in the United States
Vladimir Hlasny and
Paolo Verme
No 452, Working Papers from ECINEQ, Society for the Study of Economic Inequality
Abstract:
The paper re-estimates the Gini inequality index for the United States using the Current Population Survey between 1979 and 2014 and two alternative correction methods for top income biases. Top incomes in household surveys are affected by a variety of biases related to survey design, income measurement and post-survey data adjustments. The paper corrects for selected biases using a stochastic approach based on reweighting and a semi-parametric approach based on replacing observations. Both methodologies show that income inequality in the United States has been consistently underestimated during the period considered. The level of underestimation is up to 6.83 percentage points depending on the year considered, choice of correction method and choice of modalities within methods. The degree of underestimation is positively and significantly associated with mean income, non-response rates, the initial level of inequality and the degree of departure of the top incomes distribution from a Pareto distribution.
Keywords: Top incomes; inequality measures; survey nonresponse; Pareto distribution; parametric estimation. (search for similar items in EconPapers)
JEL-codes: D31 D63 N35 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2017-11
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Citations: View citations in EconPapers (13)
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http://www.ecineq.org/milano/WP/ECINEQ2017-452.pdf (application/pdf)
Related works:
Journal Article: The Impact of Top Incomes Biases on the Measurement of Inequality in the United States (2022) 
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Persistent link: https://EconPapers.repec.org/RePEc:inq:inqwps:ecineq2017-452
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