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The Impact of Top Incomes Biases on the Measurement of Inequality in the United States
Author(s) -
Hlasny Vladimir,
Verme Paolo
Publication year - 2022
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/obes.12472
Subject(s) - current population survey , econometrics , inequality , economics , estimation , economic inequality , parametric statistics , demographic economics , affect (linguistics) , population , statistics , mathematics , demography , psychology , mathematical analysis , management , communication , sociology
The paper assesses how top incomes biases affect the estimation of income inequality in the United States using the Current Population Survey (the March Annual Social and Economic Supplement) and two alternative correction methods – a stochastic approach based on reweighting and a semi‐parametric approach based on replacing observations. Consistently with previous studies, both methods and their joint application show that income inequality in the United States between 1979 and 2014 has been consistently underestimated by several percentage points. The level of underestimation is positively and significantly associated with mean income, non‐response rates and the initial level of inequality. Reweighting is found to address top incomes biases – specifically those related to unit and item non‐response – consistently and more effectively than replacing , possibly because widely used parametric distributions do not represent US top incomes accurately.