The Great Overestimation: Tax Data and Inequality Measurements in the United States, 1913–1943

Abstract

Historical measures of income inequality in the United States must grapple with the challenge of data quality. We examine one such problem affecting the well‐known estimates of income inequality produced by Piketty and Saez (2003) using the records of the Internal Revenue Service (IRS). Prior to 1943, incomes were self‐reported. Combined with lax enforcement on the part of the IRS, self‐reporting of incomes could provide a misleading portrait of the income distribution. To test the accuracy of IRS records, we compare them to independently tabulated state income tax returns between 1919 and 1945 from states with more comprehensive and rigorously enforced tax collection procedures. State income tax records show lower overall levels of income inequality than IRS records. However, we still find that top income concentrations declined across the period between 1929 and World War II. These findings attest to the sensitivity of distributional estimation to the reporting selectivity and economic quality of underlying tax data, suggesting that the existing IRS‐derived series systematically overstates top‐income concentration in the interwar period. (JEL H2, N32, D31, E01)

Income inequality and party alternation: State‐level evidence from the United States

“…By 2010 the amount of national income going to the top 10% of earners was almost 50% compared to 40% in 1900. Geloso and Magness (2020) argue that federal data can overstate income inequality, and using state‐level data to examine changes in income inequality finds less disparity.…”

Economic freedom improves income mobility: evidence from Canadian provinces, 1982–2018

“…This research can be divided into two categories. The first is the literature that attempts to properly measure inequality (see notably Auten and Splinter, 2018, 2019, 2021; Burkhauser et al ., 2012; Geloso et al ., 2021; Geloso and Magness, 2020; Kopczuk et al ., 2010; Larrimore et al ., 2021; Mechling et al ., 2017; Piketty et al ., 2018; Piketty and Saez, 2003). The second is the literature that attempts to connect inequality to socio-economic outcomes (see notably Bowles, 2012; Corak, 2013; Deaton, 2003; Ferreira et al ., 2018; Pickett and Wilkinson, 2010).…”