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Top 1 Percent Income Shares: Comparing Estimates Using Tax Data

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  • Gerald Auten
  • David Splinter

Abstract

Many studies have used tax data to measure the U.S. income distribution, but their results vary widely. For example, in 2014 the top 1 percent share of income is 21.5 percent in Piketty and Saez (2003 and updates), 16.7 percent in the Congressional Budget Office (2018), and 13.1 percent in our analysis. What accounts for such large differences? We provide a step-by-step analysis of how methodological differences affect the results and address issues raised in Piketty, Saez, and Zucman (2018, 2019). Important differences include accounting for declining marriage rates, including social insurance and employer benefits, accounting for tax reforms, and including income missing from tax returns.

Suggested Citation

  • Gerald Auten & David Splinter, 2019. "Top 1 Percent Income Shares: Comparing Estimates Using Tax Data," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 307-311, May.
    • Handle: RePEc:aea:apandp:v:109:y:2019:p:307-11
    Note: DOI: 10.1257/pandp.20191038
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    References listed on IDEAS

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    1. Thomas Piketty & Emmanuel Saez & Gabriel Zucman, 2018. "Distributional National Accounts: Methods and Estimates for the United States," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(2), pages 553-609.
    2. Facundo Alvaredo & Anthony Atkinson & Lucas Chancel & Thomas Piketty & Emmanuel Saez & Gabriel Zucman, 2016. "Distributional National Accounts (DINA) Guidelines : Concepts and Methods used in WID.world," Working Papers halshs-02794308, HAL.
    3. Andrea Brandolini & Anthony B. Atkinson, 2001. "Promise and Pitfalls in the Use of "Secondary" Data-Sets: Income Inequality in OECD Countries As a Case Study," Journal of Economic Literature, American Economic Association, vol. 39(3), pages 771-799, September.
    4. Facundo Alvaredo & Lucas Chancel & Thomas Piketty & Gabriel Zucman, 2018. "Distributional National Accounts," Post-Print halshs-03342488, HAL.
    5. Congressional Budget Office, 2018. "The Distribution of Household Income, 2015," Reports 54646, Congressional Budget Office.
    6. Jeff Larrimore & Jacob Mortenson & David Splinter, 2021. "Household Incomes in Tax Data: Using Addresses to Move from Tax-Unit to Household Income Distributions," Journal of Human Resources, University of Wisconsin Press, vol. 56(2), pages 600-631.
    7. Congressional Budget Office, 2018. "The Distribution of Household Income, 2014," Reports 53597, Congressional Budget Office.
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    Citations

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    Cited by:

    1. Süssmuth, Bernd & Wieschemeyer, Matthias, 2022. "Taxation and the distributional impact of inflation: The U.S. post-war experience," Economic Modelling, Elsevier, vol. 111(C).
    2. Nishant Yonzan & Branko Milanovic & Salvatore Morelli & Janet Gornick, 2022. "Drawing a Line: Comparing the Estimation of Top Incomes between Tax Data and Household Survey Data," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 67-95, March.
    3. Advani, Arun & Summers, Andy & Tarrant, Hannah, 2020. "Measuring UK top incomes," CAGE Online Working Paper Series 490, Competitive Advantage in the Global Economy (CAGE).
    4. Advani, Arun & Summers, Andy & Tarrant, Hannah, 2022. "Measuring top income shares in the UK," CAGE Online Working Paper Series 610, Competitive Advantage in the Global Economy (CAGE).
    5. Dennis J. Fixle & Marina Gindelsky & Robert Kornfeld, 2021. "The Feasibility of a Quarterly Distribution of Personal Income," BEA Working Papers 0191, Bureau of Economic Analysis.
    6. Di Caro, Paolo & Figari, Francesco & Fiorio, Carlo & Manzo, Marco & Riganti, Andrea, 2022. "One step forward and three steps back: pros and cons of a flat tax reform," MPRA Paper 113684, University Library of Munich, Germany.
    7. Jonathan Rothwell, 2019. "The Political Economy of Inequality in Rich Democracies," LIS Working papers 772, LIS Cross-National Data Center in Luxembourg.
    8. Emmanuel Saez & Gabriel Zucman, 2020. "Trends in US Income and Wealth Inequality: Revising After the Revisionists," Working Papers halshs-03022102, HAL.
    9. Cohn, Alain & Jessen, Lasse J. & Klašnja, Marko & Smeets, Paul, 2023. "Wealthy Americans and redistribution: The role of fairness preferences," Journal of Public Economics, Elsevier, vol. 225(C).
    10. Judith Niehues & Maximilian Stockhausen & Andreas Peichl & Charlotte Bartels & Mario Bossler & Bernd Fitzenberger & Arnim Seidlitz & Moritz Kuhn & Till Baldenius & Sebastian Kohl & Moritz Schularick &, 2020. "Ungleichheit unter der Lupe – neue politische Antworten auf ein bekanntes Thema," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 73(02), pages 03-26, February.

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    More about this item

    JEL classification:

    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution

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