IDEAS home Printed from https://ideas.repec.org/a/aea/apandp/v109y2019p307-11.html
   My bibliography  Save this article

Top 1 Percent Income Shares: Comparing Estimates Using Tax Data

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.aeaweb.org/doi/10.1257/pandp.20191038
    Download Restriction: no
    File URL: https://www.aeaweb.org/doi/10.1257/pandp.20191038.appx
    Download Restriction: no
    File URL: https://www.aeaweb.org/doi/10.1257/pandp.20191038.ds
    Download Restriction: Access to full text is restricted to AEA members and institutional subscribers.
    ---><---

    References listed on IDEAS

    as
    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 & Lucas Chancel & Thomas Piketty & Gabriel Zucman, 2018. "Distributional National Accounts," PSE-Ecole d'économie de Paris (Postprint) halshs-03342488, HAL.
    3. 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.
    4. 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.
    5. Congressional Budget Office, 2018. "The Distribution of Household Income, 2014," Reports 53597, Congressional Budget Office.
    6. 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.
    7. Congressional Budget Office, 2018. "The Distribution of Household Income, 2015," Reports 54646, Congressional Budget Office.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    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. 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.
    4. Jonathan Rothwell, 2019. "The Political Economy of Inequality in Rich Democracies," LIS Working papers 772, LIS Cross-National Data Center in Luxembourg.
    5. 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).
    6. 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).
    7. Süssmuth, Bernd & Wieschemeyer, Matthias, 2022. "Taxation and the distributional impact of inflation: The U.S. post-war experience," Economic Modelling, Elsevier, vol. 111(C).
    8. Emmanuel Saez & Gabriel Zucman, 2020. "Trends in US Income and Wealth Inequality: Revising After the Revisionists," NBER Working Papers 27921, National Bureau of Economic Research, Inc.
    9. Advani, Arun & Summers, Andy & Tarrant, Hannah, 2020. "Measuring UK top incomes," CAGE Online Working Paper Series 490, Competitive Advantage in the Global Economy (CAGE).
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Thomas Piketty & Emmanuel Saez & Gabriel Zucman, 2019. "Simplified Distributional National Accounts," AEA Papers and Proceedings, American Economic Association, vol. 109, pages 289-295, May.
    2. Jonathan Rothwell, 2019. "The Political Economy of Inequality in Rich Democracies," LIS Working papers 772, LIS Cross-National Data Center in Luxembourg.
    3. Pawel Bukowski & Filip Novokmet, 2019. "Between communism and capitalism: long-term inequality in Poland, 1892-2015," CEP Discussion Papers dp1628, Centre for Economic Performance, LSE.
    4. Arun Advani, 2022. "Who does and doesn't pay taxes?," Fiscal Studies, John Wiley & Sons, vol. 43(1), pages 5-22, March.
    5. Jesse Bricker & Sarena Goodman & Alice Henriques Volz & Kevin B. Moore, 2021. "A Wealth of Information: Augmenting the Survey of Consumer Finances to Characterize the Full U.S. Wealth Distribution," Finance and Economics Discussion Series 2021-053, Board of Governors of the Federal Reserve System (U.S.).
    6. Filip Novokmet & Thomas Piketty & Gabriel Zucman, 2018. "From Soviets to oligarchs: inequality and property in Russia 1905-2016," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 189-223, June.
    7. Stefan Jestl & Emanuel List, 2020. "Distributional National Accounts (DINA) for Austria, 2004-2016," wiiw Working Papers 175, The Vienna Institute for International Economic Studies, wiiw.
    8. Yonatan Berman, 2022. "The Long-Run Evolution of Absolute Intergenerational Mobility," American Economic Journal: Applied Economics, American Economic Association, vol. 14(3), pages 61-83, July.
    9. Luis Estévez Bauluz, 2017. "Revised and extended national wealth series: Australia, Canada, France, Germany, Italy, Japan, the UK and the USA," PSE Working Papers halshs-02797842, HAL.
    10. Anthony B. Atkinson & Alessandra Casarico & Sarah Voitchovsky, 2018. "Top incomes and the gender divide," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 16(2), pages 225-256, June.
    11. Stefan Jestl & Emanuel List, 2020. "Distributional National Accounts (DINA) for Austria, 2004-2016," World Inequality Lab Working Papers halshs-03022077, HAL.
    12. Luis Estévez Bauluz, 2017. "Revised and extended national wealth series: Australia, Canada, France, Germany, Italy, Japan, the UK and the USA," Working Papers halshs-02797842, HAL.
    13. 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.
    14. Advani, Arun & Summers, Andy & Tarrant, Hannah, 2020. "Measuring UK top incomes," CAGE Online Working Paper Series 490, Competitive Advantage in the Global Economy (CAGE).
    15. Garbinti, Bertrand & Goupille-Lebret, Jonathan & Piketty, Thomas, 2018. "Income inequality in France, 1900–2014: Evidence from Distributional National Accounts (DINA)," Journal of Public Economics, Elsevier, vol. 162(C), pages 63-77.
    16. Bruce D. Meyer & Derek Wu & Grace Finley & Patrick Langetieg & Carla Medalia & Mark Payne & Alan Plumley, 2020. "The Accuracy of Tax Imputations: Estimating Tax Liabilities and Credits Using Linked Survey and Administrative Data," NBER Chapters, in: Measuring Distribution and Mobility of Income and Wealth, pages 459-498, National Bureau of Economic Research, Inc.
    17. Gabriel Zucman, 2019. "Global Wealth Inequality," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 109-138, August.
    18. Osvaldo Larrañaga & Benjamín Echecopar & Nicolás Grau, 2022. "Una nueva estimación de la desigualdad de ingresos en Chile," Estudios Públicos, Centro de Estudios Públicos, vol. 0(167), pages 45-76.
    19. Blotevogel, Robert & Imamoglu, Eslem & Moriyama, Kenji & Sarr, Babacar, 2022. "Income inequality measures and economic growth channels," Journal of Macroeconomics, Elsevier, vol. 72(C).
    20. Martin Ravallion, 2022. "Missing Top Income Recipients," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(1), pages 205-222, March.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aea:apandp:v:109:y:2019:p:307-11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michael P. Albert (email available below). General contact details of provider: https://edirc.repec.org/data/aeaaaea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.