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Visualizing Income Distribution in the United States

Author

Listed:
  • Humberto Barreto

    (Department of Economics and Management, DePauw University)

  • Sang T. Truong

    (Department of Economics and Management, DePauw University)

Abstract

Visit research.depauw.edu/econ/incomevis to see a novel, eye-catching visual display of the income distribution in the United States that conveys fundamental information about the evolution and current level of income inequality to a wide audience. We use IPUMS CPS data to create household income deciles adjusted for price level and household size for each of the 50 states and the District of Columbia from 1976 to 2018. We adjust for state price differences from 2008 to 2018. Plotting these data gives a 3D chart that provides a startling picture of income differences within and across states over time. Those interested in further customization can use our Python visualization toolbox, incomevis, available at pypi.org/project/incomevis.

Suggested Citation

  • Humberto Barreto & Sang T. Truong, 2020. "Visualizing Income Distribution in the United States," Working Papers 2020-03, DePauw University, School of Business and Leadership and Department of Economics and Management.
    • Handle: RePEc:dew:wpaper:2020-03
    as

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    File URL: https://www.depauw.edu/site/learn/dew/wpaper/workingpapers/DePauw2020-03-Barreto-Truong-Incomevis.pdf
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    References listed on IDEAS

    as
    1. Jonathan Heathcote & Fabrizio Perri & Giovanni L. Violante, 2010. "Unequal We Stand: An Empirical Analysis of Economic Inequality in the United States: 1967-2006," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 13(1), pages 15-51, January.
    2. Dorfman, Robert, 1979. "A Formula for the Gini Coefficient," The Review of Economics and Statistics, MIT Press, vol. 61(1), pages 146-149, February.
    3. Murphy, Kevin M & Welch, Finis, 1990. "Empirical Age-Earnings Profiles," Journal of Labor Economics, University of Chicago Press, vol. 8(2), pages 202-229, April.
    4. Ingvild Almås & Magne Mogstad, 2012. "Older or Wealthier? The Impact of Age Adjustment on Wealth Inequality," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(1), pages 24-54, March.
    5. Hartmann, Dominik & Guevara, Miguel R. & Jara-Figueroa, Cristian & Aristarán, Manuel & Hidalgo, César A., 2017. "Linking Economic Complexity, Institutions, and Income Inequality," World Development, Elsevier, vol. 93(C), pages 75-93.
    6. Formby, John P & Seaks, Terry G, 1980. "Paglin's Gini Measure of Inequality: A Modification," American Economic Review, American Economic Association, vol. 70(3), pages 479-482, June.
    7. Aaberge, Rolf, 2001. "Axiomatic Characterization of the Gini Coefficient and Lorenz Curve Orderings," Journal of Economic Theory, Elsevier, vol. 101(1), pages 115-132, November.
    8. Dünhaupt, Petra, 2014. "An empirical assessment of the contribution of financialization and corporate governance to the rise in income inequality," IPE Working Papers 41/2014, Berlin School of Economics and Law, Institute for International Political Economy (IPE).
    9. Orazio Attanasio & Erik Hurst & Luigi Pistaferri, 2012. "The Evolution of Income, Consumption, and Leisure Inequality in The US, 1980-2010," NBER Working Papers 17982, National Bureau of Economic Research, Inc.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    visualization; household income; inequality; microdata; big data; data-mining; Python;
    All these keywords.

    JEL classification:

    • A10 - General Economics and Teaching - - General Economics - - - General
    • A20 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - General
    • J10 - Labor and Demographic Economics - - Demographic Economics - - - General

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