IDEAS home Printed from https://ideas.repec.org/p/dew/wpaper/2020-03.html
   My bibliography  Save this paper

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

    Download full text from publisher

    File URL: https://www.depauw.edu/site/learn/dew/wpaper/workingpapers/DePauw2020-03-Barreto-Truong-Incomevis.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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).
    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. 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.
    7. Dorfman, Robert, 1979. "A Formula for the Gini Coefficient," The Review of Economics and Statistics, MIT Press, vol. 61(1), pages 146-149, February.
    8. 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.
    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)

    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. Sang T. Truong & Humberto Barreto, 2023. "Teaching Income Inequality with Data-Driven Visualization," The American Economist, Sage Publications, vol. 68(1), pages 140-155, March.
    2. Vadym Lepetyuk & Christian A. Stoltenberg, 2012. "Reconciling consumption inequality with income inequality," Working Papers. Serie AD 2012-19, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    3. Haiyan Ding & Hui He, 2018. "A Tale of Transition: An Empirical Analysis of Economic Inequality in Urban China, 1986-2009," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 29, pages 106-137, July.
    4. Michael Bar & Moshe Hazan & Oksana Leukhina & David Weiss & Hosny Zoabi, 2018. "Why did rich families increase their fertility? Inequality and marketization of child care," Journal of Economic Growth, Springer, vol. 23(4), pages 427-463, December.
    5. Olivier Coibion & Yuriy Gorodnichenko & Lorenz Kueng & John Silvia, 2012. "Innocent Bystanders? Monetary Policy and Inequality in the U.S," NBER Working Papers 18170, National Bureau of Economic Research, Inc.
    6. Moira Daly & Dmytro Hryshko & Iourii Manovskii, 2022. "Improving The Measurement Of Earnings Dynamics," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(1), pages 95-124, February.
    7. Aristotelis Boukouras, 2016. "Capitalist Spirit and the Markets: Why Income Inequality Matters," Discussion Papers in Economics 16/16, Division of Economics, School of Business, University of Leicester.
    8. Youngsoo Jang & Minchul Yum, 2022. "Nonlinear Occupations and Female Labor Supply Over Time," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 46, pages 51-73, October.
    9. Rupert, Peter & Zanella, Giulio, 2015. "Revisiting wage, earnings, and hours profiles," Journal of Monetary Economics, Elsevier, vol. 72(C), pages 114-130.
    10. Mian, A. & Sufi, A., 2016. "Who Bears the Cost of Recessions? The Role of House Prices and Household Debt," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 255-296, Elsevier.
    11. Fatih Guvenen & Fatih Karahan & Serdar Ozkan & Jae Song, 2021. "What Do Data on Millions of U.S. Workers Reveal About Lifecycle Earnings Dynamics?," Econometrica, Econometric Society, vol. 89(5), pages 2303-2339, September.
    12. Bruce D. Meyer & James X. Sullivan, 2013. "Consumption and Income Inequality and the Great Recession," American Economic Review, American Economic Association, vol. 103(3), pages 178-183, May.
    13. Youngsoo Jang & Minchul Yum, 2022. "Nonlinear Occupations and Female Labor Supply Over Time," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 46, pages 51-73, October.
    14. Amy Beech & Rosetta Dollman & Richard Finlay & Gianni La Cava, 2014. "The Distribution of Household Spending in Australia," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 13-22, March.
    15. Osberg, Lars, 2013. "Instability implications of increasing inequality: Evidence from North America," Economic Modelling, Elsevier, vol. 35(C), pages 918-930.
    16. I. Josa & A. Aguado, 2020. "Measuring Unidimensional Inequality: Practical Framework for the Choice of an Appropriate Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 149(2), pages 541-570, June.
    17. Reza Najarzadeh & Alireza Keikha & Hassan Heydari, 2021. "Dynamics of consumption distribution and economic fluctuations," Economic Change and Restructuring, Springer, vol. 54(3), pages 847-876, August.
    18. Yamaguchi, Shintaro, 2010. "The effect of match quality and specific experience on career decisions and wage growth," Labour Economics, Elsevier, vol. 17(2), pages 407-423, April.
    19. Manfred M. Fischer & Florian Huber & Michael Pfarrhofer, 2018. "The transmission of uncertainty shocks on income inequality: State-level evidence from the United States," Papers 1806.08278, arXiv.org.
    20. Kumar, Sanjesh & Singh, Baljeet, 2019. "Barriers to the international diffusion of technological innovations," Economic Modelling, Elsevier, vol. 82(C), pages 74-86.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:dew:wpaper:2020-03. 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: Humberto Barreto (email available below). General contact details of provider: https://edirc.repec.org/data/emdepus.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.