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Teaching Income Inequality with Data-driven Visualization

Author

Listed:
  • Sang Truong

    (Department of Computer Science, Stanford University)

  • Humberto Barreto

    (Department of Economics and Management, DePauw University)

Abstract

The distribution of household income is a central concern in economics due to its strong influence on society’s well-being and social cohesion. Yet, non-expert audi-ences face serious obstacles in understanding conventional measures of inequality. To effectively communicate the extent of income inequality in the United States, we have developed a novel technique for visualizing income distribution and its dispersion over time by using U.S. household income microdata from the Current Population Survey. The result is a striking dynamic animation of income distribu-tion over time, drawing public attention and encouraging further investigation of income inequality. Detailed implementation is available at https://github.com/sangttruong/incomevis. An interactive demonstration of our project is available at https://research.depauw.edu/econ/incomevis/.

Suggested Citation

  • Sang Truong & Humberto Barreto, 2022. "Teaching Income Inequality with Data-driven Visualization," Working Papers 2022-01, DePauw University, School of Business and Leadership and Department of Economics and Management.
    • Handle: RePEc:dew:wpaper:2022-01
    as

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    File URL: https://www.depauw.edu/site/learn/dew/wpaper/workingpapers/DePauw2022-01-Truong-Barreto-IncomeVis.pdf
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    References listed on IDEAS

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    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. Milton Friedman, 1962. "Introduction to "The Interpolation of Time Series by Related Series"," NBER Chapters, in: The Interpolation of Time Series by Related Series, pages 1-3, National Bureau of Economic Research, Inc.
    5. 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.
    6. 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.
    7. 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.
    8. Cynthia Harter & Carlos J. Asarta, 2022. "Teaching Methods in Undergraduate Intermediate Theory, Statistics and Econometrics, and Other Upper-Division Economics Courses: Results From a Sixth National Quinquennial Survey," The American Economist, Sage Publications, vol. 67(1), pages 132-146, March.
    9. 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.
    10. 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).
    11. Milton Friedman, 1962. "The Interpolation of Time Series by Related Series," NBER Books, National Bureau of Economic Research, Inc, number frie62-1, March.
    12. Arthur Alderson & Jason Beckfield & Francois Nielsen, 2005. "Exactly How has Income Inequality Changed? Patterns of Distributional Change in Core Societies," LIS Working papers 422, LIS Cross-National Data Center in Luxembourg.
    13. 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.
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    More about this item

    Keywords

    3D; data visualization; data-driven education; Gini; survey; microdata; bootstrapping;
    All these keywords.

    JEL classification:

    • A2 - General Economics and Teaching - - Economic Education and Teaching of Economics
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • D6 - Microeconomics - - Welfare Economics
    • E6 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • Y1 - Miscellaneous Categories - - Data: Tables and Charts

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