IDEAS home Printed from https://ideas.repec.org/p/dew/wpaper/2022-01.html
   My bibliography  Save this paper

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

    Download full text from publisher

    File URL: https://www.depauw.edu/site/learn/dew/wpaper/workingpapers/DePauw2022-01-Truong-Barreto-IncomeVis.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    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. 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.
    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.
    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. 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.
    2. Fullerton, Thomas M. & Jiménez, Alan A. & Walke, Adam G., 2015. "An econometric analysis of retail gasoline prices in a border metropolitan economy," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 450-461.
    3. Jonathan Eaton & Samuel Kortum & Brent Neiman & John Romalis, 2016. "Trade and the Global Recession," American Economic Review, American Economic Association, vol. 106(11), pages 3401-3438, November.
    4. Barnett, William A. & Su, Liting, 2017. "Data sources for the credit-card augmented Divisia monetary aggregates," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 899-910.
    5. Zadrozny, Peter A., 2016. "Extended Yule–Walker identification of VARMA models with single- or mixed-frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 438-446.
    6. de Haen, H. & von Braun, J., 1977. "Regionale Veränderungen des Arbeitseinsatzes in der Landwirtschaft – Demographische Analyse und arbeitsmarktpolitische Schlussfolgerungen," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 14.
    7. Alvaredo, Facundo & Atkinson, Anthony B. & Morelli, Salvatore, 2018. "Top wealth shares in the UK over more than a century," Journal of Public Economics, Elsevier, vol. 162(C), pages 26-47.
    8. 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).
    9. Thomas M. FULLERTON & Miguel MARTINEZ & Wm. Doyle SMITH & Adam WALKE, 2015. "Inflationary Dynamics in Guatemala," Journal of Economics and Political Economy, KSP Journals, vol. 2(4), pages 436-444, December.
    10. 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.
    11. Peter Fuleky & Carl S. Bonham, 2013. "Forecasting with Mixed Frequency Samples: The Case of Common Trends," Working Papers 201305, University of Hawaii at Manoa, Department of Economics.
    12. Yu Jin & Wallace E. Huffman, 2016. "Measuring public agricultural research and extension and estimating their impacts on agricultural productivity: new insights from U.S. evidence," Agricultural Economics, International Association of Agricultural Economists, vol. 47(1), pages 15-31, January.
    13. De Vita, G. & Endresen, K. & Hunt, L.C., 2006. "An empirical analysis of energy demand in Namibia," Energy Policy, Elsevier, vol. 34(18), pages 3447-3463, December.
    14. T. M. Fullerton & A. G. Walke, 2013. "Public transportation demand in a border metropolitan economy," Applied Economics, Taylor & Francis Journals, vol. 45(27), pages 3922-3931, September.
    15. 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.
    16. Bernardí Cabred & Jose Pavía, 1999. "EstimatingJ (>1) quarterly time series in fulfilling annual and quarterly constraints," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 5(3), pages 339-349, August.
    17. Eric Ghysels & J. Isaac Miller, 2015. "Testing for Cointegration with Temporally Aggregated and Mixed-Frequency Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(6), pages 797-816, November.
    18. Fullerton, Thomas M. Jr & Walke, Adam G., 2012. "Border Zone Mass Transit Demand in Brownsville and Laredo," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 51(2).
    19. 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.
    20. 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.

    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

    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:2022-01. 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.