IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v415y2014icp54-60.html
   My bibliography  Save this article

Race, gender and the econophysics of income distribution in the USA

Author

Listed:
  • Shaikh, Anwar
  • Papanikolaou, Nikolaos
  • Wiener, Noe

Abstract

The econophysics “two-class” theory of Yakovenko and his co-authors shows that the distribution of labor incomes is roughly exponential. This paper extends this result to US subgroups categorized by gender and race. It is well known that Males have higher average incomes than Females, and Whites have higher average incomes than African-Americans. It is also evident that social policies can affect these income gaps. Our surprising finding is that nonetheless intra-group distributions of pre-tax labor incomes are remarkably similar and remain close to exponential. This suggests that income inequality can be usefully addressed by taxation policies, and overall income inequality can be modified by also shifting the balance between labor and property incomes.

Suggested Citation

  • Shaikh, Anwar & Papanikolaou, Nikolaos & Wiener, Noe, 2014. "Race, gender and the econophysics of income distribution in the USA," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 54-60.
    • Handle: RePEc:eee:phsmap:v:415:y:2014:i:c:p:54-60
    DOI: 10.1016/j.physa.2014.07.043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437114006153
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2014.07.043?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dale W. Jorgenson & J. Steven Landefeld, 2006. "Blueprint for Expanded and Integrated US Accounts: Review, Assessment, and Next Steps," NBER Chapters, in: A New Architecture for the US National Accounts, pages 13-112, National Bureau of Economic Research, Inc.
    2. Jagielski, Maciej & Kutner, Ryszard, 2013. "Modelling of income distribution in the European Union with the Fokker–Planck equation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2130-2138.
    3. Markus Schneider, 2013. "Illustrating the Implications of How Inequality is Measured: Decomposing Earnings Inequality by Race and Gender," Journal of Labor Research, Springer, vol. 34(4), pages 476-514, December.
    4. A. Drăgulescu & V.M. Yakovenko, 2001. "Evidence for the exponential distribution of income in the USA," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 20(4), pages 585-589, April.
    5. Jeff Larrimore & Richard V. Burkhauser & Shuaizhang Feng & Laura Zayatz, 2008. "Consistent Cell Means for Topcoded Incomes in the Public Use March CPS (1976-2007)," NBER Working Papers 13941, National Bureau of Economic Research, Inc.
    6. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical mechanics of money, wealth, and income," Papers 0905.1518, arXiv.org, revised Dec 2009.
    7. A. Christian Silva & Victor M. Yakovenko, 2004. "Temporal evolution of the "thermal" and "superthermal" income classes in the USA during 1983-2001," Papers cond-mat/0406385, arXiv.org, revised Oct 2004.
    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. Ellis Scharfenaker, Markus P.A. Schneider, 2019. "Labor Market Segmentation and the Distribution of Income: New Evidence from Internal Census Bureau Data," Working Paper Series, Department of Economics, University of Utah 2019_08, University of Utah, Department of Economics.
    2. Yong Tao & Xiangjun Wu & Tao Zhou & Weibo Yan & Yanyuxiang Huang & Han Yu & Benedict Mondal & Victor M. Yakovenko, 2019. "Exponential structure of income inequality: evidence from 67 countries," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(2), pages 345-376, June.
    3. Kitov, Ivan & Kitov, Oleg, 2015. "Gender income disparity in the USA: analysis and dynamic modelling," MPRA Paper 67146, University Library of Munich, Germany.
    4. Shaikh, Anwar & Jacobo, Juan Esteban, 2020. "Economic Arbitrage and the Econophysics of Income Inequality," Review of Behavioral Economics, now publishers, vol. 7(4), pages 299–315-2, December.
    5. Hernández-Ramírez, E. & del Castillo-Mussot, M. & Hernández-Casildo, J., 2021. "World per capita gross domestic product measured nominally and across countries with purchasing power parity: Stretched exponential or Boltzmann–Gibbs distribution?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    6. Anwar Shaikh & Amr Ragab, 2023. "Some universal patterns in income distribution: An econophysics approach," Metroeconomica, Wiley Blackwell, vol. 74(1), pages 248-264, February.
    7. Jaroonchokanan, Nawee & Termsaithong, Teerasit & Suwanna, Sujin, 2022. "Dynamics of hierarchical clustering in stocks market during financial crises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    8. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    9. Paulo L. dos Santos, 2017. "The Principle of Social Scaling," Complexity, Hindawi, vol. 2017, pages 1-9, December.
    10. Markus P. A. Schneider, 2018. "Revisiting the thermal and superthermal two-class distribution of incomes: A critical perspective," Papers 1804.06341, arXiv.org.
    11. Nikolaos Papanikolaou, 2020. "The Econophysics of Labor Income," Bulletin of Applied Economics, Risk Market Journals, vol. 7(1), pages 107-122.
    12. Soriano-Hernández, P. & del Castillo-Mussot, M. & Campirán-Chávez, I. & Montemayor-Aldrete, J.A., 2017. "Wealth of the world’s richest publicly traded companies per industry and per employee: Gamma, Log-normal and Pareto power-law as universal distributions?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 733-749.
    13. Ellis Scharfenaker & Gregor Semieniuk, 2017. "A Statistical Equilibrium Approach to the Distribution of Profit Rates," Metroeconomica, Wiley Blackwell, vol. 68(3), pages 465-499, July.
    14. Igor D. S. Siciliani & Marcelo H. R. Tragtenberg, 2017. "Kinetic theory and Brazilian income distribution," Papers 1709.06480, arXiv.org.
    15. Paulo dos Santos, 2016. "The Principle of Social Scaling," Working Papers 1606, New School for Social Research, Department of Economics.
    16. Tao, Yong, 2021. "Boltzmann-like income distribution in low and middle income classes: Evidence from the United Kingdom," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    17. Tao, Yong & Wu, Xiangjun & Li, Changshuai, 2017. "Rawls' fairness, income distribution and alarming level of Gini coefficient," Economics Discussion Papers 2017-67, Kiel Institute for the World Economy (IfW Kiel).
    18. Soriano-Hernández, P. & del Castillo-Mussot, M. & Córdoba-Rodríguez, O. & Mansilla-Corona, R., 2017. "Non-stationary individual and household income of poor, rich and middle classes in Mexico," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 403-413.
    19. Jangho Yang, 2018. "Information Theoretic Approaches In Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 32(3), pages 940-960, July.
    20. Anwar Shaikh, 2017. "Income Distribution, Econophysics and Piketty," Review of Political Economy, Taylor & Francis Journals, vol. 29(1), pages 18-29, January.
    21. Ellis Scharfenaker & Markus P. A. Schneider, 2023. "Labor Market Segmentation and the Distribution of Income: New Evidence from Internal Census Bureau Data," Working Papers 23-41, Center for Economic Studies, U.S. Census Bureau.

    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. Shaikh, Anwar & Jacobo, Juan Esteban, 2020. "Economic Arbitrage and the Econophysics of Income Inequality," Review of Behavioral Economics, now publishers, vol. 7(4), pages 299–315-2, December.
    2. Anwar Shaikh & Amr Ragab, 2023. "Some universal patterns in income distribution: An econophysics approach," Metroeconomica, Wiley Blackwell, vol. 74(1), pages 248-264, February.
    3. Soriano-Hernández, P. & del Castillo-Mussot, M. & Campirán-Chávez, I. & Montemayor-Aldrete, J.A., 2017. "Wealth of the world’s richest publicly traded companies per industry and per employee: Gamma, Log-normal and Pareto power-law as universal distributions?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 733-749.
    4. Díaz, Juan D. & Gutiérrez Cubillos, Pablo & Tapia Griñen, Pablo, 2021. "The exponential Pareto model with hidden income processes: Evidence from Chile," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    5. Néda, Zoltán & Gere, István & Biró, Tamás S. & Tóth, Géza & Derzsy, Noemi, 2020. "Scaling in income inequalities and its dynamical origin," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    6. Anwar Shaikh, 2018. "Some Universal Patterns in Income Distribution: An Econophysics Approach," Working Papers 1808, New School for Social Research, Department of Economics.
    7. Soriano-Hernández, P. & del Castillo-Mussot, M. & Córdoba-Rodríguez, O. & Mansilla-Corona, R., 2017. "Non-stationary individual and household income of poor, rich and middle classes in Mexico," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 403-413.
    8. Zoltan Neda & Istvan Gere & Tamas S. Biro & Geza Toth & Noemi Derzsy, 2019. "Scaling in Income Inequalities and its Dynamical Origin," Papers 1911.02449, arXiv.org, revised Mar 2020.
    9. Ellis Scharfenaker, Markus P.A. Schneider, 2019. "Labor Market Segmentation and the Distribution of Income: New Evidence from Internal Census Bureau Data," Working Paper Series, Department of Economics, University of Utah 2019_08, University of Utah, Department of Economics.
    10. Costas Efthimiou & Adam Wearne, 2016. "Household Income Distribution in the USA," Papers 1602.06234, arXiv.org.
    11. Hernández-Ramírez, E. & del Castillo-Mussot, M. & Hernández-Casildo, J., 2021. "World per capita gross domestic product measured nominally and across countries with purchasing power parity: Stretched exponential or Boltzmann–Gibbs distribution?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    12. Schulz, Jan & Mayerhoffer, Daniel M., 2021. "A network approach to consumption," BERG Working Paper Series 173, Bamberg University, Bamberg Economic Research Group.
    13. Tao, Yong, 2015. "Universal laws of human society’s income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 435(C), pages 89-94.
    14. Kaldasch, Joachim, 2012. "Evolutionary model of the personal income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5628-5642.
    15. Inoue, Jun-ichi & Ghosh, Asim & Chatterjee, Arnab & Chakrabarti, Bikas K., 2015. "Measuring social inequality with quantitative methodology: Analytical estimates and empirical data analysis by Gini and k indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 184-204.
    16. Aktaev, Nurken E. & Bannova, K.A., 2022. "Mathematical modeling of probability distribution of money by means of potential formation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    17. Bourguignon, Marcelo & Saulo, Helton & Fernandez, Rodrigo Nobre, 2016. "A new Pareto-type distribution with applications in reliability and income data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 166-175.
    18. Gregor Semieniuk & Victor M. Yakovenko, 2020. "Historical Evolution of Global Inequality in Carbon Emissions and Footprints versus Redistributive Scenarios," Papers 2004.00111, arXiv.org.
    19. Paulo L. dos Santos, 2017. "The Principle of Social Scaling," Complexity, Hindawi, vol. 2017, pages 1-9, December.
    20. Blair Fix, 2018. "Hierarchy and the power-law income distribution tail," Journal of Computational Social Science, Springer, vol. 1(2), pages 471-491, September.

    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:eee:phsmap:v:415:y:2014:i:c:p:54-60. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.