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Do wealth distributions follow power laws? Evidence from "rich lists"

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  • Michal Brzezinski

Abstract

We use data on wealth of the richest persons taken from the "rich lists" provided by business magazines like Forbes to verify if upper tails of wealth distributions follow, as often claimed, a power-law behaviour. The data sets used cover the world's richest persons over 1996-2012, the richest Americans over 1988-2012, the richest Chinese over 2006-2012 and the richest Russians over 2004-2011. Using a recently introduced comprehensive empirical methodology for detecting power laws, which allows for testing goodness of fit as well as for comparing the power-law model with rival distributions, we find that a power-law model is consistent with data only in 35% of the analysed data sets. Moreover, even if wealth data are consistent with the power-law model, usually they are also consistent with some rivals like the log-normal or stretched exponential distributions.

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  • Michal Brzezinski, 2013. "Do wealth distributions follow power laws? Evidence from "rich lists"," Papers 1304.0212, arXiv.org.
    • Handle: RePEc:arx:papers:1304.0212
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    3. Stefan Bach & Andreas Thiemann & Aline Zucco, 2015. "The Top Tail of the Wealth Distribution in Germany, France, Spain, and Greece," Discussion Papers of DIW Berlin 1502, DIW Berlin, German Institute for Economic Research.
    4. Wang, Yuanjun & You, Shibing, 2016. "An alternative method for modeling the size distribution of top wealth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 443-453.
    5. Bach, Stefan & Thiemann, Andreas & Zucco, Aline, 2019. "Looking for the missing rich: tracing the top tail of the wealth distribution," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 26(6), pages 1234-1258.
    6. Westermeier, Christian, 2016. "Estimating top wealth shares using survey data - An empiricist's guide," Discussion Papers 2016/21, Free University Berlin, School of Business & Economics.
    7. Jan Schulz & Mishael Milaković, 2023. "How Wealthy are the Rich?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 69(1), pages 100-123, March.
    8. Junho Na & Jeong-dong Lee & Chulwoo Baek, 2017. "Is the service sector different in size heterogeneity?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(1), pages 95-120, April.
    9. Campolieti, Michele, 2019. "The durations of recession and prosperity: What distribution do they follow?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    10. Li, Cong & Xu, Hedong & Fan, Suohai, 2020. "Synergistic effects of self-optimization and imitation rules on the evolution of cooperation in the investor sharing game," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    11. Carsten Schröder & Charlotte Bartels & Markus M. Grabka & Martin Kroh & Rainer Siegers, 2018. "A Novel Sampling Strategy for Surveying High-Worth Individuals - An Application Using the Socio-Economic Panel," SOEPpapers on Multidisciplinary Panel Data Research 978, DIW Berlin, The German Socio-Economic Panel (SOEP).
    12. Frank A. Cowell & Philippe Kerm, 2015. "Wealth Inequality: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(4), pages 671-710, September.
    13. Fuyuo Nagayama, 2013. "Wealth inequality among the Forbes 400 and U.S. households overall," Research Rap Special Report, Federal Reserve Bank of Philadelphia, issue Jul.
    14. Anand Sahasranaman & Henrik Jeldtoft Jensen, 2019. "Dynamics of reallocation within India's income distribution," Papers 1909.04452, arXiv.org, revised Oct 2020.
    15. Yunfei Li & Diego Rybski & Jürgen P. Kropp, 2021. "Singularity cities," Environment and Planning B, , vol. 48(1), pages 43-59, January.

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