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Income distribution patterns from a complete social security database

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  • N. Derzsy
  • Z. Neda
  • M. A. Santos

Abstract

We analyze the income distribution of employees for 9 consecutive years (2001-2009) using a complete social security database for an economically important district of Romania. The database contains detailed information on more than half million taxpayers, including their monthly salaries from all employers where they worked. Besides studying the characteristic distribution functions in the high and low/medium income limits, the database allows us a detailed dynamical study by following the time-evolution of the taxpayers income. To our knowledge, this is the first extensive study of this kind (a previous japanese taxpayers survey was limited to two years). In the high income limit we prove once again the validity of Pareto's law, obtaining a perfect scaling on four orders of magnitude in the rank for all the studied years. The obtained Pareto exponents are quite stable with values around $\alpha \approx 2.5$, in spite of the fact that during this period the economy developed rapidly and also a financial-economic crisis hit Romania in 2007-2008. For the low and medium income category we confirmed the exponential-type income distribution. Following the income of employees in time, we have found that the top limit of the income distribution is a highly dynamical region with strong fluctuations in the rank. In this region, the observed dynamics is consistent with a multiplicative random growth hypothesis. Contrarily with previous results obtained for the japanese employees, we find that the logarithmic growth-rate is not independent of the income.

Suggested Citation

  • N. Derzsy & Z. Neda & M. A. Santos, 2012. "Income distribution patterns from a complete social security database," Papers 1203.1880, arXiv.org.
  • Handle: RePEc:arx:papers:1203.1880
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    References listed on IDEAS

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    1. A.B. Atkinson & F. Bourguignon (ed.), 2000. "Handbook of Income Distribution," Handbook of Income Distribution, Elsevier, edition 1, volume 1, number 1.
    2. Sitabhra Sinha, 2005. "The Rich Are Different!: Pareto Law from asymmetric interactions in asset exchange models," Papers physics/0504197, arXiv.org.
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    Cited by:

    1. Gere, István & Kelemen, Szabolcs & Tóth, Géza & Biró, Tamás S. & Néda, Zoltán, 2021. "Wealth distribution in modern societies: Collected data and a master equation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    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. Istvan Gere & Szabolcs Kelemen & Geza Toth & Tamas Biro & Zoltan Neda, 2021. "Wealth distribution in modern societies: collected data and a master equation approach," Papers 2104.04134, arXiv.org.
    4. Anwar Shaikh, 2018. "Some Universal Patterns in Income Distribution: An Econophysics Approach," Working Papers 1808, New School for Social Research, Department of Economics.
    5. Scott Lawrence & Qin Liu & Victor M. Yakovenko, 2013. "Global inequality in energy consumption from 1980 to 2010," Papers 1312.6443, arXiv.org, revised Mar 2014.
    6. Oancea, Bogdan & Andrei, Tudorel & Pirjol, Dan, 2017. "Income inequality in Romania: The exponential-Pareto distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 486-498.
    7. 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.
    8. Alberto Russo, 2014. "A Stochastic Model of Wealth Accumulation with Class Division," Metroeconomica, Wiley Blackwell, vol. 65(1), pages 1-35, February.
    9. Biró, T.S. & Néda, Z., 2018. "Unidirectional random growth with resetting," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 335-361.
    10. Tudorel Andrei & Bogdan Oancea & Peter Richmond & Gurjeet Dhesi & Claudiu Herteliu, 2017. "Decomposition of the Inequality of Income Distribution by Income Types - Application for Romania," Papers 1709.07960, arXiv.org.
    11. 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).
    12. Xu, Yan & Wang, Yougui & Tao, Xiaobo & Ližbetinová, Lenka, 2017. "Evidence of Chinese income dynamics and its effects on income scaling law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 487(C), pages 143-152.

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