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A study of the personal income distribution in Australia

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  • Anand Banerjee
  • Victor M. Yakovenko
  • T. Di Matteo
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    Abstract

    We analyze the data on personal income distribution from the Australian Bureau of Statistics. We compare fits of the data to the exponential, log-normal, and gamma distributions. The exponential function gives a good (albeit not perfect) description of 98% of the population in the lower part of the distribution. The log-normal and gamma functions do not improve the fit significantly, despite having more parameters, and mimic the exponential function. We find that the probability density at zero income is not zero, which contradicts the log-normal and gamma distributions, but is consistent with the exponential one. The high-resolution histogram of the probability density shows a very sharp and narrow peak at low incomes, which we interpret as the result of a government policy on income redistribution.

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    File URL: http://arxiv.org/pdf/physics/0601176
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number physics/0601176.

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    Date of creation: Jan 2006
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    Publication status: Published in Physica A 370, 54-59 (2006)
    Handle: RePEc:arx:papers:physics/0601176

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    Web page: http://arxiv.org/

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    Cited by:
    1. Newby, Michael & Behr, Adam & Feizabadi, Mitra Shojania, 2011. "Investigating the distribution of personal income obtained from the recent U.S. data," Economic Modelling, Elsevier, vol. 28(3), pages 1170-1173, May.
    2. Sebastian Guala, 2009. "Taxes in a Wealth Distribution Model by Inelastically Scattering of Particles," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 7(1), pages 1-7.
    3. Joachim Kaldasch, 2013. "Evolutionary Model of a Anonymous Consumer Durable Market," Papers 1306.3395, arXiv.org.
    4. Kaldasch, Joachim, 2012. "Evolutionary model of the personal income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5628-5642.
    5. Kaldasch, Joachim, 2012. "Evolutionary model of the growth and size of firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(14), pages 3751-3769.
    6. 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.
    7. Kaldasch, Joachim, 2011. "The Product Life Cycle of Durable Goods," EconStor Preprints 50530, ZBW - German National Library of Economics.
    8. Brzezinski, Michal, 2014. "Do wealth distributions follow power laws? Evidence from ‘rich lists’," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 406(C), pages 155-162.
    9. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical mechanics of money, wealth, and income," Papers 0905.1518, arXiv.org, revised Dec 2009.
    10. Guo, Qiang & Gao, Li, 2012. "Distribution of individual incomes in China between 1992 and 2009," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(21), pages 5139-5145.
    11. Bertotti, Maria Letizia & Modanese, Giovanni, 2011. "From microscopic taxation and redistribution models to macroscopic income distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(21), pages 3782-3793.

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