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Applications of Statistical Physics Distributions to Several Types of Income

Received: 16 March 2014     Accepted: 9 April 2014     Published: 20 April 2014
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Abstract

This paper explores several types of income which have not been explored so far by authors who tackled income and wealth distribution using Statistical Physics. The main types of income we plan to analyze are income before redistribution (or gross income), income of retired people (or pensions), and income of active people (mostly wages). The distributions used to analyze income distributions are Fermi-Dirac distribution and polynomial distribution (as this is present in describing the behavior of dynamic systems in certain aspects). The data we utilize for our analysis are from France and the UK. We find that both distributions are robust in describing these varieties of income. The main finding we consider to be the applicability of these distributions to pensions, which are not regulated entirely by market mechanisms

Published in American Journal of Physics and Applications (Volume 2, Issue 2)
DOI 10.11648/j.ajpa.20140202.14
Page(s) 61-66
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2014. Published by Science Publishing Group

Keywords

Fermi-Dirac Distribution, Polynomial Distribution, Gross Income, Pensions, Wages, Cumulative Distribution Function

References
[1] E. Oltean, F. V. Kusmartsev, “A study of methods from statistical mechanics applied to income distribution”, ENEC, Bucharest-Romania, 2012.
[2] E. Oltean, F.V. Kusmartsev, “A polynomial distribution applied to income and wealth distribution”, Journal of Knowledge Management, Economics, and Information Technology, Bucharest, Romania, 2013.
[3] URL: http://data.library.utoronto.ca/datapub/codebooks/cstdsp/13f0022/2001/analytic.htm.
[4] Upper limit on income by decile group in 1987–2009 in Finland, URL: http://www.stat.fi/til/tjt/2009/tjt_2009_2011-05-20_tau_005_en.html.
[5] URL: http://en.wikipedia.org/wiki/Fermi%E2%80%93Dirac_statistics#Distribution_of_particles_over_energy.
[6] URL: http://www.ons.gov.uk/ons/search/index.html?newquery=household+income+by+decile&newoffset=0&pageSize=50&sortBy=&applyFilters=true
[7] URL: www.insee.fr
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  • APA Style

    Elvis Oltean, Fedor V. Kusmartsev. (2014). Applications of Statistical Physics Distributions to Several Types of Income. American Journal of Physics and Applications, 2(2), 61-66. https://doi.org/10.11648/j.ajpa.20140202.14

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    ACS Style

    Elvis Oltean; Fedor V. Kusmartsev. Applications of Statistical Physics Distributions to Several Types of Income. Am. J. Phys. Appl. 2014, 2(2), 61-66. doi: 10.11648/j.ajpa.20140202.14

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    AMA Style

    Elvis Oltean, Fedor V. Kusmartsev. Applications of Statistical Physics Distributions to Several Types of Income. Am J Phys Appl. 2014;2(2):61-66. doi: 10.11648/j.ajpa.20140202.14

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  • @article{10.11648/j.ajpa.20140202.14,
      author = {Elvis Oltean and Fedor V. Kusmartsev},
      title = {Applications of Statistical Physics Distributions to Several Types of Income},
      journal = {American Journal of Physics and Applications},
      volume = {2},
      number = {2},
      pages = {61-66},
      doi = {10.11648/j.ajpa.20140202.14},
      url = {https://doi.org/10.11648/j.ajpa.20140202.14},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajpa.20140202.14},
      abstract = {This paper explores several types of income which have not been explored so far by authors who tackled income and wealth distribution using Statistical Physics. The main types of income we plan to analyze are income before redistribution (or gross income), income of retired people (or pensions), and income of active people (mostly wages). The distributions used to analyze income distributions are Fermi-Dirac distribution and polynomial distribution (as this is present in describing the behavior of dynamic systems in certain aspects). The data we utilize for our analysis are from France and the UK. We find that both distributions are robust in describing these varieties of income. The main finding we consider to be the applicability of these distributions to pensions, which are not regulated entirely by market mechanisms},
     year = {2014}
    }
    

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  • TY  - JOUR
    T1  - Applications of Statistical Physics Distributions to Several Types of Income
    AU  - Elvis Oltean
    AU  - Fedor V. Kusmartsev
    Y1  - 2014/04/20
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    N1  - https://doi.org/10.11648/j.ajpa.20140202.14
    DO  - 10.11648/j.ajpa.20140202.14
    T2  - American Journal of Physics and Applications
    JF  - American Journal of Physics and Applications
    JO  - American Journal of Physics and Applications
    SP  - 61
    EP  - 66
    PB  - Science Publishing Group
    SN  - 2330-4308
    UR  - https://doi.org/10.11648/j.ajpa.20140202.14
    AB  - This paper explores several types of income which have not been explored so far by authors who tackled income and wealth distribution using Statistical Physics. The main types of income we plan to analyze are income before redistribution (or gross income), income of retired people (or pensions), and income of active people (mostly wages). The distributions used to analyze income distributions are Fermi-Dirac distribution and polynomial distribution (as this is present in describing the behavior of dynamic systems in certain aspects). The data we utilize for our analysis are from France and the UK. We find that both distributions are robust in describing these varieties of income. The main finding we consider to be the applicability of these distributions to pensions, which are not regulated entirely by market mechanisms
    VL  - 2
    IS  - 2
    ER  - 

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Author Information
  • Department of Physics, Loughborough University, Loughborough, the UK

  • Department of Physics, Loughborough University, Loughborough, the UK

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