IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1603.08383.html
   My bibliography  Save this paper

Modelling income, wealth, and expenditure data by use of Econophysics

Author

Listed:
  • Elvis Oltean

Abstract

In the present paper, we identify several distributions from Physics and study their applicability to phenomena such as distribution of income, wealth, and expenditure. Firstly, we apply logistic distribution to these data and we find that it fits very well the annual data for the entire income interval including for upper income segment of population. Secondly, we apply Fermi-Dirac distribution to these data. We seek to explain possible correlations and analogies between economic systems and statistical thermodynamics systems. We try to explain their behavior and properties when we correlate physical variables with macroeconomic aggregates and indicators. Then we draw some analogies between parameters of the Fermi-Dirac distribution and macroeconomic variables. Thirdly, as complex systems are modeled using polynomial distributions, we apply polynomials to the annual sets of data and we find that it fits very well also the entire income interval. Fourthly, we develop a new methodology to approach dynamically the income, wealth, and expenditure distribution similarly with dynamical complex systems. This methodology was applied to different time intervals consisting of consecutive years up to 35 years. Finally, we develop a mathematical model based on a Hamiltonian that maximizes utility function applied to Ramsey model using Fermi-Dirac and polynomial utility functions. We find some theoretical connections with time preference theory. We apply these distributions to a large pool of data from countries with different levels of development, using different methods for calculation of income, wealth, and expenditure.

Suggested Citation

  • Elvis Oltean, 2016. "Modelling income, wealth, and expenditure data by use of Econophysics," Papers 1603.08383, arXiv.org.
  • Handle: RePEc:arx:papers:1603.08383
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1603.08383
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Drăgulescu, Adrian & Yakovenko, Victor M., 2001. "Exponential and power-law probability distributions of wealth and income in the United Kingdom and the United States," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 213-221.
    2. Clementi, F. & Di Matteo, T. & Gallegati, M. & Kaniadakis, G., 2008. "The κ-generalized distribution: A new descriptive model for the size distribution of incomes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3201-3208.
    3. Anand Banerjee & Victor M. Yakovenko, 2009. "Universal patterns of inequality," Papers 0912.4898, arXiv.org, revised Apr 2010.
    4. F. Clementi & M. Gallegati & G. Kaniadakis, 2009. "A k-generalized statistical mechanics approach to income analysis," Papers 0902.0075, arXiv.org, revised Feb 2009.
    5. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
    6. Clementi, F. & Gallegati, M., 2005. "Power law tails in the Italian personal income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 350(2), pages 427-438.
    7. Adrian A. Dragulescu, 2003. "Applications of physics to economics and finance: Money, income, wealth, and the stock market," Papers cond-mat/0307341, arXiv.org, revised Jul 2003.
    8. Chami Figueira, F. & Moura, N.J. & Ribeiro, M.B., 2011. "The Gompertz–Pareto income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 689-698.
    9. 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.
    10. Banerjee, Anand & Yakovenko, Victor M. & Di Matteo, T., 2006. "A study of the personal income distribution in Australia," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 54-59.
    11. F. Clementi & M. Gallegati & G. Kaniadakis, 2007. "κ-generalized statistics in personal income distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 187-193, May.
    12. repec:cup:cbooks:9781107013445 is not listed on IDEAS
    13. Anirban Chakraborti & Bikas K. Chakrabarti, 2000. "Statistical mechanics of money: How saving propensity affects its distribution," Papers cond-mat/0004256, arXiv.org, revised Jun 2000.
    14. Moshe Levy & Sorin Solomon, 1996. "Power Laws Are Logarithmic Boltzmann Laws," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 7(04), pages 595-601.
    15. Elvis Oltean & Fedor V. Kusmartsev, 2013. "A Polynomial Distribution Applied to Income and Wealth Distribution," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 3(4), pages 1-2, August.
    16. A. Chakraborti & B.K. Chakrabarti, 2000. "Statistical mechanics of money: how saving propensity affects its distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 17(1), pages 167-170, September.
    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. G. Ruiz & A. F. de Marcos, 2018. "Evidence for criticality in financial data," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 91(1), pages 1-5, January.
    2. G. Bertarelli & R. Chambers & N. Salvati, 2021. "Outlier robust small domain estimation via bias correction and robust bootstrapping," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 331-357, March.

    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. Costas Efthimiou & Adam Wearne, 2016. "Household Income Distribution in the USA," Papers 1602.06234, arXiv.org.
    2. Aydiner, Ekrem & Cherstvy, Andrey G. & Metzler, Ralf, 2018. "Wealth distribution, Pareto law, and stretched exponential decay of money: Computer simulations analysis of agent-based models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 278-288.
    3. Soares, Abner D. & Moura Jr., Newton J. & Ribeiro, Marcelo B., 2016. "Tsallis statistics in the income distribution of Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 158-171.
    4. Cui, Jian & Pan, Qiuhui & Qian, Qian & He, Mingfeng & Sun, Qilin, 2013. "A multi-agent dynamic model based on different kinds of bequests," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1393-1397.
    5. 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.
    6. Tian, Songtao & Liu, Zhirong, 2020. "Emergence of income inequality: Origin, distribution and possible policies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    7. Carmen Pellicer-Lostao & Ricardo Lopez-Ruiz, 2010. "Transition from Exponential to Power Law Distributions in a Chaotic Market," Papers 1011.5187, arXiv.org.
    8. Patriarca, Marco & Chakraborti, Anirban & Germano, Guido, 2006. "Influence of saving propensity on the power-law tail of the wealth distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 723-736.
    9. D. S. Quevedo & C. J. Quimbay, 2019. "Piketty's second fundamental law of capitalism as an emergent property in a kinetic wealth-exchange model of economic growth," Papers 1903.00952, arXiv.org, revised Mar 2019.
    10. 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.
    11. Chami Figueira, F. & Moura, N.J. & Ribeiro, M.B., 2011. "The Gompertz–Pareto income distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 689-698.
    12. Adams Vallejos & Ignacio Ormazabal & Felix A. Borotto & Hernan F. Astudillo, 2018. "A new $\kappa$-deformed parametric model for the size distribution of wealth," Papers 1805.06929, arXiv.org.
    13. 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.
    14. Jayadev, Arjun, 2008. "A power law tail in India's wealth distribution: Evidence from survey data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(1), pages 270-276.
    15. Garanina, O.S. & Romanovsky, M.Yu., 2015. "New multi-parametric analytical approximations of exponential distribution with power law tails for new cars sells and other applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 1-9.
    16. 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.
    17. Victor M. Yakovenko, 2012. "Applications of statistical mechanics to economics: Entropic origin of the probability distributions of money, income, and energy consumption," Papers 1204.6483, arXiv.org.
    18. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical mechanics of money, wealth, and income," Papers 0905.1518, arXiv.org, revised Dec 2009.
    19. Vallejos, Adams & Ormazábal, Ignacio & Borotto, Félix A. & Astudillo, Hernán F., 2019. "A new κ-deformed parametric model for the size distribution of wealth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 819-829.
    20. Boghosian, Bruce M. & Devitt-Lee, Adrian & Johnson, Merek & Li, Jie & Marcq, Jeremy A. & Wang, Hongyan, 2017. "Oligarchy as a phase transition: The effect of wealth-attained advantage in a Fokker–Planck description of asset exchange," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 476(C), pages 15-37.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:1603.08383. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.