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Physicists' approach to studying socio-economic inequalities: Can humans be modelled as atoms?

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  • Kiran Sharma
  • Anirban Chakraborti

Abstract

A brief overview of the models and data analyses of income, wealth, consumption distributions by the physicists, are presented here. It has been found empirically that the distributions of income and wealth possess fairly robust features, like the bulk of both the income and wealth distributions seem to reasonably fit both the log-normal and Gamma distributions, while the tail of the distribution fits well to a power law (as first observed by sociologist Pareto). We also present our recent studies of the unit-level expenditure on consumption across multiple countries and multiple years, where it was found that there exist invariant features of consumption distribution: the bulk is log-normally distributed, followed by a power law tail at the limit. The mechanisms leading to such inequalities and invariant features for the distributions of socio-economic variables are not well-understood. We also present some simple models from physics and demonstrate how they can be used to explain some of these findings and their consequences.

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  • Kiran Sharma & Anirban Chakraborti, 2016. "Physicists' approach to studying socio-economic inequalities: Can humans be modelled as atoms?," Papers 1606.06051, arXiv.org, revised Aug 2018.
  • Handle: RePEc:arx:papers:1606.06051
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    References listed on IDEAS

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    1. Anirban Chakraborti & Damien Challet & Arnab Chatterjee & Matteo Marsili & Yi-Cheng Zhang & Bikas K. Chakrabarti, 2013. "Statistical Mechanics of Competitive Resource Allocation using Agent-based Models," Papers 1305.2121, arXiv.org, revised Sep 2014.
    2. Sinha, Sitabhra, 2006. "Evidence for power-law tail of the wealth distribution in India," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 359(C), pages 555-562.
    3. 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.
    4. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    5. Frédéric Abergel & Hideaki Aoyama & Bikas K. Chakrabarti & Anirban Chakraborti & Asim Gosh, 2015. "Econophysics and data-driven modelling of market dynamics," Post-Print hal-01226816, HAL.
    6. Chatterjee, Arnab & Chakrabarti, Anindya S. & Ghosh, Asim & Chakraborti, Anirban & Nandi, Tushar K., 2016. "Invariant features of spatial inequality in consumption: The case of India," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 442(C), pages 169-181.
    7. Slanina, Frantisek, 2013. "Essentials of Econophysics Modelling," OUP Catalogue, Oxford University Press, number 9780199299683.
    8. M. Patriarca & A. Chakraborti & E. Heinsalu & G. Germano, 2007. "Relaxation in statistical many-agent economy models," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 219-224, May.
    9. Anirban Chakraborti & Dhruv Raina & Kiran Sharma, 2016. "Can an interdisciplinary field contribute to one of the parent disciplines from which it emerged?," Papers 1605.08354, arXiv.org.
    10. M. Patriarca & E. Heinsalu & A. Chakraborti, 2010. "Basic kinetic wealth-exchange models: common features and open problems," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 73(1), pages 145-153, January.
    11. repec:cup:cbooks:9781107013445 is not listed on IDEAS
    12. Anirban Chakraborti & Damien Challet & Arnab Chatterjee & Matteo Marsili & Yi-Cheng Zhang & Bikas K. Chakrabarti, 2013. "Statistical Mechanics of Competitive Resource Allocation using Agent-based Models," Papers 1305.2121, arXiv.org, revised Sep 2014.
    13. Els Heinsalu & Marco Patriarca, 2014. "Kinetic models of immediate exchange," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 87(8), pages 1-10, August.
    14. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: II. Agent-based models," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 1013-1041.
    15. Marco Patriarca & Anirban Chakraborti & Kimmo Kaski & Guido Germano, 2005. "Kinetic theory models for the distribution of wealth: power law from overlap of exponentials," Papers physics/0504153, arXiv.org, revised May 2005.
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