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Regional Inequality Simulations Based on Asset Exchange Models with Exchange Range and Local Support Bias

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  • Takeshi Kato
  • Yasuyuki Kudo
  • Hiroyuki Mizuno
  • Yoshinori Hiroi

Abstract

To gain insights into the problem of regional inequality, we proposed new regional asset exchange models based on existing kinetic income-exchange models in economic physics. We did this by setting the spatial exchange range and adding bias to asset fraction probability in equivalent exchanges. Simulations of asset distribution and Gini coefficients showed that suppressing regional inequality requires, firstly an increase in the intra-regional economic circulation rate, and secondly the narrowing down of the exchange range (inter-regional economic zone). However, avoiding over-concentration of assets due to repeat exchanges requires adding a third measure; the local support bias (distribution norm). A comprehensive solution incorporating these three measures enabled shifting the asset distribution from over-concentration to exponential distribution and eventually approaching the normal distribution, reducing the Gini coefficient further. Going forward, we will expand these models by setting production capacity based on assets, path dependency on two-dimensional space, bias according to disparity, and verify measures to reduce regional inequality in actual communities.

Suggested Citation

  • Takeshi Kato & Yasuyuki Kudo & Hiroyuki Mizuno & Yoshinori Hiroi, 2020. "Regional Inequality Simulations Based on Asset Exchange Models with Exchange Range and Local Support Bias," Applied Economics and Finance, Redfame publishing, vol. 7(5), pages 10-23, September.
    • Handle: RePEc:rfa:aefjnl:v:7:y:2020:i:5:p:10-23
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    References listed on IDEAS

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    1. Enrique Garcilazo & Joaquim Oliveira Martins, 2015. "The Contribution of Regions to Aggregate Growth in the OECD," Economic Geography, Taylor & Francis Journals, vol. 91(2), pages 205-221, April.
    2. repec:dau:papers:123456789/14816 is not listed on IDEAS
    3. Asim Ghosh & Arnab Chatterjee & Anindya S. Chakrabarti & Bikas K Chakrabarti, 2014. "Zipf's law in city size from a resource utilization model," Papers 1403.1822, arXiv.org, revised Oct 2014.
    4. Arshad, Sidra & Hu, Shougeng & Ashraf, Badar Nadeem, 2019. "Zipf’s law, the coherence of the urban system and city size distribution: Evidence from Pakistan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 87-103.
    5. 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.
    6. Victor M. Yakovenko & J. Barkley Rosser, 2009. "Colloquium: Statistical mechanics of money, wealth, and income," Papers 0905.1518, arXiv.org, revised Dec 2009.
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    Cited by:

    1. Takeshi Kato & Yoshinori Hiroi, 2021. "Wealth disparities and economic flow: Assessment using an asset exchange model with the surplus stock of the wealthy," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-16, November.
    2. Takeshi Kato & Yoshinori Hiroi, 2021. "Wealth disparities and economic flow: Assessment using an asset exchange model with the surplus stock of the wealthy," Papers 2108.07888, arXiv.org, revised Nov 2021.
    3. Takeshi Kato, 2022. "Islamic and capitalist economies: Comparison using econophysics models of wealth exchange and redistribution," Papers 2206.05443, arXiv.org, revised Sep 2022.

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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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