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Analysis of resources distribution in economics based on entropy

Author

Listed:
  • Antoniou, I
  • Ivanov, V.V
  • Korolev, Yu.L
  • Kryanev, A.V
  • Matokhin, V.V
  • Suchanecki, Z

Abstract

We propose a new approach to the problem of efficient resources distribution in different types of economic systems. We also propose to use entropy as an indicator of the efficiency of resources distribution. Our approach is based on methods of statistical physics in which the states of economic systems are described in terms of the density functions ρ(g,α) of the variable g parametrized by α. The parameter α plays a role of the integral characteristic of the state of the economic system. Having the density function ρ(g,α) we can use the corresponding entropy to evaluate the efficiency of the resources distribution. Our theoretical study have been tested on real data related to the portfolio investment.

Suggested Citation

  • Antoniou, I & Ivanov, V.V & Korolev, Yu.L & Kryanev, A.V & Matokhin, V.V & Suchanecki, Z, 2002. "Analysis of resources distribution in economics based on entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 304(3), pages 525-534.
    • Handle: RePEc:eee:phsmap:v:304:y:2002:i:3:p:525-534
    DOI: 10.1016/S0378-4371(01)00575-1
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    References listed on IDEAS

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    1. Jean-Philippe Bouchaud & Marc Mezard, 2000. "Wealth condensation in a simple model of economy," Science & Finance (CFM) working paper archive 500026, Science & Finance, Capital Fund Management.
    2. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
    3. Bouchaud, Jean-Philippe & Mézard, Marc, 2000. "Wealth condensation in a simple model of economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 282(3), pages 536-545.
    4. 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.
    5. 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.
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    Cited by:

    1. Jorge Antunes & Rangan Gupta & Zinnia Mukherjee & Peter Wanke, 2022. "Information entropy, continuous improvement, and US energy performance: a novel stochastic-entropic analysis for ideal solutions (SEA-IS)," Annals of Operations Research, Springer, vol. 313(1), pages 289-318, June.
    2. Zhengyin Zhou & Xiaoling Wang & Ruirui Sun & Xuefei Ao & Xiaopei Sun & Mingrui Song, 2014. "Study of the comprehensive risk analysis of dam-break flooding based on the numerical simulation of flood routing. Part II: Model application and results," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 72(2), pages 675-700, June.
    3. Antoniou, I & Ivanov, V.V & Kryanev, A.V & Matokhin, V.V & Shapovalov, M.V, 2004. "On the efficient resources distribution in economics based on entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 549-562.
    4. Rui Liu & Yun Chen & Jianping Wu & Lei Gao & Damian Barrett & Tingbao Xu & Xiaojuan Li & Linyi Li & Chang Huang & Jia Yu, 2017. "Integrating Entropy‐Based Naïve Bayes and GIS for Spatial Evaluation of Flood Hazard," Risk Analysis, John Wiley & Sons, vol. 37(4), pages 756-773, April.

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