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Agent-Based Model Approach to Complex Phenomena in Real Economy

Author

Listed:
  • Hiroshi Iyetomi
  • Hideaki Aoyama
  • Yoshi Fujiwara
  • Yuichi Ikeda
  • Wataru Souma

Abstract

An agent-based model for firms' dynamics is developed. The model consists of firm agents with identical characteristic parameters and a bank agent. Dynamics of those agents is described by their balance sheets. Each firm tries to maximize its expected profit with possible risks in market. Infinite growth of a firm directed by the "profit maximization" principle is suppressed by a concept of "going concern". Possibility of bankruptcy of firms is also introduced by incorporating a retardation effect of information on firms' decision. The firms, mutually interacting through the monopolistic bank, become heterogeneous in the course of temporal evolution. Statistical properties of firms' dynamics obtained by simulations based on the model are discussed in light of observations in the real economy.

Suggested Citation

  • Hiroshi Iyetomi & Hideaki Aoyama & Yoshi Fujiwara & Yuichi Ikeda & Wataru Souma, 2009. "Agent-Based Model Approach to Complex Phenomena in Real Economy," Papers 0901.1794, arXiv.org.
  • Handle: RePEc:arx:papers:0901.1794
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    File URL: http://arxiv.org/pdf/0901.1794
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    References listed on IDEAS

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    1. Masanao Aoki, "undated". "Reconstructing Macroeconomics: A Perspective from Statistical Physics and Combinatorial Stochastic Processes," UCLA Economics Online Papers 390, UCLA Department of Economics.
    2. Aoki,Masanao & Yoshikawa,Hiroshi, 2007. "Reconstructing Macroeconomics," Cambridge Books, Cambridge University Press, number 9780521831062, March.
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    1. repec:spr:jeicoo:v:12:y:2017:i:1:d:10.1007_s11403-015-0149-5 is not listed on IDEAS
    2. repec:eee:phsmap:v:488:y:2017:i:c:p:112-120 is not listed on IDEAS
    3. Barroso, Ricardo Vieira & Lima, Joaquim Ignacio Alves Vasconcellos & Lucchetti, Alexandre Henrique & Cajueiro, Daniel Oliveira, 2016. "Interbank network and regulation policies: an analysis through agent-based simulations with adaptive learning," MPRA Paper 73308, University Library of Munich, Germany.

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