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Modeling Aggregate Behavior and Fluctuations in Economics

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  • Aoki,Masanao

Abstract

This book has two components: stochastic dynamics and stochastic random combinatorial analysis. The first discusses evolving patterns of interactions of a large but finite number of agents of several types. Changes of agent types or their choices or decisions over time are formulated as jump Markov processes with suitably specified transition rates: optimisations by agents make these rates generally endogenous. Probabilistic equilibrium selection rules are also discussed, together with the distributions of relative sizes of the bases of attraction. As the number of agents approaches infinity, we recover deterministic macroeconomic relations of more conventional economic models. The second component analyses how agents form clusters of various sizes. This has applications for discussing sizes or shares of markets by various agents which involve some combinatorial analysis patterned after the population genetics literature. These are shown to be relevant to distributions of returns to assets, volatility of returns, and power laws.

Suggested Citation

  • Aoki,Masanao, 2004. "Modeling Aggregate Behavior and Fluctuations in Economics," Cambridge Books, Cambridge University Press, number 9780521606196.
  • Handle: RePEc:cup:cbooks:9780521606196
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    Cited by:

    1. Carl Chiarella & Corrado Di Guilmi, 2011. "Limit Distribution of Evolving Strategies in Financial Markets," Research Paper Series 294, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. Chiarella, Carl & Di Guilmi, Corrado, 2011. "The financial instability hypothesis: A stochastic microfoundation framework," Journal of Economic Dynamics and Control, Elsevier, vol. 35(8), pages 1151-1171, August.
    3. Fabio Tramontana, 2010. "Economics as a compartmental system: a simple macroeconomic example," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 57(4), pages 347-360, December.
    4. Roman, Mihai Daniel, 2008. "Entreprises behavior in cooperative and punishment‘s repeated negotiations," MPRA Paper 37527, University Library of Munich, Germany, revised 05 Jan 2009.
    5. Y. Ikeda & W. Souma & H. Aoyama & Y. Fujiwara & H. Iyetomi, 2010. "Analysis of labor productivity using large-scale data of firm’s financial statements," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 76(4), pages 491-499, August.
    6. Scalas, Enrico & Gallegati, Mauro & Guerci, Eric & Mas, David & Tedeschi, Alessandra, 2006. "Growth and allocation of resources in economics: The agent-based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 86-90.
    7. LI, XI HAO & Gallegati, Mauro, 2015. "Stock-Flow Dynamic Projection," MPRA Paper 62047, University Library of Munich, Germany.
    8. Sergey Sosnovskiy, 2015. "On financial applications of the two-parameter Poisson-Dirichlet distribution," Papers 1501.01954, arXiv.org, revised Jul 2015.
    9. Alfarano, Simone & Lux, Thomas & Wagner, Friedrich, 2010. "Excess Volatility and Herding in an Artificial Financial Market: Analytical Approach and Estimation," MPRA Paper 24719, University Library of Munich, Germany.
    10. Charles D. Brummitt & Kenan Huremovic & Paolo Pin & Matthew H. Bonds & Fernando Vega-Redondo, 2017. "Contagious disruptions and complexity traps in economic development," Papers 1707.05914, arXiv.org.
    11. Roman, Mihai Daniel, 2010. "A game theoretic approach of war with financial influences," MPRA Paper 38389, University Library of Munich, Germany.

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