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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.

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Bibliographic Info

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This book is provided by Cambridge University Press in its series Cambridge Books with number 9780521606196 and published in 2004.

Order: http://www.cambridge.org/uk/catalogue/catalogue.asp?isbn=9780521606196
Handle: RePEc:cup:cbooks:9780521606196

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Cited by:
  1. 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.
  2. Wright, Ian, 2008. "Implicit Microfoundations for Macroeconomics," Economics Discussion Papers 2008-41, Kiel Institute for the World Economy.
  3. 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, vol. 76(4), pages 491-499, August.
  4. Masanao Aoki, 2002. "Open Models of Share Markets with Two Dominant Types of Participants," UCLA Economics Online Papers 107, UCLA Department of Economics.
  5. Fujiwara, Yoshi & Souma, Wataru & Aoyama, Hideaki & Kaizoji, Taisei & Aoki, Masanao, 2003. "Growth and fluctuations of personal income," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 321(3), pages 598-604.
  6. 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.
  7. repec:ebl:ecbull:v:3:y:2007:i:2:p:1-10 is not listed on IDEAS
  8. Enrico Scalas & Mauro Gallegati & Eric Guerci & David Mas & Alessandra Tedeschi, 2006. "Growth and Allocation of Resources in Economics: The Agent-Based Approach," Papers physics/0608221, arXiv.org.
  9. Cars H. Hommes, 2005. "Heterogeneous Agent Models in Economics and Finance," Tinbergen Institute Discussion Papers 05-056/1, Tinbergen Institute.
  10. Masanao Aoki & Hiroshi Yoshikawa, 2012. "Non-self-averaging in macroeconomic models: a criticism of modern micro-founded macroeconomics," Journal of Economic Interaction and Coordination, Springer, vol. 7(1), pages 1-22, May.
  11. M. Gallegati & A. Palestrini & D. Gatti & E. Scalas, 2006. "Aggregation of Heterogeneous Interacting Agents: The Variant Representative Agent Framework," Journal of Economic Interaction and Coordination, Springer, vol. 1(1), pages 5-19, May.
  12. Fabio Tramontana & Mauro Gallegati, 2010. "Economics as a compartmental system: a simple macroeconomic example," Working Papers 1011, University of Urbino Carlo Bo, Department of Economics, Society & Politics - Scientific Committee - L. Stefanini & G. Travaglini, revised 2010.
  13. 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.

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