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Reconstructing Aggregate Dynamics in Heterogeneous Agents Models. A Markovian Approach

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  • Domenico Delli Gatti
  • Corrado Di Guilmi
  • Mauro Gallegati
  • Simone Landini

Abstract

The restrictive assumptions imposed by the traditional methods of aggregation prevented so far a sound analysis of complex system of feedback between microeconomic variables and macroeconomic outcomes. This issue seems to be crucial in macroeconomic modelling, in particular for the analysis of financial fragility, as conceived in the Keynesian and New Keynesian literature. In the present paper a statistical mechanics aggregation method is applied to a financial fragility model. The result is a consistent representation of the economic system that considers the heterogeneity of firms, their interactive behaviour and the feedback effects between micro, meso and macro level. In this approach, the impact of micro financial variables can be analytically assessed. The whole dynamics is described by a system of dynamic equations that well mimics the evolution of a numerically solved agent based model with the same features.

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Bibliographic Info

Article provided by Presses de Sciences-Po in its journal Revue de l'OFCE.

Volume (Year): N° 124 (2012)
Issue (Month): 5 ()
Pages: 117-146

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Handle: RePEc:cai:reofsp:reof_124_0117

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Web page: http://www.cairn.info/revue-de-l-ofce.htm

Related research

Keywords: financial fragility; Markov Dynamics; heterogeneity; mean-field interaction; master equation;

References

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  1. 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.
  2. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2006. "Time-Variation of Higher Moments in a Financial Market with Heterogeneous Agents: An Analytical Approach," Working Papers wpn06-01, Warwick Business School, Finance Group.
  3. Foley Duncan K., 1994. "A Statistical Equilibrium Theory of Markets," Journal of Economic Theory, Elsevier, vol. 62(2), pages 321-345, April.
  4. Carl Chiarella & Corrado Di Guilmi, 2010. "The Financial Instability Hypothesis:a Stochastic Microfoundation Framework," Research Paper Series 273, Quantitative Finance Research Centre, University of Technology, Sydney.
  5. Lewbel, Arthur, 1992. "Aggregation with Log-Linear Models," Review of Economic Studies, Wiley Blackwell, vol. 59(3), pages 635-42, July.
  6. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
  7. James E. Smith, 1993. "Moment Methods for Decision Analysis," Management Science, INFORMS, vol. 39(3), pages 340-358, March.
  8. Mishael Milakovic, 2001. "A Statistical Equilibrium Model of Wealth Distribution," Computing in Economics and Finance 2001 214, Society for Computational Economics.
  9. Gatti, Domenico Delli & Guilmi, Corrado Di & Gaffeo, Edoardo & Giulioni, Gianfranco & Gallegati, Mauro & Palestrini, Antonio, 2005. "A new approach to business fluctuations: heterogeneous interacting agents, scaling laws and financial fragility," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 489-512, April.
  10. Hinich, Melvin J. & Foster, John & Wild, Phillip, 2006. "Structural change in macroeconomic time series: A complex systems perspective," Journal of Macroeconomics, Elsevier, vol. 28(1), pages 136-150, March.
  11. Alfarano, Simone & Milakovic, Mishael, 2009. "Network structure and N-dependence in agent-based herding models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(1), pages 78-92, January.
  12. Weidlich, Wolfgang & Braun, Martin, 1992. "The Master Equation Approach to Nonlinear Economics," Journal of Evolutionary Economics, Springer, vol. 2(3), pages 233-65, October.
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