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Growth and allocation of resources in economics: The agent-based approach

Author

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  • Eric Guerci

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur, GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Enrico Scalas

    (DISTA - Dipartimento di Scienze e Tecnologie Avanzate - UPO - Università degli Studi del Piemonte Orientale - Amedeo Avogadro)

  • Mauro Gallegati

    (Polytechnic University of Marche - Polytechnic University of Marche)

  • David Mas

    (Chercheur indépendant)

  • Alessandra Tedeschi

    (Chercheur indépendant)

Abstract

Some agent-based models for growth and allocation of resources are described. The first class considered consists of conservative models, where the number of agents and the size of resources are constant during time evolution. The second class is made up of multiplicative noise models and some of their extensions to continuous time.

Suggested Citation

  • Eric Guerci & Enrico Scalas & Mauro Gallegati & David Mas & Alessandra Tedeschi, 2006. "Growth and allocation of resources in economics: The agent-based approach," Post-Print halshs-00871047, HAL.
  • Handle: RePEc:hal:journl:halshs-00871047
    DOI: 10.1016/j.physa.2006.04.038
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    References listed on IDEAS

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    1. Thomas Lux & Eleni Samanidou & Stefan Reitz (ed.), 2005. "Nonlinear Dynamics and Heterogeneous Interacting Agents," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-540-27296-0, December.
    2. Scalas, Enrico, 2006. "The application of continuous-time random walks in finance and economics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 362(2), pages 225-239.
    3. Scalas, Enrico & Gorenflo, Rudolf & Mainardi, Francesco, 2000. "Fractional calculus and continuous-time finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 284(1), pages 376-384.
    4. Sorin Solomon, 2000. "Generalized Lotka-Volterra (GLV) Models of Stock Markets," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 3(01n04), pages 301-322.
    5. Giulio Bottazzi & Angelo Secchi, 2006. "Explaining the distribution of firm growth rates," RAND Journal of Economics, RAND Corporation, vol. 37(2), pages 235-256, June.
    6. Adrian Dragulescu & Victor M. Yakovenko, 2000. "Statistical mechanics of money," Papers cond-mat/0001432, arXiv.org, revised Aug 2000.
    7. Enrico Scalas, 2006. "Five Years of Continuous-time Random Walks in Econophysics," Lecture Notes in Economics and Mathematical Systems, in: Akira Namatame & Taisei Kaizouji & Yuuji Aruka (ed.), The Complex Networks of Economic Interactions, pages 3-16, Springer.
    8. Champernowne,D. G. & Cowell,F. A., 1999. "Economic Inequality and Income Distribution," Cambridge Books, Cambridge University Press, number 9780521589598.
    9. Mainardi, Francesco & Raberto, Marco & Gorenflo, Rudolf & Scalas, Enrico, 2000. "Fractional calculus and continuous-time finance II: the waiting-time distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 468-481.
    10. Bottazzi, Giulio & Secchi, Angelo, 2003. "Why are distributions of firm growth rates tent-shaped?," Economics Letters, Elsevier, vol. 80(3), pages 415-420, September.
    11. Masanao Aoki, 2001. "Modeling Aggregate Behavior and Fluctuations in Economics: Stochastic Views of Interacting Agents," UCLA Economics Online Papers 142, UCLA Department of Economics.
    12. Aoki,Masanao, 2004. "Modeling Aggregate Behavior and Fluctuations in Economics," Cambridge Books, Cambridge University Press, number 9780521606196, September.
    13. Domenico Costantini & Ubaldo Garibaldi & Paolo Viarengo, 2005. "A Finitary Characterization of the Ewens Sampling Formula," Lecture Notes in Economics and Mathematical Systems, in: Thomas Lux & Eleni Samanidou & Stefan Reitz (ed.), Nonlinear Dynamics and Heterogeneous Interacting Agents, pages 221-236, Springer.
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    Cited by:

    1. Einar Erlingsson & Simone Alfarano & Marco Raberto & Hlynur Stefánsson, 2013. "On the distributional properties of size, profit and growth of Icelandic firms," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 57-74, April.
    2. Angle, John, 2011. "The particle system model of income and wealth more likely to imply an analogue of thermodynamics in social science," MPRA Paper 28864, University Library of Munich, Germany.
    3. Pavel Exner & Petr v{S}eba, 2007. "A Markov process associated with plot-size distribution in Czech Land Registry and its number-theoretic properties," Papers 0711.1836, arXiv.org, revised Dec 2007.
    4. Carmen Pellicer-Lostao & Ricardo Lopez-Ruiz, 2011. "Application of Chaotic Number Generators in Econophysics," Papers 1110.4506, arXiv.org, revised Oct 2011.

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    Keywords

    Equilibrium; Growth;

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