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From particles to firms: a kinetic model of climbing up evolutionary landscapes

Author

Listed:
  • Nicola Bellomo
  • Giovanni Dosi
  • Damian A. Knopoff
  • Maria Enrica Virgillito

Abstract

This paper represents the first attempt to bridge the evolutionary theory in economics and the theory of active particles in mathematics. It seeks to present a kinetic model for an evolutionary formalization of socio-economic systems. The derived new mathematical formulation intends to formalize the processes of learning and selection as the two fundamental drivers of evolutionary systems [7]. To coherentl y represent the aforementioned properties, the kinetic theory of active particles [1] is here further developed, including the complex interaction of two hierarchical functional subsystems. Modeling and simulations enlighten the predictive ability of the approach. Finally, we outline the potential avenues for future research.

Suggested Citation

  • Nicola Bellomo & Giovanni Dosi & Damian A. Knopoff & Maria Enrica Virgillito, 2020. "From particles to firms: a kinetic model of climbing up evolutionary landscapes," LEM Papers Series 2020/04, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    • Handle: RePEc:ssa:lemwps:2020/04
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    References listed on IDEAS

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    1. Giovanni Dosi & Marcelo C. Pereira & Maria Enrica Virgillito, 2017. "The footprint of evolutionary processes of learning and selection upon the statistical properties of industrial dynamics," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(2), pages 187-210.
    2. G. Dosi & M. C. Pereira & M. E. Virgillito, 2018. "On the robustness of the fat-tailed distribution of firm growth rates: a global sensitivity analysis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(1), pages 173-193, April.
    3. Marina Dolfin & Dami'an Knopoff & Leone Leonida & Dario Maimone Ansaldo Patti, 2015. "Escaping the trap of 'blocking': a kinetic model linking economic development and political competition," Papers 1602.08442, arXiv.org.
    4. Pareschi, Lorenzo & Toscani, Giuseppe, 2013. "Interacting Multiagent Systems: Kinetic equations and Monte Carlo methods," OUP Catalogue, Oxford University Press, number 9780199655465.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Petr Bujok, 2021. "The Real-Life Application of Differential Evolution with a Distance-Based Mutation-Selection," Mathematics, MDPI, vol. 9(16), pages 1-15, August.

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    More about this item

    Keywords

    Evolutionary dynamics; idiosyncratic learning; market selection; active particles; kinetic theory.;
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