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Statistical mechanics of complex economies

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  • Marco Bardoscia
  • Giacomo Livan
  • Matteo Marsili

Abstract

In the pursuit of ever increasing efficiency and growth, our economies have evolved to remarkable degrees of complexity, with nested production processes feeding each other in order to create products of greater sophistication from less sophisticated ones, down to raw materials. The engine of such an expansion have been competitive markets that, according to General Equilibrium Theory (GET), achieve efficient allocations under specific conditions. We study large random economies within the GET framework, as templates of complex economies, and we find that a non-trivial phase transition occurs: the economy freezes in a state where all production processes collapse when either the number of primary goods or the number of available technologies fall below a critical threshold. As in other examples of phase transitions in large random systems, this is an unintended consequence of the growth in complexity. Our findings suggest that the Industrial Revolution can be regarded as a sharp transition between different phases, but also imply that well developed economies can collapse if too many intermediate goods are introduced.

Suggested Citation

  • Marco Bardoscia & Giacomo Livan & Matteo Marsili, 2015. "Statistical mechanics of complex economies," Papers 1511.09203, arXiv.org, revised Apr 2017.
  • Handle: RePEc:arx:papers:1511.09203
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    Cited by:

    1. Qingru Sun & Xiangyun Gao & Shaobo Wen & Sida Feng & Ze Wang, 2019. "Modeling the impulse response complex network for studying the fluctuation transmission of price indices," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(4), pages 835-858, December.
    2. José Balsa-Barreiro & Aymeric Vié & Alfredo J. Morales & Manuel Cebrián, 2020. "Deglobalization in a hyper-connected world," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-4, December.
    3. Célestin Coquidé & José Lages & Leonardo Ermann & Dima Shepelyansky, 2022. "COVID-19 impact on the international trade," Post-Print hal-03536528, HAL.
    4. Demidov, Denis & Frahm, Klaus M. & Shepelyansky, Dima L., 2020. "What is the central bank of Wikipedia?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    5. C'elestin Coquid'e & Leonardo Ermann & Jos'e Lages & D. L. Shepelyansky, 2019. "Influence of petroleum and gas trade on EU economies from the reduced Google matrix analysis of UN COMTRADE data," Papers 1903.01820, arXiv.org.
    6. Leonie Wenz & Anders Levermann & Sven Norman Willner & Christian Otto & Kilian Kuhla, 2020. "Post-Brexit no-trade-deal scenario: Short-term consumer benefit at the expense of long-term economic development," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-14, September.
    7. Jean Philippe Bouchaud & Matteo Marsili & Jean-Pierre Nadal, 2023. "Application of spin glass ideas in social sciences, economics and finance," Post-Print hal-04145594, HAL.
    8. Cárdenas, Juan Pablo & Vidal, Gerardo & Urbina, Carolina & Olivares, Gastón & Fuentes, Miguel Angel, 2018. "Social crises. A network model approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 35-48.
    9. Célestin Coquidé & José Lages & Dima Shepelyansky, 2020. "Interdependence of sectors of economic activities for world countries from the reduced Google matrix analysis of WTO data," Post-Print hal-02132487, HAL.
    10. Jean-Philippe Bouchaud & Matteo Marsili & Jean-Pierre Nadal, 2023. "Application of spin glass ideas in social sciences, economics and finance," Papers 2306.16165, arXiv.org.

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