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Maximum entropy model for business cycle synchronization

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  • Xi, Ning
  • Muneepeerakul, Rachata
  • Azaele, Sandro
  • Wang, Yougui

Abstract

The global economy is a complex dynamical system, whose cyclical fluctuations can mainly be characterized by simultaneous recessions or expansions of major economies. Thus, the researches on the synchronization phenomenon are key to understanding and controlling the dynamics of the global economy. Based on a pairwise maximum entropy model, we analyze the business cycle synchronization of the G7 economic system. We obtain a pairwise-interaction network, which exhibits certain clustering structure and accounts for 45% of the entire structure of the interactions within the G7 system. We also find that the pairwise interactions become increasingly inadequate in capturing the synchronization as the size of economic system grows. Thus, higher-order interactions must be taken into account when investigating behaviors of large economic systems.

Suggested Citation

  • Xi, Ning & Muneepeerakul, Rachata & Azaele, Sandro & Wang, Yougui, 2014. "Maximum entropy model for business cycle synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 189-194.
    • Handle: RePEc:eee:phsmap:v:413:y:2014:i:c:p:189-194
    DOI: 10.1016/j.physa.2014.07.005
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    Cited by:

    1. Kang, Sang Hoon & Lahmiri, Salim & Uddin, Gazi Salah & Arreola Hernandez, Jose & Yoon, Seong-Min, 2020. "Inflation cycle synchronization in ASEAN countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    2. Antonakakis, Nikolaos & Gogas, Periklis & Papadimitriou, Theophilos & Sarantitis, Georgios Antonios, 2016. "International business cycle synchronization since the 1870s: Evidence from a novel network approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 286-296.
    3. Farzad Alavi Fard & Firmin Doko Tchatoka & Sivagowry Sriananthakumar, 2021. "Maximum Entropy Evaluation of Asymptotic Hedging Error under a Generalised Jump-Diffusion Model," JRFM, MDPI, vol. 14(3), pages 1-19, February.
    4. António M Lopes & J A Tenreiro Machado & John S Huffstot & Maria Eugénia Mata, 2018. "Dynamical analysis of the global business-cycle synchronization," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-25, February.
    5. Matesanz, David & Ortega, Guillermo J., 2016. "On business cycles synchronization in Europe: A note on network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 287-296.

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