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Functional structure in production networks

Author

Listed:
  • Carolina Mattsson
  • Frank W. Takes
  • Eelke M. Heemskerk
  • Cees Diks
  • Gert Buiten
  • Albert Faber
  • Peter M. A. Sloot

Abstract

Production networks are integral to economic dynamics, yet dis-aggregated network data on inter-firm trade is rarely collected and often proprietary. Here we situate company-level production networks among networks from other domains according to their local connectivity structure. Through this lens, we study a regional and a national network of inferred trade relationships reconstructed from Dutch national economic statistics and re-interpret prior empirical findings. We find that company-level production networks have so-called functional structure, as previously identified in protein-protein interaction (PPI) networks. Functional networks are distinctive in their over-representation of closed squares, which we quantify using an existing measure called spectral bipartivity. Shared local connectivity structure lets us ferry insights between domains. PPI networks are shaped by complementarity, rather than homophily, and we use multi-layer directed configuration models to show that this principle explains the emergence of functional structure in production networks. Companies are especially similar to their close competitors, not to their trading partners. Our findings have practical implications for the analysis of production networks and a thorough understanding of their local connectivity structure will help us better reason about the micro-economic mechanisms behind their routine function, failure, and growth.

Suggested Citation

  • Carolina Mattsson & Frank W. Takes & Eelke M. Heemskerk & Cees Diks & Gert Buiten & Albert Faber & Peter M. A. Sloot, 2021. "Functional structure in production networks," Papers 2103.15777, arXiv.org.
  • Handle: RePEc:arx:papers:2103.15777
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    File URL: http://arxiv.org/pdf/2103.15777
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    References listed on IDEAS

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    1. Watanabe, Hayafumi & Takayasu, Hideki & Takayasu, Misako, 2013. "Relations between allometric scalings and fluctuations in complex systems: The case of Japanese firms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 741-756.
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    Cited by:

    1. László Lőrincz & Sándor Juhász & Rebeka O. Szabó, 2022. "Business transactions and ownership ties between firms," CERS-IE WORKING PAPERS 2216, Institute of Economics, Centre for Economic and Regional Studies.
    2. Mungo, Luca & Lafond, François & Astudillo-Estévez, Pablo & Farmer, J. Doyne, 2023. "Reconstructing production networks using machine learning," Journal of Economic Dynamics and Control, Elsevier, vol. 148(C).
    3. Carolina E S Mattsson & Teodoro Criscione & Frank W Takes, 2022. "Circulation of a digital community currency," Papers 2207.08941, arXiv.org, revised Jun 2023.

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