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Unfolding the hidden structure of the Hungarian multi-layer firm network

Author

Listed:
  • Andras Borsos

    (Magyar Nemzeti Bank (Central Bank of Hungary))

  • Martin Stancsics

    (Magyar Nemzeti Bank (Central Bank of Hungary))

Abstract

In this paper we offer an explorative, mainly descriptive analysis about the multi-layered network of Hungarian firms. To conduct this study, we obtained access to firm-level supplier information, on which we could superimpose also the ownership background of all Hungarian companies. Our primary focus was to explore the topological origins of shock propagation phenomena among firms. As both the supplier and the ownership layers are considered to be among the most significant shock-transmitting mediums, our data is ideal to gain insight into previously unobserved structural drivers of spreading processes. We found (i) several topological traits on micro-, meso-, and macro-scale as well, which can be responsible for facilitating contagious processes via supplier links; (ii) we could also identify separated blocks of the economy (representing different production chains) within which shocks can more freely spread in the system; (iii) furthermore, we could assess the significance of economic entities regarding the extent they can influence the economy via their ownership relations.

Suggested Citation

  • Andras Borsos & Martin Stancsics, 2020. "Unfolding the hidden structure of the Hungarian multi-layer firm network," MNB Occasional Papers 2020/139, Magyar Nemzeti Bank (Central Bank of Hungary).
    • Handle: RePEc:mnb:opaper:2020/139
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    File URL: https://www.mnb.hu/letoltes/mnb-op-139-final-1.pdf
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    Citations

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    Cited by:

    1. Csaba Burger, 2022. "Defaulting Alone: The Geography of Sme Owner Numbers and Credit Risk in Hungary," MNB Occasional Papers 2022/144, Magyar Nemzeti Bank (Central Bank of Hungary).
    2. William Schueller & Christian Diem & Melanie Hinterplattner & Johannes Stangl & Beate Conrady & Markus Gerschberger & Stefan Thurner, 2022. "Propagation of disruptions in supply networks of essential goods: A population-centered perspective of systemic risk," Papers 2201.13325, arXiv.org.
    3. Zlata Tabachov'a & Christian Diem & Andr'as Borsos & Csaba Burger & Stefan Thurner, 2023. "Estimating the impact of supply chain network contagion on financial stability," Papers 2305.04865, arXiv.org.
    4. Christian Diem & Andr'as Borsos & Tobias Reisch & J'anos Kert'esz & Stefan Thurner, 2021. "Quantifying firm-level economic systemic risk from nation-wide supply networks," Papers 2104.07260, arXiv.org.

    More about this item

    Keywords

    ownership network; producƟon network; supply chain; spillover; shock propagaƟon; contagion;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production

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