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Analyzing credit risk transmission to the non-financial sector in Europe: a network approach

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  • Gross, Christian
  • Siklos, Pierre

Abstract

We use a factor model and elastic net shrinkage to model a high-dimensional network of European CDS spreads. Our empirical approach allows us to assess the joint transmission of bank and sovereign risk to the non-financial corporate sector. Our findings identify a sectoral clustering in the CDS network, where financial institutions are in the center and non-financial entities as well as sovereigns are grouped around the financial center. The network has a geographical component reflected in different patterns of real-sector risk transmission across countries. Our framework also provides dynamic estimates of risk transmission, a useful tool for systemic risk monitoring. JEL Classification: C32, C38, C55, F3, G01, G15

Suggested Citation

  • Gross, Christian & Siklos, Pierre, 2018. "Analyzing credit risk transmission to the non-financial sector in Europe: a network approach," ESRB Working Paper Series 78, European Systemic Risk Board.
    • Handle: RePEc:srk:srkwps:201878
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    2. Lu Yang & Lei Yang & Xue Cui, 2023. "Sovereign default network and currency risk premia," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    3. Julio Gálvez, 2021. "Measuring interconnectedness across institutions and sectors," Financial Stability Review, Banco de España, issue Autumn.
    4. Yang, Lu, 2023. "Oil price bubbles: The role of network centrality on idiosyncratic sovereign risk," Resources Policy, Elsevier, vol. 82(C).
    5. Gül Huyugüzel Kışla & Y. Gülnur Muradoğlu & A. Özlem Önder, 2022. "Spillovers from one country’s sovereign debt to CDS (credit default swap) spreads of others during the European crisis: a spatial approach," Journal of Asset Management, Palgrave Macmillan, vol. 23(4), pages 277-296, July.
    6. Niţoi, Mihai & Pochea, Maria Miruna, 2022. "The nexus between bank connectedness and investors’ sentiment," Finance Research Letters, Elsevier, vol. 44(C).
    7. Julio Gálvez, 2021. "Measuring interconnectedness across institutions and sectors," Revista de Estabilidad Financiera, Banco de España, issue Otoño.
    8. Bax, Karoline & Bonaccolto, Giovanni & Paterlini, Sandra, 2024. "Spillovers in Europe: The role of ESG," Journal of Financial Stability, Elsevier, vol. 72(C).
    9. Egger, Peter H. & Li, Jie & Zhu, Jiaqing, 2023. "The network and own effects of global-systemically-important-bank designations," Journal of International Money and Finance, Elsevier, vol. 136(C).
    10. Bonaccolto, Giovanni & Borri, Nicola & Consiglio, Andrea, 2023. "Breakup and default risks in the great lockdown," Journal of Banking & Finance, Elsevier, vol. 147(C).
    11. Tihana Skrinjaric, 2022. "Macroeconomic effects of systemic stress: a rolling spillover index approach," Public Sector Economics, Institute of Public Finance, vol. 46(1), pages 109-140.
    12. Alexander Pütz & Pierre L. Siklos & Christoph Sulewski, 2019. "“Who pays the piper calls the tune” – Networks and transaction costs in commodity markets," CQE Working Papers 8819, Center for Quantitative Economics (CQE), University of Muenster.
    13. Julio Gálvez, 2021. "Measuring interconnectedness across institutions and sectors," Financial Stability Review, Banco de España, issue Autumn.

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    More about this item

    Keywords

    connectedness; contagion; credit risk; financial-real linkages; large datasets; networks; systemic risk;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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