IDEAS home Printed from
   My bibliography  Save this paper

Measuring the default risk of sovereign debt from the perspective of network


  • Hongwei Chuang
  • Hwai-Chung Ho


Recently, there has been a growing interest in network research, especially in these fields of biology, computer science, and sociology. It is natural to address complex financial issues such as the European sovereign debt crisis from the perspective of network. In this article, we construct a network model according to the debt--credit relations instead of using the conventional methodology to measure the default risk. Based on the model, a risk index is examined using the quarterly report of consolidated foreign claims from the Bank for International Settlements (BIS) and debt/GDP ratios among these reporting countries. The empirical results show that this index can help the regulators and practitioners not only to determine the status of interconnectivity but also to point out the degree of the sovereign debt default risk. Our approach sheds new light on the investigation of quantifying the systemic risk.

Suggested Citation

  • Hongwei Chuang & Hwai-Chung Ho, 2013. "Measuring the default risk of sovereign debt from the perspective of network," Papers 1304.3814,
  • Handle: RePEc:arx:papers:1304.3814

    Download full text from publisher

    File URL:
    File Function: Latest version
    Download Restriction: no

    References listed on IDEAS

    1. Lakka, Spyridoula & Michalakelis, Christos & Varoutas, Dimitris & Martakos, Draculis, 2013. "Competitive dynamics in the operating systems market: Modeling and policy implications," Technological Forecasting and Social Change, Elsevier, vol. 80(1), pages 88-105.
    2. Mercure, J.-F. & Pollitt, H. & Chewpreecha, U. & Salas, P. & Foley, A.M. & Holden, P.B. & Edwards, N.R., 2014. "The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector," Energy Policy, Elsevier, vol. 73(C), pages 686-700.
    3. Raouf Boucekkine & David De La Croix & Omar Licandro, 2004. "MODELLING VINTAGE STRUCTURES WITH DDEs: PRINCIPLES AND APPLICATIONS," Mathematical Population Studies, Taylor & Francis Journals, vol. 11(3-4), pages 151-179.
    4. Weiss, Martin & Patel, Martin K. & Junginger, Martin & Perujo, Adolfo & Bonnel, Pierre & van Grootveld, Geert, 2012. "On the electrification of road transport - Learning rates and price forecasts for hybrid-electric and battery-electric vehicles," Energy Policy, Elsevier, vol. 48(C), pages 374-393.
    5. BOUCEKKINE, Raouf & DE LA CROIX, David & LICANDRO, Omar, 2006. "Vintage capital," CORE Discussion Papers 2006024, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    7. Jean-Francois Mercure, 2012. "On the changeover timescales of technology transitions and induced efficiency changes: an overarching theory," Papers 1209.0424,
    8. Andrew Atkeson & Patrick J. Kehoe, 2007. "Modeling the Transition to a New Economy: Lessons from Two Technological Revolutions," American Economic Review, American Economic Association, vol. 97(1), pages 64-88, March.
    9. Arthur, W Brian, 1989. "Competing Technologies, Increasing Returns, and Lock-In by Historical Events," Economic Journal, Royal Economic Society, vol. 99(394), pages 116-131, March.
    10. Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
    11. Arrow, Kenneth & Bolin, Bert & Costanza, Robert & Dasgupta, Partha & Folke, Carl & Holling, C.S. & Jansson, Bengt-Owe & Levin, Simon & Mäler, Karl-Göran & Perrings, Charles & Pimentel, David, 1996. "Economic growth, carrying capacity, and the environment," Environment and Development Economics, Cambridge University Press, vol. 1(01), pages 104-110, February.
    12. Geels, Frank W., 2002. "Technological transitions as evolutionary reconfiguration processes: a multi-level perspective and a case-study," Research Policy, Elsevier, vol. 31(8-9), pages 1257-1274, December.
    13. R. M. Solow & J. Tobin & C. C. von Weizsäcker & M. Yaari, 1966. "Neoclassical Growth with Fixed Factor Proportions," Review of Economic Studies, Oxford University Press, vol. 33(2), pages 79-115.
    14. Costanza, Robert, 1995. "Economic growth, carrying capacity, and the environment," Ecological Economics, Elsevier, vol. 15(2), pages 89-90, November.
    15. Saviotti, P P & Mani, G S, 1995. "Competition, Variety and Technological Evolution: A Replicator Dynamics Model," Journal of Evolutionary Economics, Springer, vol. 5(4), pages 369-392, December.
    16. Wilson, Charlie, 2012. "Up-scaling, formative phases, and learning in the historical diffusion of energy technologies," Energy Policy, Elsevier, vol. 50(C), pages 81-94.
    17. Karolina Safarzyńska & Jeroen Bergh, 2010. "Evolutionary models in economics: a survey of methods and building blocks," Journal of Evolutionary Economics, Springer, vol. 20(3), pages 329-373, June.
    18. John Metcalfe, 2008. "Accounting for economic evolution: Fitness and the population method," Journal of Bioeconomics, Springer, vol. 10(1), pages 23-49, April.
    19. Geoffrey Hodgson & Kainan Huang, 2012. "Evolutionary game theory and evolutionary economics: are they different species?," Journal of Evolutionary Economics, Springer, vol. 22(2), pages 345-366, April.
    20. Malerba, Franco, et al, 1999. "'History-Friendly' Models of Industry Evolution: The Computer Industry," Industrial and Corporate Change, Oxford University Press, vol. 8(1), pages 3-40, March.
    21. Karolina Safarzyńska & Jeroen Bergh, 2013. "An evolutionary model of energy transitions with interactive innovation-selection dynamics," Journal of Evolutionary Economics, Springer, vol. 23(2), pages 271-293, April.
    22. Mercure, Jean-François, 2012. "FTT:Power : A global model of the power sector with induced technological change and natural resource depletion," Energy Policy, Elsevier, vol. 48(C), pages 799-811.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.
    2. Chuang, Hongwei, 2016. "Brokers’ financial network and stock return," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 172-183.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1304.3814. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.