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Input-Output-based Measures of Systemic Importance

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  • Aldasoro, Iñaki
  • Angeloni, Ignazio

Abstract

The analyses of intersectoral linkages of Leontief (1941)and Hirschman (1958) provide a natural way to study the transmission of risk among interconnected banks and to measure their systemic importance. In this paper we show how classic input-output analysis can be applied to banking and how to derive six indicators that capture different aspects of systemic importance, using a simple numerical example for illustration. We also discuss the relationship with other approaches, most notably network centrality measures, both formally and by means of a simulated network.

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  • Aldasoro, Iñaki & Angeloni, Ignazio, 2013. "Input-Output-based Measures of Systemic Importance," MPRA Paper 49557, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:49557
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    Cited by:

    1. Aldasoro, Iñaki & Alves, Iván, 2018. "Multiplex interbank networks and systemic importance: An application to European data," Journal of Financial Stability, Elsevier, vol. 35(C), pages 17-37.
    2. Aldasoro, Iñaki & Delli Gatti, Domenico & Faia, Ester, 2017. "Bank networks: Contagion, systemic risk and prudential policy," Journal of Economic Behavior & Organization, Elsevier, vol. 142(C), pages 164-188.
    3. Angeloni, Ignazio & Faia, Ester & Winkler, Roland, 2014. "Exit strategies," European Economic Review, Elsevier, vol. 70(C), pages 231-257.
    4. Denbee, Edward & Julliard, Christian & Li, Ye & Yuan, Kathy, 2021. "Network risk and key players: A structural analysis of interbank liquidity," Journal of Financial Economics, Elsevier, vol. 141(3), pages 831-859.
    5. Irion, Kristina & Helberger, Natali, 2017. "Smart TV and the online media sector: User privacy in view of changing market realities," Telecommunications Policy, Elsevier, vol. 41(3), pages 170-184.
    6. Ma, Jing & He, Jianmin & Liu, Xiaoxing & Wang, Chao, 2019. "Diversification and systemic risk in the banking system," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 413-421.
    7. Sam Langfield & Kimmo Soramäki, 2016. "Interbank Exposure Networks," Computational Economics, Springer;Society for Computational Economics, vol. 47(1), pages 3-17, January.
    8. Halkos, George & Tsilika, Kyriaki, 2016. "Climate change impacts: Understanding the synergetic interactions using graph computing," MPRA Paper 75037, University Library of Munich, Germany.
    9. Li, Yanshuang & Zhuang, Xintian & Wang, Jian & Zhang, Weiping, 2020. "Analysis of the impact of Sino-US trade friction on China’s stock market based on complex networks," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    10. Cahen-Fourot, Louison & Campiglio, Emanuele & Dawkins, Elena & Godin, Antoine & Kemp-Benedict, Eric, 2020. "Looking for the Inverted Pyramid: An Application Using Input-Output Networks," Ecological Economics, Elsevier, vol. 169(C).
    11. Aldasoro, Iñaki & Hüser, Anne-Caroline & Kok, Christoffer, 2022. "Contagion accounting in stress-testing," Journal of Economic Dynamics and Control, Elsevier, vol. 137(C).
    12. Cahen-Fourot, Louison & Campiglio, Emanuele & Godin, Antoine & Kemp-Benedict, Eric & Trsek, Stefan, 2021. "Capital stranding cascades: The impact of decarbonisation on productive asset utilisation," Energy Economics, Elsevier, vol. 103(C).
    13. Iñaki Aldasoro & Anne-Caroline Hüser & Christoffer Kok Sørensen, 2020. "Contagion Accounting," BIS Working Papers 908, Bank for International Settlements.
    14. Chen, Wei & Hou, Xiaoli & Jiang, Manrui & Jiang, Cheng, 2022. "Identifying systemically important financial institutions in complex network: A case study of Chinese stock market," Emerging Markets Review, Elsevier, vol. 50(C).
    15. Kang, Dongsuk & Lee, Duk Hee, 2017. "Energy shocks and detecting influential industries," Energy, Elsevier, vol. 125(C), pages 234-247.
    16. Huang, Wei-Qiang & Wang, Dan, 2018. "A return spillover network perspective analysis of Chinese financial institutions’ systemic importance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 405-421.
    17. Halkos, George E. & Tsilika, Kyriaki D., 2017. "Climate change effects and their interactions: An analysis aiming at policy implications," Economic Analysis and Policy, Elsevier, vol. 53(C), pages 140-146.
    18. Hüser, Anne-Caroline, 2016. "Too interconnected to fail: A survey of the Interbank Networks literature," SAFE Working Paper Series 91, Leibniz Institute for Financial Research SAFE, revised 2016.
    19. Huang, Wei-Qiang & Wang, Dan, 2018. "Systemic importance analysis of chinese financial institutions based on volatility spillover network," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 19-30.

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    More about this item

    Keywords

    banks; input-output; systemic risk; too-interconnected-to fail; networks; interbank markets;
    All these keywords.

    JEL classification:

    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • G00 - Financial Economics - - General - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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