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Incentivizing Resilience in Financial Networks

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  • Matt V. Leduc
  • Stefan Thurner

Abstract

When banks extend loans to each other, they generate a negative externality in the form of systemic risk. They create a network of interbank exposures by which they expose other banks to potential insolvency cascades. In this paper, we show how a regulator can use information about the financial network to devise a transaction-specific tax based on a network centrality measure that captures systemic importance. Since different transactions have different impact on creating systemic risk, they are taxed differently. We call this tax a Systemic Risk Tax (SRT). We use an equilibrium concept inspired by the matching markets literature to show analytically that this SRT induces a unique equilibrium matching of lenders and borrowers that is systemic-risk efficient, i.e. it minimizes systemic risk given a certain transaction volume. On the other hand, we show that without this SRT multiple equilibrium matchings exist, which are generally inefficient. This allows the regulator to effectively stimulate a `rewiring' of the equilibrium interbank network so as to make it more resilient to insolvency cascades, without sacrificing transaction volume. Moreover, we show that a standard financial transaction tax (e.g. a Tobin-like tax) has no impact on reshaping the equilibrium financial network because it taxes all transactions indiscriminately. A Tobin-like tax is indeed shown to have a limited effect on reducing systemic risk while it decreases transaction volume.

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  • Matt V. Leduc & Stefan Thurner, 2016. "Incentivizing Resilience in Financial Networks," Papers 1606.03595, arXiv.org, revised Jun 2017.
  • Handle: RePEc:arx:papers:1606.03595
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    References listed on IDEAS

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    Cited by:

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    2. Diem, Christian & Pichler, Anton & Thurner, Stefan, 2020. "What is the minimal systemic risk in financial exposure networks?," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    3. Zhang, Simpson & van der Schaar, Mihaela, 2020. "Reputational dynamics in financial networks during a crisis," Journal of Financial Stability, Elsevier, vol. 49(C).
    4. Leonardo Badea & Daniel Ştefan Armeanu & Iulian Panait & Ştefan Cristian Gherghina, 2019. "A Markov Regime Switching Approach towards Assessing Resilience of Romanian Collective Investment Undertakings," Sustainability, MDPI, vol. 11(5), pages 1-24, March.
    5. Mohamed Belhaj & Renaud Bourlès & Frédéric Deroïan, 2020. "Prudential Regulation in Financial Networks," AMSE Working Papers 2030, Aix-Marseille School of Economics, France.
    6. Morteza Alaeddini & Philippe Madiès & Paul J. Reaidy & Julie Dugdale, 2023. "Interbank money market concerns and actors’ strategies—A systematic review of 21st century literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 573-654, April.
    7. Poledna, Sebastian & Bochmann, Olaf & Thurner, Stefan, 2017. "Basel III capital surcharges for G-SIBs are far less effective in managing systemic risk in comparison to network-based, systemic risk-dependent financial transaction taxes," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 230-246.
    8. Aymeric Vié & Alfredo J. Morales, 2021. "How Connected is Too Connected? Impact of Network Topology on Systemic Risk and Collapse of Complex Economic Systems," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1327-1351, April.
    9. Xu, Runjie & Mi, Chuanmin & Mierzwiak, Rafał & Meng, Runyu, 2020. "Complex network construction of Internet finance risk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    10. Runjie Xu & Chuanmin Mi & Rafal Mierzwiak & Runyu Meng, 2019. "Complex Network Construction of Internet Financial risk," Papers 1904.06640, arXiv.org, revised Aug 2019.
    11. Aymeric Vi'e & Alfredo J. Morales, 2019. "How connected is too connected? Impact of network topology on systemic risk and collapse of complex economic systems," Papers 1912.09814, arXiv.org.

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    More about this item

    JEL classification:

    • C78 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Bargaining Theory; Matching Theory
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • G01 - Financial Economics - - General - - - Financial Crises
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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