IDEAS home Printed from https://ideas.repec.org/p/fip/fednsr/356.html
   My bibliography  Save this paper

Which bank is the \\"central\\" bank? an application of Markov theory to the Canadian Large Value Transfer System

Author

Listed:
  • Morten L. Bech
  • James T. E. Chapman
  • Rod Garratt

Abstract

Recently, economists have argued that a bank's importance within the financial system depends not only on its individual characteristics but also on its position within the banking network. A bank is deemed to be \\"central\\" if, based on our network analysis, it is predicted to hold the most liquidity. In this paper, we use a method similar to Google's PageRank procedure to rank banks in the Canadian Large Value Transfer System (LVTS). In doing so, we obtain estimates of the payment processing speeds for the individual banks. These differences in processing speeds are essential for explaining why observed daily distributions of liquidity differ from the initial distributions, which are determined by the credit limits selected by banks.

Suggested Citation

  • Morten L. Bech & James T. E. Chapman & Rod Garratt, 2008. "Which bank is the \\"central\\" bank? an application of Markov theory to the Canadian Large Value Transfer System," Staff Reports 356, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:356
    Note: For a published version of this report, see Morten L. Bech, James T. E. Chapman, and Rod Garratt, "Which Bank Is the 'Central' Bank?" Journal of Monetary Economics 57, no. 3 (April 2010): 352-63.
    as

    Download full text from publisher

    File URL: https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr356.pdf
    Download Restriction: no

    File URL: https://www.newyorkfed.org/medialibrary/media/research/staff_reports/sr356.html
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Michael Boss & Helmut Elsinger & Martin Summer & Stefan Thurner, 2004. "An Empirical Analysis of the Network Structure of the Austrian Interbank Market," Financial Stability Report, Oesterreichische Nationalbank (Austrian Central Bank), issue 7, pages 77-87.
    2. Morten L. Bech & Rodney J. Garratt, 2012. "Illiquidity in the Interbank Payment System Following Wide‐Scale Disruptions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 44(5), pages 903-929, August.
    3. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Sean O'Connor & James Chapman & Kirby Millar, 2008. "Liquidity Efficiency and Distribution in the LVTS: Non-Neutrality of System Changes under Network Asymmetry," Discussion Papers 08-11, Bank of Canada.
    2. Monica Billio & Mila Getmansky & Andrew W. Lo & Loriana Pelizzon, 2010. "Econometric Measures of Systemic Risk in the Finance and Insurance Sectors," NBER Working Papers 16223, National Bureau of Economic Research, Inc.
    3. B. Craig & D. Salakhova & M. Saldias, 2018. "Payments delay: propagation and punishment," Working papers 671, Banque de France.
    4. Mr. Jorge A Chan-Lau, 2010. "Balance Sheet Network Analysis of Too-Connected-to-Fail Risk in Global and Domestic Banking Systems," IMF Working Papers 2010/107, International Monetary Fund.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bech, Morten L. & Chapman, James T.E. & Garratt, Rodney J., 2010. "Which bank is the "central" bank?," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 352-363, April.
    2. Clara Machado & Carlos León & Miguel Sarmiento & Freddy Cepeda & Orlando Chipatecua & Jorge Cely, 2011. "Riesgo Sistémico Y Estabilidad Del Sistema De Pagos De Alto Valor En Colombia: Análisis Bajo," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 29(65), pages 106-175, June.
    3. Paolo Bartesaghi & Michele Benzi & Gian Paolo Clemente & Rosanna Grassi & Ernesto Estrada, 2019. "Risk-dependent centrality in economic and financial networks," Papers 1907.07908, arXiv.org, revised Apr 2020.
    4. Clara Machado & Carlos León & Miguel Sarmiento & Freddy Cepeda & Orlando Chipatecua & Jorge Cely, 2011. "Riesgo Sistémico Y Estabilidad Del Sistema De Pagos De Alto Valor En Colombia: Análisis Bajo Topología De Redes Y Simulación De Pagos," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 29(65), pages 106-175, June.
    5. Galbiati, Marco & Soramäki, Kimmo, 2011. "An agent-based model of payment systems," Journal of Economic Dynamics and Control, Elsevier, vol. 35(6), pages 859-875, June.
    6. Alesia Kalbaska & Cesario Mateus, 2019. "From sovereigns to banks: evidence on cross-border contagion," Journal of Banking Regulation, Palgrave Macmillan, vol. 20(1), pages 86-103, March.
    7. Kanno, Masayasu, 2020. "Interconnectedness and systemic risk in the US CDS market," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    8. Thomas J. Sargent & John Stachurski, 2022. "Economic Networks: Theory and Computation," Papers 2203.11972, arXiv.org, revised Jul 2022.
    9. Karimi, Fatemeh & Lotfi, Shahriar & Izadkhah, Habib, 2021. "Community-guided link prediction in multiplex networks," Journal of Informetrics, Elsevier, vol. 15(4).
    10. D’Errico, Marco & Battiston, Stefano & Peltonen, Tuomas & Scheicher, Martin, 2018. "How does risk flow in the credit default swap market?," Journal of Financial Stability, Elsevier, vol. 35(C), pages 53-74.
    11. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves & Lee, Lung-Fei, 2011. "Criminal Networks: Who is the Key Player?," Research Papers in Economics 2011:7, Stockholm University, Department of Economics.
    12. Aref Mahdavi Ardekani, 2020. "Liquidity, Interbank Network Topology and Bank Capital," Post-Print halshs-02967226, HAL.
    13. Agnieszka Rusinowska & Rudolf Berghammer & Harrie de Swart & Michel Grabisch, 2011. "Social networks: Prestige, centrality, and influence (Invited paper)," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00633859, HAL.
    14. Gabrielle Demange, 2018. "Contagion in Financial Networks: A Threat Index," Management Science, INFORMS, vol. 64(2), pages 955-970, February.
    15. Lin, Dan & Wu, Jiajing & Xuan, Qi & Tse, Chi K., 2022. "Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    16. Yao Hongxing & Lu Yunxia, 2017. "Analyzing the Potential Influence of Shanghai Stock Market Based on Link Prediction Method," Journal of Systems Science and Information, De Gruyter, vol. 5(5), pages 446-461, October.
    17. Zhepeng Li & Xiao Fang & Xue Bai & Olivia R. Liu Sheng, 2017. "Utility-Based Link Recommendation for Online Social Networks," Management Science, INFORMS, vol. 63(6), pages 1938-1952, June.
    18. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Shokrollahi, Arman, 2015. "Improving detection of influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 833-845.
    19. Dequiedt, Vianney & Zenou, Yves, 2017. "Local and consistent centrality measures in parameterized networks," Mathematical Social Sciences, Elsevier, vol. 88(C), pages 28-36.
    20. Morten L. Bech & Antoine Martin & James J. McAndrews, 2012. "Settlement liquidity and monetary policy implementation—lessons from the financial crisis," Economic Policy Review, Federal Reserve Bank of New York, vol. 18(Mar), pages 3-20.

    More about this item

    Keywords

    network; federal funds; money markets; interbank; topology;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    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:fip:fednsr:356. See general information about how to correct material in RePEc.

    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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Gabriella Bucciarelli (email available below). General contact details of provider: https://edirc.repec.org/data/frbnyus.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.