IDEAS home Printed from https://ideas.repec.org/p/boe/boeewp/0830.html

Liquidity transformation, collateral assets and counterparties

Author

Listed:
  • Calebe de Roure

    (Reserve Bank of Australia)

  • Nick McLaren

    (Bank of England)

Abstract

We investigate how counterparties’ characteristics, and the collateral they use, interact with their demand for liquidity in the Bank of England’s (BoE) operations. Between 2010 and 2016 there was regular usage of two BoE facilities: Indexed Long-Term Repos (ILTR) and the Funding for Lending Scheme (FLS). Using BoE proprietary data, we show that participation in ILTR is not skewed towards riskier counterparties, and is instead consistent with safe counterparties using the facilities to meet their liquidity needs. Collateral assets used for FLS are less liquid, since almost all assets are loan portfolios. Riskier and larger institutions are more likely to pre-position collateral in the FLS, but these counterparties do not subsequently draw upon FLS more than others do. Overall, our study points to no systemic misincentives; rather banks react to incentives in the manner intended by the policy objectives. Our results support the view that the central bank can provide market liquidity without absorbing undue risks onto its balance sheet.

Suggested Citation

  • Calebe de Roure & Nick McLaren, 2019. "Liquidity transformation, collateral assets and counterparties," Bank of England working papers 830, Bank of England.
    • Handle: RePEc:boe:boeewp:0830
    as

    Download full text from publisher

    File URL: https://www.bankofengland.co.uk/-/media/boe/files/working-paper/2019/liquidity-transformation-collateral-assets-and-counterparties.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Fernández-Val, Iván & Weidner, Martin, 2016. "Individual and time effects in nonlinear panel models with large N, T," Journal of Econometrics, Elsevier, vol. 192(1), pages 291-312.
    2. Falko Fecht & Kjell G. Nyborg & Jörg Rocholl & Jiri Woschitz, 2016. "Collateral, Central Bank Repos, and Systemic Arbitrage," Swiss Finance Institute Research Paper Series 16-66, Swiss Finance Institute.
    3. Fecht, Falko & Nyborg, Kjell G. & Rocholl, Jörg, 2011. "The price of liquidity: The effects of market conditions and bank characteristics," Journal of Financial Economics, Elsevier, vol. 102(2), pages 344-362.
    4. Nyborg, Kjell G. & Östberg, Per, 2014. "Money and liquidity in financial markets," Journal of Financial Economics, Elsevier, vol. 112(1), pages 30-52.
    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. Greppmair, Stefan & Paludkiewicz, Karol & Steffen, Sascha, 2025. "Collateral easing and safe asset scarcity: How money markets benefit from low-quality collateral," Discussion Papers 20/2025, Deutsche Bundesbank.
    2. repec:bdi:wptemi:misp_032_23 is not listed on IDEAS

    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. Nyborg, Kjell G., 2017. "Reprint of: Central bank collateral frameworks," Journal of Banking & Finance, Elsevier, vol. 83(C), pages 232-248.
    2. Fuhrer, Lucas Marc, 2018. "Liquidity in the repo market," Journal of International Money and Finance, Elsevier, vol. 84(C), pages 1-22.
    3. Nyborg, Kjell G., 2017. "Central bank collateral frameworks," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 198-214.
    4. Fuhrer, Lucas Marc & Müller, Benjamin & Steiner, Luzian, 2017. "The Liquidity Coverage Ratio and security prices," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 292-311.
    5. Ajay Kumar Mishra & Bhavik Parikh & Ronald W. Spahr, 2021. "Contemporaneous linkages: Funding liquidity and stock market spirals," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5912-5929, October.
    6. Weidner, Martin & Zylkin, Thomas, 2021. "Bias and consistency in three-way gravity models," Journal of International Economics, Elsevier, vol. 132(C).
    7. Botosaru, Irene & Muris, Chris & Pendakur, Krishna, 2023. "Identification of time-varying transformation models with fixed effects, with an application to unobserved heterogeneity in resource shares," Journal of Econometrics, Elsevier, vol. 232(2), pages 576-597.
    8. Raf Van Gestel & Tobias Müller & Johan Bosmans, 2018. "Learning from failure in healthcare: Dynamic panel evidence of a physician shock effect," Health Economics, John Wiley & Sons, Ltd., vol. 27(9), pages 1340-1353, September.
    9. Massimiliano Affinito, 2013. "Central bank refinancing, interbank markets, and the hypothesis of liquidity hoarding: evidence from a euro-area banking system," Temi di discussione (Economic working papers) 928, Bank of Italy, Economic Research and International Relations Area.
    10. Wang, Fa, 2017. "Maximum likelihood estimation and inference for high dimensional nonlinear factor models with application to factor-augmented regressions," MPRA Paper 93484, University Library of Munich, Germany, revised 19 May 2019.
    11. Giulio Cornelli, 2025. "When bricks meet bytes: does tokenisation fill gaps in traditional real estate markets?," BIS Working Papers 1311, Bank for International Settlements.
    12. Gindo Tampubolon, 2023. "Climate justice for persons with disability: Few harmed much, fewer still harmed too much," WIDER Working Paper Series wp-2023-2, World Institute for Development Economic Research (UNU-WIDER).
    13. Fecht, Falko & Weber, Patrick, 2023. "Who borrows from the Eurosystem’s lender-of-the-last-resort facility?," Journal of Banking & Finance, Elsevier, vol. 150(C).
    14. Andersen, Torben G. & Fusari, Nicola & Todorov, Viktor & Varneskov, Rasmus T., 2019. "Unified inference for nonlinear factor models from panels with fixed and large time span," Journal of Econometrics, Elsevier, vol. 212(1), pages 4-25.
    15. George Kapetanios & Laura Serlenga & Yongcheol Shin, 2024. "Testing for correlation between the regressors and factor loadings in heterogeneous panels with interactive effects," Advanced Studies in Theoretical and Applied Econometrics, in: Subal C. Kumbhakar & Robin C. Sickles & Hung-Jen Wang (ed.), Advances in Applied Econometrics, pages 147-195, Springer.
    16. Simon Hartmann & Rok Spruk, 2023. "The impact of unilateral BIT terminations on FDI: Quasi-experimental evidence from India," The Review of International Organizations, Springer, vol. 18(2), pages 259-296, April.
    17. Yang Yang, 2023. "Hukou Identity and Economic Behaviours: A Social Identity Perspective," Erudite Ph.D Dissertations, Erudite, number ph23-02 edited by Catherine Bros & Julie Lochard, December.
    18. Mariam Camarero & Sergi Moliner & Cecilio Tamarit, 2021. "Is there a euro effect in the drivers of US FDI? New evidence using Bayesian model averaging techniques," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 157(4), pages 881-926, November.
    19. Chernozhukov, Victor & Fernández-Val, Iván & Weidner, Martin, 2024. "Network and panel quantile effects via distribution regression," Journal of Econometrics, Elsevier, vol. 240(2).
    20. Thibaut Lamadon & Elena Manresa & Stephane Bonhomme, 2016. "Discretizing Unobserved Heterogeneity," 2016 Meeting Papers 1536, Society for Economic Dynamics.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • E41 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Demand for Money
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    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:boe:boeewp:0830. 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: Research (email available below). General contact details of provider: https://edirc.repec.org/data/boegvuk.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.