IDEAS home Printed from https://ideas.repec.org/a/eee/ecosys/v45y2021i1s0939362520300704.html
   My bibliography  Save this article

The pro-cyclicality of risk weights for credit exposures: Driven by the retail segment

Author

Listed:
  • Malovaná, Simona

Abstract

This paper examines the pro-cyclicality of implicit risk weights of credit exposures and the potential contribution of accommodative monetary policy using data for the Czech Republic. The empirical results indicate that risk weights behave pro-cyclically under the IRB approach and acyclically under the STA approach. The pro-cyclical behaviour of IRB risk weights is caused primarily by the retail exposures, the strongest effects being in the highest and lowest quantiles of risk weights. The risk weights for retail exposures behave pro-cyclically not only with regard to the business cycle, but also with respect to the financial cycle and house price growth. In addition, monetary policy easing contributes to the pro-cyclicality in higher quantiles of risk weights.

Suggested Citation

  • Malovaná, Simona, 2021. "The pro-cyclicality of risk weights for credit exposures: Driven by the retail segment," Economic Systems, Elsevier, vol. 45(1).
    • Handle: RePEc:eee:ecosys:v:45:y:2021:i:1:s0939362520300704
    DOI: 10.1016/j.ecosys.2020.100763
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0939362520300704
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecosys.2020.100763?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Internal ratings-based approach; Monetary policy; Procyclicality; Retail exposures; Risk weights;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • 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

    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:eee:ecosys:v:45:y:2021:i:1:s0939362520300704. 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.

    We have no bibliographic 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.

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