IDEAS home Printed from https://ideas.repec.org/a/fau/fauart/v67y2017i6p462-491.html
   My bibliography  Save this article

The Time Dimension of the Links Between Loss Given Default and the Macroeconomy

Author

Listed:
  • Tomas Konecny

    () (European Systemic Risk Board
    Czech National Bank)

  • Jakub Seidler

    (ING Bank NV, Prague, Czech Republic,
    Czech National Bank (at the time this paper was written))

  • Aelta Belyaeva

    (CERGE-EI, Charles University)

  • Konstantin Belyaev

    (CERGE-EI, Charles University)

Abstract

Most studies focusing on the determinants of loss given default (LGD) have largely ignored possible lagged effects of the macroeconomy on LGD. We fill this gap by employing a wide set of macroeconomic covariates on a retail portfolio that represents 15% of the Czech consumer credit market over the period 2002–2012. We find an important time dimension to the links between LGD and the aggregate economy in the Czech Republic. The model that allows exclusively for contemporaneous effects includes a number of significant macroeconomic variables, some of which have non-intuitive signs. Nonetheless, a more general time structure of the LGD model makes current macroeconomic variables largely irrelevant and highlights the importance of delayed responses of LGD to the macroeconomic environment.

Suggested Citation

  • Tomas Konecny & Jakub Seidler & Aelta Belyaeva & Konstantin Belyaev, 2017. "The Time Dimension of the Links Between Loss Given Default and the Macroeconomy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 67(6), pages 462-491, October.
  • Handle: RePEc:fau:fauart:v:67:y:2017:i:6:p:462-491
    as

    Download full text from publisher

    File URL: http://journal.fsv.cuni.cz/storage/1399_462_-_491_seidler_final_issue_6_2017.pdf
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    as
    1. Radovan Chalupka & Juraj Kopecsni, 2009. "Modeling Bank Loan LGD of Corporate and SME Segments: A Case Study," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 360-382, Oktober.
    2. Bastos, João A., 2010. "Forecasting bank loans loss-given-default," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2510-2517, October.
    3. Calabrese, Raffaella & Zenga, Michele, 2010. "Bank loan recovery rates: Measuring and nonparametric density estimation," Journal of Banking & Finance, Elsevier, vol. 34(5), pages 903-911, May.
    4. Bruche, Max & González-Aguado, Carlos, 2010. "Recovery rates, default probabilities, and the credit cycle," Journal of Banking & Finance, Elsevier, vol. 34(4), pages 754-764, April.
    5. Edward I. Altman & Brooks Brady & Andrea Resti & Andrea Sironi, 2005. "The Link between Default and Recovery Rates: Theory, Empirical Evidence, and Implications," The Journal of Business, University of Chicago Press, vol. 78(6), pages 2203-2228, November.
    6. Stefano Caselli & Stefano Gatti & Francesca Querci, 2008. "The Sensitivity of the Loss Given Default Rate to Systematic Risk: New Empirical Evidence on Bank Loans," Journal of Financial Services Research, Springer;Western Finance Association, vol. 34(1), pages 1-34, August.
    7. Bellotti, Tony & Crook, Jonathan, 2012. "Loss given default models incorporating macroeconomic variables for credit cards," International Journal of Forecasting, Elsevier, vol. 28(1), pages 171-182.
    8. Dermine, J. & de Carvalho, C. Neto, 2006. "Bank loan losses-given-default: A case study," Journal of Banking & Finance, Elsevier, vol. 30(4), pages 1219-1243, April.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    credit losses; loss given default; recovery rates; workout LGD;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

    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:fau:fauart:v:67:y:2017:i:6:p:462-491. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Lenka Herrmannova). General contact details of provider: http://edirc.repec.org/data/icunicz.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.