IDEAS home Printed from https://ideas.repec.org/a/mcb/jmoncb/v27y1995i1p202-16.html
   My bibliography  Save this article

A Multinomial Logit Analysis of Problem Loan Resolution Choices in Banking

Author

Listed:
  • Lawrence, Edward C
  • Arshadi, Nasser

Abstract

This paper presents a conceptual framework of problem loan resolution choices that is a function of the combined borrower and lender decisions. A bank will choose a workout option if its expected value is greater than the outcome under a no-workout plan. For the borrower, if the reputational penalty due to a default is less than the opportunity cost of the best new alternative, the borrower will have an incentive to default. If the reverse holds then the borrower will be better-off with a loan workout. Using a unique data set composed of borrower, lender and economic factors we empirically examine the problem loan resolution choices. The, results provide support for our conceptual framework that problem loan choices are based on combined borrower/lender variables. Copyright 1995 by Ohio State University Press.

Suggested Citation

  • Lawrence, Edward C & Arshadi, Nasser, 1995. "A Multinomial Logit Analysis of Problem Loan Resolution Choices in Banking," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(1), pages 202-216, February.
  • Handle: RePEc:mcb:jmoncb:v:27:y:1995:i:1:p:202-16
    as

    Download full text from publisher

    File URL: http://links.jstor.org/sici?sici=0022-2879%28199502%2927%3A1%3C202%3AAMLAOP%3E2.0.CO%3B2-8&origin=bc
    File Function: full text
    Download Restriction: Access to full text is restricted to JSTOR subscribers. See http://www.jstor.org for details.

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

    Citations

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


    Cited by:

    1. Anthony Pennington-Cross, 2010. "The Duration of Foreclosures in the Subprime Mortgage Market: A Competing Risks Model with Mixing," The Journal of Real Estate Finance and Economics, Springer, vol. 40(2), pages 109-129, February.
    2. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    3. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
    4. Chien-An Wang, 2012. "Determinants of the Choice of Formal Bankruptcy Procedure: An International Comparison of Reorganization and Liquidation," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(2), pages 4-28, March.
    5. Alexander N. Bogin & William M. Doerner & William D. Larson, 2016. "Missing the Mark: House Price Index Accuracy and Mortgage Credit Modeling," Working Papers 2016-010, The George Washington University, Department of Economics, Research Program on Forecasting.
    6. Fabián Enrique Salazar Villano, 2013. "Cuantificación del riesgo de incumplimiento en créditos de libre inversión: un ejercicio econométrico para una entidad bancaria del municipio de Popayán, Colombia," ESTUDIOS GERENCIALES, UNIVERSIDAD ICESI, December.
    7. Sorokina, Nonna & Thornton, John H., 2016. "Reactions of equity markets to recent financial reforms," Journal of Economics and Business, Elsevier, vol. 87(C), pages 50-69.
    8. Michelle A. Danis & Anthony Pennington-Cross, 2005. "A dynamic look at subprime loan performance," Working Papers 2005-029, Federal Reserve Bank of St. Louis.
    9. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
    10. Danis, Michelle A. & Pennington-Cross, Anthony, 2008. "The delinquency of subprime mortgages," Journal of Economics and Business, Elsevier, vol. 60(1-2), pages 67-90.
    11. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
    12. Timotej Jagric & Vita Jagric & Davorin Kracun, 2011. "Does Non-linearity Matter in Retail Credit Risk Modeling?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(4), pages 384-402, August.
    13. Chien-An Wang, 2012. "Determinants of the Choice of Formal Bankruptcy Procedure: An International Comparison of Reorganization and Liquidation," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 48(2), pages 4-28, March.

    More about this item

    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:mcb:jmoncb:v:27:y:1995:i:1:p:202-16. 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: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0022-2879 .

    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 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.

    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.