IDEAS home Printed from https://ideas.repec.org/a/bla/stanee/v58y2004i3p365-380.html
   My bibliography  Save this article

Scoring bank loans that may go wrong: a case study

Author

Listed:
  • J. S. Cramer

Abstract

A bank employs logistic regression with state‐dependent sample selection to identify loans that may go wrong. The data consist of some 20 000 loans for which a number of conventional accounting ratios of the debtor firm are known; after two years just over 600 have gone wrong. Inspection shows that the state‐dependent sampling technique does not work because the data do not satisfy the standard logit model. Several variants on this model are considered, and it is found that a bounded logit with a ceiling of (far) less than 1 fits the data better. When it comes to their performance in an independent data‐set, however, the differences between the various methods of analysis are negligible.

Suggested Citation

  • J. S. Cramer, 2004. "Scoring bank loans that may go wrong: a case study," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(3), pages 365-380, August.
    • Handle: RePEc:bla:stanee:v:58:y:2004:i:3:p:365-380
    DOI: 10.1111/j.1467-9574.2004.00127.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-9574.2004.00127.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1467-9574.2004.00127.x?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Yu Xie & Charles F. Manski, 1989. "The Logit Model and Response-Based Samples," Sociological Methods & Research, , vol. 17(3), pages 283-302, February.
    2. Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
    3. Franses, Ph.H.B.F. & Slagter, E. & Cramer, J.S., 1999. "Censored regression analysis in large samples with many zero observations," Econometric Institute Research Papers EI 9939-A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Manski, Charles F & Lerman, Steven R, 1977. "The Estimation of Choice Probabilities from Choice Based Samples," Econometrica, Econometric Society, vol. 45(8), pages 1977-1988, November.
    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. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    2. Annemiek Vuren & Daniel Vuuren, 2007. "Financial Incentives in Disability Insurance in the Netherlands," De Economist, Springer, vol. 155(1), pages 73-98, March.
    3. J.S. Cramer, 2005. "Omitted Variables and Misspecified Disturbances in the Logit Model," Tinbergen Institute Discussion Papers 05-084/4, Tinbergen Institute.
    4. Medema, Lydian & Koning, Ruud H. & Lensink, Robert, 2009. "A practical approach to validating a PD model," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 701-708, April.
    5. Annemiek Vuren & Daniel Vuuren, 2007. "Financial Incentives in Disability Insurance in the Netherlands," De Economist, Springer, vol. 155(1), pages 73-98, March.
    6. Hussein A. Abdou & John Pointon, 2011. "Credit Scoring, Statistical Techniques And Evaluation Criteria: A Review Of The Literature," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 59-88, April.

    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. Esmeralda Ramalho, 2004. "Covariate Measurement Error in Endogenous Stratified Samples," Economics Working Papers 2_2004, University of Évora, Department of Economics (Portugal).
    2. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    3. Esmerelda A. Ramalho & Richard Smith, 2003. "Discrete choice non-response," CeMMAP working papers 07/03, Institute for Fiscal Studies.
    4. Pamela Giustinelli, 2016. "Group Decision Making With Uncertain Outcomes: Unpacking Child–Parent Choice Of The High School Track," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 57(2), pages 573-602, May.
    5. Ramalho Esmeralda A., 2010. "Covariate Measurement Error: Bias Reduction under Response-Based Sampling," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-34, September.
    6. repec:jss:jstsof:08:i02 is not listed on IDEAS
    7. Stock, Ruth Maria & von Hippel, Eric & Gillert, Nils Lennart, 2016. "Impacts of personality traits on consumer innovation success," Research Policy, Elsevier, vol. 45(4), pages 757-769.
    8. Maalouf, Maher & Trafalis, Theodore B., 2011. "Robust weighted kernel logistic regression in imbalanced and rare events data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 168-183, January.
    9. Esmeralda Ramalho, 2004. "Binary models with misclassification in the variable of interest," Economics Working Papers 3_2004, University of Évora, Department of Economics (Portugal).
    10. Esmeralda A. Ramalho & Richard J. Smith, 2013. "Discrete Choice Non-Response," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 80(1), pages 343-364.
    11. Abhirup Chakrabarti & Will Mitchell, 2013. "The Persistent Effect of Geographic Distance in Acquisition Target Selection," Organization Science, INFORMS, vol. 24(6), pages 1805-1826, December.
    12. Abay, Kibrom A., 2015. "Investigating the nature and impact of reporting bias in road crash data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 71(C), pages 31-45.
    13. Avanzini, Diego & Martı́nez, Juan Francisco & Pérez, Vı́ctor, 2020. "Assessing mortgage default risk in full-recourse economies, with an application to the case of Chile," Latin American Journal of Central Banking (previously Monetaria), Elsevier, vol. 1(1).
    14. Ramalho, Esmeralda A., 2002. "Regression models for choice-based samples with misclassification in the response variable," Journal of Econometrics, Elsevier, vol. 106(1), pages 171-201, January.
    15. Ahmed, M.S. & Attouch, M.K. & Dabo-Niang, S., 2018. "Binary functional linear models under choice-based sampling," Econometrics and Statistics, Elsevier, vol. 7(C), pages 134-152.
    16. Yossi Perelman & Meir Yaish & Benjamin Bental, 2019. "The price of religiosity: Enticing young Haredi men into secular academic studies," Rationality and Society, , vol. 31(2), pages 129-151, May.
    17. Nguimkeu, Pierre & Denteh, Augustine & Tchernis, Rusty, 2019. "On the estimation of treatment effects with endogenous misreporting," Journal of Econometrics, Elsevier, vol. 208(2), pages 487-506.
    18. Adele Bergin, 2015. "Employer Changes and Wage Changes: Estimation with Measurement Error in a Binary Variable," LABOUR, CEIS, vol. 29(2), pages 194-223, June.
    19. Kocięcki, Andrzej & Kolasa, Marcin, 2023. "A solution to the global identification problem in DSGE models," Journal of Econometrics, Elsevier, vol. 236(2).
    20. Steimetz, Seiji S.C. & Brownstone, David, 2005. "Estimating commuters' "value of time" with noisy data: a multiple imputation approach," Transportation Research Part B: Methodological, Elsevier, vol. 39(10), pages 865-889, December.
    21. John K. Dagsvik & Zhiyang Jia, 2016. "Labor Supply as a Choice Among Latent Jobs: Unobserved Heterogeneity and Identification," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 487-506, April.

    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:bla:stanee:v:58:y:2004:i:3:p:365-380. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0039-0402 .

    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.