IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpdc/0109009.html
   My bibliography  Save this paper

Scoring Drop-Out at a Microlender in Bolivia

Author

Listed:
  • Mark Schreiner

    (Washington University in St. Louis)

Abstract

This paper presents a scoring model that predicts the risk of drop-out for borrowers at a microfinance lender in Bolivia. Drop-out risk was greater for women, manufacturers, newer borrowers, and those with more arrears. Out-of-sample tests suggest that scoring may help microfinance lenders to detect segments of their clientele (and even specific current clients) who are at-risk of drop-out.

Suggested Citation

  • Mark Schreiner, 2001. "Scoring Drop-Out at a Microlender in Bolivia," Development and Comp Systems 0109009, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpdc:0109009
    Note: Type of Document - Adobe Acrobat 3.0; prepared on Windows 98; to print on Adobe Acrobat 3.0; pages: ; figures: Included in pdf file
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/dev/papers/0109/0109009.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wiginton, John C., 1980. "A Note on the Comparison of Logit and Discriminant Models of Consumer Credit Behavior," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(3), pages 757-770, September.
    2. Jenkins, Stephen P, 1995. "Easy Estimation Methods for Discrete-Time Duration Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 57(1), pages 129-138, February.
    3. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541, September.
    4. Greene, William, 1998. "Sample selection in credit-scoring models1," Japan and the World Economy, Elsevier, vol. 10(3), pages 299-316, July.
    5. Navajas, Sergio & Schreiner, Mark & Meyer, Richard L. & Gonzalez-vega, Claudio & Rodriguez-meza, Jorge, 2000. "Microcredit and the Poorest of the Poor: Theory and Evidence from Bolivia," World Development, Elsevier, vol. 28(2), pages 333-346, February.
    6. Boyes, William J. & Hoffman, Dennis L. & Low, Stuart A., 1989. "An econometric analysis of the bank credit scoring problem," Journal of Econometrics, Elsevier, vol. 40(1), pages 3-14, January.
    7. Loretta J. Mester, 1997. "What's the point of credit scoring?," Business Review, Federal Reserve Bank of Philadelphia, issue Sep, pages 3-16.
    8. Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, December.
    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. Schicks, Jessica, 2014. "Over-Indebtedness in Microfinance – An Empirical Analysis of Related Factors on the Borrower Level," World Development, Elsevier, vol. 54(C), pages 301-324.

    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. 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.
    2. Dalila Boughaci & Abdullah A. K. Alkhawaldeh & Jamil J. Jaber & Nawaf Hamadneh, 2021. "Classification with segmentation for credit scoring and bankruptcy prediction," Empirical Economics, Springer, vol. 61(3), pages 1281-1309, September.
    3. Mark Schreiner, 2001. "A Scoring Model of the Risk of Costly Arrears at a Microfinance Lender in Bolivia," Development and Comp Systems 0109005, University Library of Munich, Germany.
    4. Lee, Kyungeun & Lee, Hyesu & Lee, Hyoseop & Yoon, Yoonjin & Lee, Eunjung & Rhee, Wonjong, 2018. "Assuring explainability on demand response targeting via credit scoring," Energy, Elsevier, vol. 161(C), pages 670-679.
    5. Adnan Dželihodžić & Dženana Đonko & Jasmin Kevrić, 2018. "Improved Credit Scoring Model Based on Bagging Neural Network," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(06), pages 1725-1741, November.
    6. Renaud Bourlès & Anastasia Cozarenco & Dominique Henriet & Xavier Joutard, 2022. "Business Training with a Better-Informed Lender: Theory and Evidence from Microcredit in France," Annals of Economics and Statistics, GENES, issue 148, pages 65-108.
    7. Kiefer, Nicholas M. & Larson, C. Erik, 2006. "Specification and Informational Issues in Credit Scoring," Working Papers 06-11, Cornell University, Center for Analytic Economics.
    8. Dinh, Thi Huyen Thanh & Kleimeier, Stefanie, 2007. "A credit scoring model for Vietnam's retail banking market," International Review of Financial Analysis, Elsevier, vol. 16(5), pages 471-495.
    9. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    10. Degryse, H.A. & Cerqueiro, G.M. & Ongena, S., 2007. "Distance, Bank Organizational Structure and Credit," Other publications TiSEM 34c2f607-3395-4fd9-9c52-4, Tilburg University, School of Economics and Management.
    11. Ha-Thu Nguyen, 2016. "Reject inference in application scorecards: evidence from France," EconomiX Working Papers 2016-10, University of Paris Nanterre, EconomiX.
    12. Carlos Serrano-Cinca & Begoña Gutiérrez-Nieto & Nydia M. Reyes, 2013. "A Social Approach to Microfinance Credit Scoring," Working Papers CEB 13-013, ULB -- Universite Libre de Bruxelles.
    13. Badreddine Benyacoub & Souad ElBernoussi & Abdelhak Zoglat & Mohamed Ouzineb, 2022. "Credit Scoring Model Based on HMM/Baum-Welch Method," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1135-1154, March.
    14. Astebro, Thomas & Bernhardt, Irwin, 2003. "Start-up financing, owner characteristics, and survival," Journal of Economics and Business, Elsevier, vol. 55(4), pages 303-319.
    15. Y Kim & S Y Sohn, 2007. "Technology scoring model considering rejected applicants and effect of reject inference," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1341-1347, October.
    16. Li Gan & Roberto Mosquera, 2008. "An Empirical Study of the Credit Market with Unobserved Consumer Typers," NBER Working Papers 13873, National Bureau of Economic Research, Inc.
    17. Ha Thu Nguyen, 2016. "Reject inference in application scorecards: evidence from France," Working Papers hal-04141601, HAL.
    18. Fernandes, Guilherme Barreto & Artes, Rinaldo, 2016. "Spatial dependence in credit risk and its improvement in credit scoring," European Journal of Operational Research, Elsevier, vol. 249(2), pages 517-524.
    19. Guilherme Barreto & Fernandes Rinaldo Artes, 2013. "Spatial correlation in credit risk and its improvement in credit scoring," Business and Economics Working Papers 180, Unidade de Negocios e Economia, Insper.
    20. Berger, Allen N & Frame, W Scott & Miller, Nathan H, 2005. "Credit Scoring and the Availability, Price, and Risk of Small Business Credit," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(2), pages 191-222, April.

    More about this item

    Keywords

    Scoring; credit risk; risk management; financial institutions; microfinance;
    All these keywords.

    JEL classification:

    • O54 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Latin America; Caribbean
    • O57 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Comparative Studies of Countries

    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:wpa:wuwpdc:0109009. 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: EconWPA The email address of this maintainer does not seem to be valid anymore. Please ask EconWPA to update the entry or send us the correct address (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    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.