IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v183y2007i1p472-478.html
   My bibliography  Save this article

Random effects logistic regression model for default prediction of technology credit guarantee fund

Author

Listed:
  • Sohn, So Young
  • Kim, Hong Sik

Abstract

No abstract is available for this item.

Suggested Citation

  • Sohn, So Young & Kim, Hong Sik, 2007. "Random effects logistic regression model for default prediction of technology credit guarantee fund," European Journal of Operational Research, Elsevier, vol. 183(1), pages 472-478, November.
  • Handle: RePEc:eee:ejores:v:183:y:2007:i:1:p:472-478
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(06)01039-3
    Download Restriction: Full text for ScienceDirect subscribers only

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

    References listed on IDEAS

    as
    1. Sohn, S. Y., 1996. "Random effects meta analysis of military recruiting," Omega, Elsevier, vol. 24(2), pages 141-151, April.
    2. Gentry, Ja & Newbold, P & Whitford, Dt, 1985. "Classifying Bankrupt Firms With Funds Flow Components," Journal of Accounting Research, Wiley Blackwell, vol. 23(1), pages 146-160.
    3. Tam, KY, 1991. "Neural network models and the prediction of bank bankruptcy," Omega, Elsevier, vol. 19(5), pages 429-445.
    4. Molinero, C Mar & Ezzamel, M, 1991. "Multidimensional scaling applied to corporate failure," Omega, Elsevier, vol. 19(4), pages 259-274.
    5. Pompe, Paul P.M. & Bilderbeek, Jan, 2005. "The prediction of bankruptcy of small- and medium-sized industrial firms," Journal of Business Venturing, Elsevier, vol. 20(6), pages 847-868, November.
    6. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    7. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    8. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    9. Johnsen, Thomajean & Melicher, Ronald W., 1994. "Predicting corporate bankruptcy and financial distress: Information value added by multinomial logit models," Journal of Economics and Business, Elsevier, vol. 46(4), pages 269-286, October.
    10. Zopounidis, Constantin & Doumpos, Michael, 1999. "A Multicriteria Decision Aid Methodology for Sorting Decision Problems: The Case of Financial Distress," Computational Economics, Springer;Society for Computational Economics, vol. 14(3), pages 197-218, 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. Ju, Yong Han & Sohn, So Young, 2014. "Updating a credit-scoring model based on new attributes without realization of actual data," European Journal of Operational Research, Elsevier, vol. 234(1), pages 119-126.
    2. Yonghan Ju & So Young Sohn, 2015. "Stress test for a technology credit guarantee fund based on survival analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(3), pages 463-475, March.
    3. Mihaela NICOLAU & Nicoleta BARBUTA-MISU, 2011. "Aggregated Index For Modelling The Influence Of Fiscal, Financial And Social Policies On Enterprise Financial Performance," EuroEconomica, Danubius University of Galati, issue 5(30), pages 13-20, December.
    4. Bravo, Cristián & Maldonado, Sebastián & Weber, Richard, 2013. "Granting and managing loans for micro-entrepreneurs: New developments and practical experiences," European Journal of Operational Research, Elsevier, vol. 227(2), pages 358-366.
    5. S Y Sohn & Y Kim & B T Kim, 2009. "Cost of ownership model for spare engines purchase for the Korean navy acquisition program," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(12), pages 1674-1682, December.
    6. Nicoleta BARBUTA-MISU, 2011. "A Specific Model for Assessing the Financial Performance:Case study on Building Sector Enterprises of Galati County - Romania," Risk in Contemporary Economy, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, pages 318-325.
    7. Nicoleta Barbuta-Misu, 2012. "Aggregated Index for Modelling the Influence of Financial Variables on Enterprise Performance," EuroEconomica, Danubius University of Galati, issue 2(31), pages 155-165, May.
    8. Yonghan Ju & So Young Sohn, 2017. "Technology Credit Scoring Based on a Quantification Method," Sustainability, MDPI, Open Access Journal, vol. 9(6), pages 1-16, June.
    9. Kim, Hong Sik & Sohn, So Young, 2010. "Support vector machines for default prediction of SMEs based on technology credit," European Journal of Operational Research, Elsevier, vol. 201(3), pages 838-846, March.
    10. Bo Kyeong Lee & So Young Sohn, 2017. "A Credit Scoring Model for SMEs Based on Accounting Ethics," Sustainability, MDPI, Open Access Journal, vol. 9(9), pages 1-15, September.
    11. Chen, Cathy W.S. & Dong, Manh Cuong & Liu, Nathan & Sriboonchitta, Songsak, 2019. "Inferences of default risk and borrower characteristics on P2P lending," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    12. Shi, Xiaojun & Zhang, Shunming, 2010. "An incentive-compatible solution for trade credit term incorporating default risk," European Journal of Operational Research, Elsevier, vol. 206(1), pages 178-196, October.
    13. Ye Chen & Ilya O. Ryzhov, 2020. "Technical Note—Consistency Analysis of Sequential Learning Under Approximate Bayesian Inference," Operations Research, INFORMS, vol. 68(1), pages 295-307, January.
    14. So Sohn & Yoon Kim, 2013. "Behavioral credit scoring model for technology-based firms that considers uncertain financial ratios obtained from relationship banking," Small Business Economics, Springer, vol. 41(4), pages 931-943, December.

    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:eee:ejores:v:183:y:2007:i:1:p:472-478. 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: (Haili He). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.