IDEAS home Printed from
   My bibliography  Save this article

Predicting survival prospect of corporate restructuring in Korea


  • Minchoul Kim
  • Minho Kim
  • Ronald McNiel


The purpose of this article is to identify the success factors of corporate restructuring by studying the firms that have survived from the financial distress in South Korea. The logit analysis is used with the two qualitative variables of success and failure. Selected independent variables are firm risk, free asset, audit opinion, liquidity, firm size and period of existence. The results show that audit opinion, risk of the firm and firm size are the important variables in predicting the survival prospect of financially distressed firms. The percentage of correct prediction is 81.4% for the estimation sample.

Suggested Citation

  • Minchoul Kim & Minho Kim & Ronald McNiel, 2008. "Predicting survival prospect of corporate restructuring in Korea," Applied Economics Letters, Taylor & Francis Journals, vol. 15(15), pages 1187-1190.
  • Handle: RePEc:taf:apeclt:v:15:y:2008:i:15:p:1187-1190
    DOI: 10.1080/13504850601018080

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

    File URL:
    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

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

    References listed on IDEAS

    1. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    2. Catherine M. Daily & Dan R. Dalton, 1995. "CEO and director turnover in failing firms: An illusion of change?," Strategic Management Journal, Wiley Blackwell, vol. 16(5), pages 393-400.
    3. Karen Denning & Stephen Ferris & Robert Lawless, 2001. "Serial bankruptcy: plan infeasibility or just bad luck?," Applied Economics Letters, Taylor & Francis Journals, vol. 8(2), pages 105-109.
    4. Jia Liu, 2004. "Macroeconomic determinants of corporate failures: evidence from the UK," Applied Economics, Taylor & Francis Journals, vol. 36(9), pages 939-945.
    5. 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.
    6. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Alexandra Bertschi-Michel & Philipp Sieger & Thomas Wittig & Andreas Hack, 2023. "Sacrifice, Protect, and Hope for the Best: Family Ownership, Turnaround Moves, and Crisis Survival," Entrepreneurship Theory and Practice, , vol. 47(4), pages 1132-1168, July.
    2. Muñoz-Izquierdo, Nora & Segovia-Vargas, María Jesús & Camacho-Miñano, María-del-Mar & Pascual-Ezama, David, 2019. "Explaining the causes of business failure using audit report disclosures," Journal of Business Research, Elsevier, vol. 98(C), pages 403-414.
    3. Nora Muñoz-Izquierdo & María-del-Mar Camacho-Miñano & María-Jesús Segovia-Vargas & David Pascual-Ezama, 2019. "Is the External Audit Report Useful for Bankruptcy Prediction? Evidence Using Artificial Intelligence," IJFS, MDPI, vol. 7(2), pages 1-23, 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. Maria H. Kim & Graham Partington, 2015. "Dynamic forecasts of financial distress of Australian firms," Australian Journal of Management, Australian School of Business, vol. 40(1), pages 135-160, February.
    2. Enrique Batiz‐Zuk & Fabrizio López‐Gallo & Abdulkadir Mohamed & Fátima Sánchez‐Cajal, 2022. "Determinants of loan survival rates for small and medium‐sized enterprises: Evidence from an emerging economy," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(4), pages 4741-4755, October.
    3. Umair Bin YOUSAF & Khalil JEBRAN & Man WANG, 2022. "A Comparison of Static, Dynamic and Machine Learning Models in Predicting the Financial Distress of Chinese Firms," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 122-138, April.
    4. Sanjay Sehgal & Ritesh Kumar Mishra & Ajay Jaisawal, 2021. "A search for macroeconomic determinants of corporate financial distress," Indian Economic Review, Springer, vol. 56(2), pages 435-461, December.
    5. Petr Jakubík & Tatiana Škerlíková, 2014. "Macroeconomic Determinants of Firms' Default in the Czech Republic [Makroekonomické determinanty úpadku firem v České republice]," Český finanční a účetní časopis, Prague University of Economics and Business, vol. 2014(2), pages 69-80.
    6. Harada, Nobuyuki & Kageyama, Noriyuki, 2011. "Bankruptcy dynamics in Japan," Japan and the World Economy, Elsevier, vol. 23(2), pages 119-128, March.
    7. Khoja, Layla & Chipulu, Maxwell & Jayasekera, Ranadeva, 2019. "Analysis of financial distress cross countries: Using macroeconomic, industrial indicators and accounting data," International Review of Financial Analysis, Elsevier, vol. 66(C).
    8. Maria Heui-Yeong Kim & Shiguang Ma & Yanran Annie Zhou, 2016. "Survival prediction of distressed firms: evidence from the Chinese special treatment firms," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 21(3), pages 418-443, July.
    9. N. Dewaelheyns & C. van Hulle, 2007. "Aggregate Bankruptcy Rates and the Macroeconomic Environment. Forecasting Systematic Probabilities of Default," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(4), pages 541-566.
    10. Shilpa H. Shetty & Theresa Nithila Vincent, 2021. "The Role of Board Independence and Ownership Structure in Improving the Efficacy of Corporate Financial Distress Prediction Model: Evidence from India," JRFM, MDPI, vol. 14(7), pages 1-13, July.
    11. Elsayed, Mohamed & Elshandidy, Tamer, 2020. "Do narrative-related disclosures predict corporate failure? Evidence from UK non-financial publicly quoted firms," International Review of Financial Analysis, Elsevier, vol. 71(C).
    12. Lars Schweizer & Andreas Nienhaus, 2017. "Corporate distress and turnaround: integrating the literature and directing future research," Business Research, Springer;German Academic Association for Business Research, vol. 10(1), pages 3-47, June.
    13. Piñeiro Sánchez Carlos & Llano Monelos Pablo De & Rodríguez López Manuel, 2013. "A parsimonious model to forecast financial distress, based on audit evidence," Contaduría y Administración, Accounting and Management, vol. 58(4), pages 151-173, octubre-d.
    14. Antonio Davila & George Foster & Xiaobin He & Carlos Shimizu, 2015. "The rise and fall of startups: Creation and destruction of revenue and jobs by young companies," Australian Journal of Management, Australian School of Business, vol. 40(1), pages 6-35, February.
    15. Giordani, Paolo & Jacobson, Tor & Schedvin, Erik von & Villani, Mattias, 2014. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 49(4), pages 1071-1099, August.
    16. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    17. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    18. Lauren Stagnol, 2015. "Designing a corporate bond index on solvency criteria," EconomiX Working Papers 2015-39, University of Paris Nanterre, EconomiX.
    19. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.
    20. Wen Su, 2021. "Default Distances Based on the CEV-KMV Model," Papers 2107.10226,, revised May 2022.

    More about this item


    Access and download statistics


    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:taf:apeclt:v:15:y:2008:i:15:p:1187-1190. 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: Chris Longhurst (email available below). General contact details of provider: .

    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.