IDEAS home Printed from https://ideas.repec.org/a/ags/reapec/50146.html
   My bibliography  Save this article

Understanding Differences Between Financial Distress and Bankruptcy

Author

Listed:
  • Platt, Harlan D.
  • Platt, Marjorie B.

Abstract

For the most part, research purporting to address the issue of financial distress has actually studied samples of bankrupt companies. Financial distress and bankruptcy are different. In contrast, this paper starts with a sample of companies that are financially distressed but not yet bankrupt. The sample was obtained by screening the Compustat industry database with a three-tiered identification system. The screen bifurcated companies into financially and non-financially distressed groups. A multi-tiered screen reduces the incidence of mistakenly identifying a non-distressed company as financially distressed. The paper then compares factors indicating the likelihood of future bankruptcies to those indicating future financial distress. To do this, an early warning financial-distress model was developed and compared to a methodologically similar existent model of bankruptcy. The final financial distress model included only one variable present in the bankruptcy model and four new variables. The limited overlap of explanatory factors between the models questions the similarity of financial distress and bankruptcy. Statistical tests lend support to the notion that the bankruptcy process is not just a continuation of a downward spiraling cycle of financial distress. Our hypothesis is that financial distress is something that happens to companies as a consequence of operating decisions or external forces while bankruptcy is something that companies choose to do to protect their assets from creditors.

Suggested Citation

  • Platt, Harlan D. & Platt, Marjorie B., 2006. "Understanding Differences Between Financial Distress and Bankruptcy," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 2(2), pages 1-17.
  • Handle: RePEc:ags:reapec:50146
    DOI: 10.22004/ag.econ.50146
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/50146/files/1-Harlan%20D%20Platt.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.50146?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
    ---><---

    References listed on IDEAS

    as
    1. Yang, Z. R. & Platt, Marjorie B. & Platt, Harlan D., 1999. "Probabilistic Neural Networks in Bankruptcy Prediction," Journal of Business Research, Elsevier, vol. 44(2), pages 67-74, February.
    2. Richard Whitaker, 1999. "The early stages of financial distress," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 23(2), pages 123-132, June.
    3. Paul Asquith & Robert Gertner & David Scharfstein, 1994. "Anatomy of Financial Distress: An Examination of Junk-Bond Issuers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(3), pages 625-658.
    4. Altman, Edward I. & Marco, Giancarlo & Varetto, Franco, 1994. "Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)," Journal of Banking & Finance, Elsevier, vol. 18(3), pages 505-529, May.
    5. John, Kose & Lang, Larry H P & Netter, Jeffry, 1992. "The Voluntary Restructuring of Large Firms in Response to Performance Decline," Journal of Finance, American Finance Association, vol. 47(3), pages 891-917, July.
    6. 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.
    7. Schipper, K, 1977. "Financial Distress In Private Colleges," Journal of Accounting Research, Wiley Blackwell, vol. 15, pages 1-53.
    8. Mensah, Ym, 1984. "An Examination Of The Stationarity Of Multivariate Bankruptcy Prediction Models - A Methodological Study," Journal of Accounting Research, Wiley Blackwell, vol. 22(1), pages 380-395.
    9. 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.
    10. Gilson, Stuart C., 1989. "Management turnover and financial distress," Journal of Financial Economics, Elsevier, vol. 25(2), pages 241-262, December.
    11. Gilson, Stuart C. & John, Kose & Lang, Larry H. P., 1990. "Troubled debt restructurings*1: An empirical study of private reorganization of firms in default," Journal of Financial Economics, Elsevier, vol. 27(2), pages 315-353, October.
    12. Frydman, Halina & Altman, Edward I & Kao, Duen-Li, 1985. "Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress," Journal of Finance, American Finance Association, vol. 40(1), pages 269-291, March.
    13. Lo, Andrew W., 1986. "Logit versus discriminant analysis : A specification test and application to corporate bankruptcies," Journal of Econometrics, Elsevier, vol. 31(2), pages 151-178, March.
    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. Luca Ianni & Gianluca Marullo & Stefania Migliori & Francesco De Luca, 2021. "I modelli predittivi della crisi e dell?insolvenza aziendale. Una systematic review," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(2), pages 127-146.
    2. Čater, Tomaž & Čater, Barbara & Milić, Patricia & Žabkar, Vesna, 2023. "Drivers of corporate environmental and social responsibility practices: A comparison of two moderated mediation models," Journal of Business Research, Elsevier, vol. 159(C).
    3. Anita Nandi & Partha Pratim Sengupta & Abhijit Dutta, 2019. "Diagnosing the Financial Distress in Oil Drilling and Exploration Sector of India through Discriminant Analysis," Vision, , vol. 23(4), pages 364-373, December.
    4. Ugur, Mehmet & Solomon, Edna & Zeynalov, Ayaz, 2022. "Leverage, competition and financial distress hazard: Implications for capital structure in the presence of agency costs," Economic Modelling, Elsevier, vol. 108(C).
    5. Konstantaras, Konstantinos & Siriopoulos, Costas, 2011. "Estimating financial distress with a dynamic model: Evidence from family owned enterprises in a small open economy," Journal of Multinational Financial Management, Elsevier, vol. 21(4), pages 239-255, October.
    6. Nina Ponikvar & Katja Zajc Kejžar & Darja Peljhan, 2018. "The role of financial constraints for alternative firm exit modes," Small Business Economics, Springer, vol. 51(1), pages 85-103, June.
    7. Jože Damijan & Jozef Konings & Črt Kostevc & Katja Zajc Kejžar, 2022. "Explaining the Low Level of Investment in Slovenia," European Economy - Discussion Papers 169, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission.
    8. Jarmila Horváthová & Martina Mokrišová & Martin Bača, 2023. "Bankruptcy Prediction for Sustainability of Businesses: The Application of Graph Theoretical Modeling," Mathematics, MDPI, vol. 11(24), pages 1-20, December.
    9. Lu, Yang-Cheng & Shen, Chung-Hua & Wei, Yu-Chen, 2013. "Revisiting early warning signals of corporate credit default using linguistic analysis," Pacific-Basin Finance Journal, Elsevier, vol. 24(C), pages 1-21.
    10. Sumani Sumani, 2019. "The Structure of Good Corporate Governance and Financial Indicators as Predictor of Financial Distress in Mining Sector Company in Indonesia," Research in Business and Management, Macrothink Institute, vol. 6(1), pages 1-12, February.
    11. Mário S. Céu & Raquel M. Gaspar, 2023. "Financial Distress in European Vineyards and Olive Groves," Working Papers REM 2023/0266, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    12. Reni Yendrawati & Nafil Adiwafi, 2020. "Comparative analysis of Z-score, Springate, and Zmijewski models in predicting financial distress conditions," Journal of Contemporary Accounting, Master in Accounting Program, Faculty of Business & Economics, Universitas Islam Indonesia, Yogyakarta, Indonesia, vol. 2(2), pages 72-80, May.

    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. Harlan D. Platt & Marjorie B. Platt, 2008. "Financial Distress Comparison Across Three Global Regions," JRFM, MDPI, vol. 1(1), pages 1-34, December.
    2. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
    3. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
    4. 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.
    5. du Jardin, Philippe, 2012. "The influence of variable selection methods on the accuracy of bankruptcy prediction models," MPRA Paper 44383, University Library of Munich, Germany.
    6. Sami Ben Jabeur & Youssef Fahmi, 2014. "Les modèles de prévision de la défaillance des entreprises françaises : une approche comparative," Working Papers 2014-317, Department of Research, Ipag Business School.
    7. Becchetti, Leonardo & Sierra, Jaime, 2003. "Bankruptcy risk and productive efficiency in manufacturing firms," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2099-2120, November.
    8. Luca Ianni & Gianluca Marullo & Stefania Migliori & Francesco De Luca, 2021. "I modelli predittivi della crisi e dell?insolvenza aziendale. Una systematic review," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(2), pages 127-146.
    9. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    10. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
    11. ElBannan, Mona A., 2021. "On the prediction of financial distress in emerging markets: What matters more? Empirical evidence from Arab spring countries," Emerging Markets Review, Elsevier, vol. 47(C).
    12. Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
    13. Kalay, Avner & Singhal, Rajeev & Tashjian, Elizabeth, 2007. "Is Chapter 11 costly?," Journal of Financial Economics, Elsevier, vol. 84(3), pages 772-796, June.
    14. Carlos Serrano-Cinca, 1997. "Feedforward neural networks in the classification of financial information," The European Journal of Finance, Taylor & Francis Journals, vol. 3(3), pages 183-202.
    15. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    16. Cakir, Murat, 2005. "Firma Başarısızlığının Dinamiklerinin Belirlenmesinde Makina Öğrenmesi Teknikleri: Ampirik Uygulamalar ve Karşılaştırmalı Analiz [Machine Learning Techniques in Determining the Dynamics of Corporat," MPRA Paper 55975, University Library of Munich, Germany.
    17. Van Laere, Elisabeth & Baesens, Bart, 2010. "The development of a simple and intuitive rating system under Solvency II," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 500-510, June.
    18. Philippe Jardin & David Veganzones & Eric Séverin, 2019. "Forecasting Corporate Bankruptcy Using Accrual-Based Models," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 7-43, June.
    19. du Jardin, Philippe & Séverin, Eric, 2012. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," European Journal of Operational Research, Elsevier, vol. 221(2), pages 378-396.
    20. Iskandar, Azwar, 2015. "Model Prediksi Financial Distress Dengan Binary Logit (Studi Kasus Emiten Jakarta Islamic Index) [Application of Binary Logit Regression on Financial Distress Prediction of Jakarta Islamic Index]," MPRA Paper 82694, University Library of Munich, Germany.

    More about this item

    Keywords

    Financial Economics;

    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:ags:reapec:50146. 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: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/aelinnz.html .

    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.