IDEAS home Printed from https://ideas.repec.org/a/sae/ausman/v6y1981i1p23-50.html
   My bibliography  Save this article

The Prediction of Corporate Failure: Testing the Australian Experience

Author

Listed:
  • A. D. Castagna
  • Z. P. Matolcsy

    (Kuring-gai College of Advanced Education. The helpful comments of L.H. Greenwood, referees of this journal, and the support of The Sydney Stock Exchange are gratefully acknowledged.)

Abstract

The purpose of this paper is to address some of the methodological issues which have evolved from the literature on corporate failures, and to report the results of an empirical investigation on the usefulness of financial models for the prediction of corporate failures. The experimental design is based on the 21 listed public companies that failed in Australia during the period 1963 to 1977, inclusive, and which met with minimum data requirements. It examines the performance of linear versus quadratic classification rules; temporal versus atemporal models; equal versus unequal priors of failure, variable dimension reduction, and a validation test proposed by Lachenbruch (1967). The results of the study suggest that it is difficult to identify a unique model to predict corporate failures, without specifying the utility preference of the user. Utility preference in this context refers to the minimization of either Type I, Type II, or the overall error rate of a failure model.

Suggested Citation

  • A. D. Castagna & Z. P. Matolcsy, 1981. "The Prediction of Corporate Failure: Testing the Australian Experience," Australian Journal of Management, Australian School of Business, vol. 6(1), pages 23-50, June.
    • Handle: RePEc:sae:ausman:v:6:y:1981:i:1:p:23-50
    DOI: 10.1177/031289628100600102
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/031289628100600102
    Download Restriction: no
    File URL: https://libkey.io/10.1177/031289628100600102?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. Edmister, Robert O., 1972. "An Empirical Test of Financial Ratio Analysis for Small Business Failure Prediction," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(2), pages 1477-1493, March.
    2. 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.
    3. 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.
    4. Altman, Edward I. & Margaine, Michel & Schlosser, Michel & Vernimmen, Pierre, 1974. "Financial and Statistical Analysis for Commercial Loan Evaluation: A French Experience," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 9(2), pages 195-211, 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. Rose Kenney & Gianni La Cava & David Rodgers, 2016. "Why Do Companies Fail?," RBA Research Discussion Papers rdp2016-09, Reserve Bank of Australia.
    2. 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.
    3. Lillian Cheung & Amnon Levy, 1998. "An integrative analysis of business bankruptcy in Australia," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 22(2), pages 149-167, June.
    4. Divesh Sharma & Errol Iselin, 2003. "The decision usefulness of reported cash flow and accrual information in a behavioural field experiment," Accounting and Business Research, Taylor & Francis Journals, vol. 33(2), pages 123-135.
    5. Z.P. Matolcsy & G.P. Pazmandy, 1995. "Predicting Half-Yearly Accounting Income Numbers With Statistical Models," Australian Accounting Review, CPA Australia, vol. 5(10), pages 56-63, November.
    6. Izan, H. Y., 1984. "Corporate distress in Australia," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 303-320, June.
    7. Malcolm Smith & Yun Ren & Yinan Dong, 2011. "The predictive ability of “conservatism” and “governance” variables in corporate financial disclosures," Asian Review of Accounting, Emerald Group Publishing Limited, vol. 19(2), pages 171-185, July.
    8. Marianna SUCCURRO & Lidia MANNARINO, 2014. "The Impact Of Financial Structure On Firms’ Probability Of Bankruptcy: A Comparison Across Western Europe Convergence Regions," Regional and Sectoral Economic Studies, Euro-American Association of Economic Development, vol. 14(1), pages 81-94.
    9. Juliana Yim & Heather Mitchell, 2007. "Predicting Financial Distress In The Australian Financial Service Industry," Australian Economic Papers, Wiley Blackwell, vol. 46(4), pages 375-388, December.

    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. Sebastian Klaudiusz Tomczak & Edward Radosiński, 2017. "The effectiveness of discriminant models based on the example of the manufacturing sector," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(3), pages 81-97.
    2. Antonio David Somoza Lopez & Josep Vallverdu Calafell, 2003. "Una comparacion de la seleccion de los ratios contables en los modelos contable-financieros de prediccion de la insolvencia empresarial," Working Papers in Economics 94, Universitat de Barcelona. Espai de Recerca en Economia.
    3. 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.
    4. du Jardin, Philippe & Séverin, Eric, 2011. "Predicting corporate bankruptcy using a self-organizing map: An empirical study to improve the forecasting horizon of a financial failure model," MPRA Paper 44262, University Library of Munich, Germany.
    5. Jeyhun A. Abbasov, 2017. "Financial ratios and the prediction of bankruptcy," Working Papers 1705, Central Bank of Azerbaijan Republic.
    6. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    7. Kolari, James & Glennon, Dennis & Shin, Hwan & Caputo, Michele, 2002. "Predicting large US commercial bank failures," Journal of Economics and Business, Elsevier, vol. 54(4), pages 361-387.
    8. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    9. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
    10. Skogsvik, Kenth, 2005. "On the Choice-Based Sample Bias in Probabilistic Business Failure Prediction," SSE/EFI Working Paper Series in Business Administration 2005:13, Stockholm School of Economics, revised 09 Jan 2006.
    11. Ali DERAN & Omer ISKENDEROGLU & Incilay ERDURU, 2014. "Regional Differences and Financial Ratios: A Comparative Approach on Companies of ISE City Indexes," International Journal of Economics and Financial Issues, Econjournals, vol. 4(4), pages 946-955.
    12. Situm Mario, 2014. "Inability of Gearing-Ratio as Predictor for Early Warning Systems," Business Systems Research, Sciendo, vol. 5(2), pages 23-45, September.
    13. Philosophov, Leonid V. & Philosophov, Vladimir L., 2002. "Corporate bankruptcy prognosis: An attempt at a combined prediction of the bankruptcy event and time interval of its occurrence," International Review of Financial Analysis, Elsevier, vol. 11(3), pages 375-406.
    14. Rassoul Yazdipour & Richard Constand, 2010. "Predicting Firm Failure: A Behavioral Finance Perspective," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 14(3), pages 90-104, Fall.
    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. Zhichao Luo & Pingyu Hsu & Ni Xu, 2020. "SME Default Prediction Framework with the Effective Use of External Public Credit Data," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
    17. Layla Khoja & Maxwell Chipulu & Ranadeva Jayasekera, 2016. "Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling," Review of Quantitative Finance and Accounting, Springer, vol. 46(3), pages 483-518, April.
    18. Ciampi, Francesco, 2015. "Corporate governance characteristics and default prediction modeling for small enterprises. An empirical analysis of Italian firms," Journal of Business Research, Elsevier, vol. 68(5), pages 1012-1025.
    19. Petr Jakubík & Petr Teplý, 2011. "The JT Index as an Indicator of Financial Stability of Corporate Sector," Prague Economic Papers, Prague University of Economics and Business, vol. 2011(2), pages 157-176.
    20. Qunfeng LIAO & Seyed MEHDIAN, 2016. "Measuring Financial Distress And Predicting Corporate Bankruptcy: An Index Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 17, pages 33-51, June.

    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:sae:ausman:v:6:y:1981:i:1:p:23-50. 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: SAGE Publications (email available below). General contact details of provider: http://www.agsm.edu.au .

    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.