IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v66y2019ics1057521919300869.html
   My bibliography  Save this article

Analysis of financial distress cross countries: Using macroeconomic, industrial indicators and accounting data

Author

Listed:
  • Khoja, Layla
  • Chipulu, Maxwell
  • Jayasekera, Ranadeva

Abstract

This paper applies three-way multidimensional scaling and cluster analysis to examine the nature of insolvency in the Gulf Corporation Council, the United Kingdom and the United States of America between from 2004 to 2012. The findings of this paper reveal that analysing the financial statements data with indicators of industrial and macroeconomic, provide a better understanding of the performance of the solvent and insolvent firms cross-counties. The results proved that the financial health of firms should be examined in situ within the local macro environment. There is also a clear implication for managers of firms as paying most of ones attention to one aspect of financial performance appears to increase the risk of insolvency.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:finana:v:66:y:2019:i:c:s1057521919300869
    DOI: 10.1016/j.irfa.2019.101379
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521919300869
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.irfa.2019.101379?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
    ---><---

    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. Hernandez Tinoco, Mario & Holmes, Phil & Wilson, Nick, 2018. "Polytomous response financial distress models: The role of accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 276-289.
    2. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    3. Peel, MJ & Peel, DA & Pope, PF, 1986. "Predicting corporate failure-- Some results for the UK corporate sector," Omega, Elsevier, vol. 14(1), pages 5-12.
    4. Pamela K. Coats & L. Franklin Fant, 1993. "Recognizing Financial Distress Patterns Using a Neural Network Tool," Financial Management, Financial Management Association, vol. 22(3), Fall.
    5. 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.
    6. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    7. Nada Mselmi & Amine Lahiani & Taher Hamza, 2017. "Financial distress prediction: The case of French small and medium-sized firms," Post-Print hal-03529325, HAL.
    8. Goudie, A W & Meeks, G, 1991. "The Exchange Rate and Company Failure in a Macro-Micro Model of the UK Company Sector," Economic Journal, Royal Economic Society, vol. 101(406), pages 444-457, May.
    9. 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.
    10. Molinero, C Mar & Ezzamel, M, 1991. "Multidimensional scaling applied to corporate failure," Omega, Elsevier, vol. 19(4), pages 259-274.
    11. Varetto, Franco, 1998. "Genetic algorithms applications in the analysis of insolvency risk," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1421-1439, October.
    12. Wadhwani, Sushil B, 1986. "Inflation, Bankruptcy, Default Premia and the Stock Market," Economic Journal, Royal Economic Society, vol. 96(381), pages 120-138, March.
    13. Jia Liu, 2004. "Macroeconomic determinants of corporate failures: evidence from the UK," Applied Economics, Taylor & Francis Journals, vol. 36(9), pages 939-945.
    14. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    15. Mselmi, Nada & Lahiani, Amine & Hamza, Taher, 2017. "Financial distress prediction: The case of French small and medium-sized firms," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 67-80.
    16. Platt, Harlan D. & Platt, Marjorie B., 1991. "A note on the use of industry-relative ratios in bankruptcy prediction," Journal of Banking & Finance, Elsevier, vol. 15(6), pages 1183-1194, December.
    17. Evi Neophytou & Cecilio Mar Molinero, 2004. "Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 677-710, June.
    18. Young, Garry, 1995. "Company Liquidations, Interest Rates and Debt," The Manchester School of Economic & Social Studies, University of Manchester, vol. 63(0), pages 57-69, Suppl..
    19. Jayasekera, Ranadeva, 2018. "Prediction of company failure: Past, present and promising directions for the future," International Review of Financial Analysis, Elsevier, vol. 55(C), pages 196-208.
    20. Scott, James, 1981. "The probability of bankruptcy: A comparison of empirical predictions and theoretical models," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 317-344, September.
    21. Hernandez Tinoco, Mario & Wilson, Nick, 2013. "Financial distress and bankruptcy prediction among listed companies using accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 394-419.
    22. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
    23. Bhattacharjee, A. & Higson, C. & Holly, S. & Kattuman, P., 2004. "Business Failure in UK and US Quoted Firms: Impact of Macroeconomic Instability and the Role of Legal Institutions," Cambridge Working Papers in Economics 0420, Faculty of Economics, University of Cambridge.
    24. Nada Mselmi & Amine Lahiani & Taher Hamza, 2017. "Financial distress prediction: The case of French small and medium-sized firms," Post-Print hal-03380580, HAL.
    25. Abdul Aziz & David C. Emanuel & Gerald H. Lawson, 1988. "Bankruptcy Prediction ‐ An Investigation Of Cash Flow Based Models[1]," Journal of Management Studies, Wiley Blackwell, vol. 25(5), pages 419-437, September.
    26. 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.
    27. Jasim Al-Ajmi & J. H. Kim, 2012. "Are Gulf stock markets efficient? Evidence from new multiple variance ratio tests," Applied Economics, Taylor & Francis Journals, vol. 44(14), pages 1737-1747, May.
    28. Arouri, Mohamed El Hedi & Lahiani, Amine & Nguyen, Duc Khuong, 2011. "Return and volatility transmission between world oil prices and stock markets of the GCC countries," Economic Modelling, Elsevier, vol. 28(4), pages 1815-1825, July.
    29. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    30. Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
    31. Richard E. Caves, 1998. "Industrial Organization and New Findings on the Turnover and Mobility of Firms," Journal of Economic Literature, American Economic Association, vol. 36(4), pages 1947-1982, December.
    32. J. Kruskal, 1964. "Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis," Psychometrika, Springer;The Psychometric Society, vol. 29(1), pages 1-27, March.
    33. Gupta, Mc & Huefner, Rj, 1972. "Cluster Analysis Study Of Financial Ratios And Industry Characteristics," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 77-95.
    34. Frank Busing & Patrick Groenen & Willem Heiser, 2005. "Avoiding degeneracy in multidimensional unfolding by penalizing on the coefficient of variation," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 71-98, March.
    35. Evi Neophytou & Cecilio Mar Molinero, 2004. "Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5-6), pages 677-710.
    36. Common, Mick & Young, Mike, 1997. "Introduction," Ecological Economics, Elsevier, vol. 23(2), pages 79-80, November.
    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. Carmona, Pedro & Dwekat, Aladdin & Mardawi, Zeena, 2022. "No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure," Research in International Business and Finance, Elsevier, vol. 61(C).
    2. Chih‐Chun Chen & Chun‐Da Chen & Donald Lien, 2020. "Financial distress prediction model: The effects of corporate governance indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1238-1252, December.
    3. Nikolaos Daskalakis & Nikolaos Aggelakis & John Filos, 2022. "Applying, Updating and Comparing Bankruptcy Forecasting Models. The Case of Greece," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 21(3), pages 335-354, September.
    4. Katarina Valaskova & Tomas Kliestik & Dominika Gajdosikova, 2021. "Distinctive determinants of financial indebtedness: evidence from Slovak and Czech enterprises," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 16(3), pages 639-659, September.
    5. 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).
    6. 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.
    7. Baker, H. Kent & Kumar, Satish & Goyal, Kirti & Sharma, Anuj, 2021. "International review of financial analysis: A retrospective evaluation between 1992 and 2020," International Review of Financial Analysis, Elsevier, vol. 78(C).

    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. 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.
    2. 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.
    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. 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.
    5. 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.
    6. García-Gallego, Ana & Mures-Quintana, María-Jesús, 2013. "La muestra de empresas en los modelos de predicción del fracaso: influencia en los resultados de clasificación || The Sample of Firms in Business Failure Prediction Models: Influence on Classification," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 15(1), pages 133-150, June.
    7. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
    8. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
    9. 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.
    10. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
    11. Jackson, Richard H.G. & Wood, Anthony, 2013. "The performance of insolvency prediction and credit risk models in the UK: A comparative study," The British Accounting Review, Elsevier, vol. 45(3), pages 183-202.
    12. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    13. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    14. Casado Yusta, Silvia & Nœ–ez Letamendía, Laura & Pacheco Bonrostro, Joaqu’n Antonio, 2018. "Predicting Corporate Failure: The GRASP-LOGIT Model || Predicci—n de la quiebra empresarial: el modelo GRASP-LOGIT," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 294-314, Diciembre.
    15. Amin Jan & Maran Marimuthu & Muhammad Kashif Shad & Haseeb ur-Rehman & Muhammad Zahid & Ahmad Ali Jan, 2019. "Bankruptcy profile of the Islamic and conventional banks in Malaysia: a post-crisis period analysis," Economic Change and Restructuring, Springer, vol. 52(1), pages 67-87, February.
    16. Fayçal Mraihi, 2016. "Distressed Company Prediction Using Logistic Regression: Tunisian’s Case," Quarterly Journal of Business Studies, Research Academy of Social Sciences, vol. 2(1), pages 34-54.
    17. Vladislav V. Afanasev & Yulia A. Tarasova, 2022. "Default Prediction for Housing and Utilities Management Firms Using Non-Financial Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 91-110, December.
    18. 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.
    19. Youssef Zizi & Amine Jamali-Alaoui & Badreddine El Goumi & Mohamed Oudgou & Abdeslam El Moudden, 2021. "An Optimal Model of Financial Distress Prediction: A Comparative Study between Neural Networks and Logistic Regression," Risks, MDPI, vol. 9(11), pages 1-24, November.
    20. Chih‐Chun Chen & Chun‐Da Chen & Donald Lien, 2020. "Financial distress prediction model: The effects of corporate governance indicators," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1238-1252, December.

    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:finana:v:66:y:2019:i:c:s1057521919300869. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    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.