Probability of Corporate Bankruptcy: Application to Portuguese Manufacturing Industry SMEs
DOI:
https://doi.org/10.33736/ijbs.4863.2022Keywords:
Bankruptcy, manufacturing industry, SMEs, logit, financial ratiosAbstract
This paper aims to develop a model for predicting corporate bankruptcy for SMEs in the Portuguese manufacturing industry where this question remains rather unaddressed. Using profitability, activity, liquidity, leverage, and solvency ratios, it was added the size and age variables, for a group of 208 firms, including 49 bankrupt firms and 159 active firms, during the years 2011 to 2015. The logit model allowed us to estimate a model with 82.3% of predictive capacity. The most important variables identified were profitability, solvency, and size. Estimations only with the data closest to the bankruptcy date improved predictive capacity. It is evidenced that financial and non-financial variables can predict bankruptcy probability. A possible future approach would be to analyze a larger sample. Also, a larger period could be considered, allowing to test either the effects of the 2007/8 crisis or the effects of the recent economic turmoil related to Covid-19. Important for both corporate managers and investors. Conclusions may be disclosed regarding the influence that economic turmoil certainly has on corporate defaults and bankruptcies allowing its extension to other countries. The contribution of this paper is to find the best specification for a bankruptcy prediction model applied to the Portuguese manufacturing industry SMEs. This paper also contributes to the existing literature by using non-financial variables and analyzing a sector still unexplored in Portugal, albeit its conclusions can be extended to other countries.
References
Abidin, J. Z., Abdullah, N. A. H., & Khaw, K. (2021). Predicting business failure for Malaysia SMEs in the hospitality industry. Advances in Economics, Business and Management Research, 161, 67-73. https://doi.org/10.2991/aebmr.k.210121.011
Agarwal, V., & Taffler, R. (2008). Comparing the performance of market-based and accounting-based bankruptcy prediction models. Journal of Banking and Finance, 32(8), 1541-1551. https://doi.org/10.1016/j.jbankfin.2007.07.014
Agrawal, K., & Maheshwari, Y. (2019). Efficacy of industry factors for corporate default prediction. IIMB Management Review, 31(1), 71-77. https://doi.org/10.1016/j.iimb.2018.08.007
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Bilal, M., Ajayi, S. O., & Akinade, O. O. (2020). A framework for big data analytics approach to failure prediction of construction firms. Applied Computing and Informatics, 16(1/2), 207-222. https://doi.org/10.1016/j.aci.2018.04.003
Almamy, J., Aston, J., & Ngwa, L. N. (2016). An evaluation of Altman's Z-score using cash flow ratio to predict corporate failure amid the recent financial crisis: Evidence from the UK. Journal of Corporate Finance, 36, 278-285. https://doi.org/10.1016/j.jcorpfin.2015.12.009
Almansour, B. Y. (2015). Empirical model for predicting financial failure. American Journal of Economics, Finance and Management, 1(3), 113-124.
Altman, E. I. (1968). Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. The Journal of Finance, 23(4), 589-609. https://doi.org/10.1111/j.1540-6261.1968.tb00843.x
Altman, E. I., & Hotchkiss, E. (2006). Corporate financial distress and bankruptcy (3rd ed.). John Wiley and Sons Inc. https://doi.org/10.1002/9781118267806
Altman, E. I., & Sabato, G. (2007). Modelling credit risk for SMEs: Evidence from the U.S. market. Abacus, 43(3), 332-357. https://doi.org/10.1111/j.1467-6281.2007.00234.x
Altman, E. I., Haldeman, R. G., & Narayanan, P. (1977). ZETA analysis: A new model to identify bankruptcy risk of corporations. Journal of Banking and Finance, 1, 29-54. https://doi.org/10.1016/0378-4266(77)90017-6
Altman, E. I., Iwanicz‐Drozdowska, M., Laitinen, E. K., & Suvas, A. (2017). Financial distress prediction in an international context: A review and empirical analysis of Altman's Z‐Score Model. Journal of International Financial Management and Accounting, 28(2), 131-171. https://doi.org/10.1111/jifm.12053
Antunes, A. R., Prego, P., & Gonçalves, H. (2016). Firm default probabilities revisited. Economic Bulletin and Financial Stability Report Articles, 21-45.
Appiah, K. O. (2011). Predicting corporate failure and global financial crisis: Theory and implications. Journal of Modern Accounting and Auditing, 7(1), 38-47.
Araghi, M. K., & Makvandi, S. (2013). Comparing logit, probit and multiple discriminant analysis models in predicting bankruptcy of companies. Asian Journal of Finance and Accounting, 5(1), 48-60. https://doi.org/10.5296/ajfa.v5i1.2977
Arasti, Z. (2011). An empirical study on the causes of business failure in Iranian context. African Journal of Business Management, 5(17), 7488-7498. https://doi.org/10.5897/AJBM11.402
Aziz, M., & Dar, H. (2006). Predicting corporate bankruptcy: Where we stand? Corporate Governance, 6, 18-33.
https://doi.org/10.1108/14720700610649436
Balcaen, S., & Ooghe, H. (2006). 35 years of studies on business failure: An overview of the classic statistical methodologies and their related problems. The British Accounting Review, 38(1), 63-93. https://doi.org/10.1016/j.bar.2005.09.001
Bărbuță-Mișu, N., & Madaleno, M. (2020). Assessment of bankruptcy risk of large companies: European countries evolution analysis. Journal of Risk and Financial Management, 13(3), 58. https://doi.org/10.3390/jrfm13030058
Bartual, C., Garcia, F., Guijarro, F., & Moya, I. (2013). Default prediction of Spanish companies: A logistic analysis. Intellectual Economics, 7(3), 333-343. https://doi.org/10.13165/IE-13-7-3-05
Beaver, W. H. (1966). Financial ratios as predictors of failure. Journal of Accounting Research, 4, 71-111. https://doi.org/10.2307/2490171
Beaver, W. H. (2005). Have financial statements become less informative? Evidence from the ability of financial ratios to predict bankruptcy. Review of Accounting Studies, 10, 93-122. https://doi.org/10.1007/s11142-004-6341-9
Blum, M. (1974). The failing company doctrine. Boston College Industrial and Commercial Law Review, 16(1), 75-113.
Bonfim, D., (2009). Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics. Journal of Banking and Finance, 33(2), 281-299. https://doi.org/10.1016/j.jbankfin.2008.08.006
Boso, N., Adeleye, I., Donbesuur, F., & Gyensare, M. (2019). Do entrepreneurs always benefit from business failure experience? Journal of Business Research, 98, 370-379. https://doi.org/10.1016/j.jbusres.2018.01.063
Buis, M. L. (2012). Stata tip 107: The baseline is now reported. The Stata Journal, 12(1), 165-166. https://doi.org/10.1177/1536867X1201200112
Charitou, A., Neophytou, E., & Charalambous, C. (2004). Predicting corporate failure: Empirical evidence for the UK. European Accounting Review, 13(3), 465-497. https://doi.org/10.1080/0963818042000216811
Coats, P. K., & Fant, L. F. (1993). Recognizing financial distress patterns using a neural network tool. Financial Management, 22(3), 142-155. https://doi.org/10.2307/3665934
Costa, H. A. (2014). Modelo de previsão de falência: O caso da construção civil em Portugal [Bankruptcy prediction model: The case of civil construction in Portugal] [Unpublished master's thesis]. Universidade do Algarve.
Deakin, E. B. (1972). A discriminant analysis of predictors of business failure. Journal of Accounting Research, 10(1), 167-179. https://doi.org/10.2307/2490225
Diez, F. J., Duval, R., Fan, J., Garrido, J., Kalemli-Ozcan, S., Maggi, C., ... & Pierri, N. (2021). Insolvency Prospects Among Small-and-Medium-Sized Enterprises in Advanced Economies: Assessment and Policy Options (International Monetary Fund Staff Discussion Notes No. SDN/2021/002). https://www.imf.org/-/media/Files/Publications/SDN/2021/English/SDNEA2021002.ashx https://doi.org/10.5089/9781513574561.006
Dong, M. C., Tian, S., & Chen, C. W. S. (2018). Predicting failure risk using financial ratios: Quantile hazard model approach. The North American Journal of Economics and Finance, 44, 204-220. https://doi.org/10.1016/j.najef.2018.01.005
du Jardin, P., Veganzones, D., & Séverin, E. (2019). Forecasting corporate bankruptcy using accrual-based models. Computational Economics, 54(1), 7-43. https://doi.org/10.1007/s10614-017-9681-9
European Commission (2018). 2017 SBA fact sheet for Portugal. https://ec.europa.eu/docsroom/documents/26562/attachments/23/translations/en/renditions/pdf
Fama, E. F., & French, K. R. (1992). The cross-section of expected stock returns. The Journal of Finance, 47(2), 427-465. https://doi.org/10.1111/j.1540-6261.1992.tb04398.x
García, V., Marqués, A. I., Sánchez, J. S., & Ochoa-Domínguez, H. J. (2019). Dissimilarity-based linear models for corporate bankruptcy prediction. Computational Economics, 53(3), 1019-1031. https://doi.org/10.1007/s10614-017-9783-4
Hazak, A., & Männasoo, K. (2007). Indicators of corporate default - An EU based empirical study (Bank of Estonia Working Paper 10/2007). https://haldus.eestipank.ee/sites/default/files/publication/en/WorkingPapers/2007/_wp_1007.pdf
Instituto Nacional de Estadística (2017). Empresas em Portugal - 2015 [Enterprises in Portugal - 2015] (Data file). https://www.ine.pt/xportal/xmain?xpgid=ine_main&xpid=INE
Jacobson, T., Lindé, J., & Roszbach, K. (2013). Firm default and aggregate fluctuations. Journal of the European Economic Association, 11(4), 945-972. https://doi.org/10.1111/jeea.12020
Jahur, M. S., & Quadir, S. M. N. (2012). Financial distress in small and medium enterprises (SMEs) of Bangladesh: Determinants and remedial measures. Economia: Seria Management, 15(1), 46-61.
Jardim, C. P., & Pereira, E. T. (2013). Corporate bankruptcy of Portuguese firms. Zagreb International Review of Economics and Business, 16(2), 39-56.
Jayasekera, R. (2018). Prediction of company failure: Past, present and promising directions for the future. International Review of Financial Analysis, 55, 196-208. https://doi.org/10.1016/j.irfa.2017.08.009
Jones, S., Johnstone, D., & Wilson, R. (2017). Predicting corporate bankruptcy: An evaluation of alternative statistical frameworks. Journal of Business Finance and Accounting, 44(1-2), 3-34. https://doi.org/10.1111/jbfa.12218
Karels, G. V., & Prakash, A. J. (1987). Multivariate normality and forecasting of business bankruptcy. Journal of Business Finance and Accounting, 14(4), 573-593. https://doi.org/10.1111/j.1468-5957.1987.tb00113.x
Kenney, R., La Cava, G., & Rodgers, D. (2016). Why do companies fail? (Reserve Bank of Australia Working Papers No. 2016-09). https://www.rba.gov.au/publications/rdp/2016/pdf/rdp2016-09.pdf
Kim, H., & Gu, Z. (2006). A logistic regression analysis for predicting bankruptcy in the hospitality industry. The Journal of Hospitality Financial Management, 14(1), 17-34. https://doi.org/10.1080/10913211.2006.10653812
Kovacova, M., Kliestik, T., Kubala, P., Valaskova, K., Radišić, M., & Borocki, J. (2018). Bankruptcy models: Verifying their validity as a predictor of corporate failure. Polish Journal of Management Studies, 18(1), 167-179. https://doi.org/10.17512/pjms.2018.18.1.13
Laitinen, E. K. (1994). Traditional versus operating cash flow in failure prediction. Journal of Business Finance and Accounting, 21(2), 195-217. https://doi.org/10.1111/j.1468-5957.1994.tb00313.x
Lakshan, A. I., & Wijekoon, W. M. H. N. (2013). The use of financial ratios in predicting corporate failure in Sri Lanka. GSTF Journal on Business Review, 2(4), 37-43.
Le, H. H., & Viviani, J. L. (2018). Predicting bank failure: An improvement by implementing a machine-learning approach to classical financial ratios. Research in International Business and Finance, 44, 16-25. https://doi.org/10.1016/j.ribaf.2017.07.104
Levratto, N. (2013). From failure to corporate bankruptcy: A review. Journal of Innovation and Entrepreneurship, 2(20), 1-15. https://doi.org/10.1186/2192-5372-2-20
Lins, K.V., Servaes, H., & Tamayo, A. (2017). Social capital, trust, and firm performance: The value of corporate social responsibility during the financial crisis. The Journal of Finance, 74(4), 1785- 1824. https://doi.org/10.1111/jofi.12505
Lopes, J. P. (2014). Previsão de falência de pequenas e médias empresas [Unpublished master's thesis]. Universidade do Porto (Portugal).
Lukason, O. (2013). Firm bankruptcies and violations of law: An analysis of different offences. In T. Vissak, & M. Vadi (Eds.), (Dis)honesty in management (Advanced series in management, Vol. 10, pp. 127-146). Emerald Group Publishing Limited. https://doi.org/10.1108/S1877-6361(2013)0000010010
Lukason, O., & Laitinen, E. K. (2018). Firm failure processes and components of failure risk: An analysis of European bankrupt firms. Journal of Business Research, 98, 380-390. https://doi.org/10.1016/j.jbusres.2018.06.025
McKee, T. E. (2003). Rough sets bankruptcy prediction models versus auditor signalling rates. Journal of Forecasting, 22(8), 569-586. https://doi.org/10.1002/for.875
Nanayakkara, K. G. M., & Azeez, A. A. (2015). Predicting corporate financial distress in Sri Lanka: An extension to z-score model. International Journal of Business and Social Research, 5(3), 41-56. https://doi.org/10.4038/kjm.v3i1.7474
Ohlson, J. A. (1980). Financial ratios and the probabilistic prediction of bankruptcy. Journal of Accounting Research, 18(1), 109-131. https://doi.org/10.2307/2490395
Oliveira, M. P. G. (2014). A insolvência empresarial na indústria transformadora portuguesa: as determinantes financeiras e macroeconómicas [Corporate insolvency in the Portuguese manufacturing industry: Financial and macroeconomic determinants] [Unpublished master's thesis]. Universidade do Porto.
Ooghe, H. Spaenjers, C., & Vandermoere, P. (2009). Business failure prediction: Simple-intuitive models versus statistical models. The IUP Journal of Business Strategy, 6(3/4), 7-44.
Ooghe, H., & De Prijcker, S. (2008). Failure processes and causes of company bankruptcy: A typology. Management Decision, 46(2), 223-242. https://doi.org/10.1108/00251740810854131
Pacheco L., Rosa, R., & Tavares, F. (2019). Risco de falência de PME: Evidência no setor da construção em Portugal [Bankruptcy risk of SMEs: Evidence from the construction sector in Portugal]. Revista Innovar, 29(71), 143-157. https://doi.org/10.15446/innovar.v29n71.76401
Pacheco, L. (2015). SMEs probability of default: The case of the hospitality sector. Tourism and Management Studies, 11(1), 153-159.
Paolone, F., & Kesgin, S. S. (2016). Insolvency prediction in manufacturing firms. A comparative study between Italy and Turkey. International Journal of Technical Research and Applications, 4(1), 200-211.
Pervan, I., Pervan, M., & Vukoja, B. (2011). Prediction of company bankruptcy using statistical techniques - Case of Croatia. Croatian Operational Research Review, 2, 158-167.
Platt, H. D., & Platt, M. B. (1990). Development of a class of stable predictive variables: The case of bankruptcy prediction. Journal of Business Finance and Accounting, 17(1), 31-51. https://doi.org/10.1111/j.1468-5957.1990.tb00548.x
Platt, H. D., & Platt, M. B. (2002). Predicting corporate financial distress: Reflection on choice-based sample bias. Journal of Economic and Finance, 26(2), 184-199. https://doi.org/10.1007/BF02755985
Pordata (2017). Pordata - Empresas no sector da indústria transformadora: Total e por tipo [Pordata - Companies in the manufacturing sector: Total and by type] [Data set]. https://www.pordata.pt/Portugal/Empresas+no+sector+da+ind%C3%BAstria+transformadora+total+e+por+tipo-2955.
Pordata (2018). Pordata - Empresas [Data set]. https://www.pordata.pt/en/Portugal/Birth++death+and+survival+rates+of+enterprises-2883
Serrano-Cinca, C., Gutiérrez-Nieto, B., & Bernate-Valbuena, M. (2019). The use of accounting anomalies indicators to predict business failure. European Management Journal, 37(3), 353-375. https://doi.org/10.1016/j.emj.2018.10.006
Singh, B. P., & Mishra, A. K. (2016). Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies. Financial Innovation, 2(6), 1-28. https://doi.org/10.1186/s40854-016-0026-9
Situm, M. (2014). The age and size of the firm as relevant predictors for bankruptcy. Journal of Applied Economics and Business, 2(1), 5-30.
Situm, M. (2015). Analysis of correlational behavior of solvent and insolvent firms based on accounting ratios. Journal of Modern Accounting and Auditing, 11(5), 233-259. https://doi.org/10.17265/1548-6583/2015.05.001
Switzer, L. N., Tu, Q., & Wang, J. (2018). Corporate governance and default risk in financial firms over the post-financial crisis period: International evidence. Journal of International Financial Markets, Institutions and Money, 52(C), 196-210. https://doi.org/10.1016/j.intfin.2017.09.023
Taffler, R. J. (1982). Forecasting company failure in the UK using discriminant analysis and financial ratio data. Journal of the Royal Statistical Society, 145(3), 342-358. https://doi.org/10.2307/2981867
Tian, S., & Yu, Y. (2017). Financial ratios and bankruptcy predictions: An international evidence. International Review of Economics and Finance, 51, 510-526. https://doi.org/10.1016/j.iref.2017.07.025
Tong, Y., & Serrasqueiro, Z. (2021). Predictions of failure and financial distress: A study on Portuguese high and medium-high technology small and mid-sized enterprises. Journal of International Studies, 14(2), 9-25. https://doi.org/10.14254/2071-8330.2021/14-2/1
Whitaker, R. B. (1999). The early stages of financial distress. Journal of Economics and Finance, 23(2), 123-133. https://doi.org/10.1007/BF02745946
Yuan, M., Tang, C. Y., Hong, Y., & Yang, J. (2018). Disentangling and assessing uncertainties in multiperiod corporate default risk predictions. The Annals of Applied Statistics, 12(4), 2587-2617. https://doi.org/10.1214/18-AOAS1170
Zavgren, C. V. (1985). Assessing the vulnerability to failure of American industrial firms: A logistic analysis. Journal of Business Finance and Accounting, 12(1), 19-45. https://doi.org/10.1111/j.1468-5957.1985.tb00077.x
Zeitun, R., Tian, G., & Keen, S. (2007). Default probability for the Jordanian companies: A test of cash flow theory. International Research Journal of Finance and Economics, 8, 147-162.
Zeytinoglu, E., & Akarim, Y. D. (2013). Financial failure prediction using financial ratios: An empirical application on Istanbul stock exchange. Journal of Applied Finance and Banking, 3(3), 107-116.
Zmijewski, M. E. (1984). Methodological issues related to the estimation of financial distress prediction models. Journal of Accounting Research, 22, 59-82. https://doi.org/10.2307/2490859
Downloads
Published
How to Cite
Issue
Section
License
Copyright Transfer Statement for Journal
1) In signing this statement, the author(s) grant UNIMAS Publisher an exclusive license to publish their original research papers. The author(s) also grant UNIMAS Publisher permission to reproduce, recreate, translate, extract or summarize, and to distribute and display in any forms, formats, and media. The author(s) can reuse their papers in their future printed work without first requiring permission from UNIMAS Publisher, provided that the author(s) acknowledge and reference publication in the Journal.
2) For open access articles, the author(s) agree that their articles published under UNIMAS Publisher are distributed under the terms of the CC-BY-NC-SA (Creative Commons Attribution-Non Commercial-Share Alike 4.0 International License) which permits unrestricted use, distribution, and reproduction in any medium, for non-commercial purposes, provided the original work of the author(s) is properly cited.
3) For subscription articles, the author(s) agree that UNIMAS Publisher holds copyright, or an exclusive license to publish. Readers or users may view, download, print, and copy the content, for academic purposes, subject to the following conditions of use: (a) any reuse of materials is subject to permission from UNIMAS Publisher; (b) archived materials may only be used for academic research; (c) archived materials may not be used for commercial purposes, which include but not limited to monetary compensation by means of sale, resale, license, transfer of copyright, loan, etc.; and (d) archived materials may not be re-published in any part, either in print or online.
4) The author(s) is/are responsible to ensure his or her or their submitted work is original and does not infringe any existing copyright, trademark, patent, statutory right, or propriety right of others. Corresponding author(s) has (have) obtained permission from all co-authors prior to submission to the journal. Upon submission of the manuscript, the author(s) agree that no similar work has been or will be submitted or published elsewhere in any language. If submitted manuscript includes materials from others, the authors have obtained the permission from the copyright owners.
5) In signing this statement, the author(s) declare(s) that the researches in which they have conducted are in compliance with the current laws of the respective country and UNIMAS Journal Publication Ethics Policy. Any experimentation or research involving human or the use of animal samples must obtain approval from Human or Animal Ethics Committee in their respective institutions. The author(s) agree and understand that UNIMAS Publisher is not responsible for any compensational claims or failure caused by the author(s) in fulfilling the above-mentioned requirements. The author(s) must accept the responsibility for releasing their materials upon request by Chief Editor or UNIMAS Publisher.
6) The author(s) should have participated sufficiently in the work and ensured the appropriateness of the content of the article. The author(s) should also agree that he or she has no commercial attachments (e.g. patent or license arrangement, equity interest, consultancies, etc.) that might pose any conflict of interest with the submitted manuscript. The author(s) also agree to make any relevant materials and data available upon request by the editor or UNIMAS Publisher.
