TESTING FINANCIAL DISTRESS OF MANUFACTURING FIRMS IN TANZANIA: AN APPLICATION OF ALTMAN Z-SCORE MODEL

Authors

  • Omary J Ally CBE
  • Kembo M Bwana

Keywords:

Financial distress, Altman’s Z-score, manufacturing firms, Tanzania.

Abstract

There are several indicators of poor financial performance and one of them is financial distress. If financial distress is not predicted on time and quick measures been taken then bankruptcy is likely to occur. The costs associated with bankruptcy are enormous and normally tend to affect all stakeholders of the firm. The study applies Multi Discriminant Analysis (MDA) which involves consolidation of effects from all ratios which are measuring the key aspects of financial health. Keeping the above view in mind, the model has been employed to test the financial distress of six (6) manufacturing firms listed in Dar es Salaam Stock Exchange (DSE) in Tanzania from 2010 -2014. The study was based on the published secondary data extracted from annual financial report. Findings revealed that five firms were experiencing financial healthy (average Z-score above 2.99) while the remaining two manifested financial distress (average Z-score is less than 1.88) over the study period. Further findings shows that, management needs special attention on those variables which are very sensitive with regards to financial health of the firms under discussion.

References

Africa Development Group(2014) Eastern Africa Manufacturing Sector: Promoting Technology , innovation, productivity and Linkages, Tanzania Country Report

Makini, P. A. (2015). Validity of Altman’s Z-score Model in Predicting Financial Distress of Listed Companies at the Nairobi Securities Exchange. Unpublished MBA project, University of Nairobi.

Altman, E. I. (1968). Financial ratio analysis, Discriminant analysis and the prediction of corporate bankruptcy. Journal of Finance, 23(4), 589-609.

Altman, E. (1993). Corporate financial distress: A complete guide to predicting, avoiding and dealing with bankruptcy, (2nd Ed.). New York: John Wiley & Sons.

Shisia, A.,Sand , W., &Okibo W. B. (2014). An in depth analysis of the Altman’s failure prediction model on corporate financial distress in Uchumi supermarket in Kenya. European Journal of Business Management, 6(23). 27-41

Mohamed, S. (2013). Bankruptcy prediction of firms listed at the Nairobi Securities Exchange. Unpublished MSc Research Project, University of Nairobi

Mamo, A. Q. (2011). Applicability of Altman (1968) model in predicting financial distress of commercial banks in Kenya. Unpublished MBA Research Project, University of Nairobi

Kariuki, H. N. (2013). The effect of financial distress on financial performance of commercial banks in Kenya. Unpublished MBA Research Project, University of Nairobi

Robinson, R.A. and M. G. Maguire (2001) “Top common causes of construction contractor failuresâ€, Journal of Construction Accounting and Taxation, Jan/Feb 2003.

Eidleman, E.B. (2007) “A discriminant analysis of predictors of business failure,†Journal of Accounting Research, Spring, Institute of Professional Accounting, Chicago, I ll., 167- 179.

Mohammed, S (2016), Bankruptcy Prediction by Using the Altman Z-score Model in Oman: A Case Study of Raysut Cement Company SAOG and its subsidiaries, Australasian Accounting, Business and Finance Journal, 10(4), 70-80. doi:10.14453/aabfj.v10i4.6

Gerantonis, N., Vergos, K. and Christopoulos, A.G. (2009). “Can Altman Z-score Models Predict Business Failures in Greece?â€, Research Journal of International Studies, 12: 21- 28

Mizan AN and Hossain MM. 2014. Financial Soundness of Cement Industry of Bangladesh: An Empirical Investigation Using Z-score, American Journal of Trade and Policy, 1, 16-22

Appiah, K. O. (2011). Corporate Failure Prediction: Some Empirical Evidence from listed firms in Ghana. China-USA Business Review, 10(1), 32–41.

Altman, E. (1993). Corporate financial distress: A complete guide to predicting, avoiding and dealing with bankruptcy, (2nd Ed.). New York: John Wiley & Sons.

Altman, E. I. (1984). Empirical investigation of the bankruptcy cost question. The Journal of Finance, 39(4), 1067-1089.

Altman, E, I. & Hotchkiss E. (2006). Corporate financial distress and bankruptcy: Predict and avoid bankruptcy, Analyze and invest in distressed debt. John Wiley & sons Inc., Hoboken, New Jersey. Third Edition.

Dinh, Hinh T. and Célestin Monga (2013). Light Manufacturing in Tanzania. A Reform Agenda for Job Creation and Prosperity. Washington DC: The World Bank.

Andrade, G. & Kaplan, S. (1998). How costly is financial (Not economic) distress? Evidence from highly leveraged transactions that became distressed. The Journal of Finance, 53, (5), 1443-1493.

Kipruto, E. K. (2013). The validity of Altman’s failure prediction model in predicting Corporate financial distress in Uchumi Supermarket in Kenya, Unpublished MBA Project, University of Nairobi

Opler, T.C., & Titman, S. (1994). Financial distress and corporate performance. The Journal of finance, 49(3), 1015-1040.

Natalia, O. (2007). Corporate financial distress: An empirical analysis of distress risk. Doctoral Dissertation No. 3430, University of St. Gallen, Switzerland

Platt, H. D., & Platt, M. B. (2006).Understanding differences between financial distress and bankruptcy. Review of Applied Economics, 2(2), 141-157

Pranowo, K. Azam, N. Achsani, Manurung, AH., Nuryartono, N. (2010). ‘Determinant of Corporate Financial Distress in an Emerging Market Economy.’ Empirical Evidence from the Indonesian Stock Exchange 2004-2008

Shisia, A.,Sand , W., &Okibo W. B. (2014). An in depth analysis of the Altman’s failure Prediction model on corporate financial distress in Uchumi supermarket in Kenya, European Journal of Business Management, 6(23), 27-41

Sami, B. J. (2013). Financial Distress and Bankruptcy costs. In H. Dincer & U. Hacioglu. Global Strategies for Banking and Finance (369–379). United States: IGI Global.

Ray, S. (2011). Assessing Corporate Financial Distress in Automobile Industry of India: An Application of Altman’s Model. Research Journal of Finance and Accounting, 2(3), 155–169.

Shah, N. (2014). Developing Financial Distress Prediction Models Using Cutting Edge Recursive Partitioning Techniques: A Study of Australian Mining Performance. Review of Integrative Business and Economics Research, 3(2), 103–143.

Downloads

Published

2019-02-07

How to Cite

Ally, O. J., & Bwana, K. M. (2019). TESTING FINANCIAL DISTRESS OF MANUFACTURING FIRMS IN TANZANIA: AN APPLICATION OF ALTMAN Z-SCORE MODEL. Business Education Journal, 5(1). Retrieved from https://bej.cbe.ac.tz/index.php/bej/article/view/170

Issue

Section

Social Sciences