Application of Multiple Discriminant Analysis in Predicting Financial Distress of Commercial and Manufacturing State Corporations in Kenya

Abstract

Commercial and Manufacturing state owned corporations are heavily financed by the National Treasury and they perform important functions that ensure smooth running of the nation. Instances of financial distress or failure of State Corporations normally lead to great financial implications in the economy especially in terms of job losses. This raises valid concerns to investors and all other stakeholders. Therefore, the core objective of the study is to find out whether Altman (1993) model is applicable in predicting financial distress of Commercial and Manufacturing State Corporations in Kenya. This will assist various stakeholders in the Kenyan financial industry to react to distress signals in State Corporations early enough to avoid corporate failure. Exploratory research design was adopted in this study where a census was carried out on the 27 Commercial and Manufacturing State Corporations. The period of study was five (5) years ranging from the financial year 2010-2011 to 2014-2015. The audited financial accounts of State Corporations provided secondary financial data. This data was used to extract liquidity, profitability and leverage ratios which were then summed up to arrive at the Z-Score. Data analysis was conducted through the use of MS Excel where correlation and regression tests were tabulated. The research findings indicate that Altman (1993) model is reliable in predicting financial distress of Commercial and Manufacturing State Corporations in Kenya since it predicted accurately 66.32% of non-distressed corporations and 75% of distressed firms. Further, the findings provide evidence that liquidity (WC/TA), profitability (RE/TA) and leverage (BVE/TL) ratios had a major influence on financial distress prediction. Short-term profitability ratio (EBIT/TA) did not have much influence. The outcome of this study suggests that stakeholders in a firm can predict failure before it occurs by paying close attention to liquidity, long-term profitability and leverage ratios. This will enable them avoid the losses associated with failures by taking appropriate actions in advance.