An Estimation of Working Capital Management on Profit Using Logistic Regression and Discriminant Analysis

Abstract

Aims: This paper estimates working capital management on profit using logistic regression and discriminant analysis on manufacturing and industrial firms in Ghana. Study Design: Research Paper. Place and Duration of Study: Ghana, Secondary data for 2009 to 2014. Methodology: Data in the form of ratios were computed from the audited annual financial reports of 13 manufacturing and industrial firms listed on the Ghana Stock Exchange covering the period from 2009 to 2014.The ratios were used to determine the profitability of the firms. Results: The results showed that the logistic regression of the dependent variable (Profit) on the independent variables such as the Average Collection Period, the Inventory Conversion Period, the Average Payment Period, the Growth rate, the Debt Ratio, the Current Ratio and the Company Size were found to be significant and that there was no difference in variances for two firm classifications. This result implies that the linear discriminant function is effective in discriminating between a firm which effectively managed its working capital from one which did not. Conclusion: This study showed that the binary logistic regression model estimates correctly at least 75% of firm’s likelihood of managing working capital on profit while correctly discriminating the firms as having an effective management.