Working capital management and corporate profitability: Evidence from panel data analysis of manufacturing industries in India Rao K T Vigneswara, FPM Participan Finance & Accounting Area, Indian institute of Management, Indore, M.P., India Online published on 4 July, 2012. Abstract The present study investigates the relationship between the working capital management and profitability of six manufacturing industries in India by using panel data approach for a period of five years. This study used four control variables such as size, sales growth, leverage and current ratio in addition to independent test variables of Inventory holding period (INVHP), Accounts receivables period (ARP) Accounts payables period (APP) and Cash conversion cycle (CCC). At first, the impact of working capital management on profitability has been analyzed by using Pooled OLS multiple regression models. However, the Breusch-Pagan test statistic reveals that this OLS regression is inconsistent for the present study. Hence, Hausman test (1978) was applied to decide whether the fixed effect model or random effect model is consistent with the given panel data. The empirical results for automobiles, capital goods, cement, steel and Pharma industry reveal that all the four fixed effect regression models were found statistically significant at 99 percent confidence level. While in the case of capital goods industry all the variables excluding the size and the respective independent test variables in their models are found statistically significant. Based upon the empirical results of four regression models, this study rejected the four hypotheses H1, H2, H3 and H4 in the case of automobiles, capital goods, fertilizers and Pharma industry. For the cement and steel industry, the empirical result suggests that there is a statistically significant negative relationship at 99 percent confidence level between the inventory holding period, cash conversion cycle and profitability. Top Keywords working capital, panel data, Hausman test, fixed effects model, random effects model. Top |