IMPACT OF WORKING CAPITAL MANAGEMENT ON PERFORMANCE

Impact of Working Capital Management on Performance 1 IMPACT OF WORKING CAPITAL MANAGEMENT ON PERFORMANCE Impact of Working Capital Management on Performance of Listed Non Financial Companies of Pakistan: Application of OLS and LOGIT Models Irfan Ahmed University of Sargodha, Sargodha, Pakistan

Impact of Working Capital Management on Performance 2 Abstract Present study investigates the impact of working capital management on the performance of the firm using a sample of 253 non financial listed companies of Karachi Stock Exchange (KSE), Pakistan. The study used secondary data taken from Balance Sheet Analysis of Stock Listed Companies on KSE published by State Bank of Pakistan. Results were analyzed by using the Logistic Regression, OLS Regression and Pearson Correlation techniques. The result suggests that out of the five selected components of working capital management only current asset over total sales showed significant negative relationship with both the proxies of performance i.e. return on equity and return on assets. While current asset over total asset (CATA), inventory turnover, debtor s turnover and current ratio showed significant positive relationship with performance. Logistic regression results suggested that probability of firm being in profit is highly determined by CATA, CATS and CR. KEYWORDS: Working capital management, Profitability, OLS regression, Logistic regression. 1. Introduction

Impact of Working Capital Management on Performance 3 WCM is among the most important decisions taken by the financial manger. It directly affects the profitability and is considered one of the most important parts of financial decision making (Haq et al 2011). Net working capital is the excess of current assets over current liabilities of a firm. It determines the strength of the business and its liquidity position means more the working capital more the liquidity of the firm. WCM could be permanent or temporary; former is the amount of current assets company must possess for longer period of time to offset its current liabilities while later is the excess of current assets to meet seasonal current liabilities (Van Horn 2005). According to Raheman and Nasr, (2007) Management of current assets to meet short term obligations of the company is WCM. Objective of the WCM is to make sure that firm meets the operating requirements and also remain in a position to pay short term debt when they fall due (Mohamad & Noriza 2010). Mismanagement of working capital will lead a firm to liquidity crisis by reducing its profitability and creditability, so managing working capital effectively is necessary for going concern of the business and also for its profitability (Siddique & Khan 2009). Earlier we have classified WCM as temporary and permanent, now we are classifying it as aggressive and conservative. Aggressive WCM refers to the firm s strategy of having fewer current assets in proportion of total assets or having high proportion of current liabilities as compared with the total liabilities of the company. It leads a company to low liquidity or higher profitability (Van horne & Machowicz 2004). Conservative WCM technique appears with the philosophy of using long term source should be used for the entire investment in the current assets and short term should be used only for urgent situations. Distinct features of conservative WCM are increased liquidity and less risk but more interest has to be paid on the seasonal requirement for the entire period. Larger firm focus on higher sales with fewer on cash basis

Impact of Working Capital Management on Performance 4 which leads to greater cash flow problems and seasonality while smaller firms major focus is stock management and credit management policies with low profitability. When a firms credit sales increases their account receivables increases which leads to less inventory in the stock and accounts payables also increases. These three components (accounts receivable, accounts payables and inventory) of cash conversion cycle have different ways to be managed in order to maximize firm s profitability. In order to make CCC more effective, equilibrium should be maintained in accounts receivables, accounts payables and inventory that have positive significant impact on profitability of a firm. WCM is important for the growth and stability of any country s economy. Pakistan is rich in having natural resources and human skills and different industries are playing their vital role in the growth of Pakistan economy. Textile, Sugar, Chemical and Cement sectors are major contributors of country s economy. Pakistan textile industry is the largest industry of the country and is ranked 8th largest exporter of textile products around the world. Investment in the sector is US$ 7 Billion and its total exports are US$ 9.6 billion in year 2008-09. It contributes 46% to the total manufacturing and 8.5 % of the country s GDP. 38 % of the total labor force is employed in this sector and its market capitalization is 5% of the total market capitalization (Pakistan Economic Survey SBP, TDAP). Sugar Industry is ranked 2nd largest industry of Pakistan and is 5th largest sugarcane producing area in the world. It s also the 15th biggest sugar producer of the world. In 2009-10 Pakistan s sugarcane production is approximately 47.8 MMT (million metric tons), which is 2.2 MT (million tons) less from the previous year. In 2009-10 sugar imports are forecasted at 1.03 MT and 50000 tons decrease is estimated in consumption. Chemical sector is ranked in top 5 highly growing and globally traded sectors. Chemicals are divided into 2 main categories commodity and specialty chemicals. According to IAR (Industrial Advisory Report

Impact of Working Capital Management on Performance 5 2009) Imports of chemical increased but not significantly as compared to the growth of industry. In 2007-08 Pakistan imported Rs. 329 billion worth of different chemicals. Demand of chemical is increasing and the sector can grow in the long term but absence of clear policies and frameworks are a big hurdle in it. Pakistan is enriched with the cement resources and is ranked as the 5th biggest exporter in the world. Many plants are working in the private sector and there is a prediction that India will import cement from Pakistan and till 2008 Pakistan has imported 130000 tons of cement (according to Growth of Pakistan Cement Industry Overview Friday, 26 September 2008). Demand of cement has been increased significantly in the last decades. Cement Industry has captured African countries as well for its exports. Industry growth is 32% but exports increased by 111.86% (Pakistan Cement Industry Report 2009). It is evident from above discussion that textile, sugar, chemical and cement sectors are the major contributors of economic growth of Pakistan and WCM in these sectors plays a vital role in managing the affairs of their respective businesses. However, it is important to investigate the nature and processes of WCM strategies adopted by these industrial sectors of economy. Therefore, the present study is intended to investigate the empirical results of 4 major industries (Textile, sugar, chemical and cement) of Pakistan listed at KSE during period 2004 to 2009. This study will help us to analyze effect of accounting ratios on WCM and on profitability collectively. We will also derive a conclusion about the relation between WCM and profitability. Rest of the article is arranged in the following order: Section 2 provides Literature Review, Methodology is given in section 3, section 4 provides Results while Conclusion is given in the last section. 2. Literature Review

Impact of Working Capital Management on Performance 6 Various studies have been done in the past to check the relationship between profitability and WCM. Mostly, researchers used the proxies for both WCM and profitability and it remained difficult to state one exact relationship between them as different studies contain different determinants of WCM and those variables have shown different relationship with the proxies of profitability. Lazaridis & Tryfonidis (2006) worked on 131 listed companies of Athens stock exchange for four years from 2001 to 2004. Aim behind the study was to determine statistically significant relation between CCC and profitability which is measured by gross operating profit. Accounts receivable turnover, accounts payable turnover and inventory management are the three components of CCC. Pearson correlation and regression results showed that there is a negative relationship between accounts receivable turnover, accounts payable turnover & inventory management and profitability which is in line with the study of Deloof (2003). Raheman & Nasr (2007) analyzed the effect of several variables on Net Operating Profitability which includes average collection period, average payment period, ITO in days, CCC, ITO in days and CR in Pakistan. Control variables including debt ratio, size of the firm and financial asset over total asset ratio are used and they applied Pearson Correlation and Regression for purpose of analysis. Sample of 94 Pakistani listed companies for 6 years from 1999-2004 had been taken and concluded that managers can maximize shareholder value by efficiently managing components of CCC. It shows that there exists a strong negative relation between firm s profitability and measures of WCM. From emerging economy of Pakistan, Afza & Sajid (2008) investigated the relationship between aggressive/conservative working capital policies and Firm s return. They took a sample of 263 non financial companies from 17 industrial sectors after removing firms with negative equity listed on KSE which constitute the whole population for analysis. They reported a negative

Impact of Working Capital Management on Performance 7 relationship between measures of the profitability and degree of aggressiveness of financing and investment policies. According to Gill et al (2010) who extended Lazaridis & Tryfonidis (2006) study on relationship between WCM and profitability, there exists a significant relationship between CCC and profitability. They analyzed a sample of 88 firms listed on NYSE (New York Stock Exchange) for three years from 2005 to 2007 using correlation and regression analysis to conclude that their study was in line with the study of Lazaridis and Tryfonidis study and said that if a manager efficiently manages accounts receivables, accounts payables and inventory he can increase the profits of the firm. H. Jamal Zubairi (2010) studied Pakistan automobile sector and checked the impact of WCM and capital structure on profitability of the firm. To measure the profitability they used earnings before interest and taxes. Panel data set was analyzed using regression. The results showed that profitability variations due to the above mentioned four variables give three quarters of total variation. They also reported positive relation between profitability and size of the firm which is in accordance with the results of Raheman & Nasr (2007) study. In Malaysia, Mohamad & Noriza (2010) did their study by taking secondary data from Bloomberg s 72 listed companies for 5 years from 2003-2007 to derive the relationship empirically between WCM and profitability. Study was done to check effects of working capital components (such as CCC, CATA ratio, debt to asset ratio, CR and current liabilities over total asset ratio) on firm s performance and profitability measured by Tobin s Q ratio, return on invested capital and ROA. Correlation and Multiple Regression results showed a significant negative relation between working capital components and company s performance.

Impact of Working Capital Management on Performance 8 Haq et al (2011) conducted a study in Pakistan on WCM of cement industry by taking a sample of 14 cement firms listed on KSE (Karachi Stock Exchange) from year 2004-2009 in panel data set. They used eight accounting ratios (CR, QR, CATA ratio, CATS, cash turnover ratio, ITO ratio, DTO, creditor turnover ratio) as independent variables and ROI as the dependent variable. Estimated results based on Pearson correlation and Pooled Ordinary Least Square Regression shows moderate relationship between WCM and profitability of firm. Karaduman et al (2011) studied this relationship of WCM and profitability by taking data of five years of non financial companies listed at Istanbul Stock Exchange. A balanced panel sample of 127 companies was analyzed which gives total of 635 observations. CCC was used as a measure of WCM and for profitability ROA acted as a measure. The result showed that efficient management of CCC will give greater returns. From the previous studies it is evident that researchers used the accounting ratios as a proxy to check the relationship between WCM and profitability. Most frequently ROA, ROE, ROIC and Tobin s Q are the proxies used for profitability and CCC, CATA, ITO, DTO and CR are the variables used for WCM. The methodology adopted by the majority of researchers to examine the relationship is correlation analysis, OLS regression and multiple regression analysis. The results indicate that different contents of WCM show different relationship with profitability proxies and it is difficult to conclude the exact relationship of WCM with the profitability. 3. Methodology 3.1 Sample and Data The study is based on checking the relationship between WCM and profitability in the all listed non financial sectors of Pakistan industry. For the analysis of the population the sample of 263

Impact of Working Capital Management on Performance 9 companies from 4 major non financial sectors has been taken from the Balance Sheet Analysis of Joint Stock companies listed on Karachi Stock Exchange from 2004-2009 published by State Bank of Pakistan. Initially, the whole population census was taken for study and the numbers of observations were 1578 but the descriptive analysis showed presence of various outliers in the data which were removed by the procedure of 1% trimming. Finally, those firm year observations have been deleted where value of any variable found missing which reduces the sample size equal to 984 firm year observations. 3.2 VARIABLES OF STUDY & HYPOTHESIS: The following ratios representing WCM have been analyzed in the study. 1- Current Asset over Total Assets Ratio 2- Current Assets over Total Sales Ratio 3- Inventory turnover 4- Debtors Turnover 5- Current Ratio 6- Quick Ratio ROE and ROA have been used as a proxy of firm s profitability. The table 1 given below presents the definitions and expected signs of the variables. The relation between the variables had been examined by making the use of Binary Logistic Regression analysis on the unbalanced panel sample. The equation representing the relationship is as follows:

Impact of Working Capital Management on Performance 10 Where: ROE it represents ROE for firm i at time t ROA it represents ROA for firm i at time t CATA it represents CATAR for firm i at time t CATS it represents CATSR for firm i at time t ITO it represents ITO for firm i at time t DTO it represents DTO for firm i at time t CR it represents CR for firm i at time t QR it represents quick ratio QR for firm i at time t u it represents error term of the model The binary logistic regression has been used on the panel sample data. The advantage of using the binary logistic regression is that t gives the results in binary form say YES or NO which cannot be explained by ordinary least square regression. In our study it helps to determine that a firm is in profit or loss in a particular year. 3.3 ESTIMATION TECHNIQUES: Present study has used OLS as the primary estimation technique to investigate the impact of WCM on firm s performance. However, the chances of firm earning profit or suffer loss as a result of its WCM policy is yet to be investigated in detail. Therefore, present study has also incorporated binary logistic regression to determine the probability of firm being profitable or in loss due to its WCM. Logistic regression is a method for determining the relationship between predictor variables and a dichotomously coded dependent variable. It s a linear model used for binomial regression. Just like other forms of the regression analysis, it makes use of the predictor

Impact of Working Capital Management on Performance 11 variables that can be either numerical or categorical. For estimation purposes LOGIT model can be explained by the following equation: The LOGIT specification of dependent variable is: Where Y, representing dependent variable, is equal to 1 if the company is profitable and 0 if the company is in loss. The probability that the company is profitable is given by: If we assume that error follows a logistic distribution to be standard than it will be represented: On the other hand if we say that the company will not be profitable or in loss than the equation will be: The odd ratio i.e. P(Y=1)/1-P(Y=1) which states the ratio of probability that company will be profitable to the probability that company will not be profitable would be equal to: Now if we take the log of the odd ratios it will be:

Impact of Working Capital Management on Performance 12 Exponent raised to the power beta Exp (β) explains that if the value of Exp (β) is less than 1 than increase in independent variable will correspond to the decrease in the odd ratio and if the value is greater than 1 than increase in independent variable will result in an increase in the odd ratio. 4. Result and Analysis 4.1 Descriptive Analysis Table 2 of descriptive analysis reports the mean, median and standard deviation of the all dependant and independent variables. 4.2 Pearson correlation Pearson correlation is used to check the linear association among variables of the study. We found that ROE is having positive association with ROA, CATA, CR and QA at the significance level of 1%. It also has positive association with ITO and DTO but that is not significant. ROE have the negative association with CATS but association is not significant.in case of ROA there is positive association with CATA, ITO, DTO, CR and QR at the significance level of 1% and negative association with CATS at the significance level 5% shown at the end in table 3. Collinearity statistics shows that there is no multicollinearity factor in the study. 4.3 Regression Analysis: Regression Analysis is basically used to measure the relationship between dependent and independent variables. In this study Regression analysis contains two dependent variables. In

Impact of Working Capital Management on Performance 13 table 4 regression results are shown by taking ROE as dependant variable. In table 4 ROE is replaced by ROA. Table 4 shows that there is positive relationship with CATA, ITO, DTO and CR at the significance level of 1% shows that increase in these variables will significantly increase ROE of the firm. While there is negative relation with CATS at the significance level of 1%. This relation shows that increase in CATS will significantly decrease ROE of the firm. The value of R-square 0.122 shows that only 12.2% of the change in ROE is explained by the independent variables. The F-statistic value is 27.08 and is significant at the level of 1%.The adjusted R- square value is 11.7%. Table 5 shows ROA has positive relationship with CATA, ITO, DTO and CR at the significance level of 1%. While there is negative relation of ROA with CATS at the significance level of 1%. The value of R-square.310 shows that only 31% of the change in ROA is explained by the independent variables. The F-statistic value is 88.08 and is significant at the level of 1%.The value of Durban Watson test is 1.45. To check the relationship between WCM and profitability we have seen regression results for each sector individually. The results show that CATA and CATS strongly determines ROE and ROA for the textile sector. Similarly DTO is most significant in Chemical sector and ITO shows most significant results with both ROE and ROA in cement sector analysis. An important finding is that no variable shows significant results in sugar sector analysis. So, Regression was run on the three sectors (textile, chemical and cement) excluding sugar sectors and that improves the value of R-square. 4.4 Logistic Regression

Impact of Working Capital Management on Performance 14 Logistic regression is used when the dependent variable is binary. In our study it has been used to see that either the firm is profitable in a year or not. According to the results shown in table 6, 1 unit increase in CATA will cause an increase of 20.863 in the probability that the ROE will increase. CATS value gives an indication that 1 unit increase in CATS will decrease the probability of an increase in ROE by 0.362. The value for exp (β) of ITO shows that 1 unit increase in ITO will increase the probability of increase in ROE by 1.001. DTO value is giving an indication that an increase of 1 unit in DTO will decrease the chances of increase in ROE by 0.998 units. Similar to ITO, CR exp (β) shows that 1 unit increase in CR will cause an increase in the probability of increase in ROE by 1.010 units. Result reveals CATA, CATS and CR are the strong determinants of the WCM and highest value of CATA shows it the most significant determinant of WCM. Conclusion Present study investigates the relationship between WCM and profitability of a firm of 263 non financial stock listed companies at KSE (Karachi Stock Exchange). For analysis purpose financial ratios of WCM are used to check their affect on the performance of the firm in the context of 4 major non financial sectors of Pakistan. The result suggests that out of the five selected components in regression analysis CATS ratio is only variable that shows significant negative relationship with both ROE and ROA. CATA is having significant positive relationship with ROA and ROE which is in line with the studies of Noriza & Azhar (2010). ITO shows positive relationship with ROE but the results are not significant while shows significant positive relationship with ROA. DTO is also having significant positive relationship and CR shows significant positive relationship with both the proxies of profitability and these results are parallel to the study of Haq et al (2011). We hope that our results would be a contribution in the

Impact of Working Capital Management on Performance 15 study of WCM and profitability as logistic regression is first time used for analysis to the best of our knowledge. It is recommended that future research should be done specifically on the sugar sector to identify the strong determinants of profitability in this sector and to use other variables of WCM that better predicts the relationship with profitability. References Afza, Talat & Mian Sajid Nazir, 2008. Working Capital Approaches and Firm s Returns in Pakistan, Pakistan Journal of Commerce and Social Sciences, Vol.1, pp.25-36. Binti Mohammad nor Edi Azhar & Noriza Binti Mohd Saad (2010). Working Capital Management: The Effect of Market Valuation and Profitability in Malaysia. International Journal of Business and Management, Vol. 5, No. 11. Eljelly, A. (2004). Liquidity-profitability tradeoff: an empirical investigation in an emerging market. International Journal of Commerce and Management, Vol.14 (2), pp. 48-61. Gill Amarjit, Nahum Biger & Neil Mathur (2010). The Relationship Between Working Capital Management And Profitability: Evidence From The United States. Business and Economics Journal, Volume 2010: BEJ-10.

Impact of Working Capital Management on Performance 16 Haq Ikram ul, Muhammad Sohail, Khalid Zaman &Zaheer Ala (2011). The Relationship between Working Capital Management and Profitability: A Case Study of Cement Industry in Pakistan. Mediterranean Journal of Social Sciences, Vol.2, No.2. Karaduman Hasan Agan, Halil Emre Akbas, Arzu Ozsozgun Caliskan and Salih Durer (2011). The Relationship between Working Capital Management and Profitability: Evidence from an Emerging Market. International Research Journal of Finance and Economics, ISSN 1450-2887, Issue 62. Lazaridis I & Tryfonidis, D. (2006). Relationship between working capital management and profitability of listed companies in the Athens stock exchange. Journal of Financial Management and Analysis, Vol.19 (1), pp 26 35. Narware P. C. (2004). Working capital and profitability- an empirical analysis. The Management Accountant, Vol, 39 (6), pp 120-127. Raheman, Abdul & Mohamed Nasr. (2007). Working capital management and profitabilitycase of Pakistani firms. International Review of Business Research Paper, Vol 3, No1, pp.279-300. State Bank of Pakistan (2010). Balance Sheet Analysis Joint Stock Companies Listed on the Karachi Stock Exchange, online available at:www.sbp.org.pk/departments/stats/bsa.pdf Zubairi H. Jamal (2010). Impact of Working Capital Management And Capital Structure on Profitability of Automobile Firms in Pakistan. Social Science Research Network. July 31, 2010Finance and Corporate Governance Conference 2011 Paper

Impact of Working Capital Management on Performance 17 Tables: Table 1: Definitions, symbols and expected signs of the proxy variables Dependent Variables Definition Symbols Expected Signs Return on Equity Measures how much the shareholders ROE earned for their investment in the company. Return on Assets Measures the ability of firm to utilize its ROA assets to create profits Independent Variables Current Asset over Describes the proportion of current assets in CATAR Negative Total Assets Ratio comparison with total assets Current Assets over Describes the ratio of current assets to the CATSR Negative

Impact of Working Capital Management on Performance 18 Total Sales Ratio Inventory Turnover total revenues of firm Indicates the liquidity of the inventory ITO Positive Ratio Debtors Turnover Indicates the liquidity of the receivables DTO Positive Ratio Current Ratio Determines the short term debt paying CR Negative ability of the firm Quick Ratio Determines the short term debt paying QR Negative ability of the firm excluding inventories Table 2: Descriptive No MEAN MEDIAN S.D ROE 984 3.25 5.40 31.21 ROA 984 2.88 1.70 9.21 CATA 984.46 0.46.17 CATS 984.56 0.46.38 ITO 984 7.80 4.63 11.20 DTO 984 26.20 13.16 21.80 CR 984 108.05 92.50 70.92 QR 984 64.54 46.15 58.79

Impact of Working Capital Management on Performance 19 Table 3: Pearson correlation ROE ROA CATA CATS ITO DT CR QR ROE 1 ROA.741** 1 CATA.247**.302** 1 CATS -.017 -.080*.343** 1 ITO.057.107** -.244** -.202** 1 DTO.055.097** -.263** -.144**.191** 1 CR.271**.463**.531**.322** -.055 -.023 1 QR.256**.431**.431**.320**.140**.029.925** 1

Impact of Working Capital Management on Performance 20 ** Significant at level 1%; *Significant at level 5% Table 4: OLS Regression Table for ROE Unstandardized Coefficients Model T B Std. Error Sig. CATA 42.392 7.074 5.993.000 CATS -10.687 2.694-3.967.000 ITO.227.088 2.579.010 DTO.084.031 2.701.007 CR.087.016 5.388.000 (Constant) -23.699 3.412-6.945.000 Adjusted R square.117 Sig. F.000 Std. Error 29.32 Durbin Watson 1.45 Table 5: OLS Regression for ROA Unstandardised Coefficients Model B Std. Error T Sig. CATA 11.405 1.849 6.169.000

Impact of Working Capital Management on Performance 21 CATS -6.210.704-8.819.000 ITO.091.023 3.964.010 DTO.030.008 3.694.007 CR.057.004 13.669.000 (Constant) -6.624.892-7.427.000 R-Square.310 F 88.07 Adjusted R square.307 Sig. F.000 Std. Error 7.66 Durbin Watson 1.16 Table 6: Logistic Regression Model B Df Sig. Exp(B) Wald S.E CATA 3.038 1.000 20.86 21.35.657 CATS -1.017 1.000.362 16.23.235 ITO.001 1.859 1.00.032.007 DTO -.002 1.318.998.997.002 CR.010 1.000 1.01 19.16.002 (Constant) -.774 1.007.461 7.36.285

Impact of Working Capital Management on Performance 22 Cox & Snell R-Square Nagelkerke R-Square.114.163-2 log likelihood 1011.08 Chi square Df Sig Step 114.21 5.000 Block 114.21 5.000 Model 114.21 5.000