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1 ABSTRACT FACTORS THAT INFLUENCE WORKING CAPITAL REQUIREMENTS IN CANADA Amarjit Gill Professor of Business Administration College of Business Administration, Trident University International, 5665 Plaza Drive, CA, 90630, USA. The purpose of this study is to find the factors that influence the working capital requirements (wcr) in canada. a sample of 166 canadian firms listed on toronto stock exchange for a period of 3 years from was selected. this study applied co-relational and non-experimental research design. overall results indicate that operating cycle (oc), return on assets (roa), internationalization of firm, firm s growth, and firm size influence the wcr in canada. the study also found that oc, roa, leverage, internationalization of the firm, tobin's q, and firm size influence the working capital requirements in the canadian manufacturing industry. in addition, findings show that oc, roa, sales growth, and firm size affect the wcr in the canadian service industry. this study contributes to the literature on the factors that influence working capital requirements. the findings may be useful for the financial managers, investors, and financial management consultants. Keywords: Working Capital Requirements; Operating Cycle; Operating Cash Flows; Firm Growth; Return on Assets; Firm Size. 1. INTRODUCTION The purpose of this study is to find the factors that influence the working capital requirements in Canada. The working capital requirement, in the context of this study, is defined as the minimum amount of resources that a firm requires to effectively cover the usual costs and expenses necessary to operate the business. Working capital management deals with current assets and current liabilities. The working capital meets the short term financial requirements of a business enterprise. The lesser requirements of working capital leads to less need for financing and less cost of capital, which in turn, increases the availability of cash for shareholders (Ganesan, 2007). The effective management of working capital is very important because it affects the profitability and liquidity of the firm (Taleb et al., 2010). The main objective of working capital management is to maintain an optimal balance between each of the working capital components. The efficient management of working capital is a fundamental part of the overall corporate strategy to create shareholders value (Nazir & Afza, 2008, p. 294). Therefore, firms try to keep an optimal level of working capital that maximizes their value (Deloof, 2003). Theoretically, working capital management concepts may be simple and straightforward for the financial executives such as Chief Financial Officers (CFOs), but in practice, it has become one of most important issues in the organizations. Many financial executives are struggling to identify the basic working capital drivers and the appropriate level of working capital (Lamberson, 1995). The lack of understanding about the impact of working capital requirements on profitability, the lack of clarity about its determinants, and the lack of management s ability to plan and control its components may lead to insolvency and bankruptcy. Smith (1973) also argues that a large number of business failures may come from the inability of financial managers to plan and control current assets and current liabilities of their respective firms. Nazir and Afza (2008) explain that companies can minimize risk and improve overall performance by understanding the role and drivers of working capital. Therefore, it is important to understand the components of working capital to have an optimal level of working capital. The optimal level of working capital is the one in which a balance is achieved between risk and efficiency. However, an optimal level of working capital requires continuous monitoring of various components of working capital such as accounts receivables, accounts payables, inventory, cash, and marketable securities. 30

2 The efficient management of working capital does not only immunize firms from financial upheaval, but also improves the competitive position and profitability. For example, an increment in the speed of a cash cycle through receivables and payables management helps generating more profitability and liquidity. In addition, effective inventory management is critical to the management of liquidity and profitability of the firm (Taleb et al., 2010). Therefore, it is important to maintain an optimal balance between each of the working capital components. A variety of variables that might potentially be responsible for the working capital requirements can be found in the literature. In this study, the selection of explanatory variables is based on alternative theories related to working capital requirements and additional variables that were studied in reported empirical work. The choice is sometimes limited, however, due to lack of relevant data. As a result, the final set of proxy variables includes ten factors: working capital requirements, operating cycle, operating cash flows, sales growth, return on assets, Tobin s q, leverage, firm size, firm's internationalization, and industry dummy. The variables, together with theoretical predictions as to the direction of their influence on working capital requirements are summarized in Table 1. Nazir and Afza (2008, 2009) have tested variables by collecting data from Karachi Stock Exchange (KSE). This study seeks to extend these studies by analyzing data from Canada. The results might be generalized to manufacturing and service industries. This study contributes to the literature on the determinants of working capital requirements in at least two ways. First, it focuses on Canadian manufacturing and service firms while only limited research has been conducted on such firms recently. Second this study validates some of the findings of previous authors by testing the relationship between working capital requirements and operating cycle, operating cash flows, sales growth, return on assets, Tobin s q, leverage, and firm size of the sample firms. Thus, this study adds substance to the existing theory developed by previous authors. 2. LITERATURE REVIEW Working capital management is very important for creating value for shareholders (Shin & Soenen, 1998). Efficient working capital management is crucial for the business organizations because it has a significant impact on both profitability and liquidity. Therefore, it is important for the financial managers and executives to understand the requirements of working capital. Soenen (1993) used approximately 2,000 firms from 20 different industries for a period of and found a negative relationship between company's net trade cycle and its profitability as measured by the total return on total assets. The findings show that shorter net trade cycles are most commonly associated with higher profitability. Soenen explains that by carefully monitoring both the timing and magnitude of cash flows, managers can generate cash for investment purposes. The cash conversion cycle, by reflecting the net time interval between actual cash expenditures for the purchase of productive resources and the ultimate collection of receipts from product sales, provides a valid alternative for measuring corporate liquidity. In addition, author describes that the length of the cash conversion cycle is instrumental in determining the degree to which a firm must rely on external financing. Lamberson (1995) studied 50 small firms for a period of and used economic indicators as independent variables and financial ratios as dependent variables to explore the relationship between changes in working capital position and changes in the level of economic activity. The findings show that liquidity increased slightly for the sampled firms during economic expansion with no notable change in liquidity during economic slowdowns. 31

3 Weinraub and Visscher (1998) used quarterly data for a period of and collected data from 216 US firms to discuss the issues of aggressive and conservative working capital management policies. Their results show that the industries had significantly different current asset management policies. The relative nature of the working capital management policies exhibited remarkable stability over the 10 year period of study. Weinraub and Visscher also found that industry policies concerning relative aggressive/conservative liability management were significantly different. In addition, the results show a high and significant negative correlation between industry asset and liability policies. Relatively aggressive working capital asset management seems balanced by relatively conservative working capital financial management. Filbeck and Krueger (2005) provide insights into the performance of surveyed firms across key components of working capital management. Authors assessed nearly 1,000 firms and used data from a traditional working capital management survey published by CFO Magazine in United States, for a period Researchers discovered that significant differences exist between industries in working capital measures and these measures change across time. According to Filbeck and Krueger, these changes could be related to the macroeconomic factors such as interest rate, innovation rate, and competition. Chiou et al. (2006) collected quarterly data from Taiwan Stock Exchange by using 19,180 firms, for a period Although, the study revealed that debt ratio and operating cash flow can affect management of working capital, authors did not find any consistent empirical results on the relation of the working capital management to business indicator, industry effect, company growth, firm performance, and firm size. Sathyamoorthi and Wally-Dima (2008) used retail domestic companies listed on Botswana Stock Exchange from 2004 to Research findings reveal that companies adopt a conservative approach in the management of their working capital which suggests that it is not static overtime, but varies with the changes in the state of the economy. Companies tend to adopt a conservative approach in the times of high volatility and tend to adopt an aggressive approach in times of low volatility. Appuhami (2008) collected data from 416 companies listed on Thailand Stock Exchange for a period of and found a negative relationship between operating cash flow and working capital management. Nazir and Afza (2008) used 204 manufacturing firms from 16 industrial groups listed on Karachi Stock Exchange (KSE) for a period of to find the factors that determine working capital requirements. Authors used working capital requirement as a dependent variable and operating cycle of firm, level of economic activity, leverage, growth of firm, operating cash flows, firm size, industry, return on assets and Tobin s q as independent variables. Regression analysis was used on panel data for 204 non-financial firms over a span of nine years. Researchers found an evidence that operating cycle, leverage, return on assets and Tobins q significantly influence the working capital requirements. Nazir and Afza (2009) used 132 manufacturing firms from 14 industrial groups listed on Karachi Stock Exchange (KSE) between a period of They used working capital requirement (WCR) as the dependent variable. Operating cycle of the firm, level of economic activity, leverage, growth of the firm, operating cash flows, firm size, industry, return on assets, and Tobin's q were used as the determining factors of working capital requirements. Authors carried out regression analysis on the panel data for 132 non-financial firms over a period of nine years. They found positive relationships between i) operating cash flow and WCR, ii) Tobin s q and WCR, iii) return on assets and WCR, and iv leverage and WCR. Authors did not find any statistically significant relationships between i) size of the firm and WCR and ii) sales growth and WCR. They also indicate that the level of economic activity does not have any significant effect on WCR practices of firms in Pakistan. Taleb et al. (2010) used 82 industrial firms from listed on Amman Stock Exchange (ASE) for a period of Authors used working capital requirement as a dependent variable. They used operating cycle of firm, level of economic activity, leverage, growth of firm, operating cash flows, firm size, return on assets, and 32

4 Tobin s q as independent variables. Through regression analysis, researchers found statistically significant relationship between working capital requirements and operating cash flows. They also found statistically significant relationships between all independent variables and working capital requirements at every year and all period years of the study. In summary, the literature review shows that operating cycle, operating cash flows, firm s growth, return on assets, Tobin s q, leverage, firm size, and industry dummy influence working capital requirements. The present study investigates the relationship between a set of such variables and the working capital requirements of a sample of Canadian manufacturing and service firms. Table 1 summarizes the definitions and theoretical predicted signs. 3. METHODS 3.1 Measurement To remain consistent with previous studies, all the measures (except the internationalization of the firm) pertaining to the factors that influence the working capital requirements were taken from Nazir and Afza (2009, p. 32 and 33). They used cross sectional yearly data and measured the variables as follows: WCR_TA i (Working capital requirements) = [(Cash and equivalents + Marketable securities + Inventories + Accounts receivables) - (Accounts payables + Other payables)] / Total assets OC i (Operating cycle) = Sum of days in inventory plus sum of days in accounts receivables [Days in inventory = average inventory / (Annual sales/365days); Days in accounts receivables = Average accounts receivables / (Annual sales/365days)] OCF_TA i (Operating cash flows) = Cash flows generated from the routine operations of the firm and obtained directly from the cash flow statement as well as deflated by total assets (operating cash flow / total assets) Growth i (Firm s growth) = Sales variability measured by changes in annual sales (Current year s sales minus previous year s sales divided by previous year s sales) ROA i (Return on assets) = Net income of the firm divided by the total assets Q i (Tobin s q) = Sum of book value of total debt plus market value of equity divided by the book value of total assets of the firm Lev i (Leverage) = Total debt to total assets ratio for the firms (total debt / total assets) LNSize i (Firm Size) = The natural log of total assets of firm MULTI i = Internationalization of firm (Firm is assigned value 1 if it is a multinational corporation and zero otherwise) IndDum i (Industry) = IndDum is used as industry code (Firm is assigned value 1 if it is service firm and zero otherwise) μ i = the error term The study uses panel data for the period and an Ordinary Least Square (OLS) regression model to find the factors that influence working capital requirements. The model is as follows: 33

5 WCR_TA i = + 1 OC i + 2 OCF_TA i + 3 Growth i + 4 ROA i + 5 Q i + 6 Lev i + 7 LNSize i + 8 MULTI i + 9 IndDum i + μ i The study applied co-relational and non-experimental research design. The process of measurement is central to quantitative research because it provides the fundamental connection between empirical observation and mathematical expression of quantitative relationships. 3.2 Data Collection A database was built from a selection of approximately 700 financial-reports that were made public by publicly traded companies between January 1, 2008 and December 31, The selection was drawn from Mergent Online [ to collect a random sample of manufacturing and service companies. Out of approximately 700 financial-reports announced by public companies between January 1, 2008 and December 31, 2010, only 166 financial reports were usable. The cross sectional yearly data were used in this study. Thus, 166 financial reports resulted to 498 total observations. Since random sampling method was used to select companies, the sample is considered as a representative sample. For the purpose of this research, certain industries were omitted due to the type of activity. For example, all the companies from the financial services industry were omitted. In addition some of the firms were not included in the data due to lack of information for the certain time periods. 3.3 Descriptive Statistics Table 2 shows descriptive statistics of the collected variables. All variables were calculated using balance sheet (book) values. The book value was used because the companies did not provide any market value related to the variables that were used in this study. The explanatory variables are all firm specific quantities and there is no way to measure these variables in terms of their 'market value.' Furthermore, when market values are considered in such studies there's always a rather legitimate question of the date for which the 'market values' refer to. This is rather arbitrary. Hence, 'book values' as of the date of the financial reports were used in this study (Gill et al., 2010, p. 5). The explanation on descriptive statistics is as follows: i) Total observations = 166 x 3 = 498 ii) Manufacturing firms = 91 iii) Service firms = 75 iv) Multinational firms = 119 v) Local firms = 47 vi) WCR (the minimum amount of resources that a firm requires to effectively cover the usual costs and expenses necessary to operate the business) = 45% vii) Operating cycle = days viii) Operating cash flows deflated by total assets of firm = 11% ix) Firm s growth (measured by sales growth) = 25% x) Return on assets = 6% xi) Tobin s q = 2.79 xii) Firm leverage = 39% xiii) Firm size (measured by the natural log of total assets) = 2.64 millions (see Table 2) Table 3 provides the Pearson correlation for the variables used in the regression model. The findings of Pearson correlation analysis are as follows: Overall, working capital requirements (dependent variable) is i) positively correlated with operating cycle, return on assets, Tobin's Q, and industry, and ii) negatively correlated with firm size (see Table 3). 34

6 Working capital requirements is i) positively correlated with operating cycle, return on assets, and internationalization of the firm, and ii) negatively correlated with firm size in the Canadian manufacturing industry (see Table 3). Working capital requirements is i) positively correlated with operating cycle and return on assets, and ii) negatively correlated with firm size in the Canadian service industry (see Table 3). 4. REGRESSION ANALYSIS The regression analysis section presents the empirical findings on the relations of operating cycle, operating cash flows, firm s growth, return on assets, Tobin s q, leverage, firm size, internationalization of the firm, and industry dummy with working capital requirements. The Ordinary Least Square (OLS) model with cross section weight of seven sectors (consumer products, services, utilities, health care, information technology and communication, industrials, materials) from manufacturing and services industries was used to perform data analysis. The results are as follows: Overall, positive relationships between i) operating cycle (OC) and working capital requirements (WCR), ii) return on assets (ROA) and WCR, iii) internationalization of the firm and WCR, and iv) industry and WCR were found. Negative relationships between i) firm's growth (growth) and WCR and ii) firm size and WCR were found. No significant relationships between i) operating cash flow (OCF) and WCR, ii) Tobin's q and WCR, and iii) leverage and WCR were found (see Table 4). In the Canadian manufacturing industry, positive relationships between i) OC and WCR, ii) ROA and WCR, iii) Leverage and WCR, and iv) internationalization of the firm and WCR were found. Negative relationships between i) Tobin's q and WCR and ii) firm size and WCR were found. No significant relationships between i) OCF and WCR and ii) growth and WCR were found (see Table 4). In the Canadian service industry, positive relationships between i) OC and WCR and ii) ROA and WCR were found. Negative relationships between i) growth and WCR and ii) firm size and WCR were found. No significant relationships between i) OCF and WCR, ii) Tobin's q and WCR, iii) leverage and WCR, and iv) internationalization of the firm and WCR were found (see Table 4). Also note that: A test for multicollinearity was performed. All the variance inflation factor (VIF) coefficients are less than 2 and tolerance coefficients are greater than % (R 2 = 0.524) of the variance in the degree of WCR can be explained by the degree of industry, firm s growth, ROA, LNSize, MULTI, Tobin's q, OC, OCF, Leverage in Canada % (R 2 = 0.354) of the variance in the degree of WCR can be explained by the degree of MULTI, LNSize, ROA, growth, Tobin's q, OC, leverage, OCF in the Canadian manufacturing industry % (R 2 = 0.457) of the variance in the degree of WCR can be explained by the degree of MULTI, Leverage, ROA, growth, OC, LNSize, OCF, Tobin's q in the Canadian service industry. The analysis of variance (ANOVA) tests are also significant at The Durbin-Watson (D-W) values of (entire sample), (manufacturing industry), and (service industry) indicate less autocorrelations among independent variables of the model (see Table 4). 5. DISCUSSION, CONCLUSION, IMPLICATIONS, AND FUTURE RESEARCH 35

7 The main purpose of this study was to find the factors that influence the working capital requirements in Canada. This was done by collecting data from the Canadian manufacturing and service industries. Findings show that the factors that influence working capital requirements are different in the manufacturing and service industries. The positive relationship between OC and WCR indicates that the higher the days of operating cycle, the more working capital would be required by the firm as operative necessity. This finding is consistent with the results of Nazir and Afza (2008). If Canadian firms want to reduce their investment in working capital to improve the profitability, the operating cycle needs to be optimized. The positive relationship between ROA and WCR indicates that firms with higher profits are less concerned efficient management of working capital. Inefficient management of working capital has a negative impact on the bottom line of the firm. The results are consistent with the results of Nazir and Afza (2008, 2009) and Taleb et al. (2010). The positive relationship between internationalization of the firm and WCR describes that multinational corporations require and maintain higher level of working capital. The higher level of working capital is not in the favor of multinational corporations because it may have a negative impact on the profitability during the economic downturn. Therefore, firms should optimize the working capital requirements. The negative relationship between firm's growth and WCR indicates that growing firms are more sensitive to the accumulation of working capital and are not able to hold higher level of working capital. These results contradict with the findings of Taleb et al. (2010) who found a positive relationship between firm s growth and WCR. This may be because of the different economic environment in which firms operate. The different results may also be because of the different working capital management policies of different firms from different countries. The negative relationship between firm size and WCR describes that larger firms have lower working capital requirements than the smaller firms. The results contradict with the findings of Nazir and Afza (2009) who found a non-significant relationship between firm size and WCR. The positive relationship between leverage and WCR indicate that the higher level of debt requires the higher level of working capital. Therefore, firms should pay attention to accounts payables and accounts receivables. The results contradict with the findings of Nazir and Afza (2008, 2009) and Taleb et al. (2010) who found a negative relationship between leverage and WCR. The results may be different because of the different policies of the lending institutions from different countries. For example, Canadian financial institutions require firms to maintain a certain level of liquidity for the fallback position to make liability payments on a yearly basis. This may not be the case in other countries. Tobin's q is negatively affecting the working capital of the firm, indicating that efficient working capital management has no impact on the stock performance of the Canadian manufacturing companies. The findings of this paper contradict with the findings of Nazir and Afza (2008, 2009) and Taleb et al. (2010) who found a positive relationship between Tobin s q and WCR. This may be because there are other factors such as profitability of the firm, dividend payments, investors perceptions on stock market, etc., that impact on the stock performance of the Canadian firms. 5.1 Conclusion Efficient working capital management is very important to generate the higher rate of return and to maximize the shareholders wealth. When working capital requirements are not properly managed and are allocated more than required, they reduce the benefits of short-term investments. If working capital is too low, the company 36

8 may miss a lot of profitable investment opportunities or suffer short-term liquidity crisis, leading to the degradation of company credit, as it cannot respond efficiently to temporary capital requirements (Nazir and Afza, 2009, p. 35). This study found that operating cycle, leverage, ROA, and Tobin s q are the internal factors that influence working capital requirements significantly. The working capital requirements and management practices differ industry-to-industry and country-to-country. This may be one of the reasons that some of the findings contradict with the notable previous authors (e.g., Nazir and Afza, 2008, 2009; Taleb et al., 2010). Because working capital requirements and the management of working capital differ industry-to-industry and country-to-country, investors should perform careful analysis of the companies before investing in debt and equity securities. 5.2 Limitations This study is limited to the sample of Canadian manufacturing and service industry firms. The findings of this study could only be generalized to manufacturing and service firms similar to those that were included in this research. In addition, the sample size is small. 5.3 Future Research Future research should investigate generalization of the findings beyond the Canadian manufacturing and service sector. Future study may include the economic factors such as real GDP growth, business cycle, etc., together with the variables that were used in this study. REFERENCES Appuhami, B.A. (2008). The impact of firms capital expenditure on working capital management: an empirical study across industries in Thailand. International Management Review, 4(1), Chiou, J.R., Cheng, L., & Wu, H.W. (2006). The determinants of working capital management. Journal of American Academy of Business, 10(1), Deloof, M. (2003). Does working capital management affect profitability of Belgian firms? Journal of Business Finance and Accounting, 30(3/4), Filbeck, G. & Krueger, T. (2005). An analysis of working capital management results across industries. Mid- American Journal of Business, 20(2), Ganesan, V. (2007). An analysis of working capital management efficiency in telecommunication equipment industry. Rivier Academic Journal, 3(2), Gill, A., Biger, N., & Mathur, N. (2010). The relationship between working capital management and profitability: Evidence from United States. Business and Economics Journal, 2010, 1-9. Lamberson, M. (1995). Changes in working capital of small firms in relation to changes in economic activity. Mid- American Journal of Business, 10(2), Nazir, M.S. & Afza, T. (2008). On the factors determining working capital requirements. Proceedings of ASBBS, 15(1), Nazir, M.S. & Afza, T. (2009). Working Capital Requirements and the Determining Factors in Pakistan. IUP Journal of Applied Finance, 15(4), Sathyamoorthi, C.R. & Wally-Dima, L.B. (2008). Working capital management: the case of listed retail domestic companies in Botswana. The Icfaian Journal of Management Research, 7(5), Shin, H.H. & Soenen, L. (1998). Efficiency of working capital management and corporate profitability. Financial Practice and Education, 8(2), Smith, K.V. (1973). State of the art of working capital management. Financial Management, 2, Soenen, L.A. (1993). Cash conversion cycle and corporate profitability. Journal of Cash Management, 13(4), Taleb, G.A., Zoued, A.N. & Shubiri, F.N. (2010). The Determinants of Effective Working Capital Management Policy: A Case Study on Jordan. Interdisciplinary Journal of Contemporary Research in Business, 2(4), Weinraub, H.J. & Visscher, S. (1998). Industry practices relating to aggressive conservative working capital policies. Journal of Financial and Strategic Decisions, 11(2),

9 Tables Table 1: Proxy Variables Definitions and Predicted Relationships Proxy Variables Definitions Predicted sign WCR_TA i Working capital requirements deflated by total assets for firm i +/ OC i Operating cycle in days of firm i +/ OCF_TA i Operating cash flows deflated by total assets of firm i +/ Growth i Sales growth of firm i +/ ROA i Return on assets for firm i +/ Q i Tobin s q of firm i +/ Lev i Leverage as measured by debt to total assets ratio of firm i +/ LNSize i Natural log of total assets as proxy for the size for firm i +/ MULTI i Internationalization of firm i +/ IndDum i Industry dummy for firm i +/ Table 2: Descriptive Statistics of Independent, Dependent, and Control Variables ( ) Descriptive Statistics (N = 498) Min Max _ x σ WCR_TA OC OCF_TA Growth ROA Tobin's Q Lev LNSize N = Number of observations Min = Minimum Max = Maximum _ x = Mean score σ = Standard deviation 38

10 Table 3: Pearson Bivariate Correlation Analysis Entire Sample (N = 498) WCR_TA OC OCF_TA Growth ROA Tobin's Q Lev LNSize MULTI Industry WCR_TA ** ** * ** ** OC ** OCF_TA ** ** Growth ROA * * Tobin's Q ** ** Lev ** ** LNSize MULTI ** Industry 1 Manufacturing Industry (N = 273) WCR_TA OC OCF_TA Growth ROA Tobin's Q Lev LNSize MULTI WCR_TA * * ** ** OC ** ** OCF_TA * ** * Growth * ROA ** ** Tobin's Q ** Lev ** LNSize MULTI 1 Service Industry (N = 225) WCR_TA OC OCF_TA Growth ROA Tobin's Q Lev LNSize MULTI WCR_TA ** * ** OC * OCF_TA ** ** Growth ROA Tobin's Q ** Lev ** LNSize MULTI 1 ** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed) 39

11 Table 4: OLS Regression Estimates on Factors Influencing Working Capital Requirements Entire Sample (N = 498) [R 2 = 0.524; SEE = 0.262; F = 18.98; ANOVA s Test Sig. = 0.000; Durbin-Watson = 1.877] Regression Equation (A): WCR_TA = OC OCF_TA Growth ROA Tobin's q Lev LNSize MULTI Industry Unstandardized Coefficients Standardized Coefficients c Collinearity Statistics B Std. Error Beta t Sig. Tolerance VIF (Constant) OC OCF_TA Growth ROA Tobin's q Lev LNSize MULTI Industry Manufacturing Industry (N = 273) [R 2 = 0.354; SEE = 0.177; F = 5.545; ANOVA s Test Sig. = 0.000; Durbin-Watson= 2.020] Regression Equation (B): WCR_TA = OC OCF_TA Growth ROA Tobin's q Lev LNSize MULTI Unstandardized Coefficients Standardized Coefficients c Collinearity Statistics B Std. Error Beta t Sig. Tolerance VIF (Constant) OC OCF_TA Growth ROA Tobin's q Lev LNSize MULTI Service Industry (N = 225) [R 2 = 0.457; SEE = 0.326; F = 6.954; ANOVA s Test Sig. = 0.000; Durbin-Watson = 1.855] Regression Equation (C): WCR_TA = OC OCF_TA Growth ROA Tobin's q Lev LNSize MULTI Unstandardized Coefficients Standardized Coefficients c Collinearity Statistics B Std. Error Beta t Sig. Tolerance VIF (Constant) OC OCF_TA Growth ROA Tobin's q Lev LNSize MULTI a Dependent Variable: WCR_TA b Independent Variables: OC, OCF_TA, Growth, ROA, Tobin's q, Lev, LNSize, MULTI, and Industry c Linear Regression through the Origin SEE = Standard Error of the Estimate a, b, c 40

Working Capital Requirements and the Determining Factors in Pakistan Mian Sajid Nazir* and Talat Afza** Literature on corporate finance has traditionally focused on the study of long-term financial decisions.

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