The Determinant factors of working capital management in the Brazilian Market

WILSON TOSHIRO NAKAMURA Professor at the Universidade Presbiteriana Mackenzie - So Paulo- SP, Brazil and NATHALIE VICENTE NAKAMURA PALOMBINI Master Student at the Universidade Presbiteriana Mackenzie - So Paulo- SP, Brazil

Traditionally, much has been written in corporate finance literature on long term investment and financing decisions. However, investments in short term assets and less than one year resources represents a relevant part on firms balance sheet (Garcia-Teruael and MartinezSolano, 2007; Assaf Neto and Silva, 2002). On top of that, financial managers invest significant amount of time and effort on working capital management, seeking ways to balance current assets and liabilities. In this article, we provide insights into the determinant factors of working capital management taking the Brazilian market perspective by exploring companys internal factors inspired in some of the most relevant corporate finance theories such as Pecking Order Theory and Agency Theory. Using a sample of 2,976 firm observations, covering the period 2001-2008, results presented evidences that debt level, size and growth rate can affect companys working capital management. The negative relation with debt level is consistent with the Pecking Order Theory, suggesting that leveraged companies aim to work with low level of current assets, to avoid issuing new debt and equity securities. The variable free cash flow also showed a negative and significant relation with working capital management, which can suggest that companies with higher profitability present lower volume of working capital. [Keywords: Working capital, determinants, panel data, Brazil]

INTRODUCTION Based on an overview on corporate finance literature, researchers can verify that there are no robust and widely accepted theories about working capital management. So far, few studies have been performed to explore this theme compared to long term corporate finance, which includes long term investment and financing decisions. Additionally, the majority of the empirical studies that explore working capital management, aim to understand its relationship with the companys profitability and not a comprehension of its key drivers. It is a day-to-day challenge for companys managers to find balance between short term sources and uses. Decisions related to working capital management directly impact on liquidity and profitability (Appuhami, 2008; Shin and Soenen, 1998). Brealey, Myers and Allen (2008) say that there is still little knowledge about the ideal liquidity level, represented by current assets, to maximize companys value. On one hand, researches should acknowledge the earnings from liquidity, realizing that the cost of the money in cash has not a

negative net present value. On the other hand, they know that as the marginal value of liquidity decreases, the cash volume increases. Therefore, companies still dont know the ideal liquidity level and consequently working capital level, which maximize companys value. Many internal and external factors can influence the companys decision regarding the optimal level of current assets and current liability. Among these factors, there is the influence of financing corporate decisions. One of the most relevant theories about capital structure is the Pecking Order Theory from Myers and Majluf (1984). According to this theory, companies will tend to raise capital inside, consuming financial slack, before increasing financial leverage by borrowing money from outside or issuing new stocks. The financial slack can be defined by liquidity excess (Stowe in Kim and Srinivasan, 1991), found in form of current assets, securities or current assets options, all above the companys needs to meet current operations (Ang in Kim and Srinivasan, 1991) and, also, in form of riskless borrowing capacity beyond that need to meet debt serving requirements (Myers and Majluf, 1984). For Brealey, Myers and Allen (2008 p. 433) financial lack means cash, marketable securities, readily saleable real assets and ready access to the debt markets or to bank financing. For McMahon (2006), financial slack is a joint condition of high liquidity and unused debt capacity. In a situation to raise capital to invest, managers could easily get rid of liquid current assets, adopting an aggressive working capital policy, such as pushing for lower level of inventory and decreasing customers credit terms. Another factor that can influence the decision of a companys working capital level may be related to the conflict of interests between managers and shareholders, explored in the Agency Theory (Jensen and Meckling, 1976). In companies with low level of monitoring and few discipline instruments on management decisions, managers may decide not invest in projects with positive net present value or even invest in projects with negative net present value. Another agency problem source is the presence of free cash flow in excess, defined by Jensen (1986) as the cash flow in excess beyond the required to finance positive net present value projects. According to the author, in a context of substantial free cash flow, it is likely that managers invest in project with negative net present value, increasing the agency problem between managers and shareholders. Some of these projects and activities may be selfgratifying to the managers and may bring them some pecuniary benefits or other personal rewards (Chung, Michael and Kim, 2005, p. 55). In other cases, managers could be careless about investment decisions, adopting a more flexible working capital policy, with high level of inventories or generous credit policy beyond the operational needs. The discussion about the determinants of working capital management is not a simple theme. Most studies about working capital management aimed to understand its relation with companys profitability, assessing the impact of working capital policies on value creation to shareholder. Despite its importance for the organizations, there are few empirical researches. The purpose of this study is to explore the factors that influence the companys working capital management to contribute with the corporate finance knowledge of short term decisions and companys better decisions. The study focused on Brazilian companies listed in So Paulo Stock Exchange, during the period of 2001 to 2008.

LITERATURE REVIEW AND HYPHOTESES Working capital management is a relevant subject for financial managers who invest a significant amount of time and effort seeking an ideal balance level between risk and return, profitability and liquidity, in order to create value for the company (Lamberson, 1995; Appuhami, 2008; Martin and Morgan in Kim and Srinivasan, 1991). The decision process about its policy, the performance monitoring of each component, as well the actions to minimize targets deviations is a frequent, repetitive and timing consuming work (Lamberson, 1995, Appuhami, 2008). The lack of understanding about its impact on profitability, the lack of clarity about its determinants, the lack of management ability to plan and control its components, may lead to insolvency and bankruptcy. According to Smith (1973), a large number of business that failures in recent years may come from the inability of financial managers to plan and control current assets and current liabilities of their respective firms. A recent study with 14,181 small companies in Brazil also indicated the same conclusion (Sebrae, 2005). Despite its importance for the business success (Filbeck and Krueger, 2005), there are few evidences and consensus about the determinant factors of working capital management, taking into consideration the combined effect of its main components: inventory, account receivable and account payable. Nunn (1981) approached the working capital requirements splitting into seasonal and permanent needs (Gitman, 1997). The researcher explored the permanent portion of working capital that does not fluctuate with short-run changes in the business activity of the firm. Using a multiple regression model, the study used a U.S. database taking product-line businesses in many different industries, from 1971 to 1978. The study found evidences of 19 possible determinants of working capital management related to the production process, sales, accounting method, competitive position and industry factors. Hawawini, Viallet, and Vora (1986) explored data of 1,181 American firms from 36 industries over a period of 19 years (1960-1979), to investigate if the working capital policies were significantly similar within the same industrial sector and if they differ significantly among the industries. Authors concluded that there was indeed a significant and persistent industry effect on a firms investment and this effect was sustained over the time. The results were also consistent to the notion that there are industry benchmarks within industry groups to which firms adhere when setting their working capital investment policies. Filbeck and Krueger (2005) provided insights to support the importance of an efficient working capital management, assessing nearly 1,000 firms and using data from a traditional working capital management survey published by CFO Magazine in United States, for the period 1996-2000. According to the study, there were both significant differences between industries in working capital measures across time and also significant changes in these measures within industries over the time. For the researchers, these changes could be related to the macroeconomic factors such as interest rate, innovation rate and competition. Using data on a panel of U.S. corporations from 1990 through 2004, Kieschnick, Laplante and Moussawi (2006) found evidences that industry practices, firm size, future firm sales growth, the proportion of outside directors on a board, executive compensation (current portion), and CEO share ownership significantly influence the efficiency of a companys working capital management. This study suggested that managers respond positively to incentives and monitoring in managing working capital.

Using economic indicators as independent variables and financial rations as dependent variables, Lamberson (1995) explored the relationship between changes in working capital position and changes in the level of economic activity, taking as sample 50 small U.S. firms for the period 1980-1991. The study found evidences that liquidity slightly increased during economic expansion with no noticeable change in liquidity during economic slowdowns. Sathyamoorthi and Wally-Dima (2008) analyzed retail domestic companies listed in Botswana Stock Exchange, from 2004 to 2006, and found evidences that companies adopted a conservative approach in working capital management, which suggests that it is not static overtime, but varies with the change of macroeconomic factors. In times of high business volatility, companies tend to adopt a conservative approach and tend to adopt an aggressive approach in times of low volatility. Chiou, Cheng and Wu (2006) explored the factors that impact working capital management, using 19,180 firm/quarter data extracted from Taiwan Stock Exchange, for the period 19962004. The study indicated that the debt ratio and operating cash flow affected the companys working capital. On the other hand, the results did not provide evidences for the influence of the business cycle, industry effect, growth of the company, performance of the company and firm size on working capital management. Nazir and Afza (2008) explored the factors that determine the requirements of working capital management, using 204 manufacturing firms from 16 industrial groups listed at Karachi Stock Exchange, Pakistan, for a period of 1998-2006. Researchers found evidences that operating cycle, leverage, ROA and TobinsQ significantly influenced the working capital requirement. Appuhami (2008) investigated the impact of firms capital expenditure on working capital management, using data collected from listed companies in the Thailand Stock Exchange, from 2000 to 2005. The research found a negative relationship with capital expenditure, indicating that companies tend to manage working capital efficiently when find opportunities to growth by investing in fixed assets. Also, the study found positive and significant evidences between working capital requirement and operating and finance expenditure, suggesting that companies tend to increase working capital level as debt and interest expenditures increase. Also, the study suggested that companies tend to manage working capital efficiently, since it increases operating cash flows. A summary of independent variables of each research, including hypotheses and results, is shown in Table 1.

Table 1 Summary of independent variables, hypotheses and results of the literature review (continue in the following page)Dependent variable proxies-Working Capital Management Permanent working capital/sales Hypotheses: coefficient signal: + + + + + There is no significant differences + Logarithm of cash Conversion Cycle Industry practices Firms size Proportion of fixed assets Firms sales growth Market power (Herfindahl-Hirschman index) Board characteristics measured by firms number directors + + + Results: coefficient signal +Significant -Significant -Significant +Significant +Significant -Significant +Significant +Significant There is no significant differences +Significant +Significant -insignificant +Significant -insignificant -insignificant

Researchers Nunn (1981)

Independent variables Production-related variables: % small batch production, % order backlog; capital intensity; % order backlog; capital intensity; relative product-line breadth Production-related variables: % continuous process production; % capacity utilization; ; made-to-order products. Sales-related variables: media advertising/ Sales; % Sales to components Sales-related variables: Sales force expenses/Sales; % Gross margin channels. Accounting method Competitive position: relative market share; relative image Competitive position: market share instability; relative price Industry factors: industry export; industry imports, industry concentration working capital requirement-to-sales ratios within industries

Hawawini, Viallet and Vora(1986) Kieschnick, Laplante and Moussawi (2006)

Working capital requirement-to-sales ratio

Table 1 Summary of independent variables, hypotheses and results of the literature review (continue in the following page).Dependent variable proxies-Working Capital Management Hypotheses: coefficient signal: Results: coefficient signal

Researchers Kieschnick, Laplante and Moussawi (2006)

Independent variables

Logarithm of cash Conversion Cycle Board characteristics measured by proportion of outside members CEO compensation measured by total current compensation excluded stock options CEO compensation measured by CEOs total unexercised stock options. Proportion of stock held by the CEO Governance index (provisions) Economic activity

-Significant

+ + There are significant differences There are significant differences +

-Significant -insignificant +Significant -insignificant + insignificant +significant -significant - insignificant There are significant differences There are significant differences -significant -significant

Lamberson (1995)

Current ratio Quick ratio Inventory/ total asset Current asset/total asset Cash conversion consistency, days of working capital, days of sales outstanding, inventory turnover, days of payables outstanding, CFOs overall ranking. Working capital requirement/ total assets

Filbeck and Krueger (2005)

Industry significance: working capital measures between industries across the time.

Period consistency: Working capital measures within industries through time Business indicator measured by business cycle in recession Business indicator measured by business cycle

Chiou, Cheng and Wu. (2006)

-

Table 1 Summary of independent variables, hypotheses and results of the literature review.Dependent variable proxies-Working Capital Management Working capital requirement/ total assets Hypotheses: coefficient signal: There are significant differences + + + Operating cycle Operating cash flows Level of economic activity Sales growth of the firm Return on assets Tobins Q Financial leverage Firm size Industry Dummy Capital expenditure Operating expenditure Finance expenditure Operating cash flow (control) Sales growth of the firm (control) Firm performance (control) Financial leverage (control) + + + Results: coefficient signal No evidences found -significant -significant -insignificant +significant +significant +significant +significant +insignificant +insignificant +insignificant +significant +significant -significant -insignificant +significant - significant + significant + significant - significant +insignificant +insignificant +insignificant

Researchers Chiou, Cheng and Wu. (2006)

Independent variables Industry effect Debt ratio Operating cash flow Growth opportunity Firm age Firm performance Firm size

Working capital Nazir and requirement/ total Afza (2008) assets

Appuhami (2008)

Working capital requirements

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Pecking Order Theory The Pecking Order Theory takes into consideration the information asymmetry which indicates that managers know more about the firms value than potential investors (Myers and Majluf, 1984). The information asymmetry affects the choice between internal and external financing. Based on this concept, the Pecking Order Theory suggests that firms tend to rely on internal source of funds to be financed, and prefer issuing debt to equity if external financing is required (Myers and Majluf, 1984). According to Nakamura et al. (2007 p.76), that order is based on the consideration that resources generated internally do not have transaction costs and on the fact that issuing new bonds tend to sign a positive information about the company, while issuing new stocks tend, on the contrary, to sign a negative information. The information asymmetry decreases the price of new bonds to be issued and, consequently, increases the transaction costs in the capital markets derived from lack of cash (Myers and Majluf, 1984). From this point of view, companies do not pursue a specific objective for the debt level and they use external funds only when internal funds are not enough (Graham and Harvey, 2001). External source of funds are less desirable because the information asymmetry between managers and investors implies that external source of funds are underpriced in relation to the asymmetry level (Myers and Majluf, 1984). This theory, according to Chen (2004), explain the companys choice to keep an amount of reserve in cash or other forms of financial slacks to avoid the problem of lack of resources and the need of external sources. From this point of view, cash is similar to negative debt, getting external resources when there is lack of cash and paying debt when there is excess of cash. Thus, the company chooses a more passive cash management policy, waiting to liquidate an existent debt in any time with no cost (Koshio, 2005). Financial slack is a result of large holdings cash or marketable securities, or the ability to issue default-risk free debt, beyond what is needed to meet current operating and debt servicing needs (Myers and Majluf, 1984; Brealey, Myers and Allen, 2008; McMahon, 2006). To have a fast access to debt market, companies chooses a conservative financing, in a way that potential investors see them as a safe investment. According to Smith and Kim (1994) and McMahon (2006), financial slack, in adequate levels, allow the company to pursue positive net present value investment opportunities without issuing risky securities. The conventional rationale for holding financial slack - cash, liquid assets, or unused borrowing power is that the companies do not want to have to issue stock on short notice in order to pursue a valuable investment opportunity (Myers and Majluf, 1984). Brealey, Myers and Allen (2008) suggested that the Pecking Order Theory explains the reason why more profitable companies usually ask less for borrowing money not because they dont have lower levels of debt targets but because they dont need external source of funds. On the other hand, less profitable companies issue bonds because they dont have enough internal funds to finance investments decisions. In this matter, those companies also prefer issuing debt before issuing new stocks. Following this theory, not only managers of less profitable companies but also managers of more profitable companies would choose a more aggressive working capital policy, pressuring for lower level of current assets and higher level of financing via suppliers, in a way to source internally the needed funds to finance their companies and to avoid issuing debt and equity. The purpose of the first research hypothesis is to understand if companies with a higher debt level have also lower working capital level,

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reflected in lower level of inventory, lower credit terms and higher payment terms due to a management decision decide to adopt an aggressive working capital management to avoid issuing new debt and equity. Hypothesis 1: There is a negative relationship between the firms debt level and its working capital level.

Agency Theory According to the Agency Theory (Jensen and Meckling, 1976), a firm can be seen as a nexus of a set of contracting relationships (implicit as well as explicit) among individuals, by means of which shareholders principals delegate everyday decisions of business management to managers agents who should use their specific knowledge and companys resources to maximize principal agents return. Through these contracts or internal rules of the game, shareholders specify the rights of each agent in the organization, performance criteria on which agents are evaluated, and the payoff functions they face (Fama and Jensen, 1983, p. 2). Due to a non-rational and opportunistic behavior of agents (Jensen, 1994), the interests and decisions of managers are not always aligned to the shareholders interests, resulting in agency costs or agency problems. For Shleider and Vishny (1997), the essence of the agency problem is the separation of ownership and control. In large and complex organizations, these problems can be clearly observed, once the valuable and specific knowledge relevant to decision control is diffused among many internal agents across the company (Fama and Jensen, 1983). In this case, owners are not able to participate in the ratification and monitoring of each decision due to the high costs associated. Jensen and Meckling (1976) defined agency cost as the sum of the expenses in monitoring by the principal, the bonding expenditures by the agent and the inevitable residual loss derived from the separation of ownership and control. To minimize divergences of interests, the principal can establish incentives, monitoring mechanisms and instruments to make sure agents dont take actions to jeopardize their interests or to be compensated (bonding costs) in the case of any agency problem. Fama and Jensen (1983) suggested that the agency problems could be minimized through the separation of the ratification and monitoring of decisions from the initiation and implementation of decisions. Thus, organizations should count on decision control systems as formal decision hierarchy, mutual monitoring systems and active board of directors. Weir and Laing (2003) differentiated three mechanisms designed to protect shareholder interests: incentive, monitoring and disciplinary mechanisms. Incentive mechanisms include executive director shareholdings or board compensation systems (Jensen e Meckling, 1976), while monitoring mechanisms include, for example, the proportion of outside directors on board (Fama, 1980; Fama and Jensen, 1983) and disciplinary mechanisms include the market for corporate control (Jensen, 1986). Monitoring devices were designed by shareholders to aligned agents actions to their interests (Fama, 1980). According to Tirole (2005), monitoring systems include a variety of instruments such as board composition, auditors, large shareholders, large creditors, investment banks, etc. The decision of how to invest internal funds is central in the shareholders and managers conflicting interests (Jensen, 1986). For Easterbrook (1984), when managers have a substantial part of their human capital or wealth allocated in companys share, they tend to take decisions to enhance the probability of companys survival. These decisions can be

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reflected in a conservative management of working capital, reducing the risk involved in the business operation, such as to keep high level of inventories beyond the process cycle needs, to offer credit terms above the product turnover, to accept low payment terms not aligned to the market practices, etc. In that case, these investment decisions would be translated in excess of working capital. Therefore, the second research hypothesis is to investigate if companies that present monitoring mechanisms of managers actions have lower level of working capital requirement. Hypothesis 2: There is a negative relationship between management monitoring mechanisms and working capital level. According to Jensen (1986), managers with substantial free cash flow have incentives to engage the company in unnecessary expenses. He defined free cash flow as the excess of cash flow beyond the required to fund all projects that have positive net present values when discounted at the relevant cost of capital. In an organization with low level of monitoring or discipline on management actions, a high level of free cash flow may incentive managers, guided by their own interests, to undertake negative present value capital projects rather than return cash to equity holders (McMahon, 2006). Jensen (1986) suggests that manager tend to invest the free cash flow in new projects because they are motivated to cause their firms to grow beyond the optimal size. Companys growth increases managers power by increasing the resources under their control, which is also associated with increases in managers compensation, commonly linked to sales. For McMahon (2006, p. 15), retaining free cash flow is essentially a negative net present value investment in liquidity. Therefore, companies with high level of free cash flow may have higher agency costs, derived from expenditures with organizational inefficiencies or investments with negative returns. The third research hypothesis aims to explore if companies with higher level of free cash flow also have higher level of working capital, represented by the excess of the difference in current assets and liabilities as a result of investment in inefficient projects with negative or null net present value. Hypothesis 3: There is a positive relationship between the level of free cash flow and the level of working capital.

METHODOLOGY Data and sample collection To address the research hypotheses, the study used as the population frame listed companies in So Paulo Stock Exchange. Secondary data was collected from Economtica Pro and DIVEXT B&MF BOVESPA, in quarterly basis. Initially, data was collected of 357 public companies from the period of 1994 to 2008, excluding firms in financial service industries. All financial data was adjusted by the inflation index IPCA/ IBGE. After eliminating missing data and outliers, the final sample size was concentrated in 93 companies during 32 quarters of observations, from the period 2001-2008 (last quarter of 2000 was only used to calculate firm growth). Dependent variable: Working Capital Management

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To measure working capital management, the study adopted the concept of the cash conversion cycle (CCC), also known as cash cycle, which was used in many researches (Deloof, 2003; Lazaridis and Tryfonidis, 2006; Brigham and Ehrhardt, 2002; Ross, Westerfield and Jaffe, 2007). The cash conversion cycle measures the period of time in days between the payment of raw materials and the receivables of finished product sales [number of days of accounts receivable + number of days of inventory number of days of accounts payable]. The cash conversion cycle combines the working capital components more related to the operational processes, reflecting purchasing, production and sales processes. (Hawawini, Viallet and Vora, 1986). Additionally, the research explored other proxies of working capital management, to explore separately the working capital components: days of accounts receivable (D_AR), days of inventory (D_IN) and days of accounts payable (D_AP). The study chose to calculate them based on Shin and Soenen definition (1998). Number of days of accounts receivable was calculated as [account receivable x 365]/sales. Number of days inventories was calculated as [inventories x 365]/ Sales. Number of days accounts payable was calculated as [accounts payable x 365]/ sales. The research also included the working capital requirement (WCR), as a fifth proxy, calculated by [accounts receivable + inventory]/ [total assets financial assets]. Financial assets were excluded in order to remove the effect of shares in other firms, not related to the firms operational activities (Deloof, 2003). Independent variable: Debt level Nazir and Afza (2008) and Chiou, Cheng and Wu (2006) measured debt level by the debt ratio leverage calculated by the total liabilities divided by total assets. Apphumani (2008) measured leverage as total long-term debt capital divided by equity. In this study, debt level (DEBT) was measured as long term debt divided by total assets. Independent variable: Management monitoring mechanisms The concept of corporate governance resides on the basis of the agency theory, which relies on the assumption that managers not always act in accordance to the shareholders interests (Becht, Bolton and Roell, 2003 and Tirole, 2005). In Tiroles point of view (2005) the role of corporate governance is to ensure investors receive their investment returns. A corporate governance problem can be described as an agency problem and come up always when a shareholder chooses to decide something different from what the manager in charge of the company has decided (Becht, Bolton and Roell, 2003). Becht, Bolton and Roell (2003) proposed five mechanisms to minimize the agency conflicts: (1) board election to represent shareholders interests; (2) hostile takeovers or dispute for vote representation by a large shareholder; (3) active and frequent monitoring by a large shareholder or a intermediate financial part (banks, holding companies or pension funds); (4) alignment of managers interests by compensation contracts; and, (5) CEOs clear fiduciary duties to avoid corporate decisions against shareholders interests or to compensate them for damaging actions. This study chose three management monitoring mechanisms to be explored as determinants of working capital management: board composition, ownership concentration in large shareholders and management compensation. The presence of outside directors decreases the probabilities of collusive arrangements and expropriation of shareholder wealth (Fama, 1980). The board composition was measured by the participation of outside directors (OUTDIR), calculated by number of outside directors in the board divided by total directors.

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According to Shleifer and Vishny (1997), when control rights are concentrated in the hands of a small number of large investors with significant cash flow rights, decisions are conducted in an easier way and agency costs can be reduced. Tirole (2005) also acknowledge that the most common monitoring form is done by a family or a group of shareholders with the majority of votes or control block. Large investors address the agency problem because they have general interests in profit maximization and enough control over the firms assets to have their interests respected (Shleifer and Vishny, 1997). In this study, the management monitoring via ownership concentration in large investors was measured by a dummy variable (CONC) that assumed the presence of ownership concentration when one investor have more than 20% participation in the companys shares, in accordance to the studies of Pedersen and Thomsen (1997) and Siqueira (1998). To minimize agency conflicts, Jensen and Meckling (1995) suggested a reward and punishment system related to the manager individual performance. Agency theory suggests that a compensation policy can be designed to give managers incentives to select and implement actions that increase shareholder wealth (Jensen and Murphy, 1990). An effective compensation policy ties the CEOs welfare to shareholders interests by aligning the private and social costs and benefits of alternative actions and providing incentives for CEOs to take appropriate actions. The management monitoring via management compensation was measured by a dummy variable (COMP) which indicates the presence of annual compensation linked to companys profit. Independent variable: Free cash flow To measure free cash flow, the study used a measurement applied for Lehn and Poulsen (1989) which was also used by Rahman and Mohd-Saleh (2008). The calculation is shown in equation 1 below: (1) FCL =(INC TAX INTEXP PSDIV CSDIV)/TA where: FCL = free cash flow; INC = operating income before depreciation; TAX = total taxes; INTEXP = interest expenses; PSDIV = preferred stock dividends; CSDIV = common stock dividends; TA = total assets at the beginning of the fiscal year. This research measured free cash flow using the logarithm of described equation.

Control variables Larger companies may require larger investments in working capital because of their larger volume of revenues or they can use their market power to force relationships with suppliers and get reduction in payments terms (Kieschnick, Laplante and Moussawi, 2006). Firm size (SIZE) was calculated by the logarithm of firms sales (Deloof, 2003).

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Sales growth may influence the working capital management because managers can decide to prepare the company to meet a different demand level, such as building up inventories in anticipation of future sales growth (Nunn, 1981; Kieschnick, Laplante and Moussawi, 2006). Sales growth variable (GROWTH) was measured by [this years sales - previous years sales]/previous years sales (Deloof, 2003; Nazir e Afza, 2008; Appuhami, 2008). Prior researches (Nunn, 1981; Hawawini, Viallet and Vora, 1986; Kieschnick, Laplante and Moussawi, 2006; Nazir and Afza, 2008) suggested that working capital practices may differ among industries. Consequently, it is important to control for the influence of industry practices in a study about determinants of working capital management practices. This study used dummies of the three main industrial sectors: industry (IND), commerce (COM) and services and other industries (OTH). Table 2 and 3 show a summary of hypotheses, proxies of dependent variables, independent variables, control variables and expected relationships.

14Research problem Determinant factors of working capital management

Table 2 Summary of variables, proxies and expected signalsHypotheses H2 Dependent variable Working capital management

Proxies of dependent variable CCC: Cash Conversion Cycle WCR: Working Capital Requirement D_AR: Days of Accounts Receivable D_IN: Days of Inventory D_AP: Days of Accounts Payable CCC: Cash Conversion Cycle WCR: Working Capital Requirement D_AR: Days of Accounts Receivable D_IN: Days of Inventory D_AP: Days of Accounts Payable CCC: Cash Conversion Cycle WCR: Working Capital Requirement D_AR: Days of Accounts Receivable D_IN: Days of Inventory D_AP: Days of Accounts Payable CCC: Cash Conversion Cycle WCR: Working Capital Requirement D_AR: Days of Accounts Receivable D_IN: Days of Inventory D_AP: Days of Accounts Payable CCC: Cash Conversion Cycle WCR: Working Capital Requirement D_AR: Days of Accounts Receivable D_IN: Days of Inventory D_AP: Days of Accounts Payable

Independent variable Debt level

Proxies of independent variable DEBT: Total debt level at book value

Formulas = [total liabilities]/

total assets

H3

Management monitoring mechanisms

OUTDIR: Participation of outside directors in the board CONC: Presence of ownership concentration

= number of outside directors / number of total directors in the board = Dummy of presence of ownership concentration above 20% in one investor = Dummy of annual management compensation linked to profit = Log [Free Cash Flow/ total assets]

COMP: presence of annual compensation linked to profit

H4

Free Cash Flow

FCL: Free cash flow

Expected signal + + + + + + + + -

Source: authors

Table 3 Summary of control variablesControl variables SIZE: firm size GROWTH: Sales growth IND, COM, OTH Source: authors Formulas = Log [total sales] = [this years sales - previous years sales]/previous years sales r = Dummy of industrial sectors

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Model specification The econometric technique used to test the hypotheses was data panel models, which consists of a time series for each cross-section member in the data set (Wooldridge, 2005). According to Wooldridge (2005), the key feature of panel data that distinguishes them from a pooled cross section is the fact that the same cross-sectional units are followed over a given time period. Compared to cross-sections and time-series data, panel data allows researchers to identify patterns and questions, with no need to assume restrictive assumptions, explaining not only why some variables behave in a different way, but also why a specific variable behave differently across the time (Verbek, 2000). For Baltagi (2008), the use of panel data sets allows researchers to get more reliable estimates and to be able to identify and estimate effects that are simply not detectable in pure cross-sections and time-series data, with no need to assume restrictive assumptions. Also, panel data increases the ability to control for individual heterogeneity and to study complex issues of dynamic behavior. For Greene (2002), the most important advantage of a panel data set over a cross section is that it allows the researcher to get flexibility in modeling differences in behavior across individuals. The following panel data models were tested: static panel data of fixed effects, static panel data model of random effects and dynamic panel data model. Additionally, the study tested the pooled ordinary least squares (OLS) and feasible generalized least squares (FGLS). The following equations, in the form of static panel data of fixed effect, illustrate the models used in this research. 2 !%

" #

$

$

#

&

' ! " #

3

_*$ $

%

#

&

' ! " #

4

,$ $

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6 " Where: i = 1,...,N, refers to the company t = 1,..., T, refers to time CCC = cash conversion cycle D_AR = days of accounts receivable D_IN = days of inventory D_AP = days of accounts payable WCR = working capital requirement DEBT = debt level OUTDIR = outside directors participation in board composition%

CONC = dummy of presence of ownership concentration COMP =dummy of presence of annual compensation linked to profit FCF = free cash flow

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SIZE = firm size GROWTH = firm growth IND = dummy of industry COM = dummy of commerce OTH = dummy of other industry sectors = regression parameter = residual error

RESULTS After calculating the multiple linear regressions of ordinary least squares models, tests to observe traces of multicollinearity and serial correlation were performed. In order to observe signs of multicollinearity, the variance inflation factor (VIF) was calculated, indicating absence of multicollinearity. Also, the Pearson correlation coefficient matrix was calculated. The results can be observed in Table 4 and show that all proxies of independent variables and relationships present low correlation coefficients, indicating absence of multicollinearity problems. Table 4 Correlation matrixDEBT FCF CONC OUTDIR COMP SIZE GROWTH

DEBT FCF CONC OUTDIR COMP SIZE GROWTH

1,000 0,036 -0,098 0,035 -0,190 0,079 0,001

1,000 0,060 0,031 -0,017 0,146 0,089

1,000 0,044 -0,005 0,037 0,010

1,000 -0,014 0,109 0,012

1,000 -0,086 0,004

1,000 0,058

1,000

The Whites Test rejected the null hypothesis for homocedasticity. Therefore, the multiple linear regression of feasible generalized least squares (FGLS) was applied to correct the heterocedasticity problem. In the sequence, the multiple linear regressions of dynamic panel data and static panel data with fixed and random effects were calculated. In the total, 15 regression equations where included in the results of relationships between working capital managements proxies, independent variables proxies and control variables. To analyze results, regression equations were compared in relation to their explaining power, based on three tests results. The first test was applied to choose between ordinary least squares model and panel data of fixed effect model. All models presented results that rejected the hypothesis of ordinary least squares. The second test, the Lagrange multiplier test of Breusch-Pagan, was applied to test for the presence of an unobserved effect (Wooldridge, 2002). All results rejected the hypothesis that the random effect model has explanatory power. The third test, Haussmann test, which compare the fixed and random effects estimators,

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rejected the hypothesis of random effect. As a conclusion, results indicated that the fixed effect model had more explanatory power over the determinant factors of working capital compared to others, suggesting that the intercepts vary across the companies, but not over the time. Table 5 presents a summary of the fixed effect model results. Table 5 Multiple linear regression in panel data for generalized least squares with fixed effects.Dependent variables proxies CCC WCR D_AR Independent variables and proxies Debt (DEBT) -53,928 -0,221 49,950 (-2,304)** (-4,911)*** (1,698)* Free cash flow (FCF) -4,390 -0,004 -2,798 (-1,754)* (-1,490) (-1,282) Management monitoring mechanisms (CONC) (OUTDIR) (COMP) Control variables Firm size (SIZE) Firm growth (GROWTH) Constant -24,647 (-0,9635) 5,520 (1,007) -9,810 (-1,526) -39,481 (-1,565) -19,046 (-2,769)*** 308,384 (2,606)*** 0,020 (1,263) 0,024 (2,602)*** -0,002 (-0,1544) 0,062 (1,546) -0,0004 (-0,03192) -0,084 (-0,4058) -14,377 (-0,840) 3,972 (0,8802) 0,156 (0,0454) -55,933 (-2,591)*** -27,030 (-3,945)*** 373,568 (3,536)*** D_IN -19,599 (-1,958)* -2,568 (-3,660)*** D_AP 84,279 (3,982)*** -0,975 (-0,8913)

-24,962 (-1,069) -1,772 (-0,4858) -7,390 (-1,374) -28,468 (-1,670)* -11,155 (-2,787)*** 224,314 (2,973)***

-14,692 (-1,015) -3,320 (-0,8617) 2,577 (0,5509) -44,920 (-2,594)*** -19,139 (-3,005)*** 289,498 (3,470)***

Number of observations 1409 1409 1409 1409 1409 Adjusted R2 0,74 0,07 0,73 0,76 0,64 T-Test in parentheses: *** Significant at the 1% level, ** Significant at the 5% level, * Significant at the 10% level.

Debt level The independent variable debt level (DEBT) shows a significant negative relationship to cash conversion cycle (CCC) and working capital requirement (WCR). This result is consistent with the Pecking Order Theory reflected in the first research hypothesis. It suggests that companies with high debt leverage decide for a more efficient management of working capital to avoid issuing new bonds and stocks. These results are consistent with the researches of Chiou, Cheng and Wu (2006) and Nazir and Afza (2008). This interpretation can be reinforced by the analysis of the debt effects over days of inventory (D_IN) and days of accounts payables (D_AP). We can observe a negative relationship with

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days of inventory indicating that with a rising in debt level, companies are supposed to work with low inventory level. The significant and positive relationship with days of accounts payable may indicate that more leveraged companies search for negotiations to expand payment terms with suppliers. The result for the variable days of accounts receivable was significant and positive suggesting that companies with higher debt level, have higher credit terms. Management monitoring mechanisms The second research hypothesis aimed to explore the monitoring mechanisms over managers decisions as determinant factors of working capital management. The variable ownership concentration in large investors (CONC) was negatively associated with the majority of working capital management proxies. The consistence of sign may suggest that the presence of large shareholders can inhibit excess investments in accounts receivable and inventory. However, the study was unable to find statistically significant relationships. Participation of outside directors in board composition (OUTDIR) displayed a positive and significant relationship to working capital requirement (WCR). This outcome is contrary to the expectations which suggested that a board composition with larger participation of outside directors would minimize agency costs (Fama, 1980; Fama and Jensen, 1983), as observed in the results of Kieschnick, Laplante and Moussawi (2006). The relationships between annual compensation linked to profit (COMP) and the majority of working capital managements proxies presented negative sign, supporting the compensation policy importance to the agency problem control (Jensen and Meckling, 1976). However, none of the coefficients were statistically significant. Free cash flow The third research hypothesis aimed to investigate if companies with larger free cash flow also present higher level of working capital, expressed in higher inventories and more generous credit policy. It was observed a negative and statistically significant relationship between free cash flow (FCF) and the variables cash conversion cycle (CCC) and days of inventory (D_IN). The same sign was observed in the relationship with days of account receivable (D_AR) and working capital requirement (WCR), but with no statically significance. Those evidences are contrary to expectations. A possible interpretation is related to the influence of profitability, as a variable, in the composition of free cash flow formula. Profitability may be a determinant factor of working capital management to be tested in future empirical studies. Firm size Firm size (SIZE) is strongly and negatively related to days of inventory (D_IN). This result suggests that larger firms dont need to build larger inventories in the proportion to the sales increase or that firms can coordinate in a more efficient way the supply chain compared to small firms. Days of accounts receivable (D_AR) is also negatively associated with firm size, indicating that larger companies work with lower receivable terms, maybe because their market power. The variable cash conversion cycle (CCC) presented similar results, but not statistically significant. These results are contrary to the researches of Chiou, Cheng and Wu (2006); and, Kieschnick, Laplante and Moussawi (2006) that found evidences that the inefficiency of a firms working capital was positively correlated with firm size. Days of

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accounts payable (D_AP) presented a negative and significant relationship with firm size, indicating that larger companies wait less to pay their bills. Firm growth With respect to the influence of firm growth (GROWTH) on working capital management, results found a predominance of negative relationships, suggesting that lower growth companies invest more in working capital. Variables cash conversion cycle (CCC), days of inventory (D_IN) and days of accounts receivable (D_AR) presented statistically significant relationships. Researches of Chiou, Cheng and Wu (2006), Nazir and Afza (2006) and Appuhami (2008) did not show such statistic significance. Industrial sectors Due to a restriction in the chosen system that generated the regressions equations (Gretl 1.8.5), it was decided to group the 18 industrial sectors extracted from Economtica Pro, in three large groups of sectors industry, commerce and others. Because of the high participation of companies from industry in the sample, these dummy variables werent incorporated to the regression models and, consequently, the study was unable to explore their effects on working capital management. Dynamic panel data model This study used dynamic panel data model to investigate if the dependent variable working capital management could be influenced by a past behavior of the same variable. The results didnt present statistically significance for the majority of the regressions equations. Only the variable working capital requirement (WCR) presented significant and positive relationship, indicating that the choice of a part working capital policy may influence its present performance.

CONCLUSIONS The present research aimed to empirically investigate the determinant factors of working capital management using a sample of 93 companies listed in So Paulo Stock Exchange (BOVESPA) for the period of 2001-2004, in quarterly basis. The main purpose was to contribute to the understanding of short term financial decisions, which is not a theme traditionally, focused inside corporate finance literature, especially in Brazil. After reviewing the existing literature, the study found that researchers explored working capital determinants by investigating several independent variables: industry characteristics, economic activities, operational process indicators, management monitoring mechanisms, firm growth, firm size, market power, debt level, among others. Studies took place in many different countries, with different economic situation and performed based on different econometric models. Different results could be observed with no clear consensus. Given the absence of mathematic models and specific and vastly tested theories, this study chose to explore determinant factors derived from solid theories of corporate finance (Myers e Majluf s Pecking Order Theory, 1984; Jensen and Mecklings Agency Theory, 1976 and Jensen, 1984). The current study used as independent variables debt level, management monitoring mechanisms, free cash flow; and, firm size and growth, as control variables.

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In order to explore the hypotheses, the research tested the explanatory power of different regression models: ordinary least squares, feasible generalized least squares, dynamic panel data and static panel data with fixed and random effects. The fixed effect model was considered the most satisfactory regression to model to investigate the research problem. The study found evidences that companies with high level of debt choose to work with a lower level of working capital, which is consistent with previous researches (Chiou, Cheng and Wu, 2006; Nazir and Afza, 2008). These results are in accordance of Pecking Order Theory and indicate that with an increase in the financial leverage, companies will pay more attention to the working capital management in order to avoid consuming more capital in accounts receivable and inventory and to escape from issuing new bonds and stocks. Analyzing the influence of management monitoring mechanisms on working capital, the study did not find statistically significant evidences in the proxies relationships. Nevertheless, it can be observed that the majority of the relationship including ownership concentration and annual compensation linked to profit presented negative sign. It may suggest that companies with larger investors and compensation instruments can inhibit decisions involving excess of current assets beyond their operational needs. The only statistically significant relationship was observed between the variable participation of outside directors in the board composition and the variable working capital requirement. Such evidence is contrary to the research hypothesis, inspired in the Agency Theory, which defends that this is an important instrument to minimize agency problems (Fama, 1980; Fama and Jensen, 1983). Results associated to the influence of free cash flow on the working capital management, were contrary to expectations, suggesting that companies with lower level of free cash flow present higher level of working capital. A possible explanation can rely on influence of the companys profitability in measuring free cash flow. In this case, the working capital management could also be affect by the companys profitability. This proposition can be tested in upcoming researches. With respect to the control variables, the study suggests that larger and fast growing companies present lower working capital level. It was also observed a negative and significant relationship with the variable days of accounts payable, indicating that smaller companies and with lower growth speed wait more to pay their bills. The current research presented limitations that should be considered in the analysis. The first limitation is related to the industrial sectors, which could not be observed in the regression models results. The second limitation is associated to the proxies of the variable management monitoring mechanisms, which were chosen taking into consideration constraints of public database in Brazil. International studies presented other possibilities of proxies to improve the measurement of this independent variable. The study involved only companys internal factors as independent variables based on the decision to rely the study on well known finance corporate theory. The absence of external factors in the analysis represents the third limitation. The present limitations in this research can be addressed in future studies. One proposition is to explore the variable companys profitability as a determinant factor on working capital management, as explained before. Additionally, another proposition is to include as independent variable, macroeconomic factors, such as interests, economic activity, credit volume, bankruptcy risk, etc. The understanding of the impact of external factors as possible

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determinant factors of working capital management can increase the knowledge of short term investment and financing decisions.

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