The effect of financial constraints and investor protection on the relationship excess net working capital and firm value

(1)

1

The effect of financial constraints and investor protection on the

relationship excess net working capital and firm value

Abstract:

This paper provides new evidence on the relation between net working capital and firm value, with the inclusion of two moderating variables, financial constraints and investor protection. The sample is compiled of 72 countries with a total of 218 275 firm-year observations in the time period of 2007-2017. It is found that excessive net working capital of firms is negatively impacting the value of a firm. Moreover, as firms are financially constrained, it is strengthening this relationship, as well as for firms operating in countries with high investor protection, this relationship weakens.

University of Groningen Faculty of Economics and Business MSc International Financial Management

Supervisor: Dr. R.O.S. Zaal Co-assesor: Dr. N. Selmane

June 8, 2018

Student number : S2551993

Name : Mart Nijland

Study Programme : MSc IFM

Field key words : Net working capital, firm value, financial constraints, investor protection

(2)

2

1. Introduction

Many firms today are enjoying good revenues, but have uncertainties due to two facts: the inability of companies to meet short-term debts and the poor economic conditions (Javid, 2014). Well-made financial decisions are related to the capital structure, capital budgeting and working capital management of a firm. Where most firms have their focus on long-term decisions, connected with the capital structure and capital budgeting, less attention is given to working capital management (Addae and Nyarko-Baasi, 2013). Working capital management is highlighted for its importance for corporations by several articles. The short-term assets and liabilities should be carefully managed as working capital management plays an essential role in the firm’s profitability, risk, and the value of the firm (Smith, 1980). Aktas, Croci and Petmezas (2015), for example, found that a large sample of US firms that engages with working capital management, improve their stock and operating performance by the existence of a working capital policy and an optimal working capital level.

(4)

4 Several studies have examined the impact of working capital on firm performance. Their results show different findings, as a negative relationship between the performance measures of firms and a strong approach towards working capital management (Deloof, 2003; Lazardis and Tryfonidis, 2006; Ebben and Johnson, 2011; Nazir and Afza, 2009). Moreover, some papers found evidence for a positive relation between working capital and profitability (Sharma and Kumar, 2011; Mathuva, 2010). Additionally, some papers and researchers suggest that there is a trade-off between benefits and costs of net working capital. Therefore, there must be an optimal level of working capital investment.

(5)

5 protection is provided with the inclusion the hypotheses for this research. Secondly, in the following section, the methodology and the data are described. Subsequently the results are reported with robustness checks. The final section is filled with the conclusion, limitations, and suggestions for further research.

2. Literature

2. 1 Working capital

Working capital management is focused on the area of short-term finance. First of all, the “working capital” of a firm is the current assets over the current liabilities. Current assets include all cash, short-term investments, receivables, and inventories in total compared to the current liabilities such as short-term debt, account payable, federal income tax, and other liabilities (Sagan, 1955). Working capital is well managed if a company is able to manage its cash conversion cycle. The cash conversion cycle is an important measure for the working capital, as it is the time period between the purchase of raw materials and the collection of sales of finished goods (Gitman, 1974). The time interval is measured in the number of days of inventory, accounts receivable, and accounts payable.

Figure 1: Cash conversion cycle (Jordam, 2003)

(6)

6 the firm some flexibility (Deloof, 2003). Again, the question is whether the benefits outweigh the costs since late payments can be costly if the firm is offered a discount for earlier payment. A longer cash conversion cycle might increase profitability because it is related to higher sales. However, the cash conversion cycle might also decrease profitability if costs of higher investment in working capital rise faster than the benefits of holding more inventory and granting more trade credit to customers (Deloof, 2003).

Although most papers found a negative relationship between the number of days accounts receivables, accounts payables, and inventories (Deloof, 2003; Jose, Lancaster and Stevens, 1996; Lazaridis and Tryfonidis, 2006; Juan García-Teruel and Martínez-Solano, 2007; Dong and Su, 2010; Falope and Ajilore, 2009), there are papers that found contradicting evidence for a positive relationship between working capital and firm performance (Sharma and Kumar, 2011; Mathuva, 2010). Nowadays the goal of firms is to maximize the value of the firm since it encompasses both safety and profitability (Ross, Westerfield and Jaffe, 2008). As mentioned earlier, a study on profitability is less relevant because profit statistics cannot account for firm performance because future performance is neglected. Hence, the relationship between working capital on firm value is more relevant to investigate. Additionally, some papers and researchers suggest that there is a trade-off between benefits and costs of net working capital. Therefore, there must be an optimal level of working capital investment. Banos-Caballero, Garcia-Teruel, and Martinez-Solano (2012) found a concave relationship between the level of working capital and profitability for small and medium-sized Spanish firms. The same result was found for a sample of UK firms, where investment in firms with low levels of working capital was related to the higher performance of that firm (Banos-Caballero, Garcia-Teruel,, and Martinez-Solano, 2014). The opposite is suggested for investment in working capital for firms with a relatively high level of the net working capital (Banos-Caballero, Garcia-Teruel and Martinez-Solano, 2014). All in all, most studies highlight a negative relationship between working capital and firm performance profitability (Deloof, 2003; Jose, Lancaster, and Stevens, 1996; Lazaridis and Tryfonidis, 2006; García-Teruel and Martínez-Solano, 2007; Dong and Su, 2010; Falope, and Ajilore, 2009). If firms have excess working capital, there is unnecessary cash tied up in working capital. This excess cash could better be used for other operational activities since unused cash will not generate revenues or value for the firm. Subsequently, it is expected that for a firm with excessive working capital will reduce its value.

(7)

7 As stated above, there are different results and opinions of researchers upon the relationship between working capital and firm value and firm performance. The most recent paper of Aktas, Croci, and Petmezas (2015), shows the existence of an optimal level of working capital for a sample of US firms between 1982-2011. The relation between excess net working capital and stock performance is non-linear for a sample of firms in the United States. For firms with excessive working capital, the level of working capital is higher or lower than the norm of the industry they are operating in. Firms with a positive excess NWC are overinvesting in working capital, where firms with a negative excess NWC are underinvesting in working capital (Aktas, Croci and Petmezas, 2015). As stated above, additional working capital level may have positive and negative working capital effects. Within the first view, additional working capital associated with larger inventories and receivables may allow firms to increase sales, leading to firm growth. Moreover, lower supply costs, lower potential stock-outs that prevent a loss of sales, and the possibility to hedge against price fluctuations are other clear outcomes followed by larger inventories (Fazzari and Petersen, 1993; Corsten and Gruen, 2004; Blinder and Maccini, 1991). Additionally, larger receivables may provide some advantages for customers with trade credit: it opens the possibility for a firm to price discriminate, it enhances the long-term relationship with customers, and it can serve as a warranty for the quality of a particular product (Long, Malitz, and Ravid, 1993; Brennan, Maksimovic, and Zechner, 1998; Summers and Wilson, 2002). Alternatively, additional working capital requires financing and, therefore, is exposed to interest expenses, bankruptcy risk, and uncertainty about implementing value-enhancing investment projects in the short term (Kieschnick, Laplante and Moussawi, 2013; Ek and Guerin, 2011). Considering both positive and negative views related to potential benefits and costs, I will analyze whether there is a non-linear relation between working capital level and firm value.

H1.2: Positive excess net working capital negatively influences firm value H1.3: Negative excess net working capital positively influences firm value

(8)

8

2.2 Financial constraints

In a frictionless market, it is possible for firms to fund all value-increasing investment opportunities (Modigliani and Miller, 1985). In this unrealistic market, external financing is always obtainable. As a result, the availability of internal capital is less relevant since using funds from external sources is always available and, therefore, internal and external finance are perfect substitutes. In this case, the choice between internal and external finance makes no difference to firm value. However, firms are facing capital market imperfections that may lead to financial constraints. For these firms, the access to credit markets is limited, and funds are more expensive (Kieschnick, Laplante and Moussawi, 2013). Extensive research has shown that cash holdings are more valuable for financially constrained firms than for unconstrained firms (Denis and Sibilkov, 2009; Faulkender and Wang, 2006; Pinkowitz and Williamson, 2006). Other sources of funds are costly or limited for this kind of firms, followed by larger cash holding for these firms. In comparison to large firms, these smaller (constrained) firms are in the literature associated with lower liquidity, more of short-term debt, a higher proportion of current assets and volatile cash flows (Howorth and Westhead, 2003).

(9)

9 use of trade credit to finance their current operations. Thus, net working capital is an important source of finance for financially constrained firms. On the other hand, unconstrained firms are less dependent on net working capital as more alternatives to finance their operations are available. Since financially constrained firms have less access to capital markets and are more dependent on internal funds, consequently, it is expected that these excessive working capital is affecting the value of these firms more. Therefore, it is expected that funds locked up in working capital have significant impact for companies with financial deficiencies, as it cannot be used for financing their activities. The effects for firms that are less financially constrained have less impact on firm value, even though this relationship is expected to remain negative.

H2: Financial constraints strengthens the relationship between excess NWC and firm value

2.3 Investor protection

The legal system of a country has unique characteristics, traditions, and an origin that influences the development of the financial framework, and it is likely that it influences a firm’s decision-making in choosing a financial instrument. A considerable amount of literature has been published about legal systems and finance on either the long-term capital structure of firms or the development of capital markets (La Porta, Lopez-de Silanes, Shleifer and Vishny, 1997, 1998; Djankov, La Porta, Lopez-de-Silanes and Shleifer, 2008). Therefore, it is interesting to examine the influence of legal systems on short-term finance and whether it influences a firm’s decision-making and development on working capital.La Porta, Lopez-de Silanes, Shleifer and Vishny (1997) found evidence that legal rules, protecting investors and the nature of their enforcement, vary across countries. According to previous studies, better legal protection for investors is related to higher valuation of listed firms relative to their assets or changes in investments (Wurgler, 2000), higher valuation of the stock markets (La Porta, Lopez-de Silanes, Shleifer and Vishny, 2002), and larger listed firms in terms of their sales and assets (Kumar, Rajan and Zingales, 1999).

(10)

10 1997). In the research of La Porta, Lopez-de Silanes, Shleifer and Vishny (1997), it is found that common law countries offer better protection to shareholders and creditors in comparison to the civil law countries. Moreover, out of the civil law countries, they found that French civil law countries have both the weakest investor protections and the least developed capital markets. Troilo, Walkup, Abe, and Lee (2018) analyzed the impact of legal systems on the level and sourcing of working capital. They found that firms with a common-law origin compared to civil-law environments typically have lower levels of working capital and finance it from banks. Additionally, they find that countries with a civil-law origin rely on retained earnings and other financial institutions for investing in working capital. A code-law country such as China, where working capital management is particularly important, firms have limited access to long-term capital markets (Ding, Guariglia, and Knight, 2013). For example, 55% of the firm-year observations in the dataset of Ding, Guariglia and Knight (2013) did not have access to long-term debt. These Chinese firms are more dependent on internal finance, short-long-term debt, and trade credit to finance their activities. Working capital may be used as an additional source of finance, and hence a higher level of working capital is needed.

Considering the differences between common law and civil law countries it is interesting to analyze whether the relation of excess NWC and firm value is affected by the degree of investor protection since there are differences in the level of investor protection. Tradeoff theories, more specifically agency theory, focus on the tradeoff between costs and benefits related to financial activities and could explain different views of managers in different countries (Opler, Pinkowitz, Stulz and Williamson, 1999). Agency theory implies that problems arise due to conflicts of interest between stakeholders bondholders and managers (Jensen and Meckling, 1976). Opposing views between the principal (stakeholders and creditors) and agent (manager) generate agency issues, resulting in agency costs and consequently a lower firm value. One would, therefore, expect that managers in countries with low investor protection act in their own interest and pursue their own objectives at shareholder expense, and will not maximize shareholders wealth (Opler, Pinkowitz, Stulz and Williamson, 1999). La Porta, Lopez-de Silanes, Shleifer and Vishny (2000) confirm that higher investor protection is associated with lower agency costs.

(11)

11 well enforced, financial markets are broader and more valuable, and investors are more willing to finance particular firms (La Porta, Lopez-de Silanes, Shleifer and Vishny, 2002). Since investors in this kind of countries are better protected, more of the firm’s revenues can be expected in terms of interest or dividends. In contrast, adverse effects are applicable to countries with low investor protection. In these firms, managers have more control over the firm and may hold cash to pursue its own objectives.

Weak investor protection negatively affects the financing options of a firm. Subsequently, in countries with weak investor protection, investors are not willing to pay as much for financial assets. Considering that the legal system of a country is influencing the level of creditors- and shareholders protection, firms in countries with low investor protection have to compensate this by financing projects with internal funds or with close-connected banks (La Porta, Lopez-de Silanes, Shleifer, and Vishny, 2000). According to the information above, the following hypothesis could be made:

H3: The level of investor protection weakens the relationship between excess NWC and firm value.

3. Data and Methodology

3.1 Data

(12)

12

3.2 Sample distribution

Table 9, in appendix 3, illustrates the summary statistics for the NWC-to sales ratio by all industries. According to the Fama-French 49 industry classification firms are grouped into different industries. It can be seen that the median of most industries have a positive time trend. The increase of NWC can be seen as a common development through time in most of these industries. As will be explained below, the excess NWC of a firm can be calculated related to the unnecessary cash tied up in working capital of firms. Table 1 exhibits the distribution of the observations for the excess NWC for all countries. Countries with a negative excess NWC are under-investing in working capital or else over-investing in working capital (positive excess NWC). Most observations are available for firms in the USA (17%). As can be seen in table 2, the sample size increases during the 10-year period, from 2007 until 2017, due to the growing amount of observations. This with the exception of 2017, where probably some data is not available yet. The excess NWC is the lowest in 2008 which can be due to the financial crisis of 2007-2008. Moreover, this is probably also the reason that the excess NWC is growing the years thereafter, due to the economic recovery. Furthermore, the excess NWC is the highest for 2017 with a positive excess NWC of 0.060815. With regard to the summary statistics of excess NWC, the countries with the most positive excess NWC are Jordan (0.2769) and Greece (0.2681), indicating that these countries are over-investing the most in working capital. As can be seen in table 10 in the appendix, both countries with a low level of investor protection. Contrary to these countries, Ecuador 0.1643), Ghana 0.0883), Panama 0.0627), Canada (-0.0260), USA (-0.0242) and Lithuania (-0.0042) are under-investing on average in working capital.

Table 1:Excess NWC by country

Country Mean Median Sd Obs. %

(13)

(14)

14 Turkey 0.1093 0.0483 0.2527 2402 1.1% Taiwan 0.0566 0.0123 0.1983 12555 5.7% Uganda 0.0796 0.0874 0.0642 15 0.0% Ukraine 0.1105 0.0496 0.2833 118 0.1% United States -0.0242 -0.0322 0.1679 37228 17.0% Venezuela 0.0797 0.0775 0.1458 33 0.0% South Africa 0.0270 -0.0080 0.1743 1888 0.9% Zimbabwe 0.0680 -0.0161 0.2439 218 0.1% Total 0.0506363 0.0011 0.2264 218275 100.0%

This table is showing the excess NWC by country. The full sample consists of 218 275 firm-year observations for the period 2007-2017.

Table 2: Excess NWC by year

Year Mean Median Sd N

2008 0.03448 -0.00324 0.2065 11117 2009 0.04412 0.00038 0.2131 19792 2010 0.04319 0.00056 0.2131 21787 2011 0.04502 0.00000 0.2174 22514 2012 0.04960 0.00156 0.2226 23647 2013 0.05125 0.00115 0.2292 24752 2014 0.05476 0.00053 0.2347 25054 2015 0.05747 0.00049 0.2408 25308 2016 0.05611 0.00004 0.2408 25458 2017 0.06082 0.00949 0.2252 18846 Total 0.0506363 0.0010615 0.22638 218275

This table is showing the excess NWC by year. The full sample consists of 218 275 firm-year observations for the period 2007-2017.

3.3 Descriptive statistics

(15)

15 The pair-wise correlation matrix is presented in table 4. In the table can be observed that the independent and control variables are significant at the 1% level. I do not observe any correlations, that may indicate problems like multicollinearity as none of the coefficients is larger than the critical value of 0.7. There is a negative correlation between excess NWC and Tobin’s Q, what might suggest that there is a negative relationship between excess NWC and Tobin’s Q. Obviously, this will be scrutinized in the regression analysis. Interestingly are the findings for both measures of investor protection, with the anti-self-dealing index positively related to firm value, and the anti-director index negatively related to firm value. This can be justified because the measure of investor protection is based on a measure of shareholder protection and the anti-self-dealing index is more related to the development of financial markets (Djankov, La Porta, Lopez-de-Silanes, and Shleifer, 2008)

Table 3: Descriptive statistics

Obs. Mean Median Sd Min Max

Tobin's Q 218,275 1.760 1.210 1.494 0.581 7.235 Excess NWC 218,275 0.050 0.001 0.223 -0.357 0.790 Positive NWC 218,275 0.103 0.001 0.181 0.000 0.790 Negative NWC 218,275 -0.053 0.000 0.080 -0.357 0.000 Size 218,275 3.161 3.167 1.326 -0.558 6.416 Leverage 218,275 0.234 0.189 0.255 0.000 2.077 Salesgrowth 218,275 0.142 0.045 0.678 -0.997 5.095 R&D ratio 218,275 0.025 0.000 0.097 0.000 1.245 ROA 218,275 -0.004 0.048 0.327 -3.614 0.335 Dividend-payout 218,275 0.161 0.000 0.341 -0.572 1.928

Firm size (sales 218,275 6.935 7.009 3.052 0.945 12.396

Anti-self-dealing 218,275 0.602 0.579 0.191 0.075 1.000

Anti-director 218,275 3.635 4.000 1.176 1.000 5.000

(16)

16

Table 4: Pair-wise correlation matrix

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 1. TobinQ 1 2. Excess NWC -0.0703* 1 3. Size -0.2513* -0.0199* 1 4. Leverage 0.0857* -0.0202* -0.0096* 1 5. Sales growth 0.1065* 0.0703* -0.1068* -0.0197* 1 6. ROA -0.3038* 0.0666* 0.3681* -0.2893* -0.0435* 1 7. R&D ratio 0.2800* -0.0978* -0.2361* 0.0619* 0.0566* -0.4660* 1

8. Firm size (sales) -0.2440* -0.0893* 0.9477* -0.0109* -0.1106* 0.3987* -0.2376* 1

9. Dividend payout-ratio -0.0267* -0.0404* 0.1426* -0.0738* -0.0450* 0.1362* -0.0730* 0.1592* 1 10.Anti-director index -0.1790* -0.0254* 0.1165* 0.0090* -0.0188* 0.0233* -0.0491* 0.1182* 0.0760* 1

11. Anti-self-dealing index 0.0989* 0.0140* -0.1937* -0.0384* 0.0552* -0.0685* 0.0323* -0.2084* 0.0061* 0.1079* 1 This table is showing the correlation matrix for all firm-level variables. The full sample consists of 218 275 firm-year observations for the period 2007-2017. Variables are

(17)

17

3.4 Variable measurements

Excess NWC

The independent variable of this research is excess NWC. First, NWC can be calculated inventories plus receivables minus the payables. Since working capital have different needs for different industries it is necessary to control for industry effects. In the paper of Aktas, Croci and Petmezas (2015) they control for these industry effects by using the industry-median adjusted NWC-to-sales ratio. This can be done by subtracting the ratio of the median NWC of firms in a corresponding industry/year from NWC-to-sales ratio of a firm. This variable is called the excess NWC further in this paper, and measures for every firm the unnecessary cash tied up in working capital (Aktas, Croci and Petmezas, 2015). Subsequently firms with a negative excess NWC are under-investing in working capital. For these firms there is room for a more conservative working capital policy. There might be a risk of sales loss due to potential stock-outs or unsatisfied customers, when applying an extremely aggressive working capital policy (Fazzari and Petersen, 1993; Kieschnick, Laplante and Moussawi, 2013; Corsten and Gruen, 2004). For this case, the expectation is that investing in working capital may enhance the value of a firm. Shortages and interruptions in the production process could be prevented by increasing the inventories of these firms (Blinder and Maccini, 1991). Extending trade credit to customers, may stimulate the sales of these firms and provides some advantages to customers by warranties for product quality and fostering a long-term relationship with these customers (Summers and Wilson, 2002; Brennan, Maksimovic, and Zechner, 1998; Long, Malitz, and Ravid, 1993). On the other hand, a firm with a positive excess NWC is over-investing in working capital. These firms could apply a more aggressive working capital policy, by cutting down inventories and delayed payments granted to customers. Further increasing the level of NWC will probably affect these firms negatively. The previous study of Aktas, Croci, and Petmezas (2015) have based their criteria for the efficient NWC of the firm, to the one that leads to the industry-median NWC level.

Firm value

(18)

18 Tobin’s Q = The market value of equity + Total assets - Common ordinary equity

Total assets

In order to control robustness, the industry-adjusted Tobin’s Q is used in this paper. This proxy neutralizes the effect of different industries, which subsequently can account for a more robust analysis. (Campbell, 1996). Equivalent to the measurement of excess NWC, it is the difference between the Tobin’s Q for a firm minus the industry median Tobin’s Q based on the 49 industries of Fama and French.

Financial constraints

According to previous studies, there are various firm subsamples, which indicate the likelihood of firms facing financial constraints. First of all, the financial constraints of a firm could be identified by looking at dividends. Fazzari, Hubbard, Petersen, Blinder, and Poterba (1988), state that firms favor paying lower dividends or no dividends to reduce the probability of raising external funds in the future. Moreover, firms that pay more dividends are likely to have enough internal funds to cover debt payments and finance several investments (Faulkender and Wang, 2006). Almeida, Campello, and Weisbach (2004) and Faulkender and Wang (2006), measure the constraints of a firm by their dividend payout ratio. Firms with a ratio below the sample median are classified as financially constrained. Secondly, many studies use size as a proxy for measuring financial constraints (Almeida, Campello, and Weisbach, 2004; Carpenter, Fazzari, Petersen, Kashyap, and Friedman, 1994; Faulkender and Wang, 2006). Bigger firms suffer less from information asymmetries and agency costs compared to smaller firms. Subsequently, smaller firms will be more financially constrained. The bigger the size of a company, the less financially constrained a firm is. As a result, firms with a size below the sample median are classified as financially constrained.

For both proxies, two-sample t-tests are used to determine significant differences between those subsamples. As can be seen in appendixes 2.3 and 2.4, there are statistically significant differences in the means for all variables of both subsamples.

Investor protection

(19)

19 country that protects shareholders against the expropriation of managers or dominant shareholders (La Porta, Lopez-de Silanes, Shleifer and Vishny, 1998). These countries tend to protect investors more than countries that score low on the index. The latter specifically involves the protection of minority shareholders against self-dealing transactions in favor of controlling shareholders (Djankov, La Porta, Lopez-de-Silanes, and Shleifer, 2008). A higher value for this index suggests that the implication of tight regulations is associated with a high level of investor protection. Table 10 in the appendix is showing the classification of the level of investor protection per country. According to the median for both indexes, countries are divided into low and high investor protection. For both indexes, two-sample t-tests are used to determine significant differences between those subsamples. As can be seen in appendixes 2.1 and 2.2, there are statistically significant differences in the means for all variables for both subsamples.

Control variables

Four control variables are used to control firm-specific factors that may influence the firm value. The control variables used on the firm-level are leverage, firm size (SIZE), sales growth, profitability (ROA), and the ratio research and development expenditures scaled by total assets (R&D ratio). Moreover, definitions of variables are presented in appendix 1. All these variables are lagged to control for endogeneity problems.

Size: to control for firm size, the natural logarithm of the total assets is taken. Larger firms tend to be more stable firms and less likely to default (Harris and Raviv, 1991). Furthermore, large companies tend to be more profitable compared to smaller companies (Allayannis and Weston, 2001). On the other hand, Allayannis and Weston (2001) raise uncertainties about this relationship with firm value as they find a negative relationship with firm value.

(20)

20 Sales growth: furthermore, sales growth is the growth rate of sales at time t and is measured as the difference between sales of the current year and last year, divided by the sales last year. Many studies associate higher firm value with growth rates in total sales. Faster growing companies tend to have higher valuations (Aktas, Croci, and Petmezas, 2015; Klapper and Love, 2004; Maury and Pajuste, 2005).

Profitability (ROA): additionally, the profitability of a firm is related to firm value. In this paper, ROA is generated as the earnings before interests and taxes dived by the total assets of a firm. More profitable firms are more likely to have a higher firm value (Júnior and Laham, 2008).

Research and development (R&D ratio): the research and development expenditure to total assets is extensively used in the literature as a control variable for firm value since these expenses create value for the firm. Subsequently, a higher R&D ratio is related to growth, which, in turn, provide firm value (Durnev and Kim, 2005). To not further reduce the sample size, firms with missing values of R&D expenses are replaced with zero. I assume that these firms do not consider research and development expenditures.

3.5 Methodology

In order to determine the relation between excess-NWC and firm value, multiple regression models will be performed. In these models, the effect of the firm-level moderator, financial constraints, and the effect of the country-level moderator, investor protection are investigated. Panel data analysis is used since values are collected over the sample period 2007-2017 for unique identical firms. Differences between countries, industries could be identified by using this method. Moreover, I control for year, industry and country fixed effects respectively. As prior research has shown, the amount of working capital differs between industries, countries, and years (Weinraub and Visscher, 1998; Hawawini, Viallet, and Vora1986).

(21)

21 might be heteroscedasticity in the sample. Finally, the Breusch-Pagan test confirms that the results are affected by heteroscedasticity. This may lead to biased results and standard errors. To control for this problem, robust standard errors are used when running regressions. This also accounts for auto-correlation at the firm level (Petersen, 2009; Thompson, 2011). As stated above, independent and control variables are lagged to control for endogeneity problems (Aktas, Croci and Petmezas, 2015). The regressions below will be performed in order to test the hypotheses reported in the literature section. Regression 1 is testing H1.1, equation 2 tests H1.2 and H2.2. Moreover, the moderating effect of financial constraints, related to H2, is tested in regression 3 and 4. Additionally, the moderating effect of investor protection involves regression 5 and 6, that investigates H3.

1. 𝐹𝑖𝑟𝑚 𝑉𝑎𝑙𝑢𝑒_𝑖,𝑡 = 𝛼_𝑡+ 𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}+ 𝛽₂𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠_{𝑖,𝑡−1}+ 𝑌𝑒𝑎𝑟_𝑡+ 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦_𝑛+ 𝐶𝑜𝑢𝑛𝑡𝑟𝑦_𝑐+ 𝜀_𝑖,𝑡 2. 𝐹𝑖𝑟𝑚 𝑉𝑎𝑙𝑢𝑒_𝑖,𝑡 = 𝛼_𝑡+ [𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}∗ 𝐷] + [𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}∗ (1 − 𝐷)] + 𝛽₂𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠_{𝑖,𝑡−1}+ 𝑌𝑒𝑎𝑟_𝑡+ 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦_𝑛+ 𝐶𝑜𝑢𝑛𝑡𝑟𝑦_𝑐+ 𝜀_𝑖,𝑡 3. 𝐹𝑖𝑟𝑚 𝑉𝑎𝑙𝑢𝑒_𝑖,𝑡 = 𝛼_𝑡+ 𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}+ [𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}∗ 𝐷𝐼𝑉_{𝑖,𝑡−1}] + 𝛽₂𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠_{𝑖,𝑡−1}+ 𝑌𝑒𝑎𝑟_𝑡+ 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦_𝑛+ 𝐶𝑜𝑢𝑛𝑡𝑟𝑦_𝑐+ 𝜀_𝑖,𝑡 4. 𝐹𝑖𝑟𝑚 𝑉𝑎𝑙𝑢𝑒_𝑖,𝑡 = 𝛼_𝑡+ 𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}+ [𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}∗ 𝑆𝐼𝑍𝐸_{𝑖,𝑡−1}] + 𝛽₂𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠_{𝑖,𝑡−1}+ 𝑌𝑒𝑎𝑟_𝑡+ 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦_𝑛+ 𝐶𝑜𝑢𝑛𝑡𝑟𝑦_𝑐+ 𝜀_𝑖,𝑡 5. 𝐹𝑖𝑟𝑚 𝑉𝑎𝑙𝑢𝑒_𝑖,𝑡 = 𝛼_𝑡+ 𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}+ [𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}∗ 𝐴𝐷𝐼_𝑐] + 𝛽₂𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠_{𝑖,𝑡−1}+ 𝑌𝑒𝑎𝑟_𝑡+ 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦_𝑛+ 𝐶𝑜𝑢𝑛𝑡𝑟𝑦_𝑐+ 𝜀_𝑖,𝑡 6. 𝐹𝑖𝑟𝑚 𝑉𝑎𝑙𝑢𝑒_𝑖,𝑡 = 𝛼_𝑡+ 𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}+ [𝛽₁𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶_{𝑖,𝑡−1}∗ 𝐴𝑆𝐷𝐼_𝑐] + 𝛽₂𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠_{𝑖,𝑡−1}+ 𝑌𝑒𝑎𝑟_𝑡+ 𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦_𝑛+ 𝐶𝑜𝑢𝑛𝑡𝑟𝑦_𝑐+ 𝜀_𝑖,𝑡

𝐹𝑖𝑟𝑚 𝑉𝑎𝑙𝑢𝑒 = measured by Tobin’s Q and the industry-adjusted Tobin’s Q

𝑖 = 34,458

𝐸𝑥𝑐𝑒𝑠𝑠 𝑁𝑊𝐶 = Unnecessary cash tied up in working capital

(22)

22 𝑌𝑒𝑎𝑟_𝑡 = Year fixed effects

𝐼𝑛𝑑𝑢𝑠𝑡𝑟𝑦𝑛 = Industry fixed effects 𝐶𝑜𝑢𝑛𝑡𝑟𝑦_𝑐 = Country fixed effects

4. Results

4.1 Excess NWC and firm value

In the following section, the main results will be presented. The relationship between excess NWC and firm value will be explored. Table 5 present these first regressions. Since several papers and researchers have opposing views regarding the relationship between NWC and firm value, the potential non-linearity in the relation between excess NWC and firm value will be tested first. The main results of these uncertainties are summarized in the following table:

Table 5: Net working capital and firm value

Model1 Model2 Model3 model4

Excess NWC -0.470*** -0.448*** [0.031] [0.025] Excess NWC * D 0.240*** -0.303*** [0.035] [0.032] Excess NWC * (1-D) -2.766*** -0.906*** [0.101] [0.083] Size -0.329*** -0.325*** [0.009] [0.009] Leverage 0.298*** 0.295*** [0.033] [0.033] Sales growth 0.090*** 0.085*** [0.006] [0.006] R&D ratio 1.794*** 1.776*** [0.088] [0.088] ROA -0.497*** -0.472*** [0.029] [0.029] Constant 1.784*** 2.529*** 1.377*** 2.467*** [0.008] [0.209] [0.213] [0.210]

Year Yes Yes

Industry Yes Yes

Country Yes Yes

Adjusted R-squared 0.005 0.275 0.19 0.275

Observations 218275 218275 218275 218275

(23)

23 Model 1 of table 5 shows the linear relationship between excess NWC and firm value. This relation is significantly negative, but does not include control variables. With the inclusion of control variables in model 2, it can be seen that this relation is still negative. In line with Allayannis and Weston (2001), the size of a firm (log of total assets) negatively impacts firm value (Tobin’s Q), ceteris paribus. Evidence is found on the 1% significance level. Moreover, in line with the literature, leverage, sales growth and the R&D ratio of a firm positively impacts Tobin’s Q, all on the 1% significance level. Lastly it can be seen that ROA has a negative impact on Tobin’s Q (-0.497). Apparently, more profitable firms tend to be valued lower. This unexpected finding could be explained by the fact that profitability is a performance measure on the short term, whether firm value is a performance measure on the short term but especially on the long term. As stated above, there might be a nonlinear relationship between excess NWC and firm value. Some firms have low levels of net working capital and a reduction of this level may negatively affect the firm value in terms of loss of sales due to potential stock-outs or unsatisfied customers. In model 3 and 4, the slope coefficient is set different for firms that over- and underinvest in NWC by adding two interaction variables. For positive excess NWC, the excess NWC variable interacts with firms with a positive excess NWC. A dummy variable is created to account for these positive or negative excess NWC. Subsequently, the same interaction effect is created for firms with a negative excess NWC. The results of model 3 indicate that there is an optimal level of working capital. However, with the inclusion of the control variables, the coefficient estimates show negative values for both interaction variables. With a statistically significant coefficient values of -3.03 for excess NWC*D and -9.06 for excess NWC*(1-D), there is no evidence for a non-linear relationship between excess NWC and firm value. Firms that over- and underinvest in NWC both are negatively related to firm value. According to this model, hypotheses 1.3, claiming that negative excess net working capital positively influences firm value can be rejected. Positive excess NWC is negative and highly statistically significant in the relation to firm value, which confirms H1.2.

(24)

24 the linear relation of this main relationship, including the moderating effects of financial constraints and investor protection.

4.2 Financial constraints

In table 6 the dimension of financial constraints is added to the model. Model 1-2 report the results of the main relationship. In model 3-4, financial constraints are measured by the dividend payout ratio. According to the literature, firms with a dividend payout ratio below the sample median are likely to be financially constrained. A dummy variable identifying firms with financial constraints is created and interacts with excess NWC of a firm. According to model 3, the influence of the dividend payout ratio is statistically significant with a coefficient estimate of 0.263. With 99% certainty can be said that for firms with a higher dividend payout ratio, firm value is higher. As can be seen in model 4, with the inclusion of the interaction term of dividend payout * excess NWC, results are insignificant.

(25)

25

Table 6: Moderating effect of Financial constraints on NWC and firm value

model1 model2 model3 model4 model5 model6

Excess NWC -0.470*** -0.448*** -0.435*** -0.431*** -0.349*** -0.511*** [0.031] [0.025] [0.025] [0.025] [0.026] [0.039] Size -0.329*** -0.342*** -0.341*** -0.511*** -0.512*** [0.009] [0.009] [0.009] [0.017] [0.017] Leverage 0.298*** 0.317*** 0.317*** 0.284*** 0.292*** [0.033] [0.032] [0.032] [0.033] [0.033] Sales growth 0.090*** 0.091*** 0.091*** 0.071*** 0.071*** [0.006] [0.006] [0.006] [0.007] [0.007] R&D ratio 1.794*** 1.793*** 1.793*** 1.826*** 1.836*** [0.088] [0.088] [0.088] [0.087] [0.087] ROA -0.497*** -0.514*** -0.514*** -0.513*** -0.516*** [0.029] [0.028] [0.028] [0.028] [0.028] Dividend payout 0.263*** 0.263*** [0.013] [0.013]

Dividend payout * excess NWC -0.142

[0.098]

Log Sales 0.088*** 0.089***

[0.008] [0.008]

log Sales * excess NWC 0.241***

[0.046]

Constant 1.784*** 2.529*** 2.555*** 2.554*** 2.484*** 2.471***

[0.008] [0.209] [0.208] [0.208] [0.209] [0.209]

Year No Yes Yes Yes Yes Yes

Industry No Yes Yes Yes Yes Yes

Country No Yes Yes Yes Yes Yes

Adjusted R-squared 0.005 0.275 0.278 0.278 0.277 0.278

Observations 218275 218275 218275 218275 218275 218275

In this table, the results of the OLS regressions of the main relationship with the inclusion of the moderating variables of financial constraints are reported. Tobin’s Q (firm value) is the dependent variable. Year-, industry, and country fixed effects are indicated for model 2-6. *, ** and *** are established behind significant coefficients at the 0.10, 0.05 & 0.01 level. Standard errors are clustered for 34,458 firms to alleviate heteroscedasticity and autocorrelation. Furthermore, variables are winsorized at the 1% level.

4.3 Investor protection

(26)

26 lower. The interaction term Anti-director rights * excess NWC shows a statistically significant value of 0.443 on the 1% level, indicating that excess NWC on firm value is different for different values of the anti-director rights index. So, the anti-director rights index moderates the relationship between excess NWC and firm value. Higher investor protection, in this case, weakens the main relationship, which confirms hypothesis 3. In model 5 and 6, the anti-self-dealing values are incorporated with the variables. The anti-self-anti-self-dealing value of model 5 reports a negative and highly statistically significant relationship to firm value. When adding the dummy variable of investor protection, the interaction terms of anti-self-dealing * excess NWC appears to be insignificant.

Table 7: Moderating effect of investor protection on NWC and firm value

Model1 Model2 Model3 Model4 Model5 Model6

Excess NWC -0.470*** -0.448*** -0.448*** -0.619*** -0.448*** -0.432*** [0.031] [0.025] [0.025] [0.032] [0.025] [0.028] Size -0.329*** -0.329*** -0.328*** -0.329*** -0.329*** [0.009] [0.009] [0.009] [0.009] [0.009] Leverage 0.298*** 0.298*** 0.302*** 0.298*** 0.298*** [0.033] [0.033] [0.033] [0.033] [0.033] Sales growth 0.090*** 0.090*** 0.091*** 0.090*** 0.090*** [0.006] [0.006] [0.006] [0.006] [0.006] R&D ratio 1.794*** 1.794*** 1.824*** 1.794*** 1.794*** [0.088] [0.088] [0.088] [0.088] [0.088] ROA -0.497*** -0.497*** -0.503*** -0.497*** -0.498*** [0.029] [0.029] [0.029] [0.029] [0.029] Anti-director -0.442*** -0.436*** [0.123] [0.123] Anti-director* excess NWC 0.443*** [0.051] Anti-self-dealing -17.671*** -17.559*** [4.905] [4.913] Anti-self-dealing * excess NWC -0.103 [0.063] Constant 1.784*** 2.529*** 3.413*** 3.390*** 8.567*** 8.530*** [0.008] [0.209] [0.425] [0.424] [1.837] [1.840]

Adjusted R-squared 0.005 0.275 0.275 0.276 0.275 0.275

Observations 218275 218275 218275 218275 218275 218275

(27)

27

4.4 Robustness

First of all, as previous research has shown, the amount of working capital tends to be different between industries (Weinrub and Visscher, 1998; Hawawini, Viallet, and Vora, 1986). For instance, firms in manufacturing industries tend to have high levels of inventory and extend more and longer trade credit to their customers. Compared to firms in the retail industry, less trade credit is provided to customers as these customers pay much faster or directly. Furthermore, the inventories in this industry tend to be much lower, as they are rotating faster. Service industries are a particular case, as companies in these industries sometimes do not hold any inventories at all. To enhance robust results, excess NWC is determined for every industry in the Fama-French 49 industry classification.

Moreover, robustness tests are performed on the main models of table 4,5 and 6. The dependent variable, Tobin’s Q is replaced by the industry-adjusted Tobin’s Q. Firm value for the firms is neutralized by the effect of different industries, which subsequently account for a more robust analysis. When looking at the reported results in table 8, the coefficients are not remarkably different compared to the same models in the other tables. Variables that were significant in the former models remain significant with slightly different values in the same direction.

(28)

28

Table 8: Robustness with adjusted Tobin's Q as the dependent variable

Excess NWC -0.449*** -0.445*** -0.428*** -0.509*** -0.617*** -0.429*** [0.029] [0.025] [0.025] [0.038] [0.032] [0.028] Size -0.329*** -0.342*** -0.511*** -0.328*** -0.329*** [0.009] [0.009] [0.017] [0.009] [0.009] Leverage 0.300*** 0.319*** 0.293*** 0.303*** 0.300*** [0.033] [0.032] [0.033] [0.033] [0.033] Sales growth 0.082*** 0.083*** 0.063*** 0.083*** 0.082*** [0.006] [0.006] [0.007] [0.006] [0.006] R&D ratio 1.810*** 1.809*** 1.852*** 1.841*** 1.811*** [0.088] [0.088] [0.087] [0.088] [0.088] ROA -0.498*** -0.514*** -0.517*** -0.504*** -0.498*** [0.029] [0.028] [0.028] [0.029] [0.029] Dividend payout 0.260*** [0.013]

[0.098]

Log Sales 0.088***

[0.008]

interaction log Sales 0.241***

[0.046] Anti-director -0.442*** [0.122] Anti-director* excess NWC 0.445*** [0.051] Anti-self-dealing -17.824*** [4.909] Anti-self-dealing * excess NWC -0.105 [0.063] Constant 0.486*** 1.624*** 1.649*** 1.567*** 2.498*** 7.716*** [0.007] [0.209] [0.208] [0.209] [0.423] [1.838]

Observations 218275 218275 218275 218275 218275 218275

(29)

29

Table 9: Post-financial crisis

Excess NWC -0.459*** -0.458*** -0.441*** -0.526*** -0.637*** -0.442*** [0.032] [0.026] [0.027] [0.040] [0.034] [0.029] Size -0.346*** -0.360*** -0.530*** -0.346*** -0.347*** [0.010] [0.010] [0.018] [0.010] [0.010] Leverage 0.263*** 0.284*** 0.258*** 0.266*** 0.262*** [0.034] [0.034] [0.034] [0.034] [0.034] Sales growth 0.101*** 0.102*** 0.081*** 0.102*** 0.101*** [0.007] [0.007] [0.007] [0.007] [0.007] R&D ratio 1.866*** 1.869*** 1.908*** 1.901*** 1.867*** [0.095] [0.095] [0.094] [0.095] [0.095] ROA -0.464*** -0.481*** -0.482*** -0.470*** -0.464*** [0.031] [0.030] [0.030] [0.031] [0.031] Dividend payout 0.274*** [0.014]

[0.108]

Log Sales 0.089***

[0.008]

interaction log Sales 0.254***

[0.048] Anti-director -0.554*** [0.125] Anti-director* excess NWC 0.469*** [0.054] Anti-self-dealing -22.296*** [5.002] Anti-self-dealing * excess NWC -0.103 [0.067] Constant 1.818*** 2.992*** 3.019*** 2.935*** 4.087*** 10.612*** [0.008] [0.212] [0.211] [0.213] [0.429] [1.871]

Observations 187366 187366 187366 187366 187366 187366

(30)

30

5. Conclusion

The aim of this study is to extend the research on the relationship between net working capital and firm value. Many studies have a different point of view concerning the relationship between working capital van firm performance. Practitioners that have a view upon the positive effect of higher working capital in relation with firm value or firm performance raise the argument that a higher level of working capital is related to lower risk in terms of potential stock-outs and reduced-price fluctuations (Blinder and Maccini, 1991; Corsten and Gruen, 2004). Notwithstanding, other papers found a negative relationship, since overinvestment in net working capital may lead to adverse effects (Kieschnick, Laplante, and Moussawi, 2013). Furthermore, a recent paper of Aktas, Croci, and Petmezas (2015), found evidence for a non-linear relationship, suggesting that firms increment firm performance when they move closer to the optimal level of net working capital. Furthermore, traditional research related to net working capital has mainly focused on individual countries. In this study, the sample is compiled of 68 countries with a total of 218 275 firm-year observations in the time period of 2007-2017. Moreover, a study on net working capital and profitability is less relevant, since these numbers do not account for a complete measurement of firm performance. Profitability is a short-term measuring tool of performance, while the firm value is related to performance on the long-term (Wasiuzzaman, 2015). Subsequently, the relationship between working capital and firm value is investigated in this paper with the inclusion of the interaction effects of firms’ financial constraints and investor protection. According to the literature, this may impact the relationship of net working capital and firm value.

(31)

31 could be interesting for investors. Usually, the capital structure of a firm and its investment and dividend policies are important aspects for investors that assess different companies (La Porta, Lopez-de Silanes, Shleifer and Vishny, 2000; Jensen and Meckling, 1976). According to the results, the working capital policy of a firm can be an important factor when considering different investment opportunities.

Financial constraints of a firm were expected to moderate the relationship between excess NWC and firm value. Firms with these deficiencies are able to reduce their costs and are more depending on internal funds to finance their operational activities. Therefore, it was expected that additional funds locked up in working capital have a more significant negative impact on firms that are financially constrained. The findings indicate that a 1-unit increase in excess NWC causes a less negatively decrease in firm value when firms are less financially constrained. The interaction term is positive, indicating that financially constrained firms are reducing the negative effect of excess NWC on firm value. When a firm is less financially constrained, indicated by a higher level of sales, the main relationship is less negative. According to the literature, these firms reduce their financing cost by diminishing the amount of money locked up in their working capital (Hill, Kelly and Highfield, 2010). Locked up money in working capital for these firms with limited availability to external funds more negatively impacts firm value. Managers of financially constrained firms should be aware of the fact that these excess working capital levels have a strong negative impact on firm value and should adjust their working capital policy to make it more efficient.

(32)

32 In conclusion, this paper contributes to the existing literature by providing a better understanding of financial constraints and the quality of investor protection on the relationship excess net working capital and firm value. For an international sample with a distinction made between 49 industries, it is found that the value of a firm is negatively affected by excess NWC. Managers should try to limit excess NWC, as the firm value is negatively impacted by excess NWC. Furthermore, investor rights and financial constraints are important for managers when making both investment and financial decisions. Moreover, these findings show the importance of sources of external funds in making firm-related decisions. Finally, by organizing, planning and controlling working capital of firms more efficiently, firms will perform more optimally in increasingly efficient markets.

(33)

33

6. References

Addae, A. A., and Nyarko-Baasi, M., 2013. Working capital management and profitability: an empirical investigation in an emerging market. Research Journal of Finance and Accounting, 4, 143-152.

Aktas, N., Croci, E., and Petmezas, D., 2015. Is working capital management value-enhancing? Evidence from firm performance and investments. Journal of Corporate Finance, 30, 98-113.

Almeida, H., Campello, M., and Weisbach, M., 2004. "The cash flow sensitivity of cash." The Journal of Finance 59.4, 1777-1804.

Baños-Caballero, S., García-Teruel, P. J., and Martínez-Solano, P., 2012. How does working capital management affect the profitability of Spanish SMEs? Small Business Economics, 39, 517-529.

Baños-Caballero, S., García-Teruel, P. J., and Martínez-Solano, P., 2014. Working capital management, corporate performance, and financial constraints. Journal of Business Research, 67, 332-338.

Blinder, A. S., and Maccini, L. J., 1991. The resurgence of inventory research: what have we learned?. Journal of Economic Surveys, 5, 291-328.

Brennan, M. J., Maksimovic, V., and Zechner, J., 1988. Vendor financing. The Journal of Finance, 43, 1127-1141.

Buchmann, P., Roos, A., Jung, U., and Martin, A., 2008 Cash for growth: The neglected power of working-capital management. The Boston Consulting Group.

Campbell, J. Y., 1996. Understanding risk and return. Journal of Political economy, 104, 298-345.

(34)

34 Carpenter, R. E., Fazzari, S. M., Petersen, B. C., Kashyap, A. K., and Friedman, B. M., 1994. Inventory investment, internal-finance fluctuations, and the business cycle. Brookings Papers on Economic Activity, 1994, 75-138.

Corsten, D., and Gruen, T. W., 2004. Stock-outs cause walkouts. Harvard Business Review, 82, 26-28.

Danielson, M. G., and Scott, J. A., 2004. Bank loan availability and trade credit demand. Financial Review, 39, 579-600.

Daisuke, T., (2017). Working Capital Management during the Global Financial Crisis: Evidence from Japan.

Deloof, M., 2003. Does working capital management affect profitability of Belgian firms? Journal of business finance and accounting, 30, 573-588.

Deloof, M., and Jegers, M., 1996, Trade Credit, Product Quality, and Intragroup Trade: Some European Evidence, Financial Management 25, 945-968.

Denis, D. J., and Sibilkov, V., 2009. Financial constraints, investment, and the value of cash holdings. The Review of Financial Studies, 23, 247-269.

Ding, S., Guariglia, A., and Knight, J., 2013. Investment and financing constraints in China: does working capital management make a difference? Journal of Banking and Finance, 37, 1490-1507.

Djankov, S., La Porta, R., Lopez-de-Silanes, F., and Shleifer, A., 2008. The law and economics of self-dealing. Journal of financial economics, 88, 430-465.

Dong, H., and Su, J. T., 2010. The relationship between working capital management and profitability: a Vietnam case. International research journal of finance and economics, 49, 62-71.

(35)

35 Falope, O. I., and Ajilore, O. T., 2009. Working capital management and corporate profitability: evidence from panel data analysis of selected quoted companies in Nigeria. Research journal of business management, 3, 73-84.

Fama, E. F., and French, K. R., 1998. Taxes, financing decisions, and firm value. The journal of Finance, 53, 819-843.

Faulkender, M., and Wang, R., 2006. Corporate financial policy and the value of cash. The Journal of Finance, 61, 1957-1990.

Fazzari, S. M., and Petersen, B. C., 1993. Working capital and fixed investment: new evidence on financing constraints. The RAND Journal of Economics, 328-342.

Fazzari, S. M., Hubbard, R. G., Petersen, B. C., Blinder, A. S., and Poterba, J. M., 1988. Financing constraints and corporate investment. Brookings papers on economic activity, 141-206.

Gitman, L. J., 1974. Estimating corporate liquidity requirements: a simplified approach. Financial Review, 9, 79-88.

Harris, M., and Raviv, A., 1991. The theory of capital structure. the Journal of Finance, 46, 297-355.

Havoutis, N., 2003. Optimising working capital: The latest solutions. JP Morgan, New York Hawawini, G., Viallet, C., and Vora, A., 1986. Industry influence on corporate working capital decisions. Sloan Management Review, 15-24.

Hill, M. D., Kelly, G. W., and Highfield, M. J., 2010. Net operating working capital behavior: a first look. Financial management, 39, 783-805.

Howorth, C., and Westhead, P., 2003. The focus of working capital management in UK small firms. Management Accounting Research, 14, 94-111.

(36)

36 Jensen, M. C., and Meckling, W. H., 1976. Theory of the firm: Managerial behavior, agency costs and ownership structure. Journal of financial economics, 3, 305-360.

Jordam, R. W., 2003. Fundamentals of Corporate Finance, 6th ed., McGraw-Hill Companies, Boston

Jose, M. L., Lancaster, C., and Stevens, J. L., 1996. Corporate returns and cash conversion cycles. Journal of Economics and finance, 20, 33.

Juan García-Teruel, P., and Martinez-Solano, P., 2007. Effects of working capital management on SME profitability. International Journal of managerial finance, 3, 164-177.

Júnior, J. L. R., and Laham, J., 2008. The impact of hedging on firm value: evidence from Brazil. Journal of International Finance and Economics, 8.

Kieschnick, R., Laplante, M., and Moussawi, R., 2013. Working capital management and shareholders’ wealth. Review of Finance, 17, 1827-1852.

Kumar, K. B., Rajan, R. G., and Zingales, L., 1999. What determines firm size? Unpublished working paper. National bureau of economic research, Cambridge.

La Porta, R., Lopez-de-Silanes, F., Shleifer, A., and Vishny, R. W., 1997. Legal determinants of external finance. Journal of finance, 1131-1150.

Lazaridis, I., and Tryfonidis, D., 2006. Relationship between working capital management and profitability of listed companies in the Athens stock exchange. Unpublished working paper. University of Macedonia.

Long, M.S., Malitz I.B., and Ravid S.A., 1993, Trade Credit, Quality Guarantees, and Product Marketability, Financial Management 22, 117-127.

(37)

37 Maury, B., and Pajuste, A., 2005. Multiple large shareholders and firm value. Journal of Banking and Finance, 29, 1813-1834.

Modigliani, F., and Miller, M. H., 1958. The cost of capital, corporation finance and the theory of investment. The American economic review, 48, 261-297.

Myers, S. C., and Majluf, N. S., 1984. Corporate financing and investment decisions when firms have information that investors do not have. Journal of financial economics, 13, 187-221. Nazir, M. S., and Afza, T., 2009. Impact of aggressive working capital management policy on firms' profitability. IUP Journal of Applied Finance, 15, 19.

Opler, T., Pinkowitz, L., Stulz, R., and Williamson, R., 1999. The determinants and implications of corporate cash holdings. Journal of financial economics, 52, 3-46.

Petersen, M. A., and Rajan, R. G., 1997. Trade credit: theories and evidence. The review of financial studies, 10, 661-691.

Petersen, M. A., 2009. Estimating standard errors in finance panel data sets: Comparing approaches. The Review of Financial Studies, 22, 435-480.

Pinkowitz, L., Stulz, R., and Williamson, R., 2006. Does the contribution of corporate cash holdings and dividends to firm value depend on governance? A cross‐country analysis. The Journal of Finance, 61, 2725-2751.

Porta, R. L., Lopez-de-Silanes, F., Shleifer, A., and Vishny, R. W., 1998. Law and finance. Journal of political economy, 106, 1113-1155.

Porta, R., Lopez‐de‐Silanes, F., Shleifer, A., and Vishny, R.,2002. Investor protection and corporate valuation. The journal of finance, 57, 1147-1170.

(38)

38 Sagan, J., 1955. Toward a theory of working capital management. The Journal of Finance, 10, 121-129.

Sharma, A.K. and Kumar, S., 2011. Effect of Working Capital Management on Firm Profitability: Empirical Evidence from India. Global Business Review, 12, 159 – 173.

Shleifer, A., and Vishny, R. W., 1997. A survey of corporate governance. The Journal of Finance, 52, 737-783.

Smith, K., 1980. Profitability versus liquidity tradeoffs in working capital management. Readings on the management of working capital, West Publishing Company, St. Paul, New York, 549-562.

Summers, B., and Wilson, N., 2002. An empirical investigation of trade credit demand. International Journal of the Economics of Business, 9, 257-270.

Troilo, M., Walkup, B. R., Abe, M., and Lee, S., 2018. Legal systems and the financing of working capital. International Review of Economics and Finance.

Thompson, S. B., 2011. Simple formulas for standard errors that cluster by both firm and time. Journal of financial Economics, 99, 1-10.

Wasiuzzaman, S., 2015. Working capital and firm value in an emerging market. International Journal of Managerial Finance, 11, 60-79.

Weinraub, H. J., and Visscher, S., 1998. Industry practice relating to aggressive conservative working capital policies. Journal of Financial and Strategic Decision, 11, 11-18.

Woolridge, J. M., 2012. Introductory Econometrics – A modern approach (5). South-Western Cengage Learning, Manson, USA.

(39)

39

7. Appendix

Appendix 1: Definitions of variables

Variables Definition Source

Dependent variable:

Firm Value Tobin's Q = Ratio of market value of equity + total assets - common ordinary equity to total assets. Market value is defined by multiplying shares outstanding with the closing price daily

(Carter, Simkins and Simpson, 2003)

Independent variable:

Excess NWC

Excess NWC = NWC-to-sales ratio - industry median of the NWC-to-sales ratio. The excess NWC is calculated for every year, with all industries used in the Fama French 49-industry classification.

(Aktas, Croci and Petmezas, 2015)

Firm-level moderator:

Dividend payout Ratio of dividends to income before extraordinary items

(Fazzari, Hubbard and Petersen, 1988)

Firm size Firm size is determined as the natural logarithm of total sales

Country-level moderator:

Anti-director index

Based on the protection of minority shareholders in the corporate decision-making process. The index consists of 3 components concerned with shareholder voting: (1) Voting by mail, (2) Shares not deposited, (3) cumulative voting, (4) oppressed minority, (5) pre-emptive rights and (6) capital to call meeting

(Djankov, La Porta, Lopez-de-Silanes and Shleifer, 2008) Anti-self-dealing index

Involves the protection of minority shareholders against self-dealing transactions in favor of controlling shareholders. Finally, the index is calculated by taking the average of ex-ante and ex-post private control of self-dealing. A high value for this index is associated with a high level of investor protection.

(Djankov, La Porta, Lopez-de-Silanes and Shleifer, 2008)

Control variables:

Leverage The ratio of total debt to total assets (used by multiple studies)

Size The natural logarithm of total assets (used by multiple studies)

Sales growth _{The sum of the difference between sales of the current year} minus the previous year to the total sales of previous year

(used by multiple studies)

Profitability (ROA) The ratio of earnings before interests and taxes to total assets (used by multiple studies)

R&D ratio Research and development expenses to total assets (used by multiple studies)

(40)

40

Appendix 2: Two-sample t-tests

Appendix 2.1 Two-sample t-tests based on the anti-director-index

Variable Full sample High investor protection Low investor protection t-statistic

(N=218,275) (N=116,207) (N=102,068) Tobin's Q 1.760 1.592 1.952 56.671 *** Excess NWC 0.050 0.053 0.046 -7.430 *** Size 3.161 3.438 2.847 -110.000 *** Leverage 0.234 0.228 0.240 11.315 *** Sales growth 0.142 0.139 0.146 2.370 ** R&D ratio 0.025 0.015 0.038 55.056 *** Profitability -0.004 0.009 -0.018 -19.417 ***

In this table the means and t-statistics are presented of the two-sample t-tests for all firm variables with the subsamples based on the anti-director-index, for measuring the quality of investor protection. N denote the number of observations within the sample. *, ** and *** are established behind significant coefficients at the 0.10, 0.05 & 0.01 level. Furthermore, variables are winsorized at the 1% level.

Appendix 2.2 Two-sample t-tests based on the anti-self-dealing index

Variable Full sample High investor protection Low investor protection t-statistic

(N=218,275) (N=185,123) (N=33,152) Tobin's Q 1.760 1.791 1.587 -22.984 *** Excess NWC 0.050 0.045 0.078 25.360 *** Size 3.161 3.239 2.726 -65.465 *** Leverage 0.234 0.234 0.231 -1.883 * Sales growth 0.142 0.147 0.113 -8.554 *** R&D ratio 0.025 0.027 0.016 -19.922 *** Profitability -0.004 -0.011 0.034 22.814 ***

(41)

41

Appendix 2.3 Two-sample t-tests based on dividend payout

Variable Full sample Financially constrained Non-financially constrained t-statistic

(N=218,275) (N=142,605) (N=75,670) Tobin's Q 1.760 1.813 1.660 -22.821 *** Excess NWC 0.050 0.060 0.032 -27.968 *** Size 3.161 2.881 3.690 141.762 *** Leverage 0.234 0.252 0.200 -45.333 *** Sales growth 0.142 0.169 0.092 -25.221 *** R&D ratio 0.025 0.033 0.011 -50.289 *** Profitability -0.004 -0.052 0.086 95.340 ***

In this table the means and t-statistics are presented of the two-sample t-tests for all firm variables. The subsamples are based on the dividend payout ratio of firms for measuring financial constraints. N denote the number of observations within the sample. *, ** and *** are established behind significant coefficients at the 0.10, 0.05 & 0.01 level. Furthermore, variables are winsorized at the 1% level.

Appendix 2.4 Two-sample t-tests based on firm size

Variable Full sample Financially constrained Non-financially constrained t-statistic

(N=218,275) (N=109,137) (N=109,138) Tobin's Q 1.760 1.998 1.523 -75.234 *** Excess NWC 0.050 0.075 0.025 -53.229 *** Size 3.161 2.147 4.176 554.806 *** Leverage 0.234 0.220 0.248 25.311 *** Sales growth 0.142 0.192 0.092 -34.356 *** R&D ratio 0.025 0.041 0.010 -73.609 *** Profitability -0.004 -0.074 0.066 101.961 ***

(42)

42

Appendix 3: NWC-to sales ratio by industry

Table 9: NWC-to sales ratio by industry

2007 2017

Industry Median St. dev N Industry Median St. dev N

The effect of financial constraints and investor protection on the relationship excess net working capital and firm value