Journal of Internet Banking and Commerce ISSN: 1204-5357
ISSN: 1204-5357
+44-175-271-2024Faculty of Economics and Management, University of Sfax, Tunisia, Tel: 98418657; Email: nourchenehamza@gmail.com.
Habib AffesFaculty of Economics and management, University of Sfax, Tunisia.
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Bankers on Board; Debt Ratio
Research on corporate finance attached great importance to the banks’ role in the business management. Actually, companies resort to the banking indebtedness. On the other hand, the nature of the relationship between banks and companies depends on the country and the regulations in force. However, in Germany and Japan, where funding is made via banks, the Anglo-Saxon financial markets play an important role in financing and controlling companies. The German companies maintain long term relationships with the so-called bank "Hausbank". One fundamental characteristic of these banks is their participation in both the capital and the funding of companies. The presence of banks in the board of directors is a fundamental feature of the Japanese system. In fact, the Japanese Keiretsu system enables banks to become shareholders and members to the Board of Directors. Kasbi [1] suggests that the leaders’ control by the shareholders substitute the one by banks through their presence in the board of directors. Krozner and Strahan [2] showed that banks sitting on the companies’ boards of directors are rarely their main creditors.
Several studies underlined the relationships between the banks’ appointment in the board of directors, financial conditions [3], the financial distress [2,4,5] the debt ratio [3-5], the investment [3] and the firm’ performance [6].
In this research, the focus is only on the effect of the presence of banks in the board of directors on the companies’ indebtedness. The obtained results are contradictory. Actually, some authors found a positive relationship between the banking presence in the board of directors and the capital structure whereas other authors found a negative relationship. The nature of the relationship between the presence of the banks in the board of directors and indebtedness depends on the composition of the board. In fact, Byrd and Mizruchi [4], state that the board of directors consists of the banking lenders and other non-lenders as well as investors. The bankers consider three scenarios to illustrate the role of the banking administrators: it is the provision of expertise, the ability and the failure of control.
Fama and Jensen [7] state that the outside directors provide expertise and control functions. On the basis of this suggestion, Booth and Deli [8] and Byrd and Mizruchi [4] tried to find out whether the banks’ presence in the board of directors meets an expertise or control need. According to the expertise provision hypothesis, the presence of lenders and other bankers in the board of directors is positively correlated with the firm’s indebtedness ratio. However, the hypothesis of control and of inability to control gives a negative relationship between the presence of the banking lenders and of other bankers in the board of directors and the indebtedness ratio.
Ramirez [9] showed that the bankers’ presence on the boards of directors helps raise the capital.
Booth and Deli [8] and Krozner and Strahan [2] studied the characteristics of companies that affects the probability of having a bank on the board. They also showed that there is a link between the presence of banks on the board of directors and the structure of the companies’ capital. On a sample of companies of the S & P 500 index in 1992, Booth and Deli [8] showed that companies having banks on their board of directors often resort to debt financing compared to companies with no administrator banks provided that these administrator banks have no credit relationship with the company (in other words. non-affiliated governing bankers). However, the authors showed that there is no significant relationship between the bank’s presence in the board of directors and the indebtedness ratio. On a sample of companies, Krozner and Strahan [2] found no significant relationship between the indebtedness ratios and the presence of the banking directors.
Several studies examined the relationship between the presence of banks in the board of directors and the capital structure or the companies’ indebtedness ratio. Moreover, a study by Byrd and Mizruchi [4] is the main reference on the nature of this relationship. Indeed, these authors found that the presence of administrator and lending banks decreases of corporate debt.
Dittmann found that the presence of banks in the board of directors raises the companies’ debt and reduces their value. Accordingly, Ciamarra [5] showed that the banks’ designation in the board of directors led to an increase of the information held by banks about companies, to better control, to a reduction in the cost of information held by the banks, to a decrease of the debt cost, which therefore increases the companies’ indebtedness.
Engelberg [10] and Ferreira [11] found that the presence of banks in the board of directors impact positively the companies’ debt.
Matos [12] using a sample of non-financial U.S firms find that the presence of bankers on board increases the leverage ratio by 22.6%.
Hoshi [13] found that Japanese member companies within Keiretsu have a high indebtedness ratio compared to the independent ones. The authors added that the member companies within Keiretsu depend on indebtedness and more particularly on the Bank otherwise they should not fund their needs by own funds because the market reacts negatively (decline in the share price when financing is carried out through equity capital). In the same framework, Booth and Deli [8] show that the companies where the bank is present in the board of directors are very indebted from independent companies.
Using the system of simultaneous equations over the 2000/2002 period between, Byrd and Mizruchi, Ciamarra [4] tested the impact of the presence of the banks in the board of directors on the indebtedness ratio and found a positive relationship between these two variables. Mitchel and Walker [6] found that designating banks in the board of directors improves the companies’ indebtedness ratio and more specifically for those with financial difficulties or in financial distress and found no relationship for the enterprises having funding constraints. Stearns and Mizruchi [14], Pfeffer [15] and Booth and Deli [8] pointed out that there are significant relationships between the presence of banks in the companies’ board of directors and their debt ratio. They also showed that companies, and more specifically banks, hire financial administrators for their expertise.
Byrd and Mizruchi [4] studied the nature of the relationship between the presence of banks in the board of directors and the companies’ indebtedness ratio and distinguished between lending non lending banks. These authors found that the presence of director lending banks has a negative impact on the indebtedness ratio whereas the presence of administrator non lending banks varies with the likelihood of the companies’ failure. Moreover, Byrd and Mizruchi [4] concluded that administrator bankers can ensure a function of control and a function of service providers. The performance of a function depends both on the company’s situation (information asymmetry, conflicts of interest, financial distress) and its responsibility. Byrd and Mizruchi [4] set out three scenarios that illustrate the role of the administrator banks: the provision of services, the ability and the inability to control.
The research results reached the same conclusion by finding a positive relationship between the presence of investors in the board of directors and the indebtedness ratio. In fact, the investors generally tend to increase their productivity besides, a situation of financial distress does affect not them [2,4]. Berger et al. [16] confirmed this point of view when they found that the firms’ indebtedness increases in the presence of blockholdings.
Hypothesis 1: The presence of investors (blockholders) in the board of directors has a positive impact on the firm’s debt ratio.
The literature presents a set of assumptions about the relationship between the presence of banks in the board of directors and the company’s debt ratio.
First Scenario: Supplying Expertise
Banks expertise is useful in financial markets. According to this hypothesis, banks positively influence the companies’ debt ratio. According to this hypothesis, banks members of the board of directors supply a service to the company and therefore their interests are consistent with the shareholders’. As a consequence, the other non-lending banks and the investors all have a similar effect on the debt ratio. Several studies showed that the outside directors affect the capital structure. Using a sample of 300 outside directors, Lorsch and MacIver's [17] showed the role of these directors in giving advice to the company’s management about the capital structure.
Hypothése 2: the presence of lenders and other bankers in the board of directors is positively related to the company’s indebtedness ratio.
Second Scenario: The Ability to Control
Byrd and Mizruchi [4] stated that the board of directors consists of the lending, the non-lending banks and investors. They showed that if banks members of the board of directors have a control function, as a result, the impact of the lending and non-lending banks on the debt ratio differs from the investors’. The authors pointed out that the lending banks and other non-lending banks play a monitoring role that puts them in conflict with the investors, especially when the risk of financial failure is quite important. They suggested that the other banks can ensure a control function on behalf of the banking community. Moreover, in 1985, they argued that the banks have the motivation on behalf of the community and the ability to act in a coordinated way on behalf of the creditors. On the other hand, Leland and Pyle [18] and Campbell and Kracaw [19] specified that the main largest lending bank is motivated to effectively control and report the quality of its information to the market.
Hypothese 3: The presence of the lenders and other bankers in the board of directors is negatively correlated with the debt ratio
Third Scenario: The Inability to Control
The banks as directors might face several constraints that paralyze them when exercising an effective and active control. These constraints are mainly due to the problems related to their responsibility. The potential of these problems increases with the intensity of the conflict of interests and the constraints of responsibility that can be greater for the lenders who have high benefits of exercising their control function. Byrd and Mizruchi [4] suggested that the lenders may be more impeded in their control than the other bankers who have indirect conflicts of interest. Booth and Deli [8] connected the banker’s role in the board of directors as a controller and his role as provider of expertise. They found out that non lending bankers are associated with higher levels of banking debt, however, there is no significant relationship between the lenders and the debt levels. Booth and Deli [8] concluded that non lending banks act as suppliers of expertise on the boards of directors, whereas the role of the lending banks is not clear (Table 1).
| Hypotheses | Expected signs |
|---|---|
| H1: The relationship between the presence of investors in the board of directors and indebtedness is positive |
+ |
| H2: The relationship between the presence of lenders and other bankers in the board of directors and indebtedness is positive (supply of expertise) |
+ |
| H3: The relationship between the presence of lenders and other bankers in the board of directors and indebtedness is negative (ability to control) |
- |
| H4: The relationship between the banking presence on the board of directors and indebtedness is negative (the inability to control hypothesis) |
- |
Table 1: Hypothesis summary.
Hypothese 4: The presence of bankers in the board of directors is negatively correlated with the debt ratio.
Presentation of the sample
The objective of our research is to analyze the impact of the presence of banks in the firms’ boards of directors on their debt ratio. Regarding the characteristics of our sample, the study focuses on 14 firms listed on the BVMT over a seven-year period between 2003 and 2009, which makes up in all 98 comments. In this research, two types of data are taken into account: financial data and others related to the board of directors’ structure. Financial data are collected from the companies’ financial statements published by the CMF. As for the board of directors’ composition, all the necessary data were collected from the data sheets available from the BVMT values (Tunisian Stock Exchange). By performing Fisher’s test (F-test), it is recognized that our model is either an individual fixed effect or random effect model. The specification of these effects, on the basis of the Hausman test, tells us that the models that adapt to the structure of the sample data are of fixed effects.
Model
Models of Mizruchi and Byrd [4]
Simple linear model: Dettesi=β0,/+β1nbbankca+β2 pret+β3 non-pret+β4 invest+β5 outsiders+β6 logact+β7 collateral+β8 z-score+β9 growth+εi
Model interaction with the Z-score: Debtsi=β0+β1 pret*z-score+β2 non-lend*z-score+β3 invest*z-score+β4 outsiders*z-score+β5 logact+β6 collateral+β7 growthe++β8 dct+εi
β0…β9.: The estimation coefficients
εi: The regression residual
The variables: The variables used in this study are related to the structure of the board of directors, namely the presence of lenders and non-lenders, investors, outside directors. Some control variables, such as the sales growth rate, the firm’s size and the default probability, have been included in the models (Table 2).
| Variables | Significance | Measure |
|---|---|---|
| Dependent variables | ||
| Lev Debts | Indebteness Ratio | Total debts/total assets |
| Variables indèpendantes | ||
| Pret | Lending bankers | Percentage of directors bankers who have a lending relationship with the firm |
| N-Pret | The other bankers | Percentage of director bankers who have no relationship with the firm. |
| Invest | The holders of control blocks | Percentage of unaffiliated directors holding 5% or more of the company’s shares |
| Outsiders | The other external directors | Percentage of the other external directors other than the three categories mentioned above |
| Nbbankca | Number of banks in the board of directors |
Number of banks in the board of directors |
| Control variables | ||
| Growth | The company’s opportunity of growth |
A seven-year average sales (N)-Sales (N-1)/Sales (N) |
| LnTA | The company’s size | The neperian Log of the total asset accounting value |
| NANTIS | The collateral value | Percentage of non-current assets in the total assets |
| ZScore | The likelihood of financial distress |
3.3 (Result exploitation/total assets)+1 (Sales/total assets) +1.4 (non-distributed profit/ total assets)-1.2(working capital/total assets) Working capital=Current assets âÃâ¬ÃâCurrent liabilities Non distributed profit Variation of the results carried over two years |
Table 2: Variables and Measures.
Descriptive Statistics
Table 3 provides a summarizes the descriptive statistics that will be analyzed for each of the following variables: the variable linked to indebtedness, the variables related to the board of directors’ structure and the variables related to other characteristics of the sample companies. The results presented in this table show that the firms of our sample are on average indebted of 66.92% with a minimum of 0.208 per cent and a maximum of 1.566. The study of Byrd and Mizruchi [4] states that companies’ indebtedness is in the order of 30%. Descriptive statistics show that the Tunisian companies’ indebtedness is higher than the one found in the study of Byrd and Mizruchi [4].
| Variable | Obs | Mean | Std. Dev. | Min | Max |
|---|---|---|---|---|---|
| Detteslev | 98 | 0.6692876 | 0.3393827 | 0.002081 | 1.566131 |
| Nbbankca | 98 | 1.959184 | 0.9730213 | 0 | 4 |
| Nbpret | 98 | 0.7346939 | 0.8561605 | 0 | 3 |
| nbnpret | 98 | 1.244898 | 0.963897 | 0 | 4 |
| nbinvest | 98 | 2.183673 | 2.116927 | 0 | 8 |
| nboutsiders | 98 | 4.326531 | 2.666228 | 0 | 9 |
| lnta | 98 | 11.54328 | 0.9671539 | 9.507106 | 13.41303 |
| nantis | 98 | 0.5074624 | 0.3004975 | 0 | 0.953596 |
| zscore | 97 | 0.424221 | 0.7354462 | -0.913478 | 2.746831 |
| oppcroissance | 98 | 0.0501324 | 0.1410897 | -0.6627471 | 0.7270876 |
Table 3: Descriptive statistics 1.
Regarding the board of directors’ structure, the results revealed that the number of investors holding more than 5% of the capital is on average equal to 2 whereas that of the outside directors is on average equal to 4. In the study of Byrd and Mizruchi [4], the number of investors is lower than the one in the Tunisian companies. It is actually about 36% whereas that of the outside directors is equal to 7, which is considerably higher than the one in the Tunisian companies.
On the other hand, the other categories of the board of directors’ members are on average 73.46% and 124.48%, respectively, for both lenders and non-lenders. However, it should be noted that the maximum number of the lenders and non-lenders is respectively 3 and 4. The highest representation of the non-lending bankers compared to lending ones is explained by the formers’ motivation to closely control the debtor firms. The study of Byrd and Mizruchi [4] showed that the percentage of the lenders is lower than that of the Tunisian companies, whereas that of the non-lenders is higher than that of the Tunisian companies.
Moreover, Table 3 shows that the average size of the Tunisian companies measured by the natural logarithm of the total assets is 11.5435 (or 103053.134D) with a minimum of 0 and a maximum of 13. Byrd and Mizruchi [4] found that the size of the firm measured by the active total logarithm log is 4.381 (79.9179Dollars). The Tunisian firms in our sample are smaller compared to the companies in the study by Byrd and Mizruchi [4]. The average value of their collateral is 50.74%, with a minimum of 0 and a maximum of 95.35%.
Furthermore, the firms of this sub sample revealed an average Z-Score of 42.42%, with a minimum-of 91.34% and a maximum of 2.7468. Graham state that an important value of the Z-Score presumes a lesser probability of financial distress and vice versa. It can be deduced that the Tunisian companies are failing, which is also explained by their excessive indebtedness (of the order of 66.92%). The average of the firms’ growth opportunities is relatively low, that is 5%. It has a minimum-of 66.27% and a maximum of 72.70%.
The descriptive statistics given in Table 4 show an average debt ratio equal to 66.92%. Therefore, it can be deduced that the debt ratio remains unchanged even by integrating the ZScore in the first model. Mureover, the interaction of the ZScore with the variables related to the board of directors’ structure has no impact on the debt ratio (the ratio is the same for both models).
| Variable | Variable | Mean | Std. Dev. | Min | Max |
|---|---|---|---|---|---|
| ÃâàDlev | 98 | 0.6692876 | 0.3393827 | 0.002081 | 1.566131 |
| Pzscore | 98 | 0.5782811 | 1.544989 | -0.3660982 | 8.240492 |
| Npzscore | 98 | 0.424796 | 1.06163 | -1.601923 | 5.586673 |
| Iscore | 98 | 0.8853131 | 1.669645 | -2.740434 | 6.348797 |
| Ozscore | 98 | 1.767236 | 3.357492 | -7.153512 | 14.6903 |
| ÃâàLog | 98 | 11.54328 | 0.9671539 | 9.507106 | 13.41303 |
| ÃâàNnt | 98 | 0.5074624 | 0.3004975 | 0 | 0.953596 |
| ÃâàCr | 98 | 0.0501324 | 0.1410897 | -0.6627471 | 0.7270876 |
| Dct | 98 | 0.5490141 | 0.3314111 | 0 | 1 |
Table 4: Descriptive statistics 2.
Regarding the board of directors’ structure, the descriptive statistics show that the average number of lending banks members of the board of directors in interaction with the Tunisian companies’ Z Score is equal to 57.82%, the average number of non-lending banks in the companies’ turnover in an interaction with the Z score is equal to 42.47 %, while the average percentage of investors who are on the board of directors of companies equals 88.53%. On the other hand, the average number of other external directors present in the board of directors of the Tunisian failing companies is equal to 1.76. Therefore, there is a strong presence of investors and non-executive directors in the board of directors of the Tunisian companies. It seems that their presence has a positive influence on the debt ratio of the Tunisian companies.
Correlation Matrix
Correlation matrix 1 and 2 are given in Tables 5 and 6.
| lev | nbbankca | nbpret | nbnpret | nbinvest | nboutsiders | lnta | nantis | zsore | oppcroissance | |
|---|---|---|---|---|---|---|---|---|---|---|
| lev | 1.0000 | |||||||||
| nbbankca | 0.5188 | 1.0000 | ||||||||
| nbpret | 0.1235 | 0.4289 | 1.0000 | |||||||
| nbnpret | 0.4065 | 0.6173 | -0.4459 | 1.0000 | ||||||
| nbinvest | -0.3076 | -0.2701 | -0.0012 | -0.2666 | 1.0000 | |||||
| nboutsiders | 0.1580 | -0.0077 | -0.0752 | 0.0579 | -0.7175 | 1.0000 | ||||
| lnta | 0.6257 | 0.1785 | 0.0670 | 0.1185 | -0.3213 | 0.4375 | 1.0000 | |||
| nantis | 0.1275 | 0.0445 | -0.0139 | 0.0562 | 0.1176 | 0.1043 | 0.2946 | 1.0000 | ||
| zsore | 0.2330 | 0.2297 | 0.4167 | -0.1353 | -0.0388 | -0.0398 | 0.0516 | 0.2623 | 1.0000 | |
| oppcroissance | -0.3272 | -0.1775 | 0.0230 | -0.1960 | -0.1084 | -0.0946 | -0.3883 | -0.2891 | 0.0606 | 1.0000 |
Table 5: Correlation matrix 1.
| Lev | pzscore | npzcore | izscore | ozscore | log | nnt | cr | dct | |
|---|---|---|---|---|---|---|---|---|---|
| lev | 1.0000 | ||||||||
| pzscore | 0.0553 | 1.0000 | |||||||
| npzsco | 0.4249 | 0.0528 | 1.0000 | ||||||
| izscore | 0.1638 | 0.6509 | 0.3517 | 1.0000 | |||||
| ozscore | 0.0936 | 0.4274 | 0.3832 | 0.5055 | 1.0000 | ||||
| log | 0.6272 | -0.0730 | 0.1360 | -0.0475 | 0.0745 | 1.0000 | |||
| nnt | 0.1351 | -0.1341 | 0.3789 | 0.2103 | 0.3339 | 0.3001 | 1.0000 | ||
| cr | -0.3263 | 0.0999 | -0.0026 | 0.0160 | 0.0763 | -0.3873 | -0.2857 | 1.0000 | |
| dct | -0.3960 | 0.3405 | 0.1453 | 0.3333 | 0.2830 | -0.5744 | -0.1143 | 0.3350 | 1.0000 |
Table 6: Correlation matrix 2.
The results show that all the Pearson correlation coefficients are below 0.7, a limit beyond which a multicollinearity problem arises. This indicates that there is no multicollinearity between the independent variables included in the model.
Table 7 shows the first equation results which measure the direct impact of the presence of lenders and non-lenders, that is the composition of the board of directors, on the debt ratio, whereas Table 8 gives those of the second equation which includes the interaction terms of between the probability of financial failure (ZCORE) and the composition of the board of directors.
| Variables | Coefficient | p-value |
|---|---|---|
| Constante | 2.435616 | 0.004 |
| Nbbankca | -0.047122 | 0.634 |
| Nbpret | -0.0212652 | 0.829 |
| Nbnpret | 0.0030006 | 0.975 |
| Nbinvest | -0.0620177 | 0.000 |
| nboutsiders | -0.038086 | 0.012 |
| LnTA | -0.1206639 | 0.082 |
| Nantis | -0.0160647 | 0.784 |
| Zcore | 0.0623754 | 0.151 |
| Oppcroissance | -0.1482641 | 0.202 |
Table 7: Linear regressions of the board of directors' composition on the debt ratio (simple linear model).
| Variables | Coefficient | p-value |
|---|---|---|
| Lnta | -0.1382707 | 0.020 |
| Nantis | 0.0116738 | 0.839 |
| oppcroissance | 0.0804454 | 0.446 |
| Prtzscore | -0.0301212 | 0.009 |
| npretzscore | 0.112724 | 0.000 |
| Investzcore | -0.0252329 | 0.044 |
| Outzscore | -0.037065 | 0.000 |
| Dct | 0.2254381 | 0.037 |
| Constante | 2.178904 | 0.002 |
Table 8: Linear regressions of the board of directors’ composition on the debt ratio (a model interacting with the Z-Score).
On introducing the interaction ZScore variable in model.2, the significance of the lending banks changes but the associated coefficient remains negative. The presence of the lending banks in the board of directors helps ensure a follow-up and control role.
The significance of non-lending banks changes but the coefficient remains positive. The presence of non-lending banks in the board of directors plays an expertise role. On introducing the ZSCore in model 2, the significance and the coefficient associated with investors and other outside directors, and of the company’s size measured by the natural logarithm of the total assets do not change.
Regarding the control variables, namely the intangibility of the collateral and the growth opportunities, the associated factors change and become positive. The analysis of these results is oriented towards the identification of the impact of the bankers and investors’ presence in the financial companies’ boards of directors on their debt ratios.
First of all, the emphasis is on the appointment of investors holding more than 5% of the firm’s capital where it appears that this appointment causes a decrease of the debt ratio. This is explained on the basis of the significant negative coefficient (β=-0.06201). This result confirms the findings of Byrd and Mizruchi [4]. This decrease of the debt ratio related to the presence of investors in the boards of directors depends on the likelihood of the firm’s financial distress. The term interaction with the Z-Score is significantly negative (-0.0252329, p=0.044). Once the investors’ effect on the companies’ debt ratios is identified, the effect of appointing a banker in the board of directors of a non-financial company will be determined.
As described in the literature, there are three scenarios related to the impact of the presence of banks in the board of directors on the debt ratios: a positive impact of the banks in the board performing the role as providers of expertise and a negative impact showing that it is either about efficient controllers or about those who are unable to control.
On examining the results in Table 7, there is a significantly negative direct effect (β=-0.0212652, p=0.829) of the lenders on the debt ratio. This result confirms the findings of Byrd and Mizruchi [4]. Similarly, the term interacting with the Z-Score is significant and negative (β=-0.0301212, p=0.009), which makes the effect of the presence of lending banks in the board of directors on the debt ratio independent of the probability of companies’ failure. This result shows that the lenders are either efficient controllers or incapable of control, which will result in a reduction of the firm’ debts.
Regarding the effect of the other (non-lenders) bankers on the debt ratio, the linear regression results presented in line A show a positive and non-significant direct effect (β=0.0030006, p=0.975) of the other bankers on the debt ratio. The interaction term of this category of administrators with the Zcore is also significantly positive (β=0.1127241, p=0.000). Thus, unlike with the lenders, the impact of other (non-lenders) bankers on the firms’ debts ratio highly depends on the probability of financial distress.
Furthermore, it seems that the likelihood of financial distress is an important factor that affects the companies’ debt ratios. However, the firms’ size, the collateral value and growth opportunities have a negative impact on this ratio. The result association regarding the lenders and other (non-lenders) bankers shows that the formers have a negative impact on the debt ratio whereas the latters have a positive one. For the first case, the result shows that director bankers serving in the board of directors of non-financial firms are assigned a role of efficient or inefficient controllers. In the case of non-lenders, the result confirms that administrator bankers play a role of expertise providers rather than supervisors.
In this study, we examined the impact of the presence of banks on the board of directors on the debt ratio of the Tunisian companies. We find that the impact depend on the role of bankers, the composition of the board and vary with the interaction of the Z-Score in the linear model.
For this reason, two models are used: the first is simple and linear whereas the second is in interaction with the Z-Score. The results showed that the presence of lenders in the board of directors has a negative impact (control hypothesis) and the presence of non-lenders positively acts on the debt ratio (providers of expertise hypothesis). Furthermore, a negative relationship was found between the presence of investors and external directors in the board of directors and debt. The same results were also found when the failure variable measured by the Z-Score is integrated in the linear model.
Regarding the control variables, the results about the first simple linear model showed there is a significant negative relationship between the firm’s size and indebtedness, and insignificant negative relationship between collateral value, the firms’ growth opportunities and indebtedness. However, the relationship between the likelihood failure and indebtedness is positive and insignificant.
Regarding the model interacting with the Z Score, the results showed an insignificant positive relationship between the collateral value, the growth opportunities, short term debts and indebtedness. However, the relationship between the firm’s size and indebtedness is negative and significant.
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