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Journal of Small Business and Enterprise Development Impact of ownership structure on capital structure of New Zealand unlisted firms Nirosha Hewa Wellalage Stuart Locke

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Article information: To cite this document: Nirosha Hewa Wellalage Stuart Locke , (2015),"Impact of ownership structure on capital structure of New Zealand unlisted firms", Journal of Small Business and Enterprise Development, Vol. 22 Iss 1 pp. 127 - 142 Permanent link to this document: http://dx.doi.org/10.1108/JSBED-09-2011-0004 Downloaded on: 03 March 2015, At: 13:41 (PT) References: this document contains references to 60 other documents. To copy this document: [email protected] The fulltext of this document has been downloaded 56 times since 2015*

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Impact of ownership structure on capital structure of New Zealand unlisted firms Nirosha Hewa Wellalage and Stuart Locke Department of Finance, University of Waikato Management School, Hamilton, New Zealand

Impact of ownership structure 127 Received 15 September 2011 Revised 4 July 2012 Accepted 12 August 2014

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Abstract Purpose – The purpose of this paper is to use a panel of New Zealand unlisted firms from 1998 to 2009 to examine the relationship between ownership structure and firm leverage ratios. Although, the choice of the debt in capital structure is important for all firms, the scale effects may influence the degree of influence of particular financial theories upon capital structure. Design/methodology/approach – To control the endogeneity effect of insider ownership, this study uses the dynamic panel generalised method of moment estimation and uses the Granger causality test to check the causality effect of leverage and insider ownership. Findings – The findings suggest an inverse U-shape relationship of insider ownership and leverage, indicating higher insider ownership increases management entrenchment while lower insider ownership increases misalignment of the interests of management and owners. Moreover, this study finds bi-directional causation between insider ownership and firm leverage ratios. Practical implications – Finance policy needs to vary across firm type, industries and firm characteristics and should match the different borrowing requirements of small business. Originality/value – This paper contributes to literature by investigating whether the structure of equity ownership can impact cross-sectional variations in capital structure. Moreover, most of the capital structure research has been conducted in large markets like USA and publicly listed firms but this paper concentrates on the evidence from New Zealand unlisted businesses. Also, the econometric analysis is more robust due to controlling for the endogeneity effect of insider ownership. Keywords New Zealand, Insider ownership, Leverage, Small business Paper type Research paper

Introduction This paper investigates the relationship between insider ownership and capital structure choice by small businesses. The choice of the debt in capital structure is important for all firms. Since the work of Modigliani and Miller (1958), many studies have looked at the question of optimal debt level of a firm and why they choose that particular level. Large firms take on debt financing to gain tax benefits and the cheaper costs of debt compared to equity. However, Myers (1984) explains that while firms can take advantage of debt for tax deductibility, they need to be careful not to increase their risk of bankruptcy not too much to avoid the increase the risk that the firm will go bankruptcy. Institutional differences may determine the considerable variation in the use of debt. Scale effects may influence the degree of influence of particular financial theories upon capital structure. This is confirmed by Ray and Hutchinson (1983) who show that many small and medium enterprises (SMEs) use little debt or none at all. The differences between large and small firms’ financing decisions may be a direct function of the owner-manager (Cassar and Holmes, 2003). Vos et al. (2007) explain that the connectedness of SMEs create different environment from the “separate” structure of publicly listed companies. Information asymmetry is part of the moral hazard problem

Journal of Small Business and Enterprise Development Vol. 22 No. 1, 2015 pp. 127-142 © Emerald Group Publishing Limited 1462-6004 DOI 10.1108/JSBED-09-2011-0004

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128

and is more likely arise in small firms due to their close nature (Watson and Wilson, 2002). Therefore, smaller firms have less outside financing or lower debt. Moreover, risk-averse owner-managers are often reluctant to use optimal debt levels in their SMEs because they have invested a larger proportion of their personal wealth in the firm. SMEs are widely regarded as the engine of economic growth both in developing and developed nations. New Zealand business is predominantly SME based (SMEs in New Zealand: Structure and Dynamics, 2009) and provides an interesting case study for SMEs, firm financing policy and ownership structure. They are substantial generators of local- and broad-based employment, promoters of indigenous entrepreneurship, innovation and providers of goods and services to local and wider populations. Although the government is concerned about providing an economic and regulatory environment for SMEs to grow and sustain, lack of finance has continued to be a major concern and the main cause for untimely failure of many SMEs (Liedholm and Mead, 1993). According to Business Finance in New Zealand (2004) large businesses with more than 100 employees have a 16 times higher average debt amount per enterprise than smaller firms with fewer than 20 employees. Moreover, New Zealand bankruptcy laws do not provide homestead exemptions and future earnings exemptions for SME owners. Therefore, studies regarding SME capital structure are important. The Ministry of Economic Development (2010), New Zealand shows 68.8 per cent of SMEs in New Zealand have 100 per cent insider ownership. This figure exhibits the high existence of insider ownership in New Zealand SMEs. Hence, owner-managers may have significant impact on capital structure decisions. After controlling for endogeneity effects of insider ownership, this paper finds an inverse U-shape relationship between internal ownership and leverage ratio indicative of managerial entrenchment. This study also finds bi-directional causation between insider ownership and firm leverage ratio. This paper contributes to literature by investigating whether the structure of equity ownership can impact cross-sectional variations in capital structure. Moreover, most of the capital structure research has been conducted in the large markets like USA and publicly listed firms, but this paper concentrates on evidence from unlisted businesses in New Zealand. Following Pindado and Torre (2011) this study uses the generalised method of moment (GMM) dynamic panel technique to control the endogeneity effect of insider ownership in small firms, which makes the econometric analysis more robust. The majority of recent studies have ignored the endogeneity effect of insider ownership, even though they explored the use of the 2SLS regression technique. The next section of the paper reviews prior research and develops the hypotheses. It is followed by discussion of the data, variables, method and procedures used for this empirical study. The findings and implications then follows. Literature review The literature suggests that firm ownership structure has a significant influence on the firm operating risk which has subsequent implications for financial leverage. Apart from the firm-specific characteristics (size, growth, risk, profitability, tangibility and industry) firm equity ownership has a significant impact on firm capital structure (Hewa Wellalage and Locke, 2011; Pindado and Torre, 2011). Managerial share ownership is widely used in small business as a mechanism to reduce agency conflicts between managers and owners. However, the exact relationship between managerial ownership and capital structure is inconclusive (Brailsford et al., 2002). Watson and Wilson (2002) find closely held firms are more likely to retain earnings

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in the business and therefore, the possibility of access external financing is less. Using Irish SMEs, Bhaird and Lucey (2010) find evidence of lower usage of external finance in small business, indicating a desire to retain control and their debt levels can be lower than less closely held firms. Recently, some studies have found a non-linear relationship between the levels of insider ownership and leverage. The one possible explanation for that is, according to “convergence of interest” hypothesis, insider ownership is positively related to a firm’s debt level. This may be because a high level of insider ownership increases monitoring and reduces free-rider problems. Hence, high insider ownership increases debt ratios, because when monitoring by shareholders, managers cannot maintain low levels of debt to their own interests (Pindado and Torre, 2011). However, after a certain level of insider ownership, managers become entrenched and seek to reduce the risk. This may be because entrenched managers avoid having high risk through high level of debt (Fama, 1980), or they avoid the disciplinary role of debt ( Jensen, 1986). As a result, insider ownership shows a negative relationship with firm debt level. Therefore, a testable hypothesis regarding the level of insider ownership and total debt level in small business is: H1. Small business leverage levels will be lower at both low and high levels of insider ownership. Due to higher bankruptcy costs, lower marginal corporate tax rates and high-asymmetry information, small firms have proportionately less debt than larger firms (Michaelas et al., 1999). Studies of the determinants of New Zealand firm’s capital structure have also confirmed that large companies tend to use more leverage than small firms. As an example, Business Finance in New Zealand (2004) explains only 29 per cent of businesses with one-to-five employees request debt financing compared with 40 per cent of large firms. This may be due to the following reasons. First, larger firms may have higher credit ratings than their smaller counterparts and therefore it is easier to access external financing due to lower information asymmetry (Subadar et al. 2010). Second, larger firms are likely to have higher debt levels to maximise the tax benefits from debt (Rajan and Zingales, 1995). Cassar (2004) argues that due to that high cost of external borrowing, small firms may prefer lower level of debt than larger firms. This is in line with Titman and Wessels (1988) who explain that smaller scale financing results in relatively higher transaction costs. Based on agency costs theory, Um (2001) argues that due to lower monitoring costs in larger firms, larger firms tend to be using more debt than smaller firms. A testable hypothesis regarding the firm size and firm debt level in small businesses is: H2. Firm size is significantly positively related to small business debt levels. Prior studies find mixed results for firm growth and debt level. Brailsford et al. (2002) explain firm growth rate as proxy for available internal funds. Consequently, based on pecking-order theory, firms with high growth rates have a negative relationship with external financing (Myers and Majluf, 1984). Moreover, according to trade-off theory, firms with high growth rates tend to use less external financing, because growth rate is non-collateralised. Additionally, based on agency theory, Myers (1977) and Al-Najjar and Taylor (2008) find that firms with high growth rates tend to use less debt to mitigate agency conflicts that arise due to high information asymmetry. Rajan and Zingales (1995) find two main reasons for a negative relationship between firm growth

Impact of ownership structure 129

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and debt level. First, it is expected that as growth opportunities increase, the cost of financial distress also increases. Second, firms prefer to issue overvalued equity. A testable hypothesis regarding firm growth and firm debt level in small businesses is: H3. Firm growth is significantly negatively related to small business debt levels.

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130

Based on pecking-order and trade-off theories, a firm’s volatility of earnings (operating risk) increases probability of default because debt holders consider a firm’s future earnings as protection for debt (Mehran, 1992). Therefore, high-risk firms may have a negative impact on firm leverage levels. Aligned with that, Subadar et al. (2010) find a significant negative relationship between Mauritius financial firms’ risk and leverage levels. This is consistent with McConnell and Pettit (1984), who explain that high-risk firms have higher probability of bankruptcy because they tend to have less gearing. Testable hypothesis regarding firm risk and firm total debt level in small businesses is: H4. Firm risk is significantly negatively related to small business debt levels. Prior studies indicate that SME capital structure behaviour typically follows a pecking order trait (Ou and Haynes, 2006; Sogorb-Mira, 2005). Difficulties with access to and availability of external financial sources may be the main reason that small firms rely on internal sources of finance. This is consistent with Jordan et al. (1998) who find that even though more profitable SMEs have more ability to access external finance, they prefer to have internal sources of funds to finance their operations and investments. This may be because they do not like to dilute their ownership by external financing. Hence, even profitable SMEs prefer to have internal funds. Additionally, smaller companies are usually owned and managed by a single owner or family members, and they are operating without any knowledge of firm capital structure. As a result, financing is based on internally generated funds; external funds are less preferred. Therefore, testable hypothesis regarding firm profitability and debt level in small businesses is: H5. Firm profitability is negatively significantly related to small business debt levels Firms with higher proportion of tangible assets will be in a position to provide more collateral in their debts. Totally, 72 per cent of New Zealand’s external debt financing is provided by banks (Business Finance in New Zealand, 2004) and the collateral requirements of banks have a significant effect on determining capital structure in New Zealand firms. This is confirmed by Business Finance in New Zealand (2004) which indicates that due to insufficient collateral, 31 per cent of debt requests were rejected in New Zealand. Agency theory suggests that issuing debt secured by collateral may reduce the information asymmetry-related costs in financing. Tangible assets always reduce financial distress costs due to their high liquidation value (Harris and Raviv, 1991; Titman and Wessels, 1988). Prior research finds a positive relationship between firm leverage and its collateral (Frank and Goyal, 2002; Um, 2001). Nuri (2000) finds a positive relationship between firm tangibility and long-term debt and this finding is consistent with Bevan and Danbolt (2000, 2002), Van-der-Wijst and Thurik (1993) and Stohs and Mauer (1996) who indicate a positive relationship between tangibility and long-term debt. Therefore, SMEs with more tangible assets have more opportunity to issue more debt. A testable hypothesis regarding firm tangibility and firm debt level in small businesses is: H6. Firm tangibility is significantly positively related to small business debt level.

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The relationship between industry type and its effect on firm capital structure has received considerable attention in recent literature. This is confirmed by Roberts and Dowling (2002) who analyses average leverage ratios of 50 US industries and finds the degrees of leverage ratios vary from 9 per cent to a 54 per cent among industries. Bradley et al. (1984) find that industry alone has been found to explain up to 25 per cent of within-country leverage variation. Further, Jordan et al. (1998) explain that firms in the same industry have more common leverage ratios than firms from different industries. This may be because asset risks, asset prices and industry tax codes vary among industries. It may also be that a firm’s optimal capital structure will be industry related in part, because of the evidence that tax rates vary across industries (DeAngelo and Masulis, 1980). However, Jordan et al. (1998) explain that since SMEs often operate in niche markets, this would reduce the impact on industry differences in their capital structure. Testable hypothesis regarding the industry in which firms operate and firm total debt levels in small businesses is: H7. Firm operating industry is significantly related to small business debt levels. Data, variables and measure The sample of New Zealand unlisted small businesses, covering the period 1998-2008 inclusive, was made available by the Management Research Centre at the University of Waikato. The data are collected annually in conjunction with the New Zealand Institute of Chartered Accountants as part of a financial benchmarking reporting programme, and the total time series reaches back to 1982. The 11-year period is chosen to ensure there are adequate businesses in the sample as the data for earlier years is sparse. The random sample is drawn from accounting practices that prepare end of year financial returns for as many as 1,000 small businesses each year. After adjustments, the data set provides 1,320 observations from a total of 120 businesses appearing each year (Table I). Variables and measures Following prior studies, this study used total debt to total assets (DEBT) as the dependent variable (Brailsford et al., 2002; Roshan, 2009). The main explanatory variable is insider ownership percentage (OWNER). This main ownership structure explanatory variable is further divided into five categories: insider owner 0 per cent group (NIL), insider owner 0-25 per cent (LOW), insider owner 25-50 per cent (MEDIUM), insider owner 50-75 per cent (HIGH) and insider owner ⩾75 per cent (HIGHEST). As indicated by Ang et al. (2000) 100 per cent ownership firms used as no-agency cost base firms for comparison. Consistent with prior literature this study uses the following explanatory variables. Firm size (LNASSETS), industry type (INDUS), growth (GROWTH), profitability (PROFIT), tangibility (TANGI) and risk (RISK). These explanatory variables are used to distinguish the effect of the insider equity ownership on capital structure on risk, agency costs and assets specificity (Brailsford et al., 2002). Table II reports the descriptive statistics for the data. The mean value of DEBT is 0.84, with a range 0.002-21.39, suggesting smaller firms have lower debt levels. The approximation of the mean value for insider ownership is 39 per cent; the highest percentage of insider ownership is 100 per cent in the small business sample. This highlights the existence of high insider ownership in small businesses. Approximately 4 per cent of sample firms have zero insider ownership. Moreover, 36 and 43 per cent of sample firms have 0-25 per cent and 25-50 per cent insider

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Table I. Variable definition

Variable name

Definition

Dependent variables Total liability ratio (DEBT) Explanatory variables Insider ownership (OWNER) Ownership percentage NIL LOW MEDIUM HIGH HIGHEST Firm size (LNASSETS) Growth (GROWTH) RISK (RISK) Profitability (PROFIT) Tangibility (TANGI) Industry (INDUS1) Industry (INDUS2) Industry (INDUS3) Industry (INDUS4)

Variables DEBT OWNER NIL LOW MEDIUM HIGH HIGHEST LNASSETS GROWTH RISK PROFIT TANGI INDUS1 INDUS2 INDUS3 Table II. Descriptive statistics INDUS4

This ratio is defined as total liabilities divided by total assets This percentage is calculated as total number of working owners divided by sum of total number of working owners plus total number of employees Percentage of working owner ¼ 0 Percentage of working owner W 0 and o25 Percentage of working owner ⩾25 and o50 Percentage of working owner ⩾50 and o75 Percentage of working owner ⩾75 Log number of total assets This is calculated as percentage change in value of assets This is calculated as total sales is divided by total assets This ratio is calculated as net profit is divided by total assets This ratio is calculated as total fixed assets is divided by total assets Dummy variable 1, if the industry is equal to primary, otherwise ¼ 0 Dummy variable 2, if the industry is equal to energy, otherwise ¼ 0 Dummy variable 3, if the industry is equal to good, otherwise ¼ 0 Dummy variable 4, if the industry is equal to services, otherwise ¼ 0

Obs

Mean

SD

Min.

Max.

1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320 1,320

0.8397187 0.3876501 0.0393939 0.3628788 0.4310606 0.0431818 0.1234848 12.82113 0.2303587 3.566285 0.4328174 0.4525824 0.1 0.0030303 0.5068182 0.3833333

0.9224129 0.3078092 0.1946041 0.4810125 0.4954122 0.2033432 0.3291176 1.309723 1.407622 4.958453 1.750568 0.2990364 0.3001137 0.0549856 0.500143 0.4863827

0.0020614 0 0 0 0 0 0 8.055107 −0.7341936 0.060639 −1.639888 −0.6662024 0 0 0 0

21.38762 1 1 1 1 1 1 17.19288 30.00886 72.5558 55.90533 0.9996139 1 1 1 1

ownership percentage, respectively. Next, 4 per cent of the sample has 50-75 per cent insider ownership and 12 per cent of sample firms have ⩾75 per cent insider ownership. Results indicate that sample firm growth rate is 0.23. This may be because a considerable proportion of smaller firms are sole-proprietorships and their assets’ growth is low. This finding is consistent with Carpenter and Petersen (2002), who find that the growth of small firms is constrained by internal finance. According to Table II, the RISK variable indicates a mean value of 3.56. This value

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indicates high volatility in small firms’ cash flows. The mean value of PROFIT variable is 0.43 and indicates small firms in New Zealand are profitable. Firm tangibility mean value is 0.45, indicating a large proportion of total assets comes from fixed assets. The correlation matrix in Table III indicates that ownership explanatory variables are significantly correlated with firm debt level, which offers tentative support for the claim that firm insider ownership interacts with the leverage levels of small businesses.

Impact of ownership structure 133

Method Panel data covering 11 years of variables for 120 businesses was prepared initially. Prior studies have used panel OLS to control heterogeneity over time and across firms. However, panel OLS requires that the independent variables are strictly orthogonal to the error term, and that these errors are independently and identically normally distributed with a mean of zero and variance equal to σ2. If the strict exogeneity condition fails, then panel OLS will be inconsistent. The Durbin-Wu-Hausman test can be used as a diagnostic test for endogeneity of dependent variable proxies and the insider ownership variable. The estimator was first introduced by Holtz-Eakin et al. (1988) and Arellano and Bond (1991). First-differencing removes the potential for unobservable heterogeneity bias. After first-differencing, estimates are obtained via GMM using lagged values of the explanatory variables as instruments for the explanatory variables: X DY itp þ bDX it þ gDZ it þ Deit p 4 0 (1) DY it ¼ p þ kp p

DEBT NIL LOW MEDIUM HIGH HIGHEST LNASSETS GROWTH RISK PROFIT TANGI INDUS1 INDUS2 INDUS3 INDUS4 GROWTH RISK PROFIT TANGI INDUS1 INDUS2 INDUS3 INDUS4

DEBT 1.0000 −0.0309*** 0.0314*** 0.0099* −0.0215** −0.0292*** −0.2461*** 0.0307 0.4541*** 0.3364*** −0.0343 −0.0604** −0.0338 −0.0426 0.1271*** GROWTH 1.0000 −0.0163 −0.0029 0.0342 −0.0044 −0.0139 −0.0306 0.0240

NIL

LOW

MEDIUM

HIGH

1.0000 −0.1528*** −0.1763*** −0.0430 −0.0760*** 0.1279*** −0.0090 −0.0367 −0.0440 0.0216 −0.0441 0.0509** −0.0102 0.0541** RISK

1.0000 −0.6569*** −0.1603*** −0.2833*** 0.4235*** −0.0503 0.0855** −0.0519** −0.0408 −0.0125 0.0048 −0.1242*** −0.0306 PROFIT

1.0000 −0.1849*** −0.3267*** −0.1934*** −0.0192 −0.0270 0.0187 −0.0847** −0.0544** −0.0288 0.1470*** −0.0125 TANGI

1.0000 −0.0797*** −0.1084*** 0.0698* −0.0538** −0.0042 0.1052*** 0.0485 0.0476** −0.0287 0.0717*** INDUS1

HIGHEST LNASSETS

1.0000 −0.3363*** 0.0645* −0.0293 0.0764*** 0.1095*** 0.0963*** −0.0231 −0.0161 −0.0126 INDUS2

1.0000 0.5226*** 1.0000 −0.2066*** −0.0761*** 1.0000 −0.1256*** 0.0108 0.2523*** 1.0000 −0.0335 −0.0108 0.0562** −0.0212 1.0000 0.1504*** 0.0328 −0.4421*** −0.3473*** −0.0624** 0.0364 −0.0020 0.3990*** −0.1634*** −0.0294

Notes: *,**,***Correlation is significant at 10, 5 and 1 per cent level, respectively

1.0000 −0.0395 −0.3330*** −0.2552*** 0.0135 0.0992*** 0.0667** −0.0334 −0.2167*** INDUS3 INDUS4

1.0000 −0.4820***

1.0000

Table III. Correlation matrix

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An important aspect of the dynamic panel estimator is that it uses the firms’ histories as instruments for explanatory variables. If the exogeneity assumptions are valid, then we can write following orthogonality conditions: E ðX its eit Þ ¼ E ðZ its eit Þ ¼ E ðY its eit Þ ¼ 0

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134

8s4 p

(2)

Arellano and Bover (1995) and Blundell and Bond (1998) further develop the GMM estimator using first differenced variables as instruments for the equations levels in a stacked system of equations that include the equations in both levels and differences. However, the equations in the stacks may include unobservable heterogeneity. To deal with this problem, it is assumed that the ownership and other control variables exhibit a constant correlation over time. This assumption leads to an additional set of orthogonality conditions: E ½DX its ðni þ eit Þ ¼ E ½DZ its ðni þ eit Þ ¼ E ½DY its ðni þ eit Þ ¼ 0

8s4 p

(3)

A GMM panel estimation uses the orthogonal conditions of (2) and (3) equations under the assumption that there is no serial correlation in the error term, e. The analysis includes a Hansan/Sargan over-identification test for serial correlation to ensure this model specification validity. The test produces a J statistic that is distributed X2 with J-K degrees of freedom, where J is the number of instruments and K is the number of regressors under the null hypothesis of valid instruments. Panel unit root test Unit root tests, such as the well-known test augmented Dickey-Fuller test (ADF), can be used to determine whether the time series variables are non-stationary. An extension of ADF testing, developed by Levin et al. (2002), is referred to as Levin Lin Chu (LLC) is in this study. Implementing unit root tests on a pooled-cross-section data set provides improvements in statistical power compared with performing separate unit root tests. The LLC test is appropriate for a common autocorrelation coefficient, i.e. a homogenous α, and the null hypothesis is that each individual time-series contains a unit root against an alternative hypothesis that each time-series is stationary. This test method produces a single t-ratio for the panel data and this statistic is shown to have a standard normal distribution. It is assumed that each company insider ownership percentage contains a unit root and the first difference of the insider ownership percentage follows a stationary (auto regressive (AR) moving average model) ARMA process. Under the alternative hypothesis, all the insider ownership percentage, taken as a group, is assumed to be stationary: DP ij; t ¼ C ij þ pj P ij; t1 þ

kð j Þ X

bhj DP ij; th þ eij; t

h¼1

If the test statistics indicate a high level of significance, the null hypothesis is not accepted, indicating that each individual time-series does not contain a unit root. Granger causality test in panel data model The research also employs the Granger (1969) causality test. This approach tests whether X causes Y and considers how much the current Y can be explained by past values of Y and whether adding lagged values of X can improve the explanation. Y is said to be Granger-caused by X, if X helps in the prediction of Y, which is equivalent to

the coefficients of the lagged Xs being statistically significant. The Granger test is predicted on the following regression form: X X Y t¼ b0 þ b1i Y t1 þ b2i X t1 þ mt X t¼ p0 þ

X

p1i Y t1 þ

X

p2i Y ti þ vt

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where Yt and Xt are variables to be tested. Findings Table IV, the regression analysis, is undertaken in six steps using the panel data. These six steps involve regressing the ratio of total debt to total assets on each of the variables while controlling for managerial ownership variables (OWNER, NIL, LOW, MEDIUM, HIGH, HIGHEST). Due to using the lag variable as an instrument variable, and the dynamic behaviour of the regression model, Table IV only contains 999 observations. Columns 2 of Table IV present the relationship between insider ownership percentage and leverage ratio results and columns 3-7 present dynamic panel GMM results of insider ownership sub-samples. Firm leverage is found to be correlated with variables in previous studies. In Table IV, column 2 shows 1 per cent significant negative relationship between firm leverage ratio and insider ownership, indicating managerial ownership reduces external debt level. One possible explanation for that is when the level of managerial ownership increases, control over the firm passes from external shareholders to managers. At a certain point, management entrenchment arises, and it leads managers to adopt a lower level of debt, thereby avoiding substantial risk. Further, based on agency costs theory, Friend and Lang (1988) explain that managers prefer lower debt levels as a method of reducing the non-diversifiable employment risk. This situation may be worsening, especially in sole proprietorships and partnerships without employees. Firm size has a negative effect on DEBT ratio at 1 per cent significance level, indicating SME size has a significant impact on leverage. This finding is consistent with Rajan and Zingales (1995) study of publicly listed firms. They argue that due to the complex structure of information, asymmetry levels are higher for larger firms and they do not intend to have higher levels of debt. The coefficient on the growth variable (GROWTH) is negatively and statistically significant at 10 per cent level for DEBT variable, indicating firms with strong growth rely less on outside financing. This is consistent with Cotei and Farhat (2009) who studied US-listed business. The one possible explanation for that is highly growing small firms have sufficient internal funds for their financing needs. A significant positive relationship between risk and total debt level is observed for small businesses. This finding is in line with limited empirical studies that find a positive relationship between a SME’s risk and leverage (Jordan et al. 1998; Michaelas et al., 1999). Furthermore, this finding is consistent with agency theory, which predicts a positive relationship between risk and leverage, because risk intensifies a negative impact on asymmetric information (Schoubben and Hulle, 2004). Furthermore, as can be seen from Table IV, column 2, small firm profitability is positively statistically significant at 1 per cent level for the DEBT variable, indicating profitability increases a firm’s total debt level. This finding is consistent with Baum et al. (2007) and Um (2001); they find a significant positive relationship between firm profitability and debt level. This may be because highly profitable small firms rise to

Impact of ownership structure 135

Table IV. Dynamic panel GMM regressions of insider ownership and leverage ratio

PROFIT

RISK

GROWTH

LNASSETS

Percentage of working owners ⩾75(HIGHEST)

Percentage of working owners (⩾50 and o 75)(HIGH)

Percentage of working owners (⩾25 and o50)(MEDIUM)

Percentage of working owners (0Wand o25)(LOW)

Percentage of working owners ¼ 0(NIL)

Insider ownership percentage (OWNER)

Lnopexal L1.

Number of obs Number of groups ¼ 100 Regressor

(4)

(5)

(6)

(7)

−0.0586924** (0.028518) 0.1470702*** (0.0185642) 0.0115446** (0.0136652)

−0.1080945*** (0.0231604)

999 999 999 999 999 Dynamic Dynamic Dynamic Dynamic Dynamic GMM-1 GMM-2 GMM-3 GMM-4 GMM-5 −0.0617278*** −0.0578562*** −0.0625013*** −0.0628214*** −0.0632009*** (0.0028315) (0.0021584) (0.0022761) (0.002255) (0.0025596)

(3)

(continued )

−0.2198853*** (0.0188544) −0.1516387*** −0.0945144*** −0.1180895*** −0.09627*** −0.1003319*** −0.1168006*** (0.0076701) (0.0065969) (0.0068998) (0.0066078) (0.0065948) (0.0062033) −0.0071073* −0.000256 −0.0072033** 0.0000299 −0.0008092 0.0032811 (0.0039807) (0.0044449) (0.0040773) (0.0041037) (0.0046196) (0.0039622) 0.0674456*** 0.0740368*** 0.0691685*** 0.0749712*** 0.0736635*** 0.0726675*** (0.0017727) (0.0016297) (0.001649) (0.0014226) (0.0016397) (0.0015541) 0.0985139*** 0.0905119*** 0.0983816*** 0.0893401*** 0.0918163*** 0.0943575*** (0.0021089) (0.0020388) (0.0020918) (0.0024023) (0.0021576) (0.0019819)

−0.3976017*** (0.0242199)

999 Dynamic GMM

(2)

136

Variables (1)

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(3)

(4)

0.1624366 *** 0.1749311*** 0.1350536*** (0.0299759) (0.0347057) (0.0364966) −0.809697** −0.0295446 −0.2169917 (0.4030695) (0.1811166) (0.2505646) 0.9408369** 1.482278*** 1.490545*** (0.4520611) (0.3489641) (0.4064295) 0.1191595 0.4801251*** 0.2387004 (0.1966194) (0.1603727) (0.1698782) −0.4434628** −0.127702 −0.2786798* (0.2080725) (0.1501199) (0.1630494)

(2) 0.176016*** (0.0325156) 0.8236246** (0.4053372) 2.499744*** (0.5702764) 1.064222*** (0.3565951) 0.3756193 (0.3176702)

(5)

0.1452145*** (0.0370241) −0.1975105 (0.3968945) 1.833605*** (0.4979019) 0.5542898** (0.2261801) 0.0065539 (0.2176875)

0.138292*** (0.0338452) 0.9546719** (0.4222467) 2.127876*** (0.3265833) 0.9095777** (0.3564014) 0.4269726 (0.340693)

0.1013 0.3321 74.20883**

(7)

(6)

INDUS5 Regression summary statistics AR(1) 0.1031 0.0980 0.0917 0.0985 0.0978 AR(2) 0.2790 0.3513 0.2660 0.3572 0.3549 Hansan/Sargan 76.21847** 71.99026* 78.55243* 69.45138* 68.30113** Notes: This model provides standard errors which are in parentheses. *,**,***Significant at 10, 5 and 1 per cent level, respectively

INDUS4

INDUS3

INDUS2

INDUS1

TANGI

Variables (1)

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Impact of ownership structure 137

Table IV.

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138

have higher levels of debt and accompanying tax shields. Consistent with prior research, this study finds a significant positive relationship between firm tangibility and leverage ratios, indicating firms with more tangible assets have more opportunity to issue more debts. This may be because most of the time SMEs’ bank lending is collateral based. Berger and Udell (1990) find that over 70 per cent of all SME loans are collateralised. Further, Manove et al. (2001) explain that even though SMEs have positive cash flows, bank lending requires collateral. Therefore, it is expected that companies with high levels of tangible assets will take on relatively more debt resulting in a positive relationship between tangibility and SMEs’ debt levels. Table IV indicates industry type has a significant impact on small firms’ leverage ratios. Interestingly, results indicate that industry impact is positively and significantly related only when firms have more than 25 per cent of insider ownership. However, regardless of ownership level, INDUS2 (energy) is 1 per cent significantly positively related to the firm debt variable. The finding in terms of the leverage ratio and working owner percentage shows an inverse U-shaped relationship. Firms with lowest working ownership (0 per cent) have significant low-leverage ratios. However, firms with the highest working ownership (⩾75 per cent) have low-leverage ratios, suggesting managerial entrenchment where there are higher levels of insider ownership. Further, results show working ownership in the ranges between 0-25 per cent and 25-50 per cent have positive significant impacts on firm leverage levels. This is in line with Brailsford et al. who explain leverage increases with increased managerial ownership to a certain point, and after that entrenchment occurs and leverage decreases with increased managerial ownership. The auto regressive (AR) test is reported in Table III, for all variables detecting no serial correlation order 1 and order 2. There is no serial correlation in the original error εi, t, as desired. The second specification test, reported at the bottom of Table IV is the overidentification test. The Hansan-Sargan J statistics are not significant at the 5 per cent significance level for financial performance metrics, which means that the instruments are valid. Results of granger causality test The initial step is to determine whether there is a unit root in the panel data set. If there is a unit root then a frames formation to achieve stationary using an appropriate lag length is needed. Table V presents the results of the LLC test. Both leverage proxies and insider ownership variable are confirmed as stationary at the 1 per cent significance level. This result indicates the null hypothesis of unit root cannot be accepted. The Granger causality test results in Table VI provide strong evidence that insider ownership impacts firm leverage ratio (significant at 1 per cent level). Moreover, results Statistic (Tobin’s Q)

Table V. Levin-Lin-Chu (LLC) test

p-value (Tobin’s Q)

Statistic (OWNER)

p-value (OWNER)

Unadjusted −32.3480 −28.3832 Adjusted t * −18.5641 0.0000 −14.9907 0.0000 Notes: H0: Panels contain unit roots; Ha: panels are stationary. *,**,***Significant at 10, 5 and 1 per cent level, respectively

Table VI. Granger causality test Order 1

OWNER-DEBT

DEBT-OWNER

774.41***

3.30*

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provide evidence that leverage ratio also impacts firm insider ownership (significant at 10 per cent level). Summary and conclusion Using a panel of New Zealand unlisted firms during the period 1998-2009, this study examines the ownership structure and firm leverage ratio relationship. In particular, this study examines the causal relationship between insider ownership and firm leverage. Granger causality tests on panel data models show a bi-directional causal effect for insider ownership and firm leverage. The dynamic panel GMM estimator suggests a significant relationship between insider ownership and leverage. Furthermore, these findings suggest an inverse U-shaped relationship of insider ownership and leverage, indicating higher insider ownership increases management entrenchment and lower insider ownership increases misalignment of the interests of management and owners. The main implication of this study is the relevance of capital structure theories and financing as they apply to New Zealand small business. The capital structure choices in small business can be determined by firm ownership structure, firm characteristics and industry factors. Therefore, small business borrowing requirements can vary according to industry or firm type. Therefore, finance policy needs to vary across firm type, industries and firm characteristics and should match the different borrowing requirements of small business. Further, this study’s results indicate managerial ownership negatively affects firms’ total debt levels. Though managerial ownership is better for overcoming agency problems, closely held firms utilise fewer debts than non-closely held firms. This may be because owner-managers decrease non-diversifiable employment risk by decreasing the firm’s debt holdings. The Ministry of Economic Development (2009) in New Zealand indicates 68 per cent of small businesses have no employees. Therefore, there is potential to increase owner-manager specialisation in management and other areas to reduce non-diversifiable employment risk. Further, due to high insider ownership, managerial expropriation is very likely to exist in small business. There is potential merit in promulgating new rules and regulations to control the expropriation of minority shareholders. Limitations Notwithstanding the findings, the current study suffers from the following limitations, which would potentially represent opportunities for further investigation. First, the current study only used one aspect of ownership (insider ownership). Further studies may want to consider other aspects of ownership structure (owner gender, education level, age) and their effect on debt level in small businesses. Second, while this paper has provided useful insights into firm insider ownership, firm characteristics and leverage levels in unlisted businesses, the findings are based on research in a single country. Also, a more in-depth analysis of the impact of both short-term and long-term debt on insider ownership would be of interest. References Al-Najjar, B. and Taylor, P. (2008), “The relationship between capital structure and ownership structure”, Managerial Finance, Vol. 34 No. 12, pp. 919-933. Ang, J.S., Cole, R.A. and Lin, J.W. (2000), “Agency costs and ownership structure”, Journal of Finance, Vol. 55 No. 1, pp. 81-106.

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Corresponding author Nirosha Hewa Wellalage can be contacted at: [email protected]

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