1 Introduction
Theories of capital structure are among the most interesting theories in the field of
finance. The subject matter of leverage decisions and the factors influencing these
decisions have been attracting attention since the pioneering work of Modigliani and
Miller in the 1950s. The concept that general firm characteristics can affect capital
structure has received considerable attention in prior literature. In an early study, Bates
(1971) found significant differences between the financial structures of small firms and
large firms. One of these differences may be that small firms tend to have more quasidebt
and barriers to access external financing modes. However, very few studies have
looked at the small businesses (SME) context. Scale effects can influence the existence
or the degree of weight of a particular financial theory upon capital structure. As an
example, most prior studies conclude that SMEs exhibit pecking order behaviour with
regard to their financing (Cassar and Holmes, 2003; Ramlall, 2009) though larger firms
support both pecking order and trade-off theories. Differences between large and small
business capital structures may be due to differences in firm characteristics and firm
ownership structure.
Small businesses in New Zealand and elsewhere are a major source of employment,
gross domestic product and innovation. As an example, in 2009 SMEs contributed 41.9%
of New Zealand’s GDP and one-third of the total employment (Ministry of Economic
Development, 2010). However, particularly in small firms, financial leverage has been
identified as a major cause of decline (Keasey and Watson, 1986; Lowe et al., 1991;
Storey et al., 1988). The lack of maximum use of debt or no use of debt is clearly visible
in the small business sector (Michaelas et al., 1999). Ministry of Economic Development
and Statistics (2004) indicates that large businesses with more than 100 employees have a
16 times higher average debt amount per enterprise than smaller firms with less than 20
employees. Though some small businesses gain more advantages than larger businesses
from marginal tax rates, most small firms inherit fewer benefits from the debt tax shield
(Ang, 1991, 1992). Nevertheless, high bankruptcy probability and lower advantage of tax
shield benefits lead to less usage of debt in small business capital structure.
This paper examines the impact of firm characteristics including managerial
ownership, profitability, liquidity, tangibility, growth, risk, firm size, firm age and
industry on capital structure decision in SMEs. Most of the existing studies use data from
large listed companies, but it is important to consider how unlisted businesses and firm
characteristics relate in capital structure decisions. Also, this is one of the first empirical
studies to focus on the effect of ownership structure on capital structure in an unlisted
context. This study uses the recent data set available in New Zealand, covering the period
1998–2008 inclusive. Prior studies covered mostly the USA or the UK and spanned only
a few years. Additionally, the econometric analysis is more robust than prior research due
to the control in the endogeneity effect of ownership and firm characteristics and their
impact on capital structure choice.
The next section of the paper reviews prior research and develops the hypotheses and
is followed by a discussion of the data, variables, method and procedures used for this
empirical study. The findings and implications then follow.
Capital structure choice 95
2 Literature review
The basis for empirical capital structure research is the seminal study by Modigliani and
Miller (1958) who showed that in the case of perfect capital markets, capital structure is
irrelevant. However, in practice, different levels of market imperfections prevail through
the inclusion of corporate taxes, interest rates and information asymmetry. Later, three
new theories on capital structure were introduced and widely used in literature. They
were the trade-off model (Myers, 1984), the pecking order model (Myers and Majluf,
1984) and agency costs theory (Jensen, 1986).
The pecking order theory (information asymmetry theory) is based on the idea of
asymmetric information between managers and investors. The theory proposes that firms
prefer to finance new investment by first seeking internal retained earnings, then with
debt and finally with an issue of new equity. The tax benefits trade-off model is based on
the idea that firms will seek to maintain an optimal capital structure by balancing the
benefits and the costs of debt. In agency theory, a firm uses debts to reduce its free cash
flow problems and other potential conflicts between managers and shareholders. Based
on the above three theories, the factors impacting on firm capital structure can be
classified into three major categories: firm-specific characteristics, industry-specific
characteristics and market-related characteristics. This study will consider possible firmspecific
characteristics: managerial ownership, firm profitability, liquidity, tangibility,
growth, risk, size, age and the industry in which the firm operates.
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 in the business and therefore align with the pecking order theory. Higher
managerial ownership firms are reluctant to have external financing, and their debt level
can be lower than less closely held firms. Further, using Irish SMEs, Bhaird and Lucey
(2010) find evidence of lower usage of external finance in small business, indicating a
desire to retain control of closely held firms’ impacts on the external source of finance.
Non-diversifiable human capital is prevalent in small firms. According to agency theory,
Amihud and Lev (1981) and Friend and Lang (1988) explain, non-diversifiable human
capital firms reduce their non-diversifiable employment risk by decreasing firm debt
level. Further, Young et al. (2008) explain that due to high principal–principal agency
costs, SMEs experience high managerial entrenchment. This managerial entrenchment
leads to debt avoidance in SMEs. Similar to the above findings, Baum et al. (2007) find a
significant negative relationship between long-term debt and managerial ownership,
indicating high managerial discretion limits long-term debt. Testable hypotheses
regarding managerial ownership and firm total debt level, long-term debt level and shortterm
debt level in small businesses are:
Hypothesis 1a: Managerial ownership is negatively associated with firm total debt level.
Hypothesis 1b: Managerial ownership is negatively associated with firm long-term debt
level.
Hypothesis 1c: Managerial ownership is negatively associated with firm short-term debt
level.
96 N. Hewa Wellalage and S. Locke
According to pecking order theory, information asymmetry leads firms to prefer internal
finance to other sources of external funds. Therefore, more profitable firms have more
retained earnings and are less likely to use external financing options. Aligning with
pecking order theory, Antoniou et al. (2002) and Chen (2004) find a negative relationship
between leverage and past profitability. 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. Um (2001) also finds similar results and argues that
highly profitable SMEs rise to have higher levels of debt and accompanying tax shields.
This is aligned with agency theory, which predicts profitable firms with excess cash
flows require high debt levels to control managers from entrenchment (Jensen, 1986).
Also, Baum et al. (2007) find a positive relationship between short-term debt and
firm profitability in German non-financial firms. Testable hypotheses regarding firm
profitability and firm total debt level and long- and short-term debt levels in small
businesses are:
Hypothesis 2a: Firm profitability is negatively associated with firm total debt level.
Hypothesis 2b: Firm profitability is negatively associated with firm long-term debt level.
Hypothesis 2c: Firm profitability is negatively associated with firm short-term debt level.
As predicted by the pecking order model, Frieder and Martell (2006) and Lipson and
Mortal (2009) find a negative relationship between firm leverage ratios and firm
liquidity, indicating that firms with more liquid equity carry less debt. This may be
because a high level of liquidity limits a firm’s ability to commit to specific causes of
action, therefore limiting external borrowings. Davidson and Dutia (1991) show that
though SMEs had a lower level of liquidity than their larger counterparts did, even
smallest firms have disproportionately higher liquidity ratio than larger firms. Because
SMEs’ agency costs of liquidity are high, outside creditors limit the amount of debt
financing available to the company. Testable hypotheses regarding firm liquidity and
firm total debt level and long- and short-term debt levels in small businesses are:
Hypothesis 3a: Firm liquidity is negatively associated with firm total debt level.
Hypothesis 3b: Firm liquidity is negatively associated with firm long-term debt level.
Hypothesis 3c: Firm liquidity is negatively associated with firm short-term debt level.
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 high liquidation value (Harris and Raviv, 1990; Titman and Wessels, 1988).
Trade-off theory explains that a firm’s tangible assets can be used as debt collateral. Prior
research finds a positive relationship between an SME’s leverage level and its collateral
(Ibrahim and Masron, 2011). SMEs’ bank lending is collateral-based most of the time.
Berger and Udell (1990) find that over 70% of all SME loans are collateralised. Further,
Capital structure choice 97
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
tangibility assets will take on relatively more debt, resulting in a positive relationship
between tangibility and an SME’s debt level. Testable hypotheses regarding firm
tangibility and firm total debt level and long- and short-term debt levels in small
businesses are:
Hypothesis 4a: Firm tangibility is positively associated with firm total debt level.
Hypothesis 4b: Firm tangibility is positively associated with firm long-term debt level.
Hypothesis 4c: Firm tangibility is positively associated with firm short-term debt level.
Prior studies find mixed results for firm growth level and debt level. In line with agency
theory, Myers (1977) argues that firms with high growth opportunities need to use less
debt in order to mitigate conflicts between lenders and owners. Further, Myers (1984)
explains that a negative relationship may be due to high interest rates or restrictive
covenants that discourage debt taking. Rajan and Zingales (1995) find two main reasons
for a negative relationship between firm growth level and debt level. Firstly, it is
expected that as growth opportunities increase, the cost of financial distress also
increases along with it. Secondly, firms prefer to issue overvalued equity. A possible
explanation is that although growth opportunities add value, the firm cannot use growth
opportunities as collateral for lenders. However, using SMEs, Michaelas et al. (1999)
explain that growth ratio and firm leverage can have a positive relationship because
SMEs rely highly on short-term debt financing in their growth phase. This may be a
high-growth firm’s first look for less secure, more short-term debts and then only switch
for high, secure, long-term debts (Subadar et al., 2010). Nevertheless, Hutchinson (2003)
using SME data finds growth is not a very important determinant of small firms’ long- or
short-term borrowings. However, he finds growth is significantly positively related with
medium-size enterprises’ long-term debt level. Testable hypotheses regarding firm
growth opportunities and firm total debt level and long- and short-term debt levels in
small businesses are:
Hypothesis 5a: Firm growth rate is positively associated with firm total debt level.
Hypothesis 5b: Firm growth rate is positively associated with firm long-term debt level.
Hypothesis 5c: Firm growth rate is positively associated with firm short-term debt level.
Both pecking order theory and trade-off theory suggest that the negative relationship
between firm risk and debt level increases with the volatility of income. Firms may find
it necessary to arrange external funds at high cost to service the debt or face increased
bankruptcy risk. Therefore, high-risk firms prefer a low debt level. Aligned with that,
Subadar et al. (2010) find a significant negative relationship between Mauritius financial
firms’ risk and leverage levels. However, limited empirical studies find a positive
relationship between SMEs’ risks and leverage (Jordan et al., 1998; Michaelas et al.,
1999). This may be, according to agency costs theory, because risk intensifies a negative
impact on asymmetric information (Schoubben and Hulle, 2004). Testable hypotheses
regarding the firm risk level and firm total debt level and long- and short-term debt levels
in small businesses are:
98 N. Hewa Wellalage and S. Locke
Hypothesis 6a: Firm risk level is positively associated with firm total debt level.
Hypothesis 6b: Firm risk level is positively associated with firm long-term debt level.
Hypothesis 6c: Firm risk level is positively associated with firm short-term debt level.
There are many issues that impact on the relationship between firm size and firm
leverage. Nevertheless, most prior studies find significant positive results with firm size
and firm leverage (Cassar and Holmes, 2003; Rajan and Zingales, 1995). This may be
due to the following reasons. First, larger firms may have a higher credit rating than their
smaller counterparts. Therefore, it is easy to access external financing due to lower
information asymmetry (Subadar et al., 2010). Secondly, larger firms are likely to have
higher debt levels to maximise tax benefits from debt (Rajan and Zingales, 1995). Cassar
(2004) argues that due to high cost of external borrowings, small firms may be offered
lower debt levels 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 use more debts than smaller firms do. However, Barclay et al.
(1995) and Bevan and Danbolt (2002) find that there is a positive relationship between
firm size and long-term debt, and a negative relationship between firm size and shortterm
debt. It may be that smaller firms rely more on short-term debts than on long-term
debts. Further, according to Schoubben and Hulle (2004), in order to reduce issuance
costs, smaller firms prefer more short-term debts. Testable hypotheses regarding firm
size and firm total debt level and long- and short-term debt levels in small businesses are:
Hypothesis 7a: Firm size is positively associated with firm total debt level.
Hypothesis 7b: Firm size is positively associated with firm long-term debt level.
Hypothesis 7c: Firm size is positively associated with firm short-term debt level.
Ramlall (2009) posits that due to older firms requiring more external financing to keep
abreast with new technology and having more developed relationships with their banks,
which are important in lending assessments, a positive relationship can exist between
firm age and leverage levels. On the other hand, based on agency theory, younger firms
experience higher information opacity problems, which can restrict access to debt
(Bhaird and Lucey, 2010). When a firm matures, its developing credit history, reduced
information asymmetry and moral hazards lead to easy access to external financing.
Therefore, a positive relationship between firm age and firm debt level can be predicted.
Testable hypotheses regarding firm age and firm total debt level and long- and short-term
debt levels in small businesses are:
Hypothesis 8a: Firm age is positively associated with firm total debt level.
Hypothesis 8b: Firm age is positively associated with firm long-term debt level.
Hypothesis 8c: Firm age is positively associated with firm short-term debt level.
The relationship between industry type and its effect on firm capital structure has
received considerable attention in recent literature. However, based on pecking order
theory, Myers (1984) argues that a firm debt ratio is not influenced by industry; it is
Capital structure choice 99
determined by the firm itself. Harris and Raviv (1990) argue that industry type does have
a significant effect on firm leverage. This is confirmed by Roberts (2002) who analyses
average leverage ratios of 50 US industries and finds the degrees of leverage ratios vary
from 9% to 54% among industries. 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. They further explain that since SMEs often operate in niche markets, this
would reduce the impact on industry differences in their capital structure. Testable
hypotheses regarding the industry in which firms operate and firm total debt level and
long- and short-term debt levels in small businesses are:
Hypothesis 9a: Industry type is significantly associated with small firm total debt level.
Hypothesis 9b: Industry type is significantly associated with small firm long-term debt
level.
Hypothesis 9c: Industry type is significantly associated with small firm short-term debt
level.
3 Data, variables and measure
The sample of New Zealand’s 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 are sparse. Total equity
firms are excluded from the sample. The random sample is drawn from accounting
practices that prepare end-of-year financial returns for as many as 1000 small businesses
each year. After adjustments, the data set provides 1320 observations from a total of 120
businesses appearing each year.
Table 1 reports descriptive statistics for the sample data. The mean value of
TOTDEBT is 0.84, with a range of 0.002–21.39, suggesting smaller firms have lower
debt levels. The one possible explanation for that is that due to bankruptcy, costs are an
inverse function of firm size, SMEs reluctant to have more debts in their capital structure.
Further, the mean level of long-term debt is significantly less than the mean level
of short-term debt in the sample, indicating small firms prefer more short-term debts
to long-term debts. This is consistent with the limited ability of small firms to access
capital markets due to higher inflation costs of long-term debts (Cotei and Farhat, 2009).
Further, the high proportion of short-term debt to long-term debt used by small
businesses also supports evidence for fewer agency cost conflicts, because high
proportion of short-term debt reduces agency conflicts between shareholders and debt
holders. The sample confirms the high proportion of managerial ownership in small
firms. The mean insider ownership percentage is 39 and the range varies between 0% and
100%.
100 N. Hewa Wellalage and S. Locke
Table 1 Descriptive statistics
Variable Obs Mean Std. dev Min Max
TOTDEBT 1320 0.8397187 0.9224129 0.0020614 21.38762
LDEBT 1320 0.3522235 0.3402916 0 1
SDEBT 1320 0.6477765 0.3402916 0 1
OWNER 1320 0.3876501 0.3078092 0 1
PROFIT 1320 0.4328174 1.750568 –1.639888 55.90533
LNLIQUE 1320 0.317181 4.451588 0 15.84167
TANGI 1320 0.4525824 0.2990364 –0.6662024 0.9996139
GROWTH 1320 0.2303587 1.407622 –0.7341936 30.00886
RISK 1320 3.566285 4.958453 0.060639 72.5558
LNSIZE 1320 13.68468 1.268399 10.43102 18.38514
LNAGE 1320 0.7686313 0.362951 0 1.098612
INDUSTRY1 1320 0.1 0.3001137 0 1
INDUSTRY2 1320 0.0030303 0.0549856 0 1
INDUSTRY3 1320 0.5068182 0.500143 0 1
INDUSTRY4 1320 0.3833333 0.4863827 0 1
INDUSTRY5 1320 0.2 0.4001516 0 1
3.1 Variables and measures
Following prior research, this study uses three appropriate leverage measures as the
dependent variables. The most traditional measure is the ratio of total liabilities divided
by the total assets (TOTDEBT). However, Bevan and Danbolt (2000) state that there is a
potential danger of basing the analysis of capital structure determinants on overly
aggregate measures of gearing. Further, following Hall et al. (2000), in order to shed
some light on the differences between short- and long-term debt determinants, this study
also considers the following two dependent measures of leverage: total long-term debt
divided by the total assets (LDEBT) and total short-term debt divided by the total assets
(SDEBT).
Prior studies identify firm-specific characteristics which are derived from different
theoretical frames and can be determined by firm capital structure (Rajan and Zingales,
1995; Ramlall, 2009). Therefore, consistent with prior literature, this study uses
the following explanatory variables: firm size (LNASSETS), tangibility (TANGI),
liquidity (LIQU), profitability (PROFIT), risk (RISK), growth (GROWTH) and firm age
(LNAGE). However, recently very few papers extend the literature by examining the link
between ownership structure and capital structure (Bhaird and Lucey, 2010; Brailsford
et al., 2002). This study uses the OWNER variable which reflects the working owner
percentage in a firm. This is calculated as the total number of working owners divided
by the sum of the total number of employees plus the total number of working
owners. Further, this study includes five industry dummies representing primary
(PRIMARY), energy (ENERGY), goods (GOODS), services (SERVICES) and other
(OTHER) industries.
Capital structure choice 101
4 Method
Panel data covering 11 years of variables for 120 businesses were prepared initially. Prior
studies have used panel OLS to control heterogeneity over time and across firms.
However, recent research by Getzmann et al. (2010) identifies endogeneity of capital
structure determinant variables. If the strict exogeneity condition fails, then panel OLS
will be inconsistent. The Durbin–Wu–Hausman (DWH) test can be used as a diagnostic
test for endogeneity of capital structure proxies and explanatory variables. To obtain
robust estimates, a GMM panel estimator is used to estimate the relationship between
ownership structure, profitability, growth, liquidity, tangibility and risk variables and
capital structure proxies. An important aspect of the dynamic panel estimator is that it
uses the firms’ history as instruments for explanatory variables. 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 χ2 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.
5 Findings
The results revealed (Table 2) that OWNER, TANGI, LNLIQU and RISK and capital
structure proxies have a significant endogeneity problem, suggesting a need to address
the issue of potential endogeneity. Table 3 addresses the issue of potential endogeneity
by means of lag instrumental variables. Columns 2, 3 and 4 represent total debt, longterm
debt ratio and short-term debt ratio, respectively.
Table 2 The Durbin–Wu–Hausman test for endogeneity of TOTDEBT regressor
Ratio TOTDEBT LDEBT SDEBT
OWNER 3.49171** 12.9468*** 12.9468***
LNLIQUE 3.58001** 0.903669 0.903669
TANGI 0.919672 8.4808*** 8.4808***
GROWTH 0.089751 1.85842 1.59703
RISK 4.39811** 15.6471*** 15.6063***
Notes: **Significant at 5% level.
***Significant at 1% level.
The coefficient of the ownership variable is negative and statistically significant at 1%
level for TOTDEBT, indicating high managerial ownership decreases firm debt level.
This is in line with Brailsford et al. (2002), who explain that when the level
of managerial ownership increases, firm control changes from external shareholders
to the managers. After a certain point, due to managerial entrenchment, managerial
opportunism increases. Therefore, at a high level of ownership, there are incentives to
decrease debt levels. Further, based on agency theory, Friend and Lang (1988) explain
that managers prefer lower debt level as a method of reducing the non-diversifiable
employment risk. This situation may be worsening, especially in sole proprietorships and
partnerships with zero employees. Results indicate (columns 3 and 4 in Table 3) that
102 N. Hewa Wellalage and S. Locke
managerial ownership has a negative effect and a positive effect in a firm’s long- and
short-term debt levels, respectively. This indicates that managerial owners prefer to have
more short-term debts than long-term debts. This may be due to high failure risk in small
businesses and owner-managers not interested in using their personal assets as collateral
in long-term borrowings.
Furthermore, as can be seen from Table 3 column 2, firm profitability is positively
statistically significant at the 1% level for the TOTDEBT variable, indicating
profitability increases a firm’s total debt level. The result is in keeping with the trade-off
theory, which predicts that firm profitability positively affects firm total debt and longterm
debt levels. This may, according to Brick and Ravid (1985), mean that higher price
long-term debt helps avoid high profitable SME taxes. In contrast, the significant
negative coefficient on profitability and short-term debt level is consistent with the
pecking order theory of Myers (1977) and the empirical results of Brailsford et al.
(2002). Further, this finding is in line with Hovakimian et al. (2001) who conclude, in a
US context, that the effect of firm profitability on the short-term debt choice is always
consistent with pecking order theory and revision to the target in the long-term debt
choice. This may be that when small firms become profitable, short-term finance will be
substituted first by internal equity and then they will look at external financing for longterm
debt.
Notes: This model provides standard errors which are in parentheses.
*Significant at 10% level.
**Significant at 5% level.
***Significant at 1% level.
Consideration of LNLIQU (Liquidity) variable, in Table 3, reveals it is negatively related
with both TOTDEBT and SDEBT at the 1% significant level and positively related
with LDEBT at the same 1% significant level. This shows that firms with high levels of
liquid resources are reluctant to borrow short-term debt. However, findings explain that
liquidity assets can increase collateralisabilty of assets, which positively affects longterm
borrowings. Further, it reflects the fact that internal financing is less costly than
external financing for short-term financing in small business.
Firm tangibility (TANG) is positively significantly related to firm TOTDEBT level,
indicating firms with higher tangibility assets are expected to have higher debt capacity.
This is in line with the trade-off theory, which indicates firms with greater tangibility
assets have the ability to issue more debt, because tangible assets can be viewed as debt
collateral. Further, this study finds a significant positive relationship with tangibility
and long-term debt level and 1% negative significant relationship with tangibility and
short-term debt level. This is consistent with Van der Wijst and Thurik (1993),
Chittenden, et al. (1996) and Stohs and Mauer (1996), who find a positive relationship
between tangibility and long-term debt and a negative relationship between tangibility
and short-term debt. This may be because tangibility is much less important in SME
short-term debts, where perhaps, not surprisingly, more collateral is required for longterm
debt security. The result further indicates that when small firms offer collateral for
debt financing, there is a high possibility that they will choose long-term financing over
short-term financing. This is in line with Michaelas et al. (1999) who posit that when
small firms offer their collateral for debt financing, there is five times more probability
they will have long-term rather than short-term debts.
The coefficient on the growth (GROWTH) variable is negatively and statistically
significant at the 1% level for TOTDEBT variable, indicating strong growth firms rely
less on outside financing. This is consistent with the findings of Brailsford et al. (2002) in
the Australian market and Cotei and Farhat (2009) in the US market. Further, associated
with pecking order theory, we can argue that firms with higher growth opportunities may
use less debt to prevent any problems with underinvestment. This result may imply that
highly growing firms have sufficient internal funds for their financing needs, or on the
104 N. Hewa Wellalage and S. Locke
other hand, it may imply that small firms tend to be more risky and therefore prefer lower
levels of debt. However, GROWTH has no significant role in affecting the proportion of
long- or short-term debt levels.
A significant negative relationship between risk and short-term debt is observed
for small businesses. This is consistent with the trade-off theory. This may result in
arranging funds at high cost to service the debt and thus increasing the probability of
bankruptcy. Therefore, as the present value of the costs of financial distress increases
with the probability of being financially distressed, risky small firms prefer less shortterm
debt. However, in contrast to the above statement, this study finds a significant
positive relationship between firm risk and total debt ratio and long-term debt ratio. Such
results are not consistent with the trade-off theory. This may include that the moral
hazard problem outweighs the increased probability of bankruptcy, thus reducing the
underinvestment problem. This distortion may also be due to distressed SMEs borrowing
more finance to overcome bankruptcy.
Firm size has a negative effect on TOTDEBT and LDEBT at a 1% significant level
and a positive effect on SDEBT at the 1% significant level, indicating larger firms have
lower total debt and long-term debt levels. This is consistent with Rajan and Zingales
(1995) who argue that due to complex structure information, asymmetry levels are higher
for larger firms and they do not intend to have higher levels of debt. Moreover, because
issuing equity is significantly higher in smaller firms, they prefer debt than equity
(Schoubben and Hulle, 2004). Further, results indicate that larger firms have higher
short-term debt levels than their smaller counterparts.
Similar to firm size, firm age is negatively related to TOTDEBT and LDEBT, at the
1% significant level, indicating mature firms have lower debt levels and lower long-term
debt levels. This finding is consistent with Ramlall (2009) in Mauritian unlisted firms’
long-term debt level. He explains that mature established firms generate enough cash
flow and place less reliance on outside finance than younger firms. Further, this result is
consistent with the pecking order theory, which argues that as a firm matures its
reputation increases, leading to easier access to equity markets. Hence, a negative
relationship can be expected between firm age and leverage level. Furthermore, this
study finds a positive significant relationship between firm age and short-term debt level,
indicating mature firms have higher short-term debt levels. This finding relates to tradeoff
theory; as a firm matures, its debt capacity increases.
Finally, this study provides evidence that industry factors play an important role, with
some industries being more prone to leverage than others. The study also shows that
industry effect is more apparent in short-term debt than in long-term debt. This finding is
consistent with that of Bradley et al. (1984), who report significant differences and
variations of corporate debt level among industries. Almazan and Molina (2005) indicate
that high capital structure dispersion is shown by industries that are more concentrated,
use leasing more intensively and have poor corporate governance practices.
6 Implications
The main implication of this study is the relevance of capital structure theories and
financing as it applies 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 businesses’ borrowing requirements can vary according
Capital structure choice 105
to industry or firm type and firm life cycle stage. Nevertheless, finance policy needs to
vary across firm type, industries and firm characteristics, and should match with the
different borrowing requirements of small firms.
According to this finding, the overall results support the pecking order theory of
small business financing. This leads to the conclusion that no optimal debt level exists for
small businesses and they do not take the tax-benefit advantage of debts. Another
explanation is that the high probability of bankruptcy in small businesses, coupled with
the uncertain economic environment, also minimises the advantages of tax from debts.
Therefore, government or policy makers should be required to provide an environment
that makes access to external finance less of a burden for small business owners.
Further, this study explores the importance of distinguishing between long- and shortterm
debts when making decisions about the capital structure. Except for liquidity, all
other explanatory variables have a contradictory effect for short- and long-term debts in
small business. Therefore, it is required to implement separate capital structure theories
for small businesses’ long- and short-term debts.
Finally, 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. Ministry of Economic Development (2010) indicates 68% 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.
7 Limitations
Notwithstanding the findings, the current study suffers from the following limitations,
which would potentially represent opportunities for further investigation. First, the
current study used only one aspect of the ownership structure (managerial ownership).
Further studies may want to consider other aspects of ownership structure (owners’
characteristics, etc.) and their effect on capital structure choice in unlisted businesses.
Secondly, while this paper has provided useful insights into firm ownership, firm
characteristics and capital structure choice in unlisted businesses, the findings are based
on research in a single country. Finally, there are several other factors that this study was
unable to address due to data constrains.
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