CEFAGE-UE Working Paper
2011/11
Are Capital Structure Decisions of Family-Owned SMEs
Different? Empirical Evidence From Portugal
Zélia Serrasqueiro 1, Paulo Maçãs Nunes 2, Jacinto Vidigal da Silva 3
1
Management and Economics Department, Beira Interior University
and CEFAGE Research Center, Évora University
2
Management and Economics Department, Beira Interior University
and CEFAGE Research Center, Évora University
3
Management Department, Évora University, Portugal
and CEFAGE Research Center, Évora University
CEFAGE-UE, Universidade de Évora, Palácio do Vimioso, Lg. Marquês de Marialva, 8, 7000-809 Évora, Portugal
Telf: +351 266 706 581 - E-mail: [email protected] - Web: www.cefage.uevora.pt
Are Capital Structure Decisions of Family-Owned SMEs
Different? Empirical Evidence From Portugal

Zélia Serrasqueiro1
Management and Economics Department, Beira Interior University Estrada do Sineiro, Pólo IV, 6200209 Covilhã, Portugal
and CEFAGE Research Center, Évora University.
Phone: + 351 275 319 600
Fax: + 351 275 319 601
E-mail: [email protected]

Paulo Maçãs Nunes
Management and Economics Department, Beira Interior University Estrada do Sineiro, Pólo IV, 6200209 Covilhã, Portugal
and CEFAGE Research Center, Évora University.
Phone: + 351 275 319 600
Fax: + 351 275 319 601
E-mail: [email protected]

Jacinto Vidigal da Silva
e-mail: [email protected]
Management Department, Évora University, Portugal
and CEFAGE Research Center, Évora University.
Phone: +351 266 740 800
Fax: +351 266 740 831
Abstract:
This study analyses if ownership structure is an important determinant of capital
structure decisions, on basis of two sub-samples of family-owned and non-family
owned SMEs, sing panel data models. The results suggest that family ownership is an
important determinant for: i) the variations of short and long-term debt stimulated by
the financial deficit; and ii) the rate of adjustment of short and long-term debt toward
the respective target levels. The empirical evidence obtained in this study suggests that
family-owned firms have the possibility to reach their target short and long-term debt
ratios, corroborating the assumptions of Trade-Off Theory. Whereas non-family owned
firms follow almost exclusively the behaviour forecasted by Pecking Order Theory, i.e.,
when internal finance is insufficient, those firms turn to short-term debt, and their
variations of short-term debt are almost exclusively a consequence of the financial
deficit.
Keywords: Family-Owned SMEs, Long-Term Debt; Non-Family Owned SMEs, Panel Data
Models, Short-Term Debt.
JEL Classification: G32
1

Corresponding author: Zélia Serrasqueiro.
The authors gratefully acknowledge partial financial support from FCT, program POCTI.
1
1. Introduction
In the literature on the corporate capital structure decisions, one of the most debated
questions is if firms´ variations of debt are a consequence of the adjustments toward the
target debt ratio (Trade–Off Theory: Lev & Pekelman, 1975; Ang, 1976; Taggart, 1977;
Jalilvand & Harris, 1984), or, on the contrary, if firms´ variations of debt are a
consequence of the financial deficit (Pecking Order Theory: Myers, 1984; Myers &
Majluf, 1984).
However, regarding specifically the influence of ownership structure on SMEs’
capital structure decisions, only the study by López-Gracia & Sánchez-Andújar (2007)
analyses the differences of debt adjustment toward target debt ratio between Spanish
family SMEs and non-family SMEs. Those authors conclude that the rate of adjustment
of debt toward target debt ratio is greater for small family firms than for small nonfamily firms. Those authors, conclude that family ownership of SMEs is an important
characteristic for reduced information asymmetry in the relationships between
owners/managers and creditors.
As for the importance of information asymmetry in firms’ capital structure
decisions, the conclusions of Myers (1977) are quite relevant. The author concludes that
for creditors, it is easier to monitor the fulfilment of commitments related to short-term
debt, given the need for firms to pay off the debt and its charges over a shorter period of
time. Given that family ownership can be an important characteristic for reduced
information asymmetry in the relationships between owners/managers and creditors,
and considering that an efficient mechanism for creditors to reduce these kind of
problems is to grant short-term debt, and restraining the access to long-term debt, the
following questions are relevant: i) will ownership structure be an important
characteristic so as the proportion of long-term debt relative to the financial deficit
2
being greater for family-owned firms than for non-family owned firms, the opposite
being the case with the proportion of short-term debt relative to the financial deficit?;
and ii) will ownership structure be a relevant characteristic for a greater rate of
adjustment of toward target long-term debt ratio for family-owned firms than for nonfamily owned firms, the opposite happening, when short-term debt is the subject of
analysis?
Considering the state-of-the-art regarding family-owned and non-family owned
SMEs´2 capital structure decisions, the contribution of this study is to show that firm´s
family ownership is a fundamental characteristic for diminishing problems of
information asymmetry in the relationships between firm´s owners/managers and
creditors. More specifically, we find that: i) non-family owned firms, when internal
financing is insufficient, finance themselves almost exclusively through short-term debt.
When internal financing is insufficient, high dependence on short-term debt may
contribute to a target ratio of short-term debt not being due to a trade-off between debttax shields and bankruptcy costs associated with debt, but rather to the need of shortterm debt and consequently, the need to renegotiate the terms of the short-term debt
with creditors; and ii) family-owned firms are not excessively dependent on short-term
debt, even turning more to long-term debt than to short-term debt, and also having a
considerably greater rate of adjustment of long-term debt toward the target long-term
debt ratio3 than what is verified in the case of non-family firms.
The empirical evidence obtained in this study suggests that family-owned firms
have the possibility to reach their target short and long-term debt ratios, which means a
trade-off between debt-tax shields and bankruptcy costs, corroborating the assumptions
of Trade-Off Theory. Whereas non-family owned firms follow almost exclusively the
2
Since the current study focuses upon SMEs, henceforth we will refer family-owned SMEs as familyowned firms and non-family owned SMEs as non-family owned firms.
3
We will refer optimal debt level or target debt ratio as equivalent concepts.
3
behaviour forecasted by Pecking Order Theory, i.e., when internal finance is
insufficient, they turn to short-term debt, and the variations of short-term debt of nonfamily owned firms are almost exclusively a consequence of the financial deficit.
We consider two sub-samples of Portuguese SMEs for the period 1999-2006: 1) 614
family-owned firms; and 2) 240 non-family owned firms. To determine the variations of
short and long-term debt as a function of financial deficit we use OLS regressions,
estimating standard deviations according to the possible existence of heteroscedasticity.
Additionally, we use dynamic panel estimators to determine the rates of adjustment of
short and long-term debt toward the respective target levels.
After this introduction, we divide the study as follows: Section 2 presents the
theoretical framework and research hypotheses; Section 3 presents the database,
variables and estimation methods used; Section 4 presents the results obtained; Section
5 presents the discussion of the results; and, in the Section 6 we present the conclusions
of this study.
2. Theoretical Framework and Research Hypotheses
Firm succession and control are fundamental aspects for family-owned firms to
delineate their financing strategies (Brenes et al., 2006). Family-owned firms prefer
retained profits to any source of external finance (Demsetz & Lehn, 1985; James, 1999;
Romano et al., 2001; Blanco-Mazagatos et al., 2007). However, when internal finance is
insufficient, family-owned firms prefer debt to external equity (Mulkay & Sassenou,
1995; Poutziouris, 2001; Romano et al., 2001; López-Gracia & Sánchez-Andújar, 2007;
Peters & Westerheide), in order to keep firm control and firm capital in hands of the
family. The manifest preference for debt, as opposed to opening up firm equity to
4
external investors, may contribute to higher levels of debt of family-owned firms
compared to non-family owned firms.
In the framework of agency theory, one of the problems that can occur between
SMEs’ owners and/or managers and creditors is that of underinvestment, implying the
rejection of profitable projects, which in a situation of firm bankruptcy, will only benefit
creditors. In the context of problems of underinvestment, Myers (1977) concludes that
granting firms short-term, rather than long-term debt can be an effective mechanism for
reducing problems of underinvestment, since firms must pay off the debt and its charges
over quite a short period of time, this need contributing to more effective management
of firms’ financial resources.
Marchica (2008) identifies a positive relationship between ownership concentration
and the level of short-term debt with the objective to reduce firm´s exposure to
underinvestment problem. However, when expected liquidity risk costs are very high,
firms may use less short-term debt. Firms´ using short-term debt may depend on the
trade-off between the benefits of reduced exposition to underinvestment problem and
the liquidity risk costs (Johnson, 2003).
Family-owned firms may clearly prefer long-term debt rather than short-term debt,
in order to mitigate financing needs with lower liquidity risk. In family-owned firms,
the long-term survival of the firm and to pass the firm on to subsequent generations in
the family are the main goals of their owners who normally have their wealth invested
in the firm, preventing them from diversifying their personal portfolio, and so firm
bankruptcy also means firm´s owners personal bankruptcy (Ang, 1992; Bopaiah, 1998).
Additionally, the more cohesive management structure of family-owned firms (Bopaiah,
1998), the goal of family-owned firms´ owners in maintaining family reputation and
firm control reduce the risk for creditors, implying lower agency costs of debt and
5
allowing longer relationships between family-owned firms and creditors (MenéndezRequejo, 2006). In this setting, we can expect that these firms easily obtain long-term
debt than do non-family owned firms (Colot & Croquet, 2006). Family-owned firms’
easier access to long-term debt can be fundamental for financing the financial deficit
that emerges when internal finance is insufficient, preventing financial deficits from
being mostly financed through short-term debt, as a consequence of these firms being
able to obtain long-term. Therefore, family-owned firms can have a greater balance
between short and long-term debt, turning in a greater proportion to long-term debt and
less to short-term debt in situations of financial deficit than is the case in non-family
owned firms.
Based on the arguments presented before, we formulate the following researches
hypotheses:
H1: The proportion of short-term debt financing relative to the financial deficit is
greater for non-family owned than do for family-owned firms.
H2: The proportion of long-term debt financing relative to the financial deficit is
greater for family owned than do for non-family-owned firms.
Non-family owned firms’ greater dependence on short-term debt, and the
consequent need constantly to renegotiate the terms of short-term debt, can cause
greater rate of adjustment of short-term debt toward the target ratio. However, this
adjustment may not be the consequence of firms’ objective to reach the target shortterm debt ratio, but rather a consequence of the need of short-term to finance investment
opportunities, when internal funds are clearly insufficient for this purpose. Regarding
the capital structure decisions, non-family owned firms may follow particularly the
financing behaviour forecasted by Pecking Order Theory, considering that, when
6
internal finance is insufficient, these firms may have to raise short-term debt, given their
difficulty to obtain long-term debt.
Still in the context of non-family owned firms, we can expect that the problems of
information asymmetry with creditors are an obstacle for these firms to access to longterm debt. Therefore, it is expected a tiny rate of adjustment of long-term debt toward
the respective target ratio for non-family owned firms.
Blanco-Mazagatos et al. (2007) state that family-owned firms manage their financial
resources more efficiently than non-family owned firms as a consequence of the greater
frequency of ownership and management in the same hands. The fact that the goal of
owners of family firms to pass ownership on to future generations can lead familyowned firms to forego short-term strategies in favour of long-term ones (Guzzo &
Abbott, 1990; Tagiuri & Davis, 1992; James, 1999). Dyer & Whetten (2006) conclude
that family reputation is directly related to firm reputation. Such a connection may
contribute to a greater effort by owners/managers of family-owned firms to promote
efficient management of firm resources, compared to what happen in non-family owned
firms. Greater management flexibility in family-owned firms (Haynes et al., 1999), can
contribute decisively to family-owned firms making financing decisions with the goal to
reach the target short and long-term debt ratios.
On the one hand, the less constant need to resort to short-term debt, and
consequently lesser need to renegotiate the terms of the debt, can mean lower rate of the
adjustment of short-term debt toward target short-term ratio by family-owned firms,
compared to what occurs in non-family owned firms. On the other hand, the greater
ability to obtain long-term debt, committing family-owned firms to ensure solvency and
to reduce the possibility of bankruptcy, can contribute to these firms to have greater rate
7
of adjustment of long-term debt toward target debt ratio, compared to non-family owned
firms.
Summarizing, family-owned firms may not follow almost exclusively the financing
behaviour forecasted by Pecking Order Theory, since variations in their levels of short
and long-term debt may not be exclusively dependent on insufficient internal finance. In
fact, it is easier for family-owned firms to make debt adjustments toward target debt
ratios, following the financial behaviour forecasted by Trade-Off Theory, than for nonfamily owned firms.
Based on the arguments above, we formulate the following research hypotheses:
H3: The rate of adjustment of short-term debt toward the target short-term debt ratio is
greater for non-family owned firms than do for family-owned firms.
H4: The rate of adjustment of long-term debt toward the target long-term debt ratio is
greater for family owned firms than do for non-family-owned firms.
3. Sample, Variables and Estimation Method
3.1. Sample
This study uses the SABI (Sistema de Balanços Ibéricos - Analysis System of Iberian
Balance Sheets) database supplied by Bureau van Dijk, for the period 1999 to 2006.
As stated by López-Gracia & Sánchez-Andújar (2007), there is no consensus about
the criteria for defining a family firm. Various criteria are used: 1) based on the people
who effectively manage firms, or who have effective decision-making authority
(Filbeck & Lee, 2000); 2) based on who holds the firm capital (Donckels & Lambrecht,
1999; Littunen & Hyrsky, 2000); and 3) based on the possibility of transferring the
business to future generations (McConaughy & Phillips, 1999). In this context, Chua et
8
al. (1999) conclude that to define family firm, characteristics related to management,
ownership control, and the succession intention should simultaneously be considered.
For selection of family firms, we are limited by the information available on the
database used (SABI). To classify the firms we follow the criterion of López-Gracia &
Sánchez-Andújar (2007), considering as a family-owned firm those firms with a
shareholder, which may be single or family, and owning more than 50% of the total
shares, and the remaining shares being relatively diluted4. The remaining firms are
considered as non-family owned firms. This criterion of classification of family-owned
and non family -owned firms is verified by all firms of the research sample during the
period of analysis.
We
select
family-owned
and
non-family
owned
SMEs
based
on
the
recommendation of the European Union L124/36 (2003/361/CE). According to this
recommendation, a firm is considered SME when it meets two of the following criteria:
1) fewer than 250 employees; 2) annual balance sheet total not exceeding 43 million
euros; and 3) annual turnover not exceeding 50 million euros.
Using dynamic panel estimators is pertinent, since one of the main goals of this
paper is to estimate the rate of adjustment of levels of short-term debt and long-term
debt toward target debt ratios, for family-owned and for non-family owned firms.
According to Arellano & Bond (1991), for all firms making up a given sample to be
considered in the econometric analysis and in second-order autocorrelation tests, their
presence is necessary over a given number of consecutive years. Otherwise, some firms
would be eliminated from the respective econometric analysis, which could lead us to
interpret the results based on a certain number of firms, when in fact that number would
be lower.
4
This criterion is verified by all owned-firms selected for the research sample and for each year of the
period of analysis 199-2006.
9
Therefore, based on the considerations of the last-named authors, and on the criteria
considered for definition of SMEs, we obtained two sub-samples: i) 614 family-owned
SMEs (all of them are non-listed SMEs) for the period 1999-2006; and ii) 240 nonfamily owned SMEs (all of them are non-listed SMEs) for the period 1999-2006. Both
panels are balanced, the panel of family-owned firms being made up of 3684
observations, and the panel of non-family owned firms being made up of 1440
observations.
3.2. Variables5
In order to estimate the proportions of short-term debt and long-term debt financing
relative to the financial deficit, we use as dependent variables: variation of short-term
debt (ΔSLEVi,t), given by the difference between short-term debt in the current and
previous periods, and variation of long-term debt (ΔLLEVi,t), given by the difference
between long-term debt in the current and previous periods. In addition, to estimate
adjustments of short-term debt and long-term debt toward respective target debt ratios,
we use as dependent variables: short-term debt (SDi,t), given by the ratio between shortterm liabilities and total assets; long-term debt (LDi,t), given by the ratio between longterm liabilities and total assets.
To estimate the proportions of short-term debt and long-term debt financing relative
to the financial deficit, we use as independent variable financial deficit (FDi,t), given by
variation of fixed assets plus variations of working capital plus variation of long-term
5
The variables used in this study, and their corresponding measures, are in accordance with various
empirical studies in the field of SME capital structure, for example, Michaelas et al. (1999); Sogorb-Mira
(2005); López-Gracia & Sanchéz-Andújar (2007), Heyman et al. (2008), López-Gracia & Sogorb-Mira
(2008).
10
debt less cash flow6. As determinants7 used in the estimation of the adjustments of
short-term debt and long-term debt, this study considers: profitability (PROFi,t) given by
the ratio between operating profits and total assets, age (AGEi,t)8 given by the logarithm
of the number of years of the firm’s life, size (SIZEi,t) given by the logarithm of sales,
tangible assets (TANGi,t) given by the ratio between fixed assets and total assets, growth
(GROWi,t) given by the growth rate of sales, intangible assets (INTi,t) given by the ratio
between intangible assets and total assets; effective tax rate (ETRi,t) given by the ratio of
income tax paid divided by profits before taxes and after interests, non-debt tax shields
(NDTSi,t) given by the ratio between depreciation and total assets, and risk (EVOLi,t),
given by the absolute value of the variation of operating profits.
Talberg et al. (2008) conclude that firm´s industry sector influences capital structure
decisions. In order to control the possible influence of the industry sector of firms
belong to on the results, we use industry sector variables in all estimated regressions9. In
addition, we use annual dummy variables to control for the effects of possible changes
in the economic situation on the results.
6
Where variation of fixed assets is given by fixed assets in the current period minus fixed assets in the
previous period; variation of working capital is given by working capital in the current period minus
working capital in the previous period; and variation of long-term debt is given by long-term debt in the
current period minus long-term debt in the previous period, variation of long-term debt corresponds to the
amount of long-term debt to be repaid during the period t.
7
In order to test the robustness of the results obtained, we use alternative measures for some determinants
of this study: PROF*i,t given by the ratio between operational profits and sales, SIZE*i,t given by the
logarithm of total assets, GROW*i,t given by the growth rate of total assets. The results are presented in
Appendix C, Table C1.
8
Age is calculated by the difference between the current year and the year of firm´s foundation.
9
We consider three sectoral dummies representing the principal industry sectors: primary sector – I
(agriculture and fishing); secondary sector - II (manufacturing and construction); and tertiary sector -III
(commerce and services).
11
3.3. Estimation Methods
Proportion of debt financing relative to the financial deficit
According to Pecking Order Theory, the variations of firm´s capital structure are not a
consequence of firms´ goal to reach the target debt ratio, but rather to external financing
needs, when internal finance is insufficient (Shyam–Sunder & Myers, 1999). The model
suggested by Shyam–Sunder & Myers (1999), which describes the behaviour forecasted
by Pecking Order Theory regarding firm’s capital structure, can be presented as follows:
Di ,t   0  BFDi ,t  DS  d t   i ,t ,
(1)
where: Di ,t represents variations of debt, which in the specific case of this study
represents variations of short-term debt and variations of long-term debt, B is the
parameter that measures the proportion of debt financing relative to the financial deficit,
FDi ,t is the financial deficit, DS represents the industry dummies, d t represents the
temporal dummies, and  i,t is the error which is assumed to have zero average and
constant variance.
According to Pecking Order Theory, we can expect that variations of debt are a
consequence of financial deficit, and so the changes of debt will be the absolute
consequence of financial deficit, with the expectation that B  1 (Shyam–Sunder &
Myers, 1999).
Given that heteroscedasticity is normally a relevant phenomenon in empirical work
using cross-section data, standard deviations of the parameters are estimated according
to the White estimator, which provides standard deviations of the estimated parameters
consistent with the possible existence of heteroscedasticity.
12
Adjustments of Debt toward Target Debt Ratio
According to Trade–Off Theory, firms adjust their level of debt toward target debt ratio
(Lev & Pekelman, 1975; Ang, 1976; Taggart, 1977; Jalilvand & Harris, 1984).
The adjustment can be described as follows:
Di ,t  Di ,t 1   ( Di ,t *  Di ,t 1 )   i ,t ,
(2)
where Di ,t represents the debt ratio in firm i in the current period, which in this study
represents the ratios of short and long-term debt, Di ,t 1 is the debt of firm i in the
previous period, Di ,t * is the target debt ratio of firm i in the current period t, and  is
the rate of adjustment of the level of debt toward target debt ratio.
Regrouping the terms, the equation (2) can be given by:
Di ,t  (1   ) Di ,t 1  Di ,t *  i ,t ,
(3)
where 0    1. If   1 , we have Di ,t  Di ,t * , that is to say, the level of debt is equal
to the target debt ratio. In these circumstances, we would be in the “perfect world” of
Modigliani & Miller (1958), without information asymmetry and without transaction
costs. On the contrary, if   0 , then Di ,t  Di ,t 1 , the level of debt does not change
from the previous period to the current period, and so there is no adjustment of debt
toward the target debt ratio. In these circumstances, we can conclude that the firm does
not try to reach the target debt ratio. Finally, if   1 , we can conclude that firms have
excess debt and they do not reach the target debt ratio.
Just as De Miguel & Pindado (2001), Ozkan (2001), Fama & French (2002), Gaud
et al. (2005), López-Gracia & Sánchez-Andújar (2007), López-Gracia & Sogorb-Mira
(2008), this study considers that target debt ratio depends on firm’s specific
characteristics such as fixed assets, size, profitability and others.
13
Therefore, firms’ target level of debt is given by:
n
Di ,t *    K Z k ,i ,t  ui  DS  d t  vi ,t ,
(4)
K 1
where: Z K ,i ,t is the determinant10 k of the debt of firm i at the time t,  K are the
coefficients of each determinant of debt, u i are firms’ non-observable individual
effects, not directly observable from debt determinants, DS represents the industry
sector dummies, d t represents the temporal dummies, and vi ,t is the error which is
assumed to have zero average and constant variance.
Substituting (4) in (3) and regrouping terms, then:
n
Di ,t  Di ,t 1    K Z k ,i ,t   i   S   t   i ,t ,
(5)
K 1
where:   (1   ) ,  K   K ,  i  ui ,  S  DS ,  t  d t , e  i ,t  vi ,t .
To estimate equation (5) on the basis of the traditional panel methods, considering
fixed or random individual effects, we obtain biased and inconsistent estimates of the
parameters, since in addition to the existence of correlation between  i and Di ,t 1 , there
is also correlation between  i,t and Di ,t 1 , which is to say, firms’ non-observable
individual effects and the error are correlated with the lagged debt. In addition, using
dynamic estimators, rather than using traditional panel methods has the following extra
advantages: i) greater control of endogeneity; ii) greater control of possible collinearity
between explanatory variables; and iii) greater effectiveness in controlling effects
caused by the absence of relevant explanatory variables for the results.
10
As already mentioned, the specific determinants of firms are: profitability (PROF i,t), age (AGEi,t), size
(SIZEi,t), tangibility (TANGi,t), growth (GROWi,t), intangible assets (INTi,t), effective tax rate (ETRi,t),
non-debt tax shields (NDTSi,t) and risk (EVOLi,t).
14
This study uses the Generalized Moments Method – GMM system (1998) estimator,
by Blundell & Bond (1998), so as to estimate the model of partial adjustment. Blundell
& Bond (1998) conclude that when the dependent variable is persistent, the GMM
system (1998) estimator is more robust than the Generalized Moments Method – GMM
(1991) estimator11. Blundell & Bond (1998) extend the GMM (1991) estimator,
considering a system of variables at level and in first differences. For the variables at
level the instruments are presented in first differences, and for the variables in first
differences, the instruments are presented at level.
Nevertheless, the GMM system (1998) estimator can only be considered valid if: i)
the restrictions, a consequence of using the instruments, are valid; and ii) there is no
second order autocorrelation.
To test the validity of the restrictions, we use the Hansen test. The null hypothesis
indicates that the restrictions, imposed by using the instruments, are valid. By rejecting
the null hypothesis, we conclude that the restrictions are not valid, and so the results are
not robust. We test for the existence of first and second-order autocorrelation. The null
hypothesis is that there is no autocorrelation. Rejecting the null hypothesis of nonexistence of second-order autocorrelation, we conclude that the results are not robust.
For the results of the GMM system (1998) estimator to be considered robust, the
restrictions imposed by using the instruments have to be valid and there can be no
second-order autocorrelation.
11
In this study, we find persistence of debt for family-owned firms and non-family owned firms, whether
considering short or long-term debt as dependent variable. Therefore, it is clearly advisable to use the
GMM system (1998) estimator, rather than the GMM (1991) estimator.
15
4. Results
4.1. Descriptive Statistics
Table 1 below presents the results of the descriptive statistics referring to the dependent
and independent variables used in this study.
(Insert Table 1 About Here)
The average of short-term debt of non-family owned firms is greater than that of the
family-owned firms, the opposite being found for average long-term debt12. The results
of the Mann-Whitney test of differences of average values confirm that average values
of short and long-term debt are different in the context of family-owned and non-family
owned firms. The descriptive statistics suggest a greater dependence on short-term debt
in non-family owned firms, and higher levels of long-term debt in family-owned firms.
4.2. Proportion of Debt Financing Relative to the Financial Deficit and the Rate of
Adjustment of Debt toward Target Debt
Table 2 below presents the results referring to the proportions of financing of short and
long-term debt relative to the financial deficit for family-owned and non-family owned
firms13.
(Insert Table 2 About Here)
12
From analysis of the descriptive statistics of the variables, we find the maximum value of short-term
debt for family-owned and for non-family owned firms is quite high. These values may be related to firms
to certain times, in which firms have high growth rates and low levels of internal finance. In those
circumstances, the high values of short-term debt are justified by the greater ease of access to short-term
debt, compared to the terms imposed by creditors for long-term debt. Regarding total debt, the maximum
value for family-owned firms is 0.99780 and 0.99032 for non-family owned firms. The maximum values
of total debt for family-owned and non-family owned firms are clearly influenced by the levels of shortterm debt.
13
In appendix A, Tables A1 and A2 present respectively for family-owned and non-family owned firms,
the correlation matrices of the variables used in the regressions relating to the impacts of financial deficit
on variations of short and long-term debt. It is of note that correlation coefficients between independent
variables, between independent and control variables, and between control variables are not very high,
and so the possibility of collinearity between variables will not affect the results obtained in this study.
16
On the one hand, we find that the proportion of financing of short-term debt relative
to the financial deficit in family-owned firms ( BSDF  0.24117 ) is less than that identified
for non-family owned firms ( BSDNF  0.90491 ). On the other hand, the proportion of
financing of long-term debt relative to the financial deficit in family-owned firms
( BLDF  0.27766 ) is above that one found for non-family owned firms14 ( BLDNF  0.07664 ).
Table 3 presents the results of the Chow test of differences of estimated parameters
measuring the proportions of financing of short and long-term debt relative to the
financial deficit for family-owned and non-family owned firms.
(Insert Table 3 About Here)
The results of the Chow test indicate the rejection of the null hypothesis of equality
of estimated parameters measuring the relationships between the proportions of
financing of short and long-term debt relative to the financial deficit for family-owned
and non-family owned firms.
The results of the rates of adjustment to short and long-term debt toward the
respective target levels for family-owned and non-family owned firms are presented in
Table 415.
(Insert Table 4 About Here)
In the regressions relating to the adjustment of short and long-term debt toward the
respective target ratios, whether considering family-owned or non-family owned firms,
14
In appendix B, Table B1 presents the results relating to the impacts of financial deficit on variation of
total debt for family-owned and non-family owned firms. The impact of financial deficit on variation of
total debt is considerably greater for non-family owned firms ( BTDNF  0.98155 ), than for family-owned
firms ( BTDF  0.51883 ). This difference is caused by the high impact of financial deficit on variation of
short-term debt for non-family owned firms.
15
In appendix A, Tables A3 and A4 present respectively for family-owned and non-family owned firms,
the correlation matrixes of the variables used in regressions relating to adjustments of short and long-term
debt toward the respective target debt ratios. Also in these circumstances, the correlation coefficients
between the independent variables, between the independent and control variables, and between the
control variables, are not particularly high. Therefore, possible problems of collinearity between variables
will not cause bias of the estimated parameters.
17
the results of the Hansen test indicate that we cannot reject the null hypothesis of
validity of the instruments used. What is more, we cannot reject the null hypothesis of
absence of second-order autocorrelation. Given the validity of the instruments used and
absence of second-order autocorrelation, we can conclude that the results obtained with
the GMM system (1998) estimator are robust16.
The rate of adjustment of short-term debt toward target debt ratio for family-owned
firms (  SDF  0.13258 ) is lower than that one found for non-family owned firms
(  SDNF  0.24888 ). As for the rate of adjustment of long-term debt toward target debt
ratio, family-owned firms show a greater rate of adjustment (  LDF  0.18053 ) than that
one identified for non-family owned firms17 (  LDNF  0.05030 ).
Table 5 presents the results of the Chow test of differences of estimated parameters
measuring the rates of adjustment of short and long-term debt toward the respective
target ratios, for family-owned and non-family owned firms18.
(Insert Table 5 About Here)
16
Aiming to test the robustness of the empirical evidence obtained, in appendix C, Table C1 presents the
regressions referring to the adjustments of short and long-term debt toward the respective target debt
ratios, for family-owned and non-family owned firms, using alternative measures for the determinants of
PROFi,t, SIZEi,t, and GROWi,t. The empirical evidence obtained corroborates that presented in Table 5,
which confirms the empirical evidence obtained in this study. In addition, we use the LSDVC (Least
Square Dummy Variable Corrected) estimator by Bruno (2005), also with the aim of testing the
robustness of the empirical evidence presented in Table 4. Use of the LSDVC (2005) estimator is
advisable up to 30 cross-sections, as a way of testing the robustness of results obtained using the GMM
system (1998) dynamic estimators. The results from application of the LSDVC estimator by Bruno
(2005) can be requested to the authors.
17
In appendix B, Table B2 present the rates of adjustments of total debt toward the target total debt ratio
as well as the relationships between determinants and total debt, for family-owned firms and non-family
owned firms. It is worth to note that the similar rate of adjustments for family-owned
(  TDF  0.31311 ) and non-family owned firms (  TDNF  0.29918 ) . The identical rate of
adjustment of total debt toward the respective target ratios for family-owned and non-family owned
firms, is the consequence of the opposite signs of the rates of adjustments of short and long-term debt.
18
Table 5 also presents the results of the Chow test of differences of the estimated parameters measuring
relationships between determinants and short and long-term debt for family-owned and non-family owned
firms. Except for the relationship between age and long-term debt, we always reject the null hypothesis of
equality of estimated parameters measuring relationships between short and long-term debt for familyowned and non-family owned firms.
18
Also in these circumstances, the results of the Chow test indicate the rejection of the
null hypothesis of equality of estimated parameters. So we can conclude that non-family
owned firms have a greater rate of adjustment of short-term debt toward target shortterm debt than is the case in family-owned firms.
5. Discussion of the Results
The empirical evidence obtained lets us corroborate the previously formulated
hypotheses H1 and H2. The proportion of short-term debt financing relative to the
financial deficit is greater for non-family owned than do for family-owned firms; and,
the proportion of long-term debt financing relative to the financial deficit is greater for
family owned than do for non-family-owned firms.
Family-owned firms have a greater rate of adjustment of long-term debt toward the
target long-term debt than non-family owned firms. Therefore, based on these results,
we can consider the previously formulated hypotheses H3 and H4 as valid.
The empirical evidence suggests that problems of underinvestment are more
relevant in non-family owned firms than in family-owned firms. Indeed, the results
suggest that lower information asymmetry between owners/managers of family-owned
firms and creditors, compared to the case of non-family owned firms may contribute: i)
for family-owned firms to verify a greater proportion of long term financing relative to
finance deficit than the proportion of short-term financing relative to finance deficit; ii)
for family-owned firms to verify a greater rate of adjustment of long-term debt toward
target ratio, but a lower rate of adjustment of short-term debt toward target ratio.
The goal of long-term survival of family-owned firms, given the high investment
made and consequent impossibility of their owners to diversify their personal portfolio,
as well as the relevance of keeping firm ownership in the family, could be determinant
19
factors contributing for the preference of family-owned firms for long-term rather than
short-term debt, when internal finance is insufficient.
The results of the current study suggest that, in order to avoid financial stress and
liquidity risk, family-owned firms may turn in a greater proportion to long-term debt
due to the lesser information asymmetry with creditors. As for non-family owned firms,
they have more restricted terms in accessing long-term debt and cannot avoid excessive
short-term debt. In this context, the arguments of Fagiolo & Luzzi (2006) seem to be
relevant, i.e. that excessive dependence on short-term debt can lead to considerable
financial stress, given the need to pay off the debt and associated charges over a very
short period, which may threaten the implementation of good investment opportunities.
López-Gracia & Sánchez-Andújar (2007) identified a rate of adjustment of total
debt toward target debt ratio in small Spanish family-owned firms (  TDF  0.50574 )
greater than that of small Spanish non-family owned firms (  TDNF  0.29384 ). The
authors conclude that the difference between the rates of adjustments estimated is due to
the greater information asymmetry between owners/managers of non-family owned
firms and creditors, reducing the capacity of these firms to adjust total debt toward
target debt ratio, compared to the situation in family-owned firms.
The evidence obtained in this study firms allows us conclude that the rates of
adjustment of total debt toward the target level are similar for family-owned
(  TDF  0.31311 ) and non-family owned (  TDNF  0.29918 )19 firms. Thus, on the basis
of the rate of adjustment of total debt toward target debt level, we may conclude that the
problems of information asymmetry between the firms´ owners/managers and creditors
have an equal effect for family-owned and non-family owned firms. However, this
conclusion is clearly refuted, when analyzing the rates of adjustment of short and long19
See results presented in Appendix B, Table B2.
20
term debt toward the respective target debt ratios, for family-owned and for non-family
owned firms.
The results show that non-family owned firms, when internal finance is insufficient,
are excessively dependent on short-term debt ( BSDNF  0.90491 ), resorting in a very
limited proportion to long-term debt to face their financial deficit ( BLDNF  0.07664 ).
However, the rate of the adjustment of short-term debt toward target short-term ratio
ratio for non-family owned firms (  SDNF  0.24888 ) is considerably greater than the
rate of the adjustment of the long-term debt toward target level (  LDNF  0.05030 ). The
empirical evidence suggests a relationship between the proportions of short and longterm debt financing relative to the financing deficit and the rates of adjustment of short
and long-term debt toward the respective target debt ratios. Firstly, when internal
finance is insufficient, the relevance of the problems of information asymmetry between
owners/managers of non-family owned firms and creditors, seems to limit the access to
long-term debt, which contributes to a reduced rate of the adjustment of long-term debt
toward target ratio. Secondly, when internal finance is insufficient, non-family owned
firms’ excessive dependence on short-term debt contributes to a greater rate of the
adjustment of short-term debt toward target ratio. This greater rate of the adjustment of
short-term debt is probably not a consequence of the goal to reach the target level, but
rather to reach a target short-term debt ratio arising out of the dependence on for shortterm debt financing.
Regarding family-owned firms the results are contrary to those obtained for nonfamily owned firms. Indeed, when internal finance is lacking, the results suggest that
the lower information asymmetry with creditors contributes to family-owned firms to
obtain greater amounts of long-term debt ( BLDF  0.27766 ) than of short-term debt
21
( BSDF  0.24117 ), and also to a greater rate of adjustment of long-term debt toward
target level (  LDF  0.18053 ) than the rate of the adjustment of short-term debt toward
target level (  SDF  0.13258 ).
Greater possibility to obtain long-term debt, and consequently lesser need to resort
to short-term debt, reduces the stress for family-owned firms in managing their financial
resources, which may contribute to a greater rate of the adjustment of long-term debt
toward target ratio. In addition, family-owned firms seem to include in their financing
strategies the possibility of reaching target levels of short and long-term debt. Thus,
family-owned firms’ rates of adjustments of debt levels are not merely influenced by
financing needs as appears to occur in non-family owned firms. These aspects could be
fundamental for family-owned firms being more efficient in managing their financial
resources than non-family owned firms, corroborating the conclusions of BlancoMazagatos et al. (2007).
Regarding the relationships between factor determinants and short and long-term
debt for family-owned and non-family owned firms20, we now point out the main
empirical evidence obtained.
Firstly, the greater profitability does not influence negatively the level of long-term
debt of non-family owned firms, as opposed to what is verified by family-owned firms.
In addition, greater profitability for non-family owned firms means a sharper reduction
of short-term debt than in the case of family-owned firms21. These results suggest the
relative importance that long-term debt may have for non-family owned firms as a
consequence of the lack in accessing to alternative sources of long-term finance.
20
See results presented in Table 4
Observing the results presented in Table 4, we see that the parameter measuring the relationship
between profitability and short-term debt in non-family owned firms is –0.46491, and –0.32794 for
family-owned firms. The result of the Chow test (Table 5) shows that the estimated parameters cannot be
considered of equal magnitude.
21
22
Secondly, on the one hand, size is a more important determinant of long-term debt
for non-family owned firms than for family-owned firms22. On the other hand, tangible
assets are of greater relative importance for non-family owned firms being able to
substitute short-term debt for long-term debt, than they are for family-owned firms23.
The greater relative importance of size and tangible assets for non-family owned firms
to obtain long-term debt suggests the greater relevance of problems of information
asymmetry between owners/managers and creditors for this kind of firm, compared to
family-owned firms.
Thirdly, when internal finance is insufficient, family-owned firms finance their
growth, and growth opportunities24, through the use of long-term debt, whereas nonfamily owned firms turn to short-term debt for this purpose. These results show that
creditors prefer to grant short-term debt, probably as a consequence of the problems of
information asymmetry and underinvestment, in order to monitor more effectively
repayment of the debt by the non-family owned firms.
Fourthly, in the context of family-owned firms, on the one hand a higher effective
tax rate means increased use of short and long-term debt, and on the other hand greater
non-debt tax shields and greater risk contribute to lower levels of short and long-term
debt. As for non-family owned firms, effective tax rate, non-debt tax shields and level
of risk are not important determinants of short and long-term debt. This empirical
evidence is particularly relevant because it shows that variations of short and long-term
22
The results presented in Table 4 show that the parameter measuring the relationship between size and
long-term debt is 0.05802 for non-family owned firms, and 0.01892 for family-owned firms. The result of
the Chow test (Table 5) indicates the estimated parameters cannot be considered of equal magnitude.
23
As we can see from the empirical evidence presented in Table 4, on the one hand the coefficient
measuring the relationship between collateral and short-term debt in non-family owned firms is –0.22887,
and –0.10492 for family-owned firms. On the other hand, the coefficient measuring the relationship
between collateral and long-term debt in non-family owned firms is 0.28480 and 0.12794 for familyowned firms. The results of the Chow test presented in Table 5 show that, whether taking short-term debt
or long-term debt as the subject of analysis, the estimated parameters cannot be considered of equal
magnitude.
24
Growth opportunities are measured by the level of intangible assets, just as in Michaelas et al. (1999)
and Sogorb-Mira (2005).
23
debt in family-owned firms are influenced by the trade-off between debt-tax shields and
bankruptcy costs, which does not occur in non-family owned firms.
The results of the current study suggest that non-family owned firms follow the
financing behaviour predicted by Pecking Order Theory, according to which firms with
high asymmetry information problems depend mainly on debt. Short-term debt is less
sensitive to problems of asymmetric information relative to long term (Flannery, 1986).
The results obtained show that non-family owned firms depend strongly on short-term
debt, suggesting that these firms encounter higher problems of asymmetric information
than do family-owned firms. The results obtained in this study suggest that family
ownership is an important characteristic for diminishing problems of information
asymmetry and underinvestment between firm´s owners/managers and creditors.
Family-owned firms’ greater possibility to access to long-term debt can contribute
to a greater diversification of their financing sources, and corroborates the conclusions
of Haynes et al. (1999) for family firms in general. The lower financial stress that
family-owned firms may be subject to, as a consequence of greater ability to diversify
the forms of finance, may be decisive for them being able to include in their strategies
the possibility of achieving target levels of short and long-term debt. This financing
behaviour of family-owned firms is according to the assumptions of the Trade-off
Theory. Non-family firms may face higher problems of asymmetric information, since
they depend on internal finance, which insufficiency generates a dependence on shortterm debt. This financing behaviour of non family-owned firms is according to what is
predicted by Pecking Order Theory. Furthermore, the high rate of adjustment of shortterm debt toward target ratio of non-family owned firms seems to be caused by the need
to avoid financial unbalance related to the dependence of these firms on short-term debt
to finance their external financing needs.
24
6. Conclusion
Based on two samples of 614 Portuguese family-owned SMEs and 240 Portuguese nonfamily owned SMEs, using various panel data estimators, this study seeks to identify the
differences between capital structure of family-owned and non-family owned firms. On
the one hand, the proportion of short-term debt financing relative to financial deficit is
greater for non-family owned firms than for family-owned firms, and the opposite
happening with the proportion of long-term debt financing relative to financial deficit.
On the other hand, the rate of adjustment of long-term debt toward target debt ratio is of
greater in family-owned firms than in non-family owned firms, the opposite being the
case regarding the rate of adjustment of short-term debt toward target ratio.
The empirical evidence also suggests a connection between the use of short and
long-term debt for family-owned and non-family owned firms, and adjustments of short
and long-term debt toward respective target levels: i) when internal finance is
insufficient, family-owned firms resort more to long-term debt than to short-term debt,
and the rate of adjustment of long-term debt toward target level being greater than the
rate of adjustment of short-term debt toward target level; and ii) when internal finance is
insufficient, non-family firms resort almost entirely to short-term debt, the rate of
adjustment of short-term debt toward target level being considerably greater than that
obtained for long-term debt.
The results obtained allows us to conclude that Trade-Off and Pecking Order
Theories in isolation do not explain the capital structure decisions of family-owned and
non-family owned firms, and what is more, these theories are not necessarily
contradictory in that explanation. In addition, the empirical evidence obtained in this
study shows that diminished problems of information asymmetry and underinvestment,
as a consequence of family ownership, can be determinant for family-owned firms’
25
capital structure decisions to be made according to Trade-Off Theory, and not only to
Pecking Order Theory, as verified by non non-family owned firms.
This study has basically three limitations. Firstly, the unavailability of data about
management, namely regarding firms’ succession intention, prevents us from
generalizing the results of this paper to family firms in general. Secondly, the fact there
are no data about the direct relationships between firms’ owners/managers and creditors
for family-owned and for non-family owned firms made it impossible to explore the
direct influence of trusting relationships between firm’s owners/managers and creditors
on problems of underinvestment for family-owned and for non-family owned firms.
Thirdly, due to lack of data, we cannot consider the question related to intermingling,
i.e. the use of firm owners’ assets to support the business and/or the use of business
assets (other than wage and salary payments) for support of the household. However, it
would be important to investigate the differences in the incidence of intermingling
between family-owned firms and non-family owned firms and its relationship with
capital structure decisions.
For future research, we suggest the study of the differences between the capital
structure decisions of family owned firms with financial deficit and the capital structure
decisions of family owned firms with surplus.
Appendix A: Correlations Matrix
Table A1: Correlation Matrix – Family-Owned Firms – Variables of Impact of
Financial Deficit
ΔSLEVi,t
1
-0.38**
ΔLLEVi,t
ΔSLEVi,t
ΔLLEVi,t
FDi,t
DI
DII
DIII
-0.26**
0.03*
-0.12**
-0.08**
0.30**
-0.02
0.16**
0.07**
FDi,t
DI
DII
DIII
1
0.01
-0.08**
-0.10**
1
-0.28**
-0.26**
1
-0.38**
1
1
Notes: 1. ** statistical significant at the 1% level; * statistical significant at the 5% level.
26
Table A2: Correlation Matrix – Non-Family Owned Firms –
Variables of Impact of Financial Deficit
ΔSLEVi,t
1
-0.45**
ΔLLEVi,t
ΔSLEVi,t
ΔLLEVi,t
FDi,t
DI
DII
DIII
0.53**
0.07**
0.11**
0.13**
0.12**
-0.02
-0.08**
-0.10**
FDi,t
DI
DII
DIII
1
-0.02
-0.11**
-0.14**
1
-0.28**
-0.26**
1
-0.38**
1
1
Notes: 1. ** statistical significant at the 1% level.
Table A3: Correlation Matrix – Family-Owned Firms – Variables of Rate
Adjustment to Target Debt
SDi,t
LDi,t
PROFi,t
AGEi,t
SIZEi,t
TANGi,t
GROWi,t
INTi,t
ETRi,t
NDTSi,t
EVOLi,t
DI
DII
DIII
SDi,t
LDi,t
PROFi,t
AGEi,t
SIZEi,t
TANGi,t
GROWi,t
INTi,t
ETRi,t
NDTSi,t
EVOLi,t
DI
DII
DIII
1
-0.52**
-0.09**
-0.06**
-0.001
-0.41**
0.06**
-0.07**
-0.02
-0.19**
0.04**
0.12**
-0.18**
-0.15**
1
-0.15**
-0.04**
0.018
0.42**
-0.01
0.15**
-0.001
0.16**
-0.03*
0.03*
0.23**
0.12**
1
-0.05**
0.10**
-0.14**
0.02
-0.02
0.003
0.008
0.009
-0.10**
0.06**
0.11**
1
-0.32**
-0.13**
-0.03*
-0.03*
0.007
-0.05**
-0.02
0.10**
0.09**
0.01
1
0.17**
-0.0006
0.11**
0.0008
-0.03*
0.02
0.004
0.29**
-0.12**
1
-0.01
0.23**
-0.01
0.38**
-0.03*
0.17**
0.29**
-0.16**
1
-0.002
-0.0004
-0.01
0.02
-0.13**
0.21**
0.28**
1
-0.02
0.08**
-0.007
-0.01
0.05**
0.10**
1
0.01
-0.003
-0.01
0.03*
0.01
1
-0.01
0.10**
0.22**
-0.07**
1
-0.08**
0.01
0.15**
1
-0.28**
-0.26**
1
-0.38**
1
Notes: 1. ** statistical significant at the 1% level; * statistical significant at the 5% level.
Table A4: Correlation Matrix – Non-Family Owned Firms – Variables of Rate of
Adjustment to Target Debt
SDi,t
LDi,t
PROFi,t
AGEi,t
SIZEi,t
TANGi,t
GROWi,t
INTi,t
ETRi,t
NDTSi,t
EVOLi,t
DI
DII
DIII
SDi,t
1
-0.43**
-0.06*
0.13**
0.005
-0.44**
-0.05*
-0.11**
0.03
-0.19**
0.03
0.09**
0.14**
0.18**
LDi,t
PROFi,t
AGEi,t
SIZEi,t
TANGi,t
GROWi,t
INTi,t
ETRi,t
NDTSi,t
EVOLi,t
DI
DII
DIII
1
-0.21**
-0.03
0.14**
0.35**
0.12**
0.24**
-0.04
0.005
-0.008
0.01
-0.11**
-0.13**
1
-0.10**
0.009
-0.10**
0.02
-0.15**
-0.006
0.05*
-0.05*
-0.06**
0.11**
0.16**
1
0.13**
-0.006
-0.05*
-0.02
0.03
-0.14**
-0.03
0.03
0.12**
0.05*
1
0.22**
0.03
0.35**
0.02
-0.04
-0.04
-0.02
0.27**
-0.03
1
0.04*
0.35**
-0.02
0.36**
-0.0009
0.19**
0.31**
-0.17**
1
-0.008
-0.002
-0.01
0.007
-0.19**
0.25**
0.21**
1
-0.01
0.009
-0.006
0.02
0.03
0.12**
1
-0.003
-0.004
0.02
0.08**
-0.02
1
0.03
0.08**
0.29**
-0.05*
1
0.005
-0.008
0.12**
1
-0.28**
-0.26**
1
-0.38**
1
Notes: 1. ** statistical significant at the 1% level; * statistical significant at the 5% level.
Appendix B: Total Debt – Family-Owned and Non-Family Owned
Firms
Table B1: Financial Deficit and Debt Variations – OLS Regressions
Independent
variables
FDi,t
DI
DII
DIII
Family-Owned Firms
Dependent Variables
ΔTLEVi,t
Non-Family Owned Firms
Dependent Variables
ΔTLEV i,t
0.51883**
(0.05349)
0.06850
(0.17492)
0.10561
(0.18496)
-0.14793
0.98155**
(0.05327)
0.27341
(0.24668)
0.29792*
(0.13504)
0.30907*
27
CONS
F(N(0,1))
R2
Firms
Observations
(0.16004)
500172**
(80336)
400.91**
[0.0000]
0.556
614
3684
(0.14802)
20972
(70884)
2197.12**
[0.0000]
0.7337
240
1440
Notes: 1. Standard deviations in () parentheses. 2. P – values in [ ] parentheses. 3. ** statistical significant
at the 1% level; * statistical significant at the 5% level. 4. The estimates include time dummy variables.
Table B2: Rate of Adjustment to Target Debt – GMM System (1998)
Independent variables
TDi,t-1
PROFi,t
AGEi,t
SIZEi,t
TANGi,t
GROWi,t
INTi,t
ETRi,t
NDTSi,t
EVOLi,t
DI
DII
DIII
CONS
Firms
Observations
F(N(0,1))
Hansen (N(0,1))
m1 (N(0,1))
m2 (N(0,1))
Family-Owned Firms
Dependent Variable
TDi,t
0.68689**
(0.05605)
-0.52882**
(0.04334)
-0.03347**
(0.01189)
0.04941**
(0.01478)
0.02302
(0.02615)
0.00590
(0.01681)
0.24425**
(0.05814)
0.08189**
(0.02003)
-0.34223**
(0.08883)
-0.05150**
(0.01728)
0.02992**
(0.00943)
0.00291
(0.00894)
0.00771
(0.00789)
-0.12793
(0.13994)
614
3684
114.76**
[0.000]
65.98
[0.352]
-6.86**
[0.000]
0.15
[0.903]
Non-Family Owned Firms
Dependent Variable
TDi,t
0.70082**
(0.06211)
-0.47988**
(0.04018)
-0.04309**
(0.01592)
0.06451**
(0.02003)
0.05593
(0.02916)
0.02410*
(0.01172)
0.11058**
(0.03495)
0.00054
(0.00109)
-0.04030
(0.08721)
-0.00202
(0.00278)
0.02050*
(0.00911)
0.02591**
(0.00748)
0.00968
(0.01074)
-0.02573
(0.04156)
240
1440
115.99**
[0.000]
57.04
[0.408]
-6.39**
[0.000]
0.37
[0.726]
Notes: 1. Standard deviations in () parentheses. 2. P – values in [ ] parentheses. 3. ** statistical significant
at the 1% level; * statistical significant at the 5% level. 4. The estimates include time dummy variables.
28
Appendix C: Rate of Adjustment to Target Debt – Alternatives
Measures of Determinants
Table C1: Rate of Adjustment to Target Debt – Family-Owned and Non-Family
Owned Firms – GMM system (1998)
Independent variables
SDi,t-1
LDi,t-1
PROF*i,t
AGEi,t
SIZE*i,t
TANGi,t
GROW*i,t
INTi,t
ETRi,t
NDTSi,t
EVOLi,t
DI
DII
DIII
CONS
Firms
Observations
F(N(0,1))
Hansen (N(0,1))
m1 (N(0,1))
m2 (N(0,1))
Family-Owned Firms
Dependent Variables
SDi,t
LDi,t
0.85091**
(0.074839)
0.80666**
(0.06584)
-0.34858**
-0.21227**
(0.04209)
(0.03698)
-0.02834**
-0.00569
(0.00811)
(0.01028)
0.02911**
0.01804*
(0.01056)
(0.00884)
-0.10110**
0.13446**
(0.02672)
(0.03829)
-0.03201**
0.03565**
(0.00822)
(0.00845)
0.04143
0.18115**
(0.03875)
(0.03998)
0.04803**
0.03293**
(0.01178)
(0.01059)
-0.23013**
-0.11083**
(0.06345)
(0.05388)
-0.03332**
-0.01834**
(0.01024)
(0.00867)
0.01784**
0.00956
(0.00655)
(0.01528)
-0.04035**
0.04102**
(0.01455)
(0.01384)
-0.02208
0.03408**
(0.01804)
(0.01216)
-0.11055
-0.02005
(0.11834)
(0.06453)
614
614
3684
3684
57.95**
54.15**
[0.000]
[0.000]
62.44
59.16
[0.371]
[0.405]
-7.99**
-7.62**
[0.000]
[0.000]
0.13
0.06
[0.913]
[0.959]
Non-Family Owned Firms
Dependent Variables
SDi,t
LDi,t
0.76067**
(0.06983)
0.95334**
(0.08309)
-0.44045**
-0.02384
(0.04113)
(0.03564)
-0.05039**
0.00733
(0.01551)
(0.01434)
0.01042
0.05772**
(0.01171)
(0.01452)
-0.21455**
0.29345**
(0.04419)
(0.06134)
0.02698**
-0.01144
(0.00855)
(0.01408)
0.29339**
-0.17004**
(0.06334)
(0.04780)
0.00063
0.00018
(0.00072)
(0.00041)
-0.02830
-0.02477
(0.07492)
(0.07784)
0.00052
-0.00254
(0.00098)
(0.00774)
0.01562
0.00205
(0.01114)
(0.00584)
0.04290**
-0.01699
(0.00988)
(0.03277)
0.03744**
-0.02750**
(0.01311)
(0.00833)
-0.02412
-0.00198
(0.04039)
(0.01688)
240
240
1440
1440
47.78**
42.29**
[0.000]
[0.000]
43.09
38.16
[0.493]
[0.538]
-6.03**
-5.20**
[0.000]
[0.000]
0.62
0.73
[0.662]
[0.559]
Notes: 1. Standard deviations in ( ) parentheses. 2. P – values in [ ] parentheses. 3. ** statistical
significant at the 1% level; * statistical significant at the 5% level. 4. The estimates include time dummy
variables.
29
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35
Table 1: Descriptive Statistics
Family-Owned Firms
Mean
S.D.
Min.
Variable
N
SDi,t
3684
0.53028
0.21472
LDi,t
3684
0.11899
0.12006
Non-Family Owned Firms
Mean
S. D.
Min.
Max.
N
Max
0.02491
0.98809
1440
0.56508
0.22240
0.02989
0.97903
0
0.74896
1440
0.07266
0.09479
0
0.70419
Mean Difference
Mann-Whitney
Z-Statistics
-2.08*
[0.0378]
-6.34**
[0.0000]
ΔSLEVi,t
3684
716673
5.01E+0.7
-1.69E+0.9 1.78E+0.9
1440
643687
5.38E+0.7 -2.11E+0.9 2.09E+0.9
-3.76**
[0.0043]
ΔLLEVi,t
3684
1024996
3.66E+0.7
-6.49E+0.8 1.79E+0.9
1440
966041
3.96E+0.7 -6.40E+0.8 1.87E+0.9
-2.03*
[0.0399]
PROFi,t
3684
0.04998
0.08241
-0.46606
0.67880
1440
0.04872
0.07121
-0.44536
0.42785
-1.29
[0.2419]
AGEi,t
3684
2.49972
0.93377
0
4.54329
1440
2.97405
0.80446
0
5.07517
-8.67**
[0.000]
SIZEi,t
3684
15.4667
1.31833
10.5670
17.8887
1440
15.2982
1.33982
12.5323
17.9112
-1.13
[0.3487]
TANGi,t
3684
0.31492
0.21996
0
0.97679
1440
0.30662
0.20872
0.00014
0.98729
-0.76
[0.5473]
GROWi,t
3684
0.12343
0.55849
-1.0747
4.6543
1440
0.10067
0.49382
-1.12524
4.04928
-2.13*
[0.03382]
INTi,t
3684
0.01344
0.04962
0
0.72219
1440
0.01680
0.05377
0
0.71892
-5.18**
[0.0000]
ETR
3684
0.45672
1.68720
-14.2882
36.7214
1440
0.45097
1.66635
-18.8182
39.7798
-0.21
[0.8273]
NDTSi,t
3684
0.04769
0.03866
0.00003
0.31901
1440
0.04844
0.03911
0.00005
0.30331
-0.34
[0.7305]
EVOLi,t
3684
1.44253
2.76543
0.00054
18.8374
1440
1.28322
2.52662
0.00036
16.9997
-3.33**
[0.0021]
FDi,t
3684
-181497
812780
-2.12E+0.7 1.53E+0.7
1440
-194782
900365
-2.10E+0.7 1.74E+0.7
-1.56
[0.1776]
1. P – values in [ ] parentheses. 2. ** statistical significant at the 1% level; * statistical significant at the
5% level
Table 2: Impact of Financial Deficit on Debt Variations – OLS Regressions
Independent
variables
FDi,t
DI
DII
DIII
CONS
F(N(0,1))
R2
Firms
Observations
Family-Owned Firms
Dependent Variables
ΔSLEVi,t
ΔLLEVi,t
0.24117**
(0.03369)
0.14739
(0.23892)
-0.87832**
(0.31188)
-0.49725*
(0.24501)
409264**
(70443)
277.12**
[0.0000]
0.4408
614
3684
0.27766**
(0.03840)
-0.07889
(0.28747)
0.98393**
(0.29394)
0.34932
(0.32737)
371172**
(64630)
282.71**
[0.0000]
0.4569
614
3684
Non-Family Owned Firms
Dependent Variables
ΔSLEVi,t
ΔLLEVi,t
0.90491**
(0.05123)
0.36272*
(0.16997)
0.61720**
(0.18928)
0.78289**
(0.21122)
19721
(76449)
1923.26**
[0.0000]
0.6441
240
1440
0.07664*
(0.03689)
-0.08931
(0.26372)
-0.31928*
(0.15823)
-0.47382*
(0.23119)
500226**
(76688)
203.33**
[0.0000]
0.4227
240
1440
Notes: 1. Standard deviations in ( ) parentheses. 2. P – values in [ ] parentheses. 3. ** statistical
significant at the 1% level; * statistical significant at the 5% level. 4. The estimates include time dummy
variables.
36
Table 3: Impact of Financial Deficit on Debt Variations – Chow Test
Independent variables
(FDi,t)ρF-ρNF=0
F(1,12708)
Dependent Variables
ΔSLEVi,t
105.91**
[0.0000]
ΔLLEV i,t
24.78**
[0.0000]
Notes: 1. P – values in [ ] parentheses; 2. ** statistical significant at 1% level.
Table 4: Rate of Adjustment to Target Debt – GMM System (1998)
Independent variables
SDi,t-1
LDi,t-1
PROFi,t
AGEi,t
SIZEi,t
TANGi,t
GROWi,t
INTi,t
ETRi,t
NDTSi,t
EVOLi,t
DI
DII
DIII
CONS
Firms
Observations
F(N(0,1))
Hansen (N(0,1))
m1 (N(0,1))
m2 (N(0,1))
Family-Owned Firms
Dependent Variables
SDi,t
LDi,t
0.86742**
(0.07842)
0.81947**
(0.07003)
-0.32794**
-0.20088**
(0.03879)
(0.03364)
-0.02904**
-0.00443
(0.00842)
(0.00870)
0.03049**
0.01892*
(0.01177)
(0.00941)
-0.10492**
0.12794**
(0.02872)
(0.03225)
-0.03872**
0.04462**
(0.01145)
(0.01236)
0.03998
0.20427**
(0.03684)
(0.04133)
0.04872**
0.03317**
(0.01206)
(0.01002)
-0.22744**
-0.11479**
(0.05802)
(0.05502)
-0.03278**
-0.01872**
(0.01004)
(0.00899)
0.01983**
0.01009
(0.00711)
(0.01637)
-0.03827**
0.04118**
(0.01374)
(0.01409)
-0.02552*
0.03323**
(0.01244)
(0.01178)
-0.10821
-0.01972
(0.11704)
(0.06339)
614
614
3684
3684
58.12**
54.17**
[0.000]
[0.000]
61.83
59.09
[0.378]
[0.398]
-7.87**
-7.54**
[0.000]
[0.000]
0.16
0.08
[0.895]
[0.944]
Non-Family Owned Firms
Dependent Variables
SDi,t
LDi,t
0.75112**
(0.06749)
0.94970**
(0.08114)
-0.46491**
-0.01497
(0.04371)
(0.02842)
-0.04972**
0.00663
(0.01421)
(0.01390)
0.00649
0.05802**
(0.01008)
(0.01533)
-0.22887**
0.28480**
(0.04634)
(0.05801)
0.02972**
-0.00562
(0.00991)
(0.01128)
0.28721**
-0.17663**
(0.06146)
(0.04876)
0.00042
0.00012
(0.00068)
(0.00023)
-0.01874
-0.02156
(0.07346)
(0.07630)
0.00036
-0.00238
(0.00083)
(0.00697)
0.01877*
0.00173
(0.00899)
(0.00553)
0.04226**
-0.01635
(0.00963)
(0.03227)
0.03635**
-0.02667**
(0.01247)
(0.00799)
-0.02395
-0.00178
(0.03977)
(0.01663)
240
240
1440
1440
48.01**
42.22**
[0.000]
[0.000]
43.34
38.23
[0.488]
[0.533]
-6.09**
-5.33**
[0.000]
[0.000]
0.54
0.65
[0.689]
[0.573]
Notes: 1. Standard deviations in ( ) parentheses. 2. P – values in [ ] parentheses. 3. ** statistical
significant at the 1% level; * statistical significant at the 5% level. 4. The estimates include time dummy
variables.
37
Table 5: Adjustments and Determinants of Debt – Chow Test
Dependent Variables
Independent variables
SDi ,t
(SDi,t-1)αF-αNF=0
F(1,12708)
17.83**
[0.0000]
(LDi,t-1)αF-αNF=0
F(1,12708)
(PROFi,t)β1F-β1NF=0
F(1,12708)
(AGEi,t)β2F-β2NF=0
F(1,12708)
(SIZEi,t)β3F-β3NF=0
F(1,12708)
(TANGi,t)β4F-β4NF=0
F(1,12708)
(GROWi,t)β5F-β5NF=0
F(1,12708)
(INTi,t)β6F-β6NF=0
F(1,12708)
(ETRi,t)β6F-β6NF=0
F(1,12708)
(NDTSi,t)β7F-β7NF=0
F(1,12708)
(EVOLi,t)β8F-β8NF=0
F(1,12708)
Global Difference
F(9,12708)
LDi ,t
19.78**
[0.0000]
12.72**
[0.0000]
13.81**
[0.0000]
15.65**
[0.0000]
11.48**
[0.0000]
36.08**
[0.0000]
19.38**
[0.0000]
10.08**
[0.0000]
15.12**
[0.0000]
10.47**
[0.0000]
41.77**
[0.0000]
17.99**
[0.0000]
0.79
[0.6291]
22.73**
[0.0000]
12.61**
[0.0000]
22.20**
[0.0000]
26.96**
[0.0000]
8.73**
[0.0000]
6.45*
[0.0207]
5.98*
[0.0284]
37.02**
[0.0000]
Notes: 1. P - values in parenthesis [ ] 2. ** statistical significant at the 1% level; * statistical significant at
the 5% level.
38