https://doi.org/10.1016/j.cya.2016.06.010
Paper Research
Determinants of debt: Empirical evidence on firms in
the district of Santarém in Portugal
Determinantes del
endeudamiento: Evidencia empírica sobre las empresas del distrito de Santarém
en Portugal
António José dos Santos Morão Lourenço1
Eduardo Carmo Oliveira1
1Instituto
Politécnico de Santarém, Portugal
Corresponding author: António José dos Santos Morão Lourenço, email:
antonio.lourenco@esg.ipsantarem.pt
Abstract
In
recent decades, the theme of the capital structure and its determinants has
caused some controversy and aroused great interest in the financial domain.
Several theories and studies have emerged applying to this domain. This study
aims to test the explanatory power of the determinants of debt which have the
greatest support in the financial literature, size, growth, business risk,
profitability, tangibility and non-debt tax shields and its validity in
accordance with the theories of capital structure, on firms in Santarém's district. The sample contains financial data of
6184 firms for the period 2008–2012. The results indicate that firms in Santarém's district in Portugal have a high level of debt,
using mainly short-term debt. The growth and profitability have proved to be
determinants of debt, confirming the Pecking Order Theory.
Keywords: Capital structure, Debt, Determinants.
JEL classification: G30, G32.
Resumen
En las últimas décadas el tema de la
estructura del capital y sus determinantes han suscitado alguna controversia y
despertado un gran interés en el campo de las finanzas. Varias teorías y varios
estudios han surgido aplicados a este dominio. Este estudio tiene como objetivo
poner a prueba la capacidad explicativa de los factores determinantes del
endeudamiento que tienen el mayor apoyo en la literatura financiera: dimensión,
crecimiento, riesgo de negocio, rentabilidad, tangibilidad
y las ventajas fiscales no resultantes del endeudamiento y su validez de
acuerdo con las teorías de la estructura de capital, en las empresas del
distrito de Santarém. La muestra utilizada contiene los datos financieros de
6,184 empresas no financieras para el período de 2008 a 2012. Los resultados
obtenidos indican que las empresas del distrito de Santarém en Portugal tienen
un alto nivel de endeudamiento, recurriendo principalmente a corto plazo. El
crecimiento y la rentabilidad han demostrado ser factores determinantes del endeudamiento,
lo que confirma la teoría de la Jerarquía de las Fuentes de Financiación.
Palabras clave: Estructura de capital, Endeudamiento,
Determinantes.
Códigos JEL: G30, G32.
Received: 03/07/2015
Accepted: 24/01/2016
Introduction
Most firms come across
financial needs that can be satisfied using equity or using debt. Decisions
about which source of funding to be used or their ratio is one of the issues of
great importance and has generated great controversy in recent decades. At the
core of the problem are two streams, the traditionalist defense of an optimal
capital structure that leads to maximizing the firm's value and the theory of
irrelevance of capital structure, defended by Modigliani
and Miller (1958) , which considers that the value of the firm is not
affected by the way it is financed.
Underlying
this discussion researches were developed focusing on looking for aspects that
explaining the ways of financing of firms, leading to the emergence of new
theories and new determinants of debt factors. The definition and choice of the
determinants noteworthy because it lets you know what is the impact of certain
decision-making on the capital structure and the value of the firm. Although
there is continuity in theoretical development, the results obtained in
empirical studies on the determinants of debt factors have shown little
homogeneity, suggesting that this issue lacks theoretical and empirical
research.
Contextual framework
The capital structure reflects
the composition of the source of funds whether using the equity whether debt
capital ( Esperança & Matias, 2010 ), i.e., firms can
finance their assets with equity, with debt or with both. Brandão (2003, p. 218) attaches great
importance to capital structure in that: “the composition of funding sources,
including equity and debt, can influence the value of the firm”. The
optimization of the relative importance of the debt in relation to equity, in
order to maximize the firm's value, is the main structural decision in
financial management of a firm ( Mota, Barroso, Nunes, &
Ferreira, 2012 ). However, Brealey, Myers, and Allen (2007) warn that sometimes the
purpose of financing decisions may not be to maximize the overall value of the
firm, but to minimize the weighted average cost of capital. If the operating
results are not constant, the capital structure that maximizes the value of the
firm cannot reduce the weighted average cost of capital.
Managers,
when making funding decisions, should worry to gather funding sources that
achieve the optimal capital structure. As argued by Smith (cited by Teixeira, 2012 , p. 4), “the choice of the
sources and types of capital should be evaluated in relation to the level of
flexibility in terms of access, deadlines, amounts and costs for the firm, in
order to select the most advantageous solution in terms of profitability and
particular risk for the firm”. All these problems associated with the
divergence of views on the existence of an optimal capital structure led to the
emergence of various theories on the subject, as well as several empirical
studies.
The
traditional approach represented in part by Durand
(1952) , defends the existence of an optimal capital structure for each firm,
based on the debt level changes the value of the firm and establishing a
relation between the degree of the firm's indebtedness and equity, i.e. the
cost of capital can be influenced by financial structure.
In the
late 1950, Modigliani and Miller contributed to a different view on the problem
of capital structure contrasting the traditional theory. The model developed by
Modigliani and Miller (1958) is based on a perfect
capital market and concludes that the cost of capital is independent of the
firm's debt level, denying the existence of an optimal capital structure and
advocating the firm's value is independent from the capital structure. Later, Modigliani and Miller (1963) corrected the model,
including the effect of tax on business income. It was recognized that the use
of debt provide a tax benefit due to the resulting savings in interest payments
and, consequently, can increase the value of the firm.
Miller (1977) had in consideration
not only the tax on business income, but the tax on personal income. While
investigating this situation found that, on the one hand, the resulting debt
interest are deductible from taxable income and, on the other hand, are
considered income by creditors, which are subject to tax on personal income and
can thus result in the annulment of the tax effect. Thus, the tax benefit from
the financial leverage may not be relevant in maximizing the firm's value. The
debt is only advantageous if sufficient results to benefit from the
deductibility of interest, otherwise reduces the value of the firm.
The
level of indebtedness of the firms can also be influenced by agency costs
caused by conflicts of interest between the key actors involved in the firm. Jensen and Meckling (1976) identified two types of
conflict, between capital owners and managers, and between managers and
creditors. Jensen (1986) and Stulz (1990) argued that the
conflict of interest between capital owners and managers, generated by the
excess cash flow can be minimized with recourse to debt. The excessive use of
debt can cause financial difficulties, increasing the risk of insolvency and in
costly conflicts among agents interested in the firm ( Pinho & Tavares, 2012).
The
insolvency situation can arise with increasing financial difficulties
preventing the firm to meet its financial commitments to creditors. The
probability of a firm's insolvency is greater the higher the degree of
indebtedness ( Scott, 1976). Warner (1977) identified the insolvency costs as
direct and indirect. This evidence suggests an inverse relation between the
market value of firms and the value of the direct costs of insolvency, i.e., smaller
firms have higher direct costs of insolvency. For Altman (1984) indirect insolvency costs can have
a significant impact on the capital structure.
Another
widely debated area is the asymmetric information. Arose due the fact that
managers may have information about firm's policies, including investment
opportunities that other agents interested in the firm do not possess.
According to Ross (1977) , managers, in defining
the capital structure of your firm, are transmitting a signal to investors
about the financial standing of the firm.
Based
on the study of Myers and Majluf in 1984 on information asymmetry, Myers (1984) proposed the pecking order theory.
According Brealey et al. (2007) , this theory explains
why the most profitable firms use less recourse to debt, it should be such that
not to obtain lower debt ratios, but to have sufficient internal funds
available to finance their projects. Firms with high levels of profitability
and limited investment opportunities, tend to have low debt ratios, using more
debt when investment opportunities outweigh the funds generated internally ( Myers, 1984).
Determinants of debt
Among the many financial decisions that
managers faced are those related with capital structure. These decisions may be
conditioned by various determinants that have been the subject of several
studies over the past decades supported by various financial theories. Also
several empirical studies have provided further support to the results obtained
by theoretical models, as well as the emergence of new determinants of debt.
Under the insolvency costs, was defended
by Scott (1976) that the level of debt is related to the
size of the firm. The larger firms that have assets and higher results are
subject to minor financial difficulties and, therefore, lower costs of insolvency,
better access to debt and the more favorable conditions in the long-term. Warner
(1977)
revealed that smaller firms support higher insolvency costs. Several empirical
studies have found a positive relation between size and debt ( Cardoso,
2011; Ferri & Jones, 1979; Oliveira, 2012; Rajan & Zingales, 1995;
Vieira & Novo, 2010 ), however Titman
and Wessels (1988) found a negative relation.
Growth is considered a determinant of
capital structure, according to the theory of agency costs and the pecking
order theory. Jensen (1986) and Stulz (1990) argued that recourse to indebtedness of
firms, with low growth and high cash flows, can serve as a mediator of the
conflict between capital owners and managers. Firms prefer internal financing,
however this may not be enough to finance the respective growth, particularly
in firms with high growth rates. Myers
(1984)
argued that the funds generated internally by the firms are not sufficient to
finance the respective growth. The positive results obtained by Toy,
Stonehill, Remmers, Wright,
and Beekhuisen (1974) , Jorge
and Armada (2001) and Brito,
Corrar, and Batistella
(2007) indicate
that the higher the growth greater recourse to indebtedness.
In the field of theory of asymmetric
information, Leland and Pyle (1977) argued that firms with more volatile
earnings could present smaller debt ratios, once the risk of failing to fulfill
their obligations may be higher, resulting in elevated asymmetries of
information. The increased business risk may also result in increased
insolvency costs and agency cost, leading the firms to resort less debt. Toy
et al. (1974), Brito
et al. (2007), Couto and Ferreira (2010) and Oliveira
(2012),
unlike Bradley, Jarrel, and Kim
(1984) showed
a positive relation between business risk and debt.
Another factor that can influence the firm
capital structure is the profitability. Relating to the theory of tax effect, DeAngelo and Masulis
(1980)
argued that the most profitable firms, because of their ability to benefit from
higher tax deductions related to debt, debt should be more. Ross
(1977)
admitted that greater use of debt can transmit a positive signal about the
profitability of the firm. Myers
(1984) and Myers
and Majluf (1984) reported that, firms prefer
self-financing and, only after, issuance of debt, i.e. the greater the higher
profitability will be internally generated funds and lower the use of debt, as
described in the pecking order theory. This negative relation was found in
empirical studies as Toy et al. (1974), Rajan and Zingales (1995), Vieira
and Novo (2010), Cardoso
(2011) and Oliveira
(2012).
The tangibility or, as considered by some
authors, the composition of the assets, according to the theory of tax effect,
limits the ability to use the tax benefit resulting debt. The higher the value
of the tangible assets the higher the value of depreciation and its benefit in
fiscal terms and, consequently, lower the use of tax deductibility of interest
on the indebtedness. In the theoretical line of agency costs, Scott
(1976) and DeAngelo and Masulis
(1980)
argued that firms may resort to higher debt levels the greater the guarantees
on assets, primarily long-term in proportion to their tangible assets. Studies
of Rajan and Zingales (1995), Couto and Ferreira (2010), Vieira
and Novo (2010) and Oliveira
(2012)
presented empirical evidence of a positive relation between tangibility and
debt.
The non-debt tax shields, including
depreciation of assets and investment tax credits are considered by DeAngelo and Masulis
(1980) as
substitutes for tax benefits relating to debt. The increase in these benefits
can have a negative impact on debt ( Couto & Ferreira, 2010; Oliveira, 2012 ) and, consequently, a decrease in
interest and its tax benefit as proposed by the theory of tax effect.
Sample
Small and medium enterprises play a highly
important role in the Portuguese economy. Most studies on the capital structure
have been dedicated to large firms and greater focus on publicly traded firms.
However, the Portuguese business community and in particular the business
community of the Santarém's district, consists mainly
of small and medium enterprises.
The Santarém's
district reveals great importance to economic and enterprise level within the
Portuguese national economy. This district is characterized by a vast forest surface
and high agricultural productivity due to its floodplains and is even
considered as the agricultural capital of Portugal. Its strategic location
provides the development of agro-food industry, to highlight the Sugalidal group which in 2012 was considered the second
largest producer of tomato concentrate worldwide ranking of “TomatoLand”, wood and furniture industry and tanning
industry.
The report published by the Sociedade Portuguesa de Inovação (2010) attaches particular importance to the
agricultural sector, the agroindustry sector, the automobile sector, the
tanneries and textiles sector, noted that 80% of national tanneries firms are
in the district of Santarém, the sector of forestry,
which holds 27% of cork production and 10% of the production of wood and resin,
the wood industry, furniture and paper, the construction sector, the sector of
mineral non-metals, the services sector with greater relevance to the trade
activities related to tourism, transport and distribution and the environmental
sector/waste treatment.
The sample selected for this empirical
study was constituted by non-financial firms in the Santarém's
district. Secondary data was obtained from the database of Iberian Balance
Sheet Analysis System (SABI). The sample contains data for a time horizon of
five years (2008–2012) include 6184 non-financial firms, distributed on average
as shown in Table 1 , the following categories, according to
the Commission Recommendation 2003/361/EC: 14 large firms, 139 medium firms,
1034 small firms and 4997 micro firms.
Sector
of economic activity
|
Firms |
%
|
Wholesale and retail trade; repair of motor vehicles
and motorcycles |
2033
|
32.90
|
Manufacturing |
820
|
13.30
|
Construction |
665
|
10.80
|
Agriculture, livestock, hunting, forestry and
fishing |
452
|
7.30
|
Transport and storage |
429
|
6.90
|
Consulting activities, scientific, technical and
similar |
415
|
6.70
|
Accommodation, catering and similar |
411
|
6.60
|
Human health activities and social support |
282
|
4.60
|
Administrative activities and support services
|
138
|
2.20
|
Real
estate activities |
132
|
2.10
|
Other service activities
|
100
|
1.60
|
Education |
61
|
1.00
|
Activities of information and communication |
60
|
1.00
|
Artistic activities, shows, sports and
recreation |
59
|
1.00
|
Financial and insurance activities |
57
|
0.90
|
Extractive Industries |
43
|
0.70
|
Collection, purification and distribution of water;
sewerage, waste management and remediation activities |
21
|
0.30
|
Electricity, gas, steam, hot and cold water and cold
air |
6
|
0.10
|
Total
|
6184
|
100.00
|
Source: Own elaboration.
The sample distribution by economic activity sectors, represented
in Table 2 ,
indicates that about 33% of the firms belong to the trade sector wholesale and
retail trade, repair of motor vehicles and motorcycles. The manufacturing
industries, construction and agriculture, animal husbandry, forestry and
fisheries represent about 31%, the remaining sectors are less significant.
Methodology
The research strategy
adopted is based on a longitudinal study, using secondary data and the type of
correlational research/explanatory. The model follows a panel data approach,
containing financial information for examining the relation between dependent
variables and independent variables. It consists of a set of three multiple
linear regressions analyzed separately, as they are used three debt indicators.
This model follows a similar approach to other authors.
Statistical
analysis is performed using the method of generalized least squares, panel data
treatment and to refuse the package SATA v.12.
The
autoregressive model considered is the following:
(1)
where
Y i , t = firm debt as i in year t;
β 0 = constant;
β k = parameter
estimated by the model;
X = vector of the
explanatory variables;
Independent variable |
Indicator |
Size |
X1
– Number of Workers
|
X2 – Ln (Total net Assets) |
|
X3
– Ln (Turnover) |
|
Growth |
X4 – Growth rate of Total net Assets |
Business
Risk |
X5 – Coefficient of variation of EBIT |
X6 – Standard deviation of Turnover |
|
X7 – Standard deviation of EBIT |
|
Profitability |
X8 – EBIT/Total net Assets |
Tangibility |
X9 – Tangiblel
Assets/Total net Assets |
X10 – Intangiblel
Assets/Total net Assets |
|
Non-debt Tax Shileds
|
X11 – Depreciation and Amortization of
Exercise/EBITDA |
Source: Own elaboration.
¿ i , t = random error.
The vector
of explanatory variables includes K
factors, (K = 1, …, 6), which follow:
- (1) size;
- (2) growth;
- (3) business risk;
- (4) profitability;
- (5) tangibility;
- (6) non-debt tax shields.
The dependent variables
related to the capital structure of the firms are financial indicators of
indebtedness calculated from accounting data. Use three indicators ( Table 3 ) representative
of short-term debt, medium and long term debt and total debt. These indicators
were also used separately by some authors as: Jorge and Armada (2001), Brito et al. (2007) and Couto and Ferreira (2010).
The independent
variables may be determinants of debt, reflected in the respective capital
structure of firms. The choice of indicators to measure the independent
variables was based on the chosen in Portuguese studies previously conducted
and then in foreign works. As indicators of independent variables considered
were those shown in Table 4
and described below.
Three indicators were
used to analyze the variable size. The number of workers referenced in the work
of Titman and Wessels (1988), Jorge and Armada (2001) and Couto and Ferreira (2010) , the logarithm of
total net assets and logarithm of turnover, as shown in the studies of Titman and Wessels
(1988), Rajan and Zingales (1995), Brito et al. (2007), Vieira and Novo (2010), Cardoso (2011), Junior (2012) and Oliveira (2012).
The
variable growth was measured using the growth rate of total net assets, as Titman and Wessels
(1988), Jorge and
Armada (2001), Couto
and Ferreira (2010), Vieira
and Novo (2010) and Junior
(2012) annually calculated as follows1:
(2)
Like
authors such as Ferri and Jones (1979), Jorge and Armada (2001), Couto and Ferreira (2010) and Junior (2012) , to analyze the variable business
risk, indicators were used: coefficient of variation of EBIT,2 standard deviation of
turnover and standard deviation of EBIT, calculated as follows:
(3)
where
t = year;
n = number of
observations (5 years);
rt=EBIT in year tTNA in year t
;
(4)
wherex t and x t−1 – turover
in years (t) and (t − 1) respectively;y t and y t−1 – EBIT in years (t) and (t − 1) respectively;
x¯ –
average of turnover;
y¯ –
average of EBIT;
σ – standard deviation.
Profitability,
to analyze this variable, although some authors have used as an indicator
operating income or profit, Portuguese studies as Jorge and Armada (2001), Cardoso (2011) and Junior (2012) present the following indicators:
(6)
For the
tangibility variable, studies such as Titman
and Wessels (1988), Jorge
and Armada (2001), Couto and Ferreira (2010) and Cardoso (2011) have chosen to use two indicators
to measure the extent to which the tangible and intangible assets can serve as
a guarantee to creditors, so the indicators are:
(7)
The
choice of indicator that serves to measure the variable non-debt tax shields
followed an approach similar to Jorge
and Armada (2001), Couto and Ferreira (2010) and Junior (2012), with the indicator:
(8)
Research hypotheses
Based on the theories and empirical
studies on capital structure, previously reported, and in order to verify the
relation between the determinants of debt and the level of indebtedness of the
firms the following hypotheses were formulated:
- H1: There
is a positive relation between firm size and total debt.
- H2: There
is a positive relation between firm size and the long-term debt.
- H3: There
is a negative relation between firm size and the short-term debt.
- H4: There
is a positive relation between growth and debt.
- H5: There
is a negative relation between business risk and debt.
- H6: There
is a negative relation between profitability and debt.
- H7: There
is a positive relation between tangibility and total debt.
- H8: There
is a positive relation between tangibility and long-term debt.
- H9: There
is a negative relation between tangibility and short-term debt.H10: There
is a negative relation between the non-debt tax shields and the debt.
Table
5 ,
shown below, summarizes the expected relations, according to the hypotheses,
among the selected debt ratios and the potential determinants of debt.
Teste
statistics
As stated Couto and Ferreira (2010) , the generalized least
squares method, it is assumed that the errors are randomly distributed with a
Gaussian density function, and homoscedastic non-autocorrelated,
which allows to obtain not skewed and consistent estimators.
Statistical
analysis can be performed by ordinary least squares model (OLS), the fixed
effects model (FE) or random-effects model (RE). In the fixed effects model to
estimate it is made assuming that the heterogeneity of individuals is captured
in the constant part, maintaining the assumption of homogeneity of
observations. The random effects model considers the constant term not as a
fixed parameter, but as an unobservable random parameter ( Couto & Ferreira, 2010).
The
choose of the right model was made using the F
-Statistic and Hausman statistics. The F -statistic is a test of global adherence
and indicates the reliability of model used. The Hausman
statistic is a test that allows you to decide which model is more appropriate.
Both tests show statistically significant results in all regressions ( Table 6 ), so the most appropriate model
is the fixed effects model.
The presence of multicollinearity
was evaluated by means of the correlation matrix of independent variables ( Table 7 ). The correlation matrix shows
that in general the independent variables are not highly correlated, except
for: X3 Ln (turnover) with X2 Ln (total net assets).
Results
Based on descriptive
statistics (Table 8 ), it turns out that
the average debt stands at 74%. The firms of Santarém's
district, in general, have more debt in the short-term (52%) than the medium
and long term, confirming the evidenced in the work of Jorge and Armada (2001), Brito et al. (2007)
and Vieira and Novo (2010).
The short-term debt is
essentially banking, which may be a reflection of low guarantees offered and
lack of access to capital markets ( Vieira
& Novo, 2010). It is referred by Jorge
and Armada (2001) , that the fact that short-term debt average is more
than twice the average indebtedness of medium and long term can be associated
with a greater confidence on the part of firms in the banking system, to the
detriment of the capital market.
The
results obtained from the regression models for each dependent variable, total
debt (Y1) ( Table 9 ), medium and long term
debt (Y2) ( Table 10 ) and short-term debt
(Y3) ( Table 11 ) allow to observe the
level of determining factors of the debt resulting from regressions performed.
The Y1 regression (Total
Debt/TNA), for the total debt, explains about 33% of the model. It is noted
that the size, growth and profitability influence the level of total debt,
although the size when measured by the indicator number of workers is less
significant. Business risk is also statistically significant when measured
through the standard deviation of turnover. The variable size has a positive
relation with debt, except when measured by the Ln (total net assets). Business
risk and profitability shows a negative relation with debt, is not the case
with growth, which shows a positive relation. Business risk measured by the
coefficient of variation of EBIT and standard deviation of EBIT, as well as
tangibility and non-debt tax shields not shows determinants of total debt.
The Y2
regression (Long term Debt/TNA), referring to the debt in the medium and long
term, has different results of the previous regression and a substantially
lower explanatory power about 3%. The size, growth, profitability and
tangibility when measured by tangible assets, show statistically significant
results concluding be determinants of medium and long-term debt. Like the
previous regression, the number of workers is an indicator with little meaning
in the relation with the variable size with the indebtedness. Please note that
tangibility, profitability and size, except when measured by the number of
workers, have a negative relation with debt and the only one to show a positive
relation is growth. Variables business risk, leverage measured by the indicator
Intangible Assets/TNA and non-debt tax shields, do not show statistically
significant results.
The
explanatory power of regression Y3 (Short-term Debt/TNA), related to short-term
debt, is about 28%. Based on statistical evidence, show up as determinants of
debt the variables size, except when measured by the number of workers, growth,
business risk as measured by the indicator of turnover standard deviation,
profitability and tangibility when measured by tangible assets/TNA. The size,
similar to the total debt, presents a negative sign when using the Ln (total
net assets) and a positive signal when using the Ln (turnover). Growth and
tangibility have a positive relation with debt, unlike business risk where the
signal is negative. Without any statistical evidence on the relation with debt
they are the size, measured by the number of workers, business risk measured by
the coefficient of variation of EBIT and standard deviation of EBIT,
tangibility when using the indicator Intangible Assets/TNA and non-debt tax
shields.
Discussion of results
Bearing in mind the theories of capital
structure, empirical studies previously presented and hypotheses formulated we
can make some considerations about the results. The determinants of capital
structure of firms in the Santarém's district with
the greatest influence on indebtedness are: size, growth and profitability. The
influence of tangibility and business risk depends on the measure used. The
non-debt tax shields just are not able to influence the level of indebtedness
of firms. The observed and expected relations are summarized in Table
12.
The indicators used to measure the variable
size, are able to influence the level of indebtedness in all periods except the
number of workers, most likely due to the reduced number of workers at most
firms. The signs observed in all other indicators are not consistent with the
hypotheses formulated by varying the signal sometimes by the indicator, other
by the deadline, not being able to confirm the suggested by Scott
(1976) , in
which, in the context of the insolvency costs, the larger firms support smaller
costs of insolvency and therefore tend to be more in debt. Negative signals
obtained may indicate, since over 80% of the sample is micro-enterprises and
smaller firms support higher insolvency costs, as Warner
(1977)
states, creating therefore greater difficulty in accessing credit. Titman
and Wessels (1988) suggest that smaller firms are more prone
to short-term debt.
The growth variable, measured by the
growth rate indicator of total net assets, is significant across all
maturities, confirming the hypothesis formulated and in accordance with the
pecking order theory. The positive sign suggests that internally generated
funds are not sufficient to finance the respective growth, as advocated by Myers
(1984). The
results will meet de Brito et al. (2007) and Jorge
and Armada (2001) , suggesting that the higher the growth,
the greater is recourse to debt.
Under the theory of insolvency costs,
suggested by Warner (1977) , or the theory of asymmetric
information, referenced by Leland
and Pyle (1977) , it
was expected that if it obtained a negative signal at all maturities regardless
of the indicator used to measure the variable business risk. However, is only
determining factor of the debt in the short term and total when measured by
turnover standard deviation. Like Bradley
et al. (1984) ,
the results suggest that firms with more volatile turnover have lower debt
levels, reflecting greater difficulties in accessing finance.
The negative signal obtained in all
regressions for variable profitability resembles other empirical studies, such
as Titman and Wessels (1988), Rajan and Zingales (1995), Vieira
and Novo (2010) and Cardoso
(2011) ,
confirming the formulated hypothesis. The higher the profitability, lower
recourse to debt evidencing that firms prefer financing through retained
earnings, confirming the theory of the pecking order theory, as proposed by Myers
(1984) and
contrary to the theory of tax effect defended by DeAngelo and Masulis
(1980).
It turns out, in relation to the variable
tangibility; intangible assets did not serve as a guarantee to creditors.
Tangible assets have a negative relation with the medium and long term debt and
a positive relation with the short-term debt, contrary to assumptions made. Scott
(1976) and DeAngelo and Masulis
(1980) ,
based on the theory of agency costs and the theory of insolvency costs have
argued that the greater the assurance given by the assets, the higher the level
of debt. In this case, the result suggests that those serve as guarantee for
short-term debt, possibly due to the fact that the short-term debt level of the
sample firms is 52%.
It was expected a negative relation
between the non-debt tax shields and debt, to the extent that the increase of
these benefits can lead to unused tax benefits resulting from debt. However,
like Titman and Wessels (1988), Jorge
and Armada (2001) and Junior
(2012) ,
the results assume no statistical significance, not validating, therefore, the
theoretical basis of the influence of other tax benefits in deductibility of
interest as allowed by the theory of tax effect.
Conclusions
The current economic and financial
environment requires that firms are in constant transformation and upgrading,
not only in productive terms but also in economic and financial terms,
otherwise their survival proves to be very difficult. It becomes necessary for
firms to grow and modernize. For this to happen, they need to resort to
financing that can be internal or external source. The choice of the most
appropriate source to finance the assets causes great concerns, especially when
it comes to new business opportunities or to ensure the survival of the firm.
Inherent to these concerns and seeking to maximize the firm's value or
minimizing the weighted average cost of capital are several theories.
The model of Modigliani
and Miller (1958) , assuming a perfect capital market,
believes that the firm's value is not influenced by the financing structure,
contrasting the traditional approach, generating some criticism due to market imperfections.
These imperfections allied to the problem of capital structure led to the
emergence of new theories. One of the imperfections is related to the tax
effect derived from the deductibility of interest on the debt. The interaction
between the income tax and the combination of tax benefits may allow the
definition of an optimal level of debt. Another is related to agency costs,
i.e. costs related to the conflict of interest between capital owners, managers
and creditors, which can be minimized with the use of debt converging thus the
optimal capital structure. The increase of debt may cause financial
difficulties increasing the risk of insolvency. The nullity of the insolvency
costs and the present value of savings are considered the optimum capital
structure ( Esperança & Matias, 2010 ). Managers have information about firm
policies, including investment opportunities, which other stakeholders do not
have, can lead to asymmetries in information. The information transmitted must
be credible and effective in order to minimize the costs of these signals.
Following the study of informational asymmetry, Myers
(1984)
proposed the pecking order theory. Based on this theory, firms prefer internal
financing sources and only after having exhausted resort to external financing.
Following these theories also come up studies on the determinants of debt.
These determinants are explanatory of how firms are financed. In the
theoretical and empirical literature the most common
determinants were identified: size, growth, business risk, profitability,
tangibility and non-debt tax shields.
From analysis to descriptive statistics it
was concluded that 99.77% of the firms are small and medium enterprises, with
about 80% micro enterprises. The average of total debt stands at 74%, the
medium and long term at 22% and the short-term at 52%, indicating that most
firms resort to short-term bank credit.
In summary, the results from the three
multiple linear regressions, using the fixed effects model, allow the following
conclusions:
- Variables
growth and profitability are the ones that have strong statistical
evidence of being related to debt, confirming the assumptions made and the
theoretical concepts;
- The
increase in the number of workers causes an increase in total debt and
medium and long term;
- Contrary
to expectations, the negative sign obtained for the size measured by Ln
(total net assets) may indicate that the smaller the firm, the lower the
is use of debt;
- When
the turnover increases, the total debt increases. Contrary to expected,
increased turnover causes a decrease in medium and long term debt and an
increase in short-term debt;
- It
turns out that the growth rate of assets positively influences the relation
with the debt;
- Business
risk has a negative influence for total debt and short-term debt, measured
by the standard deviation of turnover. For the remaining deadlines and
indicators provides no evidence capable of influencing the level of
indebtedness;
- Increased
profitability causes a decrease in the use of debt, supporting the
proposed hypothesis and the pecking order theory;
- Contrary
to expectation, the tangible assets is an inverse relation, i.e., the
greater the increase in tangible assets, the lower the debt in the medium
and long term. In the short term there is a reverse situation;
- There
was no statistical evidence as to the non-debt tax shields.
Given the results achieved, not all
variables corroborate the theoretical studies and the hypotheses formulated.
However, they are in consonance with other empirical studies, in other words,
the problem of capital structure and of their determinant is far away from
being solved.
The few existing empirical studies on
small and medium enterprises, mainly Portuguese, is one of the limitations of
this study. Most studies are about large firms or about firms listed on the
stock market, making it difficult to compare results with the Portuguese
reality and especially with the Santarém's district,
composed mainly by micro enterprises. Another limitation relates to the use of
secondary data. The information obtained cannot be properly validated or may
not be a more harmonized at the level of several firms.
For future research, it would be more
relevant to make other studies to analyze the influence of other explanatory
variables in the capital structure, some were used in other studies, such as
the uniqueness, the business sector, regulation, quality firm reputation, the
level of exports, the location, in order to create a more expressive model in
terms of explanatory and most consistent determinants of debt.
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México.
Notes.
1Total net Assets.
2 Earnings Before Interest
and Taxes.
Copyright © 2017 Universidad
Nacional Autónoma de México, Facultad de Contaduría y Administración.
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