Are the determinants of young SME profitability different? Empirical evidence using dynamic estimators.
Nunes, Paulo Macas ; Viveiros, Ana ; Serrasqueiro, Zelia 等
1. Introduction
Various fields of knowledge have concentrated on the study of
possible determinants of firm performance. In fact, Industrial
Economics, Strategic Management and Accountability and Corporate Finance
are research areas that have focused upon the determinants of firm
performance.
For example, in the area of Industrial Economics, Bain (1956),
Porter (1980), and Slater and Olsen (2002), based on the paradigm of
Structure--Conduct--Results (S-C-R), have analyzed the variations of
firm performance. The main goal of those authors has been to verify if
economies of scale and barriers to firms' entry and exit are
important for the persistence of firm performance. In addition to the
study of the persistence of the firm performance, those authors have
concentrated their research on the influence of size on firm
performance.
In the field of Strategic Management, the main focus of the
research has been the analysis of the influence of the organizational
structure and management of internal resources on firm performance.
Teece (1981), Peteraf (1993), Levinthal (1995), Barney (2001), Moreno et
al. (2010), Travkina and Tvaronaviciene (2011), and Moreno and Castillo
(2011) have analyzed the influence of several determinants factors as
organizational structure, risk, asset structure and size on firm
performance.
Finally, in the research field of Accountability and Corporate
Finance, several studies (Jensen, Meckling 1976; Myers 1977; Stulz 1990;
Callen et al. 1993; Chan et al. 2003) have studied the influence of
capital structure on firm performance. In the context of the research
field of Accountability and Corporate Finance, the study of the
influence of debt and liquidity on firm performance is particularly
important.
One of the most frequently used measures of firm performance is
profitability. In this study, just as Adams and Buckle (2003), Amato, L.
and Amato, C. (2004), Goddard et al. (2005), Gschwandtner (2005),
Galbreath and Galvin (2008), and Macas Nunes et al. (2010), we use firm
profitability, given by the ratio of operational results to assets, as a
measure performance. As explanatory variables of profitability, just as
Macas Nunes et al. (2010), we consider: 1) Age; 2) Expenditure on
Research and Development (R & D); 3) Size; 4) Liquidity; 5)
Long-term Debt; and 6) Risk.
The various studies about determinants of profitability (Adams,
Buckle 2003; Amato, L., Amato, C. 2004; Goddard et al. 2005;
Gschwandtner 2005; Galbreath, Galvin 2008; Serrasqueiro, Macas Nunes
2008; Macas Nunes et al. 2009; Macas Nunes et al. 2010) have neglected
the study of the influence of firm age on the relationships between
determinants and profitability.
This study seeks to verify if SME age is a determinant factor of
the relationships between determinants and profitability. Considering
that SMEs are much more vulnerable and sensitive to macroeconomic
changes, economic downturns, and also to the competition within the
market, it is important to study: 1) the determinants that may stimulate
SME profitability and those that may restrict profitability; and 2)
given the importance of young SMEs in stimulating the employment and
economic growth, it is worth to verify if age of SMEs is an important
factor that may contribute to important differences between the factors
promoting and the factors restraining the firm profitability.
In Portugal, SMEs represent around 99.6% of businesses (IAPMEI
2008) and are crucial for stimulating the country's employment and
economic growth. The importance of SMEs in the context of industrial
activity in Portugal justifies the study of the influence of age on the
determinants of profitability of Portuguese SMEs. Additionally, this
study seeks to understand if governmental policies that promote the
sustainability of SME profitability should be of a different nature,
according to the subject of analysis being young or old SMEs.
Methodologically, we consider a panel made up of 1845 Portuguese
SMEs for the period 1999-2006. We consider as young SMEs those firms
those of up to 10 years of age in 2006, considering the remainder of
SMEs included in the database as old SMEs.
We use the two-step estimation method proposed by Heckman (1979),
so as to address the problem of possible bias of estimated results, as a
consequence of the matter of survival. In a first step, we estimate
probit regressions for young and old SMEs with all surviving and
non-surviving SMEs. In a second step, based on the previously estimated
probit regressions, we calculate the inverse Mill's ratio and add
it as an explanatory variable of profitability in young and old SMEs. In
this second step, we use dynamic panel estimators, namely GMM (1991),
GMM system (1998) and LSDVC (2005) estimators. It should be noted that
in the second step of estimation, just as Heckman (1979), we only
consider the surviving SMEs. Use of dynamic panel estimators, just as in
Gschwandtner (2005) and Macas Nunes et al. (2009), allows us to
determine the persistence of profitability in young and old SMEs, i.e.
we analyze the relationship between profitability in the current period
and in the previous period for young and old SME, also checking whether
age is a fundamental characteristic of the magnitude of profitability
persistence.
The empirical evidence obtained allows us make the following
contribution to the literature: age is a determinant factor of the
relationships between determinants and profitability. More specifically,
we ascertain that: 1) age, liquidity, and long-term debt influence
positively the young SMEs profitability; but age influences negatively
the old SME profitability, and liquidity and long-term debt do not
influence the old SMEs profitability; 2) size influences positively the
young and old SME profitability, but the positive influence is greater
for young SMEs than for old SMEs; 3) risk influences negatively the
young SME profitability, but it does not influence the old SMEs
profitability; 4) R & D expenditure influence positively the old SME
profitability, but do not influence the young SME profitability; and 5)
persistence of profitability is greater for old SMEs than for young
SMEs. In addition, use of the two-step estimation method allows an
additional contribution of the current study: significant differences
are found between the determinants of young and old SME survival.
After this introduction, the study is structured as follows: 1)
Section 2 presents the literature review and research hypotheses; 2)
Section 3 presents the database, variables and the estimation method
used; 3) Section 4 presents the results obtained; 4) Section 5 goes on
to discuss the results; and 5) finally, Section 6 presents the
conclusions and implications of the study.
2. Literature review and investigation hypotheses
2.1. Age
There is no consensus on the influence of age on firm performance.
On the one hand, Jovanovic (1982) concludes that the firm's owners
and/or managers need to take time to understand their real business
possibilities. According to Jovanovic (1982), only as the years pass,
firm owners and/or managers become more efficient in the selection of
the investment opportunities. Based on this argument, Jovanovic (1982)
concludes that the firms in the more advanced stages of their life-cycle
are more able to obtain higher rates of financial performance.
Younger firms are normally more proactive and have a greater
perception of the risk of the various investment alternatives that arise
(Lumpkin, Dess 1996; Lumpkin 1998; Shane, Venkataraman 2000).
Additionally, younger firms are more efficient in selecting the most
profitable investments, compared to what occurs in firms in more
advanced stages of their life-cycle, given that young firms are
particularly concentrated on their survival (Lumpkin, Dess 1996; Lumpkin
1998; Shane, Venkataraman 2000). Lumpkin and Dess (1996), Lumpkin
(1998), and Shane and Venkataraman (2000) conclude that it is expectable
that young SMEs have higher levels of profitability than do old SMEs.
SMEs are associated with considerable business risk compared to the
case of large firms. In the first years of SME life cycle, high business
risk associated with possible difficulty in obtaining credit can lead
SMEs being unable to take advantage of the investment opportunities that
arise. In addition, Jovanovic (1982) concludes that firms in the first
years of their life-cycle have the main concern of reaching the minimum
scale of efficiency that allows them to survive. Given that SMEs are
particularly exposed to risk and to the effects of competition, the
smaller size of SMEs, compared to large firms, implies greater relative
importance of the need to obtain the minimum scale of efficiency that
allows survival.
Based on the arguments above, we formulate the following
hypothesis:
H1: Age is of greater relative importance for increased
profitability in young SMEs than for increased profitability in old
SMEs.
2.2. Other determinants
2.2.1. Research and development
Andries and Debackere (2007) conclude that expenditure on Research
and Development is fundamental for an increased propensity of firms for
innovation. According to Andries and Debackere (2007), SMEs with more
intensive expenditure on Research and Development have a greater
innovative capacity, and, consequently more strategic flexibility to
diversify their investments, which may contribute decisively to
increasing their levels of profitability.
The benefits of SME investment in Research and Development are also
stated by other authors. Rogers (2004) concludes that SMEs with higher
investment in Research and Development have greater organizational
flexibility which may contribute to a greater efficiency in implementing
the growth opportunities. Taking greater advantage of growth
opportunities can mean increased SME profitability. Beise-Zee and Rammer
(2006) claim that diversification of activities, as a consequence of
SMEs' greater investment in Research and Development, can mean
greater export capacity. Less risk in SME activity, as a consequence of
greater export capacity, may contribute to increased profitability.
Finally, according to Rickne (2006), SMEs that invest more in Research
and Development have a greater propensity to be involved in cooperation
networks with other SMEs. Cooperation networks can contribute to a
greater diversification of SME activities, which can contribute to
increasing levels of profitability (Rickne 2006).
However, investment in Research and Development may contribute to
diminished SME profitability, since: 1) investment in Research and
Development contains quite a high risk, which together with the high
risk associated with SME activities in general, can lead to difficulties
in managing financial resources, when internal financing is insufficient
(Yasuda 2005; Muller, Zimmermann 2009); 2) if SMEs do not have an
extended learning period in managing Research and Development
investment, this can imply inefficient use of investment opportunities
(Muller, Zimmermann 2009); and 3) to finance Research and Development
activities, SMEs frequently need to turn to external financing, given
that internal financing may be clearly insufficient for this purpose.
The strong difficulties of SMEs to obtain external financing can mean
problems in managing their financial resources, and taking advantage of
growth opportunities (Tanabe, Watanabe 2005; Gomez, Vargas 2009; Muller,
Zimmermann 2009).
The youngest SMEs have the main goal of attaining a minimum scale
of efficiency that allows them to survive (Jovanovic 1982). Therefore,
SME diversification of activities, as a consequence of greater
investment in Research and Development, can be fundamental to reach that
goal. However, diversification of activities can also be fundamental for
the growth and sustainability of old SMEs, since they can stagnate if
beyond a certain moment of their life-cycle they do not invest in
Research and Development, and consequently they may exhaust their
profitable investment opportunities.
The contribution of age to increased SME reputation (Diamond 1989),
and diminished probability of bankruptcy (Muller, Zimmermann 2009), may
allow old SMEs an easier access to alternative financing sources. When
internal financing is insufficient, the access to alternative financing
sources can be fundamental for SMEs to finance their Research and
Development activities with less difficulty in managing their financial
resources, so contributing to increased profitability. Additionally as a
consequence of greater age, the effect of acquired experience in
managing the innovation processes (Muller, Zimmermann 2009) may
contribute to Research and Development investment of old SMEs causing
greater increase in profitability, compared to the case in young SMEs.
Based on the arguments above, we formulate the following
hypothesis:
H2: Research and Development Expenditure is of greater relative
importance for increased profitability in old SMEs than for increased
profitability in young SMEs.
2.2.2. Size
Various authors (Winter 1994; Hardwick 1997; Wyn 1998; Gschwandtner
2005) state that firm size is fundamental for increased levels of
profitability. According to the authors, greater firm size contributes
to firms to have: 1) greater ability to take advantage of economies of
scale; 2) greater capacity to diversify activities and products; and 3)
greater ability to implement strategies seeking to increase the barriers
to the entry of potential competitors.
However, other authors (Pi, Timme 1993; Goddard et al. 2005) state
that greater firm size can contribute to reduced ability of owners to
control managers' actions. Less control of managers' actions
by owners can imply investment in projects that increase managers'
own prestige, such as projects that make firms grow beyond the desirable
size, and which can contribute to diminished firm's profitability.
In the majority of SMEs, the ownership and management are in the
hands of the same individuals, therefore the negative impacts of
increased size on profitability can be minimal, and so we can expect
that greater SME size contributes to increasing firms'
profitability levels.
However, we can expect that the size of young SMEs to be more
relevant for increasing young SME profitability, compared to the case of
old SMEs. Since young SMEs in general can be far from the minimum size
that allows survival (Jovanovic 1982; Lotti et al. 2009), then the
greater size can have greater relative importance for young SMEs to
have: 1) greater ability to take advantage of economies of scale; 2)
greater capacity to diversify activities and products; and 3) greater
capacity to raise barriers to the entry of potential competitors,
compared to the case of old SMEs.
Based on the above arguments, we formulate the following
hypothesis:
H3: Size is of greater relative importance for increased
profitability in young SMEs than for increased profitability in old
SMEs.
2.2.3. Liquidity
Fama and Jensen (1983) and Myers and Rajan (1995) conclude that
when firms have excessive liquidity, managers can invest in projects
that maximize their own personal benefits, but reducing firm's
profitability. However, Ang (1991) concludes that the negative effects
of excessive liquidity on SME profitability are minimal as a consequence
of SME ownership and management, in most cases, being concentrated in
the same individuals.
Higher liquidity levels mean a greater possibility for firms to be
more effective in facing up the potential changes of their operating
markets as a consequence of increased competition (Goddard et al. 2005).
This occurs because firms with higher levels of liquidity are more able
to respond to increased competition, as a consequence of the lesser
stress in managing their financial resources.
Higher levels of liquidity can be particularly relevant for SME to
make efficient use of the various investment opportunities that arise,
contributing to increased profitability (Honjo, Harada 2006). Deloof
(2003) concludes that the importance of SME liquidity for increased SME
profitability can arise from the great possibility of firm's
accomplishment of short-term commitments, as well as from the greater
efficiency in managing financial resources to take advantage of good
investment opportunities. Fagiolo and Luzzi (2006) reinforce the
conclusions of Deloof (2003), claiming that the information asymmetry
inherent in the relationship between SME owners and creditors can cause
an excessive dependence of SMEs on short-term debt, which may generate
financial stress, due to the need to pay debt and its charges over a
very short period of time.
The youngest SMEs have greater difficulty in accessing external
financing than old SMEs. Indeed, the lesser reputation of young SMEs
(Diamond 1989) and the greater possibility of bankruptcy (Muller,
Zimmermann 2009) contribute to greater difficulties of young SMEs in
obtaining external financing on advantageous terms, compared to the case
of old SMEs. For example, creditors can grant more short-term debt, and
less long-term debt, so as to monitor more easily the repayment of the
debt and charges by SMEs. In this context, Serrasqueiro and Macas Nunes
(2010) conclude that when internal finance is insufficient, young SMEs
are excessively dependent on short-term debt, whereas old SMEs are more
able to obtain long-term debt. This being so, we can expect that
liquidity to be particularly important for increased profitability in
young SMEs.
Based on the arguments above, we formulate the following
hypothesis:
H4: Liquidity is of greater relative importance for increased
profitability in young SMEs than for increased profitability in old
SMEs.
2.2.4. Long-term debt
Jensen and Meckling (1976) conclude that firm owners/managers may
prefer debt to the finance highly profitable projects, but which may
also contain a high level of risk. When the projects are successful, the
firm's owners/managers are the main beneficiaries. On the contrary,
in the case of failure of the projects, the creditors bear almost all
the costs. Myers (1977) concludes that creditors hinder the granting of
long-term debt to firms, when the projects to be financed imply a high
level of risk. In situations of high risk associated with investment
projects, Myers (1977) concludes that creditors prefer to grant
short-term debt so as to monitor the repayment of the debt and its
charges more easily.
Fagiolo and Luzzi (2006) conclude that when internal financing is
insufficient, debt can be fundamental SMEs, so that these firms can
finance all good investment opportunities that arise. Nevertheless, the
authors conclude that the excessive dependence on short-term debt of
SMEs, when internal financing is insufficient, can contribute to reduce
the liquidity, which will lead to excessive stress in managing financial
resources, and which in turn may imply less efficient use of the good
investment opportunities.
For Fagiolo and Luzzi (2006), when internal financing is
insufficient, if SMEs have greater access to long-term debt, this can
contribute to increased SME profitability. According to these authors,
this occurs because SMEs can manage their financial resources with less
stress, which can be fundamental for taking advantage of all good
investment opportunities that arise.
Serrasqueiro and Macas Nunes (2010) conclude that when internal
financing is insufficient, young SMEs are excessively dependent on
short-term debt, whereas old SMEs, in the same circumstances, are more
able to obtain long-term debt. The greater reputation acquired with
greater SME age (Diamond 1989), as well as the lesser possibility of
bankruptcy of older SMEs (Muller, Zimmermann 2009), may be determinant
factors for older SMEs having easier access to long-term debt.
When internal financing is insufficient, SMEs' excessive
dependence on short-term debt and consequent financial stress in
managing their financial resources can lead to a greater importance of
long-term debt to increased profitability.
Based on the arguments above, we formulate the following
hypothesis:
H5: Long-term debt is of greater relative importance for increased
profitability in young SMEs than for increased profitability in old
SMEs.
2.2.5. Risk
Various authors (Fama, Jensen 1983; Titman, Wessels 1988;
Lamm-Tennant, Starks 1993; Adams, Buckle 2003) state that firms, with
high volatile operational results, are more exposed to situations of
risk.
Pettit and Singer (1985) conclude that SMEs with high operational
risk have considerable difficulty in obtaining debt. In fact, it is
sometimes difficult for creditors to assess the exact nature of SME
assets, since the great flexibility of SMEs' organizational
structure can lead to considerable changes in the composition of their
assets. Additionally, in high-risk situations, SME owners/managers can
begin investing in projects that maximize their benefits, and cease to
invest in projects that contribute to firm increased profitability.
From the above, we can expect that greater operational risk of SMEs
implies diminished levels of profitability. However, the majority of
SMEs in the beginning of their life-cycle have not yet reached the
minimum scale of efficiency that allows them to survive in their
operating markets (Jovanovic 1982). Consequently, those SMEs are more
exposed to a higher risk, and we can expect a more accentuated reduction
in the profitability of this type of SME, compared to the case of SMEs
in the later stages of their life-cycle.
Based on the reasoning set out, we formulate the following
hypothesis:
H6: Risk is of greater relative importance for diminished
profitability in young SMEs than for diminished profitability in old
SMEs.
2.2.6. Profitability in the previous period
According to Mueller (1986), there is a propensity of firm
profitability persistence over time, i.e., a statistically significant
relationship between firm profitability in the previous period and firm
profitability in the present period. That author argues that this occurs
because the possible small divergences between profitability in the
previous and present periods are immediately cancelled out by the entry
and exit of firms in the market.
In the context of persistence of firm profitability, the
conclusions of Gschwandtner (2005) are quite relevant. The author
concludes that the greater level of risk associated with firm's
activities, and the consequently greater likelihood of bankruptcy,
contribute to diminished persistence of profitability.
Young SMEs have less persistent profitability than old SMEs,
because the former are more risky, and consequently have greater
likelihood of bankruptcy, compared to the case of old SMEs.
Based on this reasoning, we formulate the following hypothesis:
H7: Persistence of profitability is greater in old SMEs than in
young SMEs.
3. Methodology
3.1. Database
This study uses the SABI (Sistema de Balancos Ibericos--System
Analysis of Iberian Balance Sheets) database supplied by Bureau van
Dijk, for the period between 1999 and 2006. We select SMEs on the basis
of the European Union's recommendation L124/36 (2003/361/CE).
According to this recommendation, a firm is considered to be an SME,
when it meets two of the following criteria: 1) fewer than 250
employees; 2) total assets under 43 million euros; 3) business turnover
under 50 million euros.
According to Arellano and Bond (1991), use of dynamic panel
estimators implies that cross-sections are included in the database for
at least four consecutive years, so as to be considered in the
econometric analysis, namely in the second-order autocorrelation tests.
These tests are fundamental to confirm the robustness of the empirical
results obtained. Given that dynamic panel estimators are used in this
study, we eliminate firms that do not belong to the database for at
least four consecutive years in the period 1999-2006.
Seeking to address the problem of possible bias in the results, and
to have a more representative database of the actual structure of
Portuguese SMEs, we consider three types of SMEs: 1) SMEs that remain in
the market for the whole period of analysis; 2) SMEs that enter in the
market during the period of analysis; and 3) SMEs that leave the market
during the period of analysis.
Given that our study's goal is to study the influence of age
on the profitability of Portuguese SMEs, we consider two research
sub-samples: 1) 495 young SMEs: 236 of which enter the market during the
period of analysis, and 36 of them leave the market during that time;
and 2) 1350 old SMEs: 162 of which leave the market during the period of
analysis. We consider as young SMEs those in existence up to a maximum
of 10 years in the end of the analysis period (1), considering as old
SMEs all those over 10 years old in the end of the analysis period (2).
Table 1 presents the structure of the database considered in this
study.
In order to test the robustness of the empirical evidence obtained,
namely if it depends on the criterion of classification used, we
consider an alternative classification criterion for young and old SMEs.
According to the alternative criterion, we consider as young SMEs those
entering the market in the period 1999-2006, considering the remainder
as old SMEs (3). In appendix, we present the results.
3.2. Variables
The following Table 2 presents the variables used in this study,
together with their corresponding measure.
The dependent variable is profitability, given by the ratio of
operational results to assets. As independent variables, we consider:
age, R & D expenditure, size, liquidity, long-term debt, and risk.
3.3. Estimation method
Studying the determinants of SME profitability without correcting
possible sample bias as a consequence of not considering the situation
of firms that left the market during the period of analysis could lead
to bias in the results obtained, given the omission of the firms with
survival difficulties. That situation could be different from that one
presented by firms with good survival possibilities.
The best way to address this problem is use of the two-step
estimation method proposed by Heckman (1979). In the first step,
considering all firms, both surviving and non-surviving, we estimate a
probit regression, in which the dependent variable has the value of 1 if
the firm is in the market, and the value of 0 if it has left the market.
As independent variables we consider the profitability determinants used
in this study.
In the second step, when estimating the regressions relating to the
profitability determinants, we only consider surviving firms, adding the
inverse Mill's ratio as another explanatory variable so as to
control for possible data bias as a consequence of survival.
The probit regression estimated in the first step allows us to
calculate the additional explanatory variable, the inverse Mill's
ratio that allows us to control for possible sample bias.
In the first step, the probit regression to estimate can be
presented as follows:
Pr([[delta].sub.i,t] = 1) = [[tau].sub.0] + [kappa][PROF.sub.i,t-1]
+ [6.summation over (K=1)] [[tau].sub.K][X.sub.K,i,t] + [S.sub.S] +
[d.sub.t] + [z.sub.i,t], (1)
where: [PROF.sub.i,t-1] is profitability in the previous period;
[X.sub.K,i,t] is the vector of the profitability determinants K
considered in this study (4); [S.sub.S] are industry sector dummy
variables (5); [d.sub.t] are annual dummy variables measuring the impact
of changes in the economic situation on the likelihood of bankruptcy;
and [z.sub.i,t] is the error.
After determining the inverse Mill's ratio (6) for each of the
observations, we consider it as an additional explanatory variable of
profitability.
In the second step, in order to estimate the regressions related to
the profitability determinants, we use dynamic panel estimators, namely
the GMM (1991), GMM system (1998) and LSDVC (2005) estimators. Using
dynamic estimators has the following advantages over traditional panel
methods (random effect panel model and fixed effect panel model): 1)
greater control of endogeneity; 2) greater control of possible
collinearity of explanatory variables; and 3) more effectiveness in
controlling effects caused by the absence of important independent
variables, for explaining the dependent variable. In addition, use of
dynamic estimators allows us to correctly determine, i.e. without result
bias, the persistence of profitability in Portuguese SMEs.
The regressions to estimate using the various dynamic panel
estimators are expressed as follows: 6
[PROF.sub.i,t] = [[beta].sub.0] + [delta][PROF.sub.i,t-1] +
[6.summation over (K=1)] [[beta].sub.K] [X.sub.k,i,t] +
[[beta].sub.[lambda]][[lambda].sub.i,t] + [S.sub.S] + [d.sub.t] +
[v.sub.i] + [e.sub.i,t], (2)
where: [[lambda].sub.i,t] is the inverse Mill's ratio; vt are
the non-observable individual effects; and [e.sub.i,t] is the error,
which assumes normal distribution.
Estimating equation (2) through traditional panel models, namely
through random and fixed effect panel models, we would obtain biased
estimates of the parameters estimated, due to the existence of
correlation between [v.sub.i] and [PROF.sub.i,t-1] and between
[e.sub.i,t] and [PROF.sub.i,t-1].
Arellano and Bond (1991) recommend the estimation of equation (2)
with the variables in first differences, using the lagged profitability
and the determinants at level. By estimating equation (2) in first
differences, non-observable individual effects ([v.sub.i]) are
eliminated, so eliminating the correlation between [v.sub.i] and
[PROF.sub.i,t-1] Use of the lags of profitability and lags of the
determinants creates orthogonal conditions between [e.sub.i,t] and
[PROF.sub.i,t-1], eliminating their correlation.
However, Blundell and Bond (1998) state that in situations of
persistence of the dependent variable, i.e. when high correlation is
found between the dependent variable in the previous and current
periods, and the number of periods is not particularly high, the GMM
(1991) estimator leads to inefficient results because the instruments
are weak, leading to bias of the estimated results. This bias is
particularly important regarding the estimated parameter measuring the
relationship between the dependent variable in the previous and current
period. In situations of high persistence of the dependent variable,
Blundell and Bond (1998) propose use of an alternative estimator,
considering a system of variables at levels in first differences. For
the variables at level, the instruments are given in first differences.
For the variables in first differences, the instruments are given in
levels.
However, the GMM (1991) and GMM system (1998) estimators can only
be valid on two conditions: 1) if the restrictions created, a
consequence of using instruments, are valid; and 2) if there is no
second-order autocorrelation. To test the validity of the restrictions
created from use of the instruments, we use the Sargan test in the case
of the GMM (1991) estimator, and the Hansen test in the case of the GMM
system (1998) estimator. In both cases, the null hypothesis is the
validity of the restrictions created by using the instruments used, the
alternative hypothesis being non-validity of use of the restrictions
created by use of the instruments. We also test for the existence of
first and second-order autocorrelation. The null hypothesis indicates
the non-existence of first and second-order autocorrelation, the
alternative hypothesis indicating the existence of first and
second-order autocorrelation. In the case of not rejecting the null
hypothesis of validity of the restrictions created by the instruments
and non-existence of second-order autocorrelation, we conclude that the
results obtained from using the GMM (1991) and GMM system (1998)
estimators are robust.
Bruno (2005) concludes that in situations where neither the number
of cross-sections nor the number of observations is very high, given the
relatively high number of instruments compared to the number of
observations, this can cause bias of the results obtained using the GMM
(1991) and GMM system (1998) estimators. Considering that the number of
cross-sections, and consequently the number of observations, is not very
high, mainly regarding young SMEs, this study also uses the estimator by
Bruno (2005), Least Squares Dummy Variable Corrected--LSDVC, in order to
test the robustness of the results previously obtained using the GMM
(1991) and GMM system (1998) dynamic estimators.
In order to test the differences in the relationships between
determinants and profitability for young SMEs and old SMEs, we use the
Chow test (7). We test for possible differences for each of the
determinants considered in this study, as well as the overall difference
for the set of determinants considered. The null hypothesis is that no
differences are found in the estimated parameters relating to
relationships between determinants and profitability for young SMEs and
old SMEs, the alternative hypothesis being existence of difference in
the estimated parameters.
4. Results
4.1. Descriptive statistics
The following Table 3 presents the descriptive statistics of the
variables used in this study for the sub-samples of young SMEs and old
SMEs.
Young SMEs have slightly higher average profitability than old
SMEs. Additionally, we find some volatility in the profitability of
young SMEs and old SMEs, since standard deviations of profitability are
above the respective means.
Regarding independent variables, we find that: 1) R & D
expenditure and risk are on average higher in young SMEs than in old
SMEs; and 2) age, size, liquidity and long-term debt are on average
higher in old SMEs than in young SMEs.
4.2. Survival analysis
The following Table 4 presents the results of the survival analysis
for young SMEs and old SMEs.
The empirical evidence allows us to conclude that (8): 1)
profitability in the previous period, age, size, liquidity and long-term
debt contribute to a greater likelihood of survival, whereas risk
contributes to a lesser likelihood of survival in young SMEs, and 2)
profitability in the previous period, age, R & D expenditure,
liquidity, and long-term debt contribute positively to the likelihood
survival in old SMEs.
The following Table 5 presents the results of the Chow test of
differences between the determinants of survival for young SMEs and old
SMEs.
We find that for each of the variables considered as determinants
of the survival of young SMEs and old SMEs, we reject the null
hypothesis of equality of the estimated parameters regarding the
relationships between profitability determinants and probability of
survival. The results of the overall Chow test confirm those
differences. Therefore, we can conclude that there are statistically
significant differences between the survival determinants of young SMEs
and old SMEs.
4.3. Dynamic panel estimators
The following Table 6 presents the regressions referring to the
relationships between determinants and profitability in young SMEs and
old SMEs, using the GMM (1991), GMM system (1998) and LSDVC (2005) (9)
estimators.
The results of the Sargan test, regardless of taking young or old
SMEs as the subject of analysis, indicate the rejection of the null
hypothesis, thus the restrictions arising from the instruments used are
valid. Therefore, and in spite of not being able to reject the null
hypothesis of second-order autocorrelation, we cannot consider the
results obtained with the GMM (1991) estimator valid.
Whether taking young or old SMEs as the subject of analysis, the
results of the Hansen test indicate that we cannot reject the null
hypothesis of validity of the restrictions, as a consequence of the
instruments used. What is more, whether taking young or old SMEs as the
subject of analysis, the results of the second-order autocorrelation
tests indicate that we cannot reject the null hypothesis of absence of
second-order autocorrelation. Based on the results of the Hansen, and
second-order autocorrelation tests, we can conclude that the results
obtained with the GMM system (1998) estimator are robust.
The results obtained with the LSDVC (2005) estimator corroborate,
in general, those obtained with the GMM system (1998), regarding the
sign, magnitude and statistically significance of the estimated
parameters.
Based on the various results obtained, we will consider the
empirical evidence from using the GMM system (1998) and LSDVC (2005)
estimators as our reference for interpreting the results.
Regarding the relationships between determinants and profitability
in young SMEs, we can conclude that: 1) profitability in the previous
period, age, size, liquidity and long-term debt positively influence
profitability, while risk negatively influences profitability.
For old SMEs, we can conclude that: 1) profitability in the
previous period, R & D expenditure, and size influence positively
profitability, while age influences negatively profitability.
Regarding the relationship between the inverse Mill's ratio
and profitability, we identify negative and statistically significant
relationships, regardless of taking young SMEs or old SMEs as the
subject of analysis. This empirical evidence obtained allows us to
conclude that using the inverse Mill's ratio seems to be effective
in solving the problem of possible result bias as a consequence of the
matter of survival. Indeed, not considering the inverse Mill's
ratio in the regressions would lead to overvaluation of the estimated
parameters.
The following Table 7 presents the results of the Chow test of
differences in the estimated parameters measuring the relationships
between determinants and profitability in young and old SMEs.
Whether using the GMM system (1998) estimator or the LSDVC (2005)
estimator, we reject the null hypothesis of equality of estimated
parameters for the relationships between the determinants considered and
profitability in young and old SMEs. The results show that there are
differences between young SMEs and old SMEs for the relationships
between determinants and profitability.
5. Discussion of the results
There is a positive relationship between age and profitability in
young SMEs, the relationship being negative in the case of old SMEs.
Therefore, age has greater relative importance for increased
profitability in young SMEs than for increased profitability in old
SMEs, and so we can accept the previously formulated hypothesis H1.
The arguments of Jovanovic (1982) are not totally corroborated by
the empirical evidence obtained in this study. In fact, greater SME age
only implies increased profitability for young SMEs, but this is not
verified by SMEs in more advanced stages of their life-cycle. Indeed,
when SMEs are young, the relative marginal importance of age for
increased profitability is relevant.
The fact that young SMEs are more proactive and more careful in
choosing their investments (Lumpkin 1998; Shane, Venkataraman 2000) may
contribute to the empirical evidence obtained in this study. The need to
survive, and consequently the need to be more proactive and more
selective with investments, together with the marginal effect of one
more year of acquired experience, in the first years of the life-cycle,
may be decisive for age contributing positively to increased
profitability in young SMEs, which does not occur in the case of old
SMEs.
The empirical evidence indicates that R & D expenditure is more
important for increased profitability in old SMEs than in young SMEs.
Indeed, we find a statistically insignificant relationship between R
& D expenditure and profitability in young SMEs, whereas the
relationship between R & D expenditure and profitability in old SMEs
is positive and statistically significant. This being so, we can accept
the previously formulated hypothesis H2.
The forecast benefits regarding the impact of R & D expenditure
on SME profitability: 1) greater organizational flexibility, and
consequently greater efficiency in taking advantage of good growth
opportunities (Rogers 2004); 2) greater diversification of activities,
and consequently greater export capacity (Beise-Zee, Rammer 2006); and
3) greater ability to establish cooperation networks, and consequently
greater possibility to diversify activities (Rickne 2006); only seem to
be relevant in the case of old SMEs.
The principal goal of young SMEs to reach the minimum scale of
efficiency that allows survival (Jovanovic 1982) may contribute to less
efficient use of R & D investment, corroborating the arguments of
Muller and Zimmermann (2009), regarding the need of the learning effect
for SMEs to become efficient in managing R & D expenditure. Indeed,
the empirical evidence obtained indicates that the learning effect may
be important for R & D expenditure to imply increased profitability.
In addition, we find that old SMEs have greater average liquidity than
young SMEs. The greater flexibility in managing financial resources may
contribute to old SMEs being more efficient in managing R & D
expenditure than young SMEs, since the young firms face greater stress
in managing their resources as a consequence of possible lower liquidity
(Tanabe, Watanabe 2005; Gomez, Vargas 2009; Muller, Zimmermann 2009).
For young and old SMEs, there is a positive and statistically
significant relationship between size and profitability. However, the
positive impact of size on profitability is greater for young SMEs than
for old ones, which is corroborated by the result of the Chow test.
Based on the empirical evidence obtained, we can conclude that size
takes on greater relative importance for increased profitability in
young SMEs than for increased profitability in old SMEs, and so we can
accept the previously formulated hypothesis H3.
The benefits of greater size for profitability forecasted by
various authors (Winter 1994; Hardwick 1997; Wyn 1998; Gschwandtner
2005): 1) greater capacity to take advantage of economies of scale; 2)
greater capacity to diversify activities and products; and 3) greater
ability to implement strategies seeking to raise barriers to the entry
of potential competitors, seem to be more important for increased
profitability in young SMEs than for increased profitability in old
SMEs.
The positive impact of size in profitability is greater for young
SMEs than do for old SMEs, which may be related to a greater proximity
to the minimum size of efficiency that allows young SMEs to survive in
their operating markets. Greater size of young SMEs, and the consequent
approach to the minimum size of efficiency that allows survival, may
contribute to young SMEs being able to manage their resources more
efficiently. Therefore, size is a greater importance for increased
profitability in young SMEs.
As would be expected, given that in most cases SME ownership and
management is concentrated in the same individuals, regardless of taking
young or old SMEs as the subject of analysis, greater size does not
imply diminished profitability. Therefore, the reasoning of Pi and Timme
(1993) and Goddard et al. (2005) regarding that greater size may
contribute to managers to invest in projects that harm profitability
does not appear to be relevant in SMEs.
We find that the relationship between liquidity and profitability
is positive and statistically significant for young SMEs, but it is not
statistically significant in the case of old SMEs. Therefore, we can
conclude that liquidity has greater relative importance for increased
profitability in young SMEs than in old SMEs, and so we can accept the
previously formulated hypothesis H4.
The fact that greater liquidity contributes to SMEs being able to
manage their financial resources with less stress, allowing them to deal
successfully with possible changes in their operating markets (Goddard
et al. 2005), seems to have greater importance for higher levels of
profitability in young SMEs, compared to what occurs in old SMEs.
The conclusions by Honjo and Harada (2006) seem to be particularly
relevant in the context of young SMEs. Indeed, less stress in managing
financial resources may be fundamental in the first years of the
life-cycle of SMEs, so that these firms can implement their investment
opportunities, which contributes to increased levels of profitability.
The impossibility to accomplish the short-term commitments, and the
consequent stress in managing financial resources can be particularly
important for SMEs in the first years of their life-cycle. Therefore,
greater liquidity may be particularly important for reducing the
impossibility of young SMEs to accomplish their short-term commitments,
leading to less stress in managing their financial resources, which can
be decisive for young SMEs to improve their levels of profitability.
However, young SMEs face more problems of liquidity due to less
reputation (Diamond 1989), and a greater probability of bankruptcy
(Muller, Zimmermann 2009), which contributes for creditors make it
difficult for young SMEs to obtain debt (Serrasqueiro, Macas Nunes
2010), compared to old SMEs.
It should also be noted that, whether taking young or old SMEs as
the subject of analysis, greater liquidity does not imply lower levels
of profitability. According to Ang (1991) that situation occurs, because
for the majority of SMEs, ownership and management are in the same
hands, so the agency problems between owners and managers being minimal.
However, our results do not corroborate the arguments of Fama and Jensen
(1983) and Myers and Rajan (1995) that greater liquidity can contribute
to managers to invest in projects that do not contribute to increased
profitability, but rather to increasing their personal benefits.
We find a positive and statistically significant relationship
between long-term debt and profitability in young SMEs, but that
relationship being statistically insignificant when our subject of
analysis is old SMEs. Based on this empirical evidence, we may conclude
that long-term debt is of greater relative importance for increased
profitability in young SMEs than for increased profitability in old
SMEs, and so we can accept the previously formulated hypothesis H5.
When internal financing is insufficient, access to long-term debt
seems to be fundamental for increased profitability in young SMEs. The
considerable risk associated with the activities of young SMEs may imply
particularly restrictive terms of credit imposed by creditors (Myers
1977). Consequently, young SMEs may become excessively dependent on
short-term debt, when internal funding is insufficient. Given the high
dependence on short-term debt, when internal financing is insufficient,
the marginal effect of long-term debt on the profitability can be
particularly relevant in young SMEs
The empirical evidence obtained in the context of young SMEs seems
corroborate the arguments of Fagiolo and Luzzi (2006), given that use of
long-term debt can be fundamental for those firms being able to reduce
possible excessive stress in managing their financial resources, as a
consequence of the need to pay off short-term debts over a short and
constant period. Indeed, as Serrasqueiro and Macas Nunes (2010)
conclude, when internal financing is insufficient, young SMEs are
particularly dependent on short-term debt. Young SMEs with less
reputation and a greater possibility of bankruptcy may face more
obstacles in obtaining long-term debt.
Given the high dependency of young SMEs on short-term debt, when
internal financing is insufficient, then the marginal effect of
long-term debt on young SME profitability can be particularly relevant.
That effect may diminish as SMEs progress in the stages of their
life-cycle, given the greater possibility of accessing long-term debt,
as suggested by the results of the descriptive statistics presented
previously.
The relationship between risk and profitability is negative and
statistically significant for young SMEs, but it not statistically
significant for old SMEs. On the basis of these results, we can accept
the previously formulated hypothesis H6.
Creditors can make it difficult for SMEs with high levels of risk
to obtain debt (Pettit, Singer 1985). Restrictive credit terms for SMEs
can be particularly severe, considering that, asides from the SME
greater possibility of bankruptcy, they may change their asset
composition, contributing considerably to greater risk meaning
diminished profitability in young SMEs. In addition, high risk combined
with a high possibility of bankruptcy in young SMEs may contribute to
their owners / managers to implement investment projects that maximize
their immediate benefits, but they do not mean increased profitability.
A great number of young SMEs have not yet reached the minimum scale
of efficiency that allows them to survive (Jovanovic 1982), which may
contribute to high-risk situations that do not allow them to take
advantage of good investment opportunities. This may occurs in the first
years of young SME life-cycle, contributing to reduced levels of
profitability.
Finally, whether taking young SMEs or old SMEs as the subject of
analysis, the empirical evidence indicates that the relationship between
profitability in the previous and present periods is statistically
significant. However, for young SMEs the estimated parameter is 0,33652,
when using the GMM system (1998) estimator, and 0.32838 with use of the
LSDVC (2005) estimator. For old SMEs, the estimated parameter is
0.55662, using the GMM system (1998) estimator, and 0.58929, using the
LSDVC (2005) estimator. The results of the Chow test show that the
estimated parameters are of a different magnitude. Therefore, we find
that persistence of profitability is greater in old SMEs than in young
SMEs, and so we can accept the previously formulated hypothesis H7.
The empirical evidence obtained in this study corroborates the
conclusions of Mueller (1986), since profitability is persistent in the
case of young and old SMEs. This may be due to the dynamic profile of
the existing markets, thereby small divergences occurring at certain
times can be solved by firms entering and leaving the markets.
In addition, the empirical evidence appears to corroborate the
conclusions of Gschwandtner (2005), since greater risk, and consequently
greater likelihood of bankruptcy in young SMEs, may contribute to less
persistence of profitability.
6. Conclusion and implications
Considering two sub-samples of SMEs: 1) 495 young SMEs; and 2) 1350
old SMEs, using the two-step estimation method in order to address
possible data bias, arising from the matter of survival, this study
investigates whether the determinants of profitability in young SMEs are
different from those in old SMEs.
The empirical evidence obtained indicates that age is a determinant
factor in the relationships between determinants and profitability in
SMEs.
Firstly, age and size are of greater relative importance for
increased profitability in young SMEs than for increased profitability
in old SMEs. Moreover, age and size are also found to be relevant for
increased probability of survival in young SMEs. Greater age and size
can also be particularly relevant for SMEs being able to efficiently
diversify activities and products, attaining more quickly the minimum
scale of efficiency, thereby contributing to increased profitability in
young SMEs.
Secondly, liquidity and long-term debt are of greater relative
importance for increased profitability in young SMEs than for increased
profitability in old SMEs. Liquidity and long-term debt are also found
to be particularly important for increased probability of survival in
young SMEs. When internal finance is insufficient, less financial stress
in managing financial resources, as a consequence of greater liquidity
and access to long-term debt, is particularly important for young SMEs
to take advantage of good investment opportunities, arising in the start
of their life-cycle, which can imply increased profitability.
Thirdly, R & D expenditure is more important for increased
profitability in old SMEs than in young SMEs. In addition, R & D
expenditure is relevant for increased likelihood of survival in old
SMEs. On the one hand, R & D expenditure can be particularly
relevant for SMEs being able to diversify their activities, in advanced
stages of their life-cycle. Diversification can imply increased
profitability; on the other hand, young SMEs may not make very efficient
use of R & D expenditure, due to adverse financial restrictions that
SMEs face in the first years of activity, as well as little experience
in managing R & D projects.
Fourthly, risk is of greater relative importance for diminished
profitability in young SMEs than for diminished profitability in old
SMEs. We also find that risk contributes to less survival in young SMEs.
The difficulties to obtain debt faced by young SMEs, the possibility of
owners/managers investing in projects that do not maximize
profitability, and the possibility of high risk situations implying the
rejection of good investment opportunities, are all factors that impose
higher levels of risk, which may imply reduced profitability in young
SMEs.
Fifthly, persistence of profitability is greater in old SMEs than
in young SMEs. Additionally, profitability in the previous period is of
greater relative importance for increased probability of survival in
young SMEs than for increased probability of survival in old SMEs. The
particular difficulties that young SMEs may face in the start of their
life-cycle, namely the possible changes of the market conditions, and
difficulties in managing financial resources, can contribute to less
persistence of profitability in this type of SME, compared to the case
of old SMEs.
The empirical evidence obtained in this study allows us to make the
following suggestions for economic policy in general and industrial
policy in particular.
It is suggested that the Portuguese government should promote
useful support to young SMEs, through the creation of special long-term
lines of credit, which would mean less stress in managing financial
resources, allowing young SMEs to take advantage of good investment
opportunities, arising in the start of their life-cycle, contributing to
increased profitability. For old SMEs, given the importance of R & D
expenditure for increased profitability and the probability of survival,
we suggest measures that contemplate financial support for investment in
R & D, so that this type of SME can diversify their activities and
products, thereby stimulating their levels of profitability.
APPENDIX
Alternative criterion for selecting SMEs based on age
Table A1. Analysis of survival--Young SMEs and Old SMEs--alternative
criterion for selecting SMEs based on age
Dependent Variable: Pr([[delta].sub.i, t] = 1)
Independent Variables Young SMEs Old SMEs
[PFOF.sub.i, t-1] 0.58748 *** 0.16445 ***
(0.06758) (0.04336)
[AGE.sub.i,t] 0.11334 *** 0.05112 ***
(0.03456) (0.01503)
R & [D.sub.i,t] 0.05998 0.35009 ***
(0.11546) (0.11637)
[SIZE.sub.i,t] 0.16112 *** 0.01114
(0.03453) (0.02874)
[LIQ.sub.i,t] 0.21123 *** 0.08544 **
(0.06473) (0.04221)
[LLEV.sub.i,t] 0.26758 *** 0.10394 *
(0.06758) (0.05303)
[EVOL.sub.i,t] -0.04993 *** -0.00194
(0.01687) (0.01599)
Pseudo [R.sup.2] 0.4545 0.38394
Firms 236 1609
Observations 1228 10543
Notes: 1. Robust Standard Deviations in parenthesis.
2. *** statistically significant at 1% level; "statistically
significant at 5% level; and * statistically significant at 10%
level. 3. Estimations include sector dummy variables, but estimated
parameters are not presented in the tables. 4. Estimates include
annual dummy variables, but estimated parameters are not presented
in the tables
Table A2. Determinants of profitability--Young SMEs and Old
SMEs--alternative criterion for selecting SMEs based on age
Dependent Variable: [PFOF.sub.i,t]
Young SMEs
Independent GMM GMM LSDVC
Variables (1991) system (2005)
(1998)
[PFOF.sub.i, t-1] 0.02839 0.28939 *** 0.29094 ***
(0.04758) (0.04556) (0.04778)
[AGE.sub.i,t]] 0.02009 0.07384 *** 0.06112 ***
(0.02455) (0.015647) (0.01454)
R & [D.sub.i,t]] -0.00453 -0.01546 -0.04098
(0.05226) (0.05778) (0.07512)
[SIZE.sub.i,t]] 0.02343 ** 0.06654 *** 0.06556 ***
(0.01133) (0.01477) (0.001123)
[LIQ.sub.i,t]] 0.14838 *** 0.09066 *** 0.08737 ***
(0.04304) (0.02598) (0.02466)
[LLEV.sub.i,t]] 0.03453 0.08737 *** 0.09635 ***
(0.04666) (0.01501) (0.02221)
[EVOL.sub.i,t]] -0.01678 ** -0.02546 *** -0.02442 ***
(0.00825) (0.00453) (0.00673)
[[lambda].sub.i,t] -0.12938 *** -0.14657 *** -0.15363 ***
(0.03928) (0.03029) (0.03848)
CONS 0.014536 0.02738
(0.04845) (0.05677)
Wald 236 236 236
F 949 1185 1185
Sargan 172.43 ***
Hansen 99.55 ***
[m.sub.1] 44.89 ***
[m.sub.2] 131.93
Firms -6.12 *** -6.56 ***
Observations -0.28 -0.22
Old SMEs
Independent GMM GMM LSDVC
Variables (1991) system (2005)
(1998)
[PFOF.sub.i, t-1] 0.14656 *** 0.52888 *** 0.55463 ***
(0.04656) (0.05436) (0.05553)
[AGE.sub.i,t]] -0.06473 *** -0.03529 *** -0.03223 ***
(0.01441) (0.00837) (0.00777)
R & [D.sub.i,t]] 0.19283 *** 0.26375 *** 0.22231 ***
(0.05779) (0.05646) (0.05449)
[SIZE.sub.i,t]] -0.02009 0.01134 * 0.02637 ***
(0.02736) (0.05882) (0.005444)
[LIQ.sub.i,t]] -0.00789 0.01099 0.01333
(0.03545) (0.04556) (0.03887)
[LLEV.sub.i,t]] -0.009839 0.01029 -0.02421
(0.01637) (0.02545) (0.02837)
[EVOL.sub.i,t]] 0.01287 0.01726 0.00887
(0.04008) (0.03551) (0.03899)
[[lambda].sub.i,t] -0.13948 *** -0.13657 *** -0.16935 ***
(0.02637) (0.02830) (0.03453)
CONS 0.03847 *** 0.03444 **
(0.01112) (0.01717)
Wald 1411 1411 1411
F 7055 8466 8466
Sargan 156.89 ***
Hansen 83.37 ***
[m.sub.1] 35.89 ***
[m.sub.2] 127.14
Firms -5.88 *** -5.65 ***
Observations -0.26 -0.43
Notes: 1. Robust Standard Deviations in parenthesis.
2. *** statistically significant at 1% level; "statistically
significant at 5% level; and * statistically significant at 10%
level. 3. Estimations include sector dummy variables, but estimated
parameters are not presented in the tables. 4. Estimates include
annual dummy variables, but estimated parameters are not presented
in the tables
doi: 10.3846/16111699.2011.620148
Acknowledgements
The authors thank the three anonymous referees for their comments.
Paulo Macas Nunes and Zelia Serrasqueiro also gratefully acknowledge
partial financial support from FCT, program POCTI. Ana Viveiros also
gratefully acknowledge financial support from BPI (Banco Portugues de
Investimento).
References
Adams, M.; Buckle, M. 2003. The determinants of corporate financial
performance in the Bermuda insurance market, Applied Financial Economics
13: 133-143. http://dx.doi.org/10.1080/09603100210105030
Amato, L.; Amato, C. 2004. Firm size, strategic advantage, and
profit rates in US retailing, Journal of Retailing and Consumer Services
11: 181-193. http://dx.doi.org/10.1016/S0969-6989(03)00036-5
Andries, P.; Debackere, K. 2007. Adaptation and performance in new
businesses: understanding the moderating effects of independence and
industry, Small Business Economics 9: 81-99.
http://dx.doi.org/10.1007/s11187-005-5640-2
Ang, J. 1991. Small business uniqueness and the theory of financial
management, The Journal of Small Business Finance 1: 1-13.
Arellano, M.; Bond, S. 1991. Some tests of specification for panel
data: Monte Carlo evidence and an application to employment equations,
Review of Economic Studies 58: 277-297.
http://dx.doi.org/10.2307/2297968
Bain, J. 1956. Barriers to New Competition. Harvard University
Press, Cambridge, MA.
Barney, J. 2001. Resource-based theories of competitive advantage:
a ten year retrospective on the resource based view, Journal of
Management 27: 643-650. http://dx.doi.org/10.1177/014920630102700602
Beise-Zee, R.; Rammer, C. 2006. Local user-producer interaction in
innovation and export performance of firms, Small Business Economics 27:
207-222. http://dx.doi.org/10.1007/s11187-006-0013-z
Blundell, M.; Bond, S. 1998. Initial conditions and moment
restrictions in dynamic panel data models, Journal of Econometrics 87:
115-143. http://dx.doi.org/10.1016/S0304-4076(98)00009-8
Bruno, G. 2005. Approximating the bias of LSDV estimator for
dynamic unbalanced panel data models, Economic Letters 87: 361-366.
http://dx.doi.org/10.1016/j.econlet.2005.01.005
Callen, J.; Cheung, C.; Kwan, C.; Yip, B. 1993. An empirical
investigation of the random character of annual earnings, Journal of
Accounting, Auditing and Finance 8: 151-162.
Chan, L.; Karceski, J.; Lakonishok, J. 2003. The level and
persistence of growth rates, The Journal of Finance 58: 643-684.
http://dx.doi.org/10.1111/1540-6261.00540
Deloof, M. 2003. Does working capital management affect
profitability of Belgian firms, Journal of Business Finance and
Accounting 30: 573-588. http://dx.doi.org/10.1111/1468-5957.00008
Diamond, D. 1989. Reputation acquisition in debt markets, Journal
of Political Economy 97: 828-862. http://dx.doi.org/10.1086/261630
Fagiolo, G.; Luzzi, A. 2006. Do liquidity constrains matter in
explaining firm size and growth? Some evidence from the Italian
manufacturing industry, Industrial and Corporate Change 15: 1-39.
http://dx.doi.org/10.1093/icc/dtj001
Fama, E.; Jensen, M. 1983. Agency problems and residual claims,
Journal of Law and Economics 26: 327-349.
http://dx.doi.org/10.1086/467038
Ferrando, A.; Kohler-Ulbrich, P.; Pal, R. 2007. Is the growth of
euro area small and medium-sized enterprises constrained by financing
barriers?, in Conference Proceedings of Financial Management
Association. Barcelona, Spain.
Galbreath, J.; Galvin, P. 2008. Firms factors, industry structure
and performance variation: new empirical evidence to a classic debate,
Journal of Business Research 61: 109-117.
http://dx.doi.org/10.1016/j.jbusres.2007.06.009
Goddard, J.; Tavakoli, M.; Wilson, J. 2005. Determinants of
profitability in European manufacturing and services: evidence from a
dynamic panel data, Applied Financial Economics 15: 1269-1282.
http://dx.doi.org/10.1080/09603100500387139
Gomez, J.; Vargas, P. 2009. The effect of financial constraints,
absorptive capacity and complementarities on the adoption of multiple
process technologies, Research Policy 38: 106-119.
http://dx.doi.org/10.1016/j.respol.2008.10.013
Gschwandtner, A. 2005. Profit persistence in the 'very'
long run: evidence from survivors and exiters, Applied Economics 37:
793-806. http://dx.doi.org/10.1080/0003684042000337406
Hardwick, P. 1997. Measuring cost inefficiency in the UK life
insurance industry, Applied Financial Economics 7: 37-44.
http://dx.doi.org/10.1080/096031097333835
Heckman, J. 1979. Sample selection bias as a specification error,
Econometrica 47: 153-161. http://dx.doi.org/10.2307/1912352
Honjo, Y.; Harada, N. 2006. SME policy, financial structure and
firm growth: evidence from Japan, Small Business Economics 27: 289-300.
http://dx.doi.org/10.1007/s11187-005-6703-0
Hyytinen, A.; Pajarinen, M. 2004. Is the cost of debt capital
higher for younger firms? The research institute of the finnish economy,
Discussion Paper No. 946.
IAPMEI. 2008. Sobre as PMEs em Portugal. Instituto de Apoio a
Pequena e Media Empresa: Lisboa.
Jensen, M.; Meckling, W. 1976. Theory of the firm: managerial
behaviour, agency costs and ownership structure, Journal of Financial
Economics 3: 306-360. http://dx.doi.org/10.1016/0304-405X(76)90026-X
Jovanovic, B. 1982. Selection and evolution of industry,
Econometrica 50: 649-670. http://dx.doi.org/10.2307/1912606
La Rocca, M.; La Rocca, T.; Cariola, A. 2009. Capital structure
decisions during a firm's life cycle, Small Business Economics
(first forthcoming): 1-24.
Lamm-Tennant, J.; Starks, L. 1993. Stock versus mutual ownership
structures: the risk implications, Journal of Business 66: 29-46.
http://dx.doi.org/10.1086/296592
Levinthal, D. 1995. Strategic management and the exploration of
diversity, in Montgomery, C. A. (Ed.). Resource-Based and Evolutionary
Theories of the Firm. Kluwer, Norwell, MA.
http://dx.doi.org/10.1007/978-1-4615-2201-0_2
Lotti, F.; Santarelli, E.; Vivarelli, M. 2009. Defending
Gibrat's law as a long--run regularity, Small Business Economics
32: 31-44. http://dx.doi.org/10.1007/s11187-007-9071-0
Lumpkin, G. 1998. Do New Entrants Have an Entrepreneurial
Orientation? Paper Presented at the 1998 Academy of Management Meeting.
San Diego, CA.
Lumpkin, G.; Dess, G. 1996. Clarifying the entrepreneurial
orientation construct and linking it to performance, Academy of
Management Review 21: 135-172.
Macas Nunes, P.; Serrasqueiro, Z.; Leitao, J. 2010. Are there non
linear relationship between the profitability of Portuguese services
SMEs and its specific determinants?, The Services Industries Journal 30:
1313-1341. http://dx.doi.org/10.1080/02642060802398853
Macas Nunes, P.; Serrasqueiro, Z.; Sequeira, T. 2009. Profitability
in Portuguese service firms: a panel data approach, The Services
Industries Journal 29: 693-707.
http://dx.doi.org/10.1080/02642060902720188
Moreno, J.; Castillo, L.; Masere, E. 2010. Firm size and
entrepreneurial characteristics: evidence from the SME sector in
Argentina, Journal of Business Economics and Management 11 : 259-282.
http://dx.doi.org/10.3846/jbem.2010.13
Moreno, J.; Castillo, L. 2011. Corporate growth, age and ownership
structure: empirical evidence in Spanish firms, Journal of Business
Economics and Management 12: 164-196.
http://dx.doi.org/10.3846/16111699.2011.555449
Mueller, D. 1986. Profits in the Long- Run. Cambridge University
Press, Cambridge.
Muller, E.; Zimmermann, V. 2009. The importance of equity finance
for R & D activity, Small Business Economics 33: 303-318.
http://dx.doi.org/10.1017/CBO9780511664731
Myers, S. 1977. Determinants of corporate borrowing, Journal of
Financial Economics 5: 147-175.
Myers, S.; Rajan, R. 1995. Liquidity and the rise of financial
intermediation, in Proceedings, Federal Reserve Bank of Chicago (issue
May), 427-446. http://dx.doi.org/10.1016/0304-405X(77)90015-0
Oliveira, B.; Fortunato, A. 2006. Firm growth and liquidity
constraints: a dynamic analysis, Small Business Economics 27: 139-156.
http://dx.doi.org/10.1007/s11187-006-0006-y
Peteraf, M. 1993. The cornerstoners of competitive advantage: a
resource based view, Strategic Management Journal 14: 179-191.
http://dx.doi.org/10.1002/smj.4250140303
Pettit, R.; Singer, R. 1985. Small business finance: a research
agenda, Financial Management 14: 47-60.
http://dx.doi.org/10.2307/3665059
Pi, L.; Timme, S. 1993. Corporate control and bank efficiency,
Journal of Banking and Finance 17: 515-530.
http://dx.doi.org/10.1016/0378-4266(93)90050-N
Porter, M. 1980. Competitive Strategy: Techniques for Analysing
Industries and Competitors. New York: The Free Press.
Rickne, A. 2006. Connectivity and performance of science-based
firms, Small Business Economics 26: 393-407.
http://dx.doi.org/10.1007/s11187-005-4848-5
Robb, A.; Robinson, D. 2009. The capital structure decisions of new
firms, Working Paper.
Rogers, M. 2004. Networks, firm size and innovation, Small Business
Economics 22: 141-153.
http://dx.doi.org/10.1023/B:SBEJ.0000014451.99047.69
Serrasqueiro, Z.; Macas Nunes, P. 2010. Is age a determinant of
financing decisions of SMEs? Empirical evidence using panel data models,
Entrepreneurship Theory and Practice (forthcoming).
http://dx.doi.org/10.1007/s11187-007-9092-8
Serrasqueiro, Z.; Macas Nunes, P. 2008. Performance and size:
empirical evidence from Portuguese SMEs, Small Business Economics 31:
195-217.
Shane, S.; Venkataraman, S. 2000. The promise of entrepreneurship
as a field of research, Academy of Management Review 25: 217-226.
Slater, S.; Olsen, E. 2002. A fresh look at industry and market
analysis, Business Horizons (sp suppl.): 15-22.
Steffens, P.; Davidsson, P.; Fitzsimmons, J. 2009. Performance
configurations over time: implications for growth-and profit, oriented
strategies, Entrepreneurship Theory and Practice 33: 125-148.
http://dx.doi.org/10.1111/j.1540- 6520.2008.00283.x
Stulz, R. 1990. Managerial discretion and optimal financing
policies, Journal of Financial Economics 26: 3-27.
http://dx.doi.org/10.1016/0304-405X(90)90011-N
Tanabe, K.; Watanabe, C. 2005. Sources of small and medium firms
excellent business performance in a service oriented economy, Journal of
Services Research 5: 5-20.
Teece, D. 1981. Internal organization and economic performance: an
empirical analysis of the profitability of principal firms, Journal of
Industrial Economics 30: 173-199. http://dx.doi.org/10.2307/2098201
Titman, S.; Wessels, R. 1988. The determinants of capital structure
choice, Journal of Finance 43: 1-19. http://dx.doi.org/10.2307/2328319
Travkina, I.; Tvaronaviciene, M. 2011. Export competitiveness and
domestic productivity facets: case of Lithuania, Journal of Business
Economics and Management 12: 49-68.
http://dx.doi.org/10.3846/16111699.2011.555360
Winter, R. 1994. The dynamics of competitive insurance markets,
Journal of Financial Intermediation 3: 379-115.
http://dx.doi.org/10.1006/jfin.1994.1011
Wyn, J. 1998. The fourth wave, Best's Review 99: 53-57.
Yasuda, T. 2005. Firm growth, size, age and behaviour in Japanese
manufacturing, Small Business Economics 24: 1-15.
http://dx.doi.org/10.1007/s11187-005-7568-y
Paulo Macas Nunes [1], Ana Viveiros [2], Zelia Serrasqueiro [3]
[1,3] Beira Interior University and CEFAGE Research Center,
Universidade da Beira Interior, Estrada do Sineiro, Ernesto Cruz-Polo
IV, 6200-209 Covilha, Portugal [2] Universidade da Beira Interior and
Banco BPI (Banco Portugues de Investimento)
E-mails: [1]
[email protected] (corresponding author); [2]
[email protected]; [3]
[email protected]
Received 01 February 2011; accepted 19 May 2011
(1) Corresponds to 2006.
(2) Hyytinen and Pajarinen (2004), Oliveira and Fortunato (2006),
Ferrando et al. (2007) and La Rocca et al. (2009) consider the same
criterion for classifying young and old SMEs.
(3) According to the alternative criterion, we consider as young
SMEs those up to 7 years old, considering as old SMEs those over 7 years
old. Robb and Robinson (2009) consider SMEs to be young up to a maximum
of 5 years of age. In this study, use of dynamic estimators, with the
consequent need for SMEs to be in the sample for at least four
consecutive years to validate the second-order autocorrelation tests,
recommends use of an alternative criterion with a higher maximum age for
classifying young SMEs. However, the alternative criterion we use is
similar to that used by Robb and Robinson (2009) since, by considering
as young SMEs those entering in the period 1999-2006, they are no more
than 7 years old. The alternative criterion used in this study is also
quite similar to the one used by Steffens et al. (2009), these authors
classifying as young SMEs those up to 8 years old, classifying as old
SMEs those over 8 years old.
(4) As mentioned before, we consider as determinants of the
profitability of young and old Portuguese SMEs: 1) age; 2) R & D
intensity; 3) size; 4) liquidity; 5) long-term debt; and 6) risk.
(5) We consider sector dummy variables representing the main
industry sectors: 1) primary sector (I) which includes agriculture and
fishing; 2) secondary sector (II) including manufacturing and
construction; and 3) tertiary sector (III) including services and
commerce.
(6) The inverse Mill's ratio is the ratio between the
cumulative density function and the density function. The designation of
inverse Mill's ratio is due to the fact that Mill's ratio
considers the inverse of Hazard ratio (also known as force of
mortality). For a detailed description of the calculation of the inverse
Mill's ratio, see Heckman (1979).
(7) We also use the Chow test to test for differences in the
determinants of survival for young SMEs and old SMEs.
(8) In Appendix, Table A1, we present the results relating to the
survival analysis of young SMEs and old SMEs, considering the
alternative criterion for classifying young and old SMEs previously
mentioned in Section 3. Methodology. The results obtained, concerning
sign, magnitude and statistical significance of the estimated
parameters, are relatively similar to those presented in Table 4, which
confirms the robustness of the empirical evidence obtained in this
study, regarding specifically the survival analysis carried out.
(9) In Appendix, Table A2, we present the results referring to the
determinants of profitability in young SMEs and old SMEs, taking the
alternative criterion for classifying young SMEs and old SMEs presented
above in Section 3. Methodology. As for sign, magnitude and statistical
significance of the estimated parameters, the results obtained are
relatively similar to those presented in Table 6, which confirms the
robustness of the empirical evidence obtained relating to the
profitability determinants of young and old SMEs.
Paulo MACAS NUNES. Ph.D. in Economics, Associate Professor at the
Department of Management and Economics to Beira Interior University and
Researcher in CEFAGE-UE (Center for Advanced Studies in Management and
Economics). The research interests are Applied Economics, Corporate
Finance, Industrial Economics and Microeconomics. Paulo Macas Nunes is
the author of articles in various journals: Journal of Business
Economics and Management, Entrepreneurship Theory & Practice;
Research Policy; Journal of Evolutionary Economics, Small Business
Economics, Industrial and Corporate Change, Journal of Business
Research, Journal of Service Management, Applied Economics, Applied
Economics Letters, Applied Financial Economics Letters, Economic Record,
The Services Industries Journal, and other journals.
Ana VIVEIROS. Master in Economics in Beira Interior University at
the Department of Management and Economics, and BPI (Banco Portugues de
Investimento) director member.
Zelia SERRASQUEIRO. Ph.D. in Management, Associate Professor at the
Department of Management and Economics to Beira Interior University and
Researcher in CEFAGE-UE (Center for Advanced Studies in Management and
Economics). The Research interests are Corporate Finance and
Entrepreneurial Finance. Zelia Serrasqueiro is the author of articles in
various journals: Journal of Business Economics and Management,
Entrepreneurship Theory & Practice; Research Policy; Journal of
Evolutionary Economics; Small Business Economics; Industrial and
Corporate Change, Journal of Business Research, Journal of Service
Management, Applied Economics, Applied Economics Letters, Applied
Financial Economics Letters, The Services Industries Journal, Social
Responsibility Journal, Review of Accounting and Finance, and other
journals.
Table 1. Description of database
Young SMEs Old SMEs
Firms Observations Firms Observations
Firms Present for the 223 1561 1188 8316
Whole Period 1999-2006
Firms Entering the Market 236 1228 0 0
in the Period 1999-2006
Firms Leaving the Market 36 172 162 776
in the Period 1999-2006
Total Number of Firms 495 1350
Total Number of 2961 9092
Observations
Table 2. Variables and measures
Variables Measures
Dependent Variable
Profitability ([PROF.sub.i, t]) Ratio of Operational Profits
before Interest and Tax to Total
Assets
Independent Variables
Age ([AGE.sub.i,t]) Logarithm of the Number of Years
of Firm Existence
Intensity of Expenditure on Research Ratio of Expenditure on Research
and Development (R & [D.sub.i,t]) and Development to Total Assets
Size ([SIZE.sub.i,t]) Logarithm of Total Assets
Liquidity ([LIQ.sub.i,t]) Ratio of Short-term Liabilities
to Current Assets
Long-term Debt ([LLEV.sub.i,t]) Ratio of Medium and Long-term
Liabilities to Total Assets
Risk ([EVOL.sub.i, t]) Absolute Value of the Percentage
Variation of Operational Profits
before Interest and Tax
Table 3. Descriptive statistics
Young SMEs
Stan.
Variable N Mean Deviation Min. Max.
[PFOF.sub.i,t] 2961 0.047 0.102 -1.511 0.581
[AGE.sub.i,t] 2961 1.674 0.316 0 2.302
R & [D.sub.i,t] 2961 0.0097 0.032 0 0.694
[SIZE.sub.i,t] 2961 14.36 1.287 10.36 17.37
[LIQ.sub.i,t] 2961 1.489 1.561 0.027 15.46
[LLEV.sub.i,t] 2961 0.062 0.159 0 0.771
[EVOL.sub.i,t] 2961 4.039 16.84 0.0007 38.11
Old SMEs
Stan.
Variable N Mean Deviation Min. Max.
[PFOF.sub.i,t] 9092 0.045 0.089 -2.034 1.293
[AGE.sub.i,t] 9092 3.107 0.524 1.791 5.096
R & [D.sub.i,t] 9092 0.0096 0.035 0 0.665
[SIZE.sub.i,t] 9092 15.15 1.211 10.62 17.69
[LIQ.sub.i,t] 9092 1.589 1.623 0.041 30.60
[LLEV.sub.i,t] 9092 0.121 0.156 0 0.820
[EVOL.sub.i,t] 9092 3.003 13.09 0.00012 31.21
Table 4. Analysis of survival--Young SMEs and Old SMEs
Dependent Variable: Pr([[delta].sub.i, t] = 1)
Independent Variables Young SMEs Old SMEs
[PFOF.sub.i, t-1] 0.54838 *** 0.19283 ***
(0.05647) (0.04774)
[AGE.sub.i,t] 0.09765 *** 0.05854 ***
(0.02765) (0.01963)
R & [D.sub.i,t] 0.08763 0.31838 ***
(0.10432) (0.09674)
[SIZE.sub.i,t] 0.13389 *** 0.02604
(0.02098) (0.03001)
[LIQ.sub.i,t] 0.17829 *** 0.08637 **
(0.04472) (0.04289)
[LLEV.sub.i,t] 0.23453 *** 0.11454 **
(0.05845) (0.05508)
[EVOL.sub.i,t] -0.04673 *** -0.00534
(0.01508) (0.01786)
Pseudo [R.sup.2] 0.43002 0.39657
Firms 459 1350
Observations 2961 9092
Notes: 1. Robust Standard Deviations in parenthesis.
2. *** statistically significant at 1% level; and ** statistically
significant at 5% level. 3. Estimations include sector dummy
variables, but estimated parameters are not presented in the tables.
4. Estimates include annual dummy variables, but estimated parameters
are not presented in the tables
Table 5. Chow test--differences for determinants of survival--Young
SMEs and Old SMEs
Dependent Variable:
Pr([[delta].sub.i,
Independent Variables t] = 1)
([PFOF.sub.i, t-1]) [[alpha].sub.YOUNG]--
[[alpha].sub.OLD] = 0 27.07 ***
F(1.12053) (0.0000)
([AGE.sub.i, t]) [[tau].sub.1YOUNG]--
[[tau.sub.1OLD] = 0 18.91 ***
F(1.12053) (0.0000)
(R & [D.sub.i, t]) [[tau].sub.2YOUNG]--
[[tau.sub.2OLD] = 0 32.33 ***
F(1.12053) (0.0000)
([SIZE.sub.i, t]) [[tau].sub.3YOUNG]-
[[tau.sub.3OLD] = 0 21.85 ***
F(1.12053) (0.0000)
([LIQ.sub.i, t]) [[tau].sub.4YOUNG]--
[[tau.sub.4OLD] = 0 23.45 ***
F(1.12053) (0.0000)
([LLEV.sub.i, t]) [[tau].sub.5YOUNG]--
[[tau.sub.5OLD] = 0 25.06 ***
F(1.12053) (0.0000)
([EVOL.sub.i, t]) [[tau].sub.6YOUNG]--
[[tau.sub.6OLD] = 0 24.41 ***
F(7.12053) (0.0000)
Global Difference 28.38 ***
F(7.12053) (0.0000)
Notes: 1. *** statistically significant at 1% level.
2. Probabilities in parenthesis
Table 6. Determinants of profitability--Young SMEs and Old SMEs
Dependent Variable: [PFOF.sub.i, t]
Young SMEs
Independent GMM GMM LSDVC
Variables (1991) system (2005)
(1998)
[PFOF.sub.i, t-1] 0.05647 0.33652 *** 0.32838 ***
(0.05097) (0.05377) (0.05182)
[AGE.sub.i, t] 0.01298 0.05647 *** 0.05093 ***
(0.01987) (0.01488) (0.01238)
R & [D.sub.i, t] -0.00783 -0.02839 -0.04536
(0.05631) (0.06088) (0.07827)
[SIZE.sub.i, t] 0.00786 0.05529 *** 0.04973 ***
(0.01332) (0.01245) (0.00901)
[LIQ.sub.i, t] 0.11889 *** 0.07998 *** 0.07453 ***
(0.03006) (0.02366) (0.02112)
[LLEV.sub.i, t] 0.02832 0.07983 *** 0.08631 ***
(0.03098) (0.01665) (0.01774)
[EVOL.sub.i, t] -0.01678 * -0.02117 *** -0.01672 **
(0.00903) (0.00568) (0.00789)
[[lambda].sub.i, t] -0.10983 *** -0.12837 *** -0.16374 ***
(0.02738) (0.02879) (0.03098)
CONS 0.01234 0.02346
(0.03829) (0.04092)
Wald 169.43 ***
F 97.04 ***
Sargan 41.02 ***
Hansen 135.10
[m.sub.1] -6.04 *** -6.35 ***
[m.sub.2] -0.37 -0.25
Firms 459 459 459
Observations 2064 2523 2523
Old SMEs
Independent GMM GMM LSDVC
Variables (1991) system (2005)
(1998)
[PFOF.sub.i, t-1] 0.11928 ** 0.55662 *** 0.58929 ***
(0.05782) (0.06283) (0.06721)
[AGE.sub.i, t] -0.08732 *** -0.04087 *** -0.03723 ***
(0.02189) (0.00956) (0.00834)
R & [D.sub.i, t] 0.17362 *** 0.28729 *** 0.24531 ***
(0.05076) (0.06089) (0.05821)
[SIZE.sub.i, t] -0.02738 * 0.01943 ** 0.02223 ***
(0.01407) (0.0091) (0.00665)
[LIQ.sub.i, t] -0.00984 0.01342 0.00982
(0.03118) (0.03749) (0.03440)
[LLEV.sub.i, t] -0.00654 0.00768 -0.01778
(0.01449) (0.02009) (0.02344)
[EVOL.sub.i, t] 0.02298 0.01982 0.00783
(0.04415) (0.03844) (0.03223)
[[lambda].sub.i, t] -0.14783 *** -0.13047 *** -0.17005 ***
(0.02873) (0.02534) (0.03228)
CONS 0.02839 ** 0.02773 *
(0.01367) (0.01409)
Wald 156.04 ***
F 81.12 ***
Sargan 38.49 ***
Hansen 126.61
[m.sub.1] -5.32 *** -5.11 ***
[m.sub.2] -0.32 -0.48
Firms 1188 1188 1188
Observations 5940 7128 7128
Notes: Robust Standard Deviations in parenthesis.
2. *** statistically significant at 1% level; "statistically
significant at 5% level; and * statistically significant at 10% level.
3. Estimations include sector dummy variables, but estimated parameters
are not presented in the tables. 4. Estimates include annual dummy
variables, but estimated parameters are not presented in the tables
Table 7. Chow test--determinants of profitability--Young SMEs and Old
SMEs
Independent Variables Dependent Variable: [PFOF.sub.i, t]
GMM system (1998) LSDVC (2005)
([PFOF.sub.i, t-1]) [[delta].sub.
YOUNG]--[[delta].sub.OLD] = 0 22.78 *** 24.55 ***
F(1.9651) (0.0000) (0.0000)
([AGE.sub.i, t]) [[beta.sub.
1YOUNG]--[[beta].sub.10LD] = 0 30.98 *** 28.98 ***
F(1.9651) (0.0000) (0.0000)
(R & [D.sub.i, t]) [[beta.sub.
2YOUNG]--[[beta].sub.20LD] = 0 32.67 *** 30.77 ***
F(1.9651) (0.0000) (0.0000)
([SIZE.sub.i, t]) [[beta.sub.
3YOUNG]--[[beta].sub.30LD] = 0 14 89 *** 11.43 ***
F(1.9651) (0.0000) (0.0000)
([LIQ.sub.i, t]) [[beta.sub.
4YOUNG]--[[beta].sub.40LD] = 0 2454 *** 23.12 ***
F(1.9651) (0.0000) (0.0000)
([LLEV.sub.i, t]) [[beta.sub.
5YOUNG]--[[beta].sub.50LD] = 0 25.99 *** 27.53 ***
F(1.9651) (0.0000) (0.0000)
([EVOL.sub.i, t]) [[beta.sub.
6YOUNG]--[[beta].sub.60LD] = 0 18.58 *** 15.67 ***
F(1.9651) (0.0000) (0.0000)
Global Difference 30.53 *** 31.04 ***
F(7.9651) (0.0000) (0.0000)
Notes: 1. *** significant at 1% level; 2. Probabilities in parenthesis
