MSc in Finance & International Business Authors : Anna Kaja Chudzinska AC70317 Stefan Lukas van der Bijl SV70600 Academic Advisor : Jan Bartholdy, PhD Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe -- An investigation based on the target adjustment model -- Aarhus School of Business September 2007
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MSc in Finance & International Business
Authors:
Anna Kaja Chudzinska AC70317
Stefan Lukas van der Bijl SV70600
Academic Advisor:
Jan Bartholdy, PhD
Capital Structure Determination of Small and Medium Sized Enterprises
in Eastern and Western Europe
-- An investigation based on the target adjustment model --
Aarhus School of Business
September 2007
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl
Abstract
An obligatory note to the reader:
We hereby declare that this MSc Thesis has been produced with the full input of both
authors. From the initial stages of finding a research subject to the analysis and
writing of the research findings, we have cooperated on every single part. No division
in workload has been made, since the full research has been conducted in the presence
of both of us.
Sincerely,
Anna Kaja Chudzinska
Stefan Lukas van der Bijl
This research paper investigates the differences in capital structures and their
determinants between Eastern and Western European Small and Medium sized
Enterprises. The Tradeoff Theory is the underlying theoretical framework which is
applied, therefore the research is based on a detailed analysis of differences in
institutional factors that fit to different aspects of the Tradeoff Theory: credit availability,
corporate taxes, bankruptcy costs and agency costs. The model tested is the target
adjustment model. Data from firms of six countries is used to study the differences in
capital structures between Eastern and Western European firms. The findings support the
hypotheses that differences exist between the two regions, and confirm that firms do have
different financing patterns. Eastern European firms have considerably lower amounts of
debt in their capital structures. These lower leverage ratios in Eastern Europe are found to
be the result of lower corporate taxes and higher bankruptcy costs. This indicates that the
role of shielding taxes is stronger in Western Europe. Besides, although bankruptcy costs
are found to be crucial in capital structure determination in both regions, they are higher
in Eastern Europe, and have a more negative influence on leverage ratios. The research
also confirms that agency costs do not have an important effect on capital structures in
Small and Medium sized Enterprises. The Tradeoff Theory is proven to explain capital
structure determination well on Small and Medium Sized Enterprises in both Eastern and
Western Europe. Besides, the research shows the relevance of improvements in the
financial systems and institutional factors of Eastern European countries.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl
OPERATING RISK is calculated as the standard deviation of Earnings Before Taxes over all years observed until
year t. PROFITABILITY is calculated as Earnings Before Taxes / Total Assets. GROWTH is calculated as the
percentage change of Total Assets in year t-1 to year t. LAGGED LEVERAGE is calculated as the respective
leverage ratio (the dependent variable of the model), in year t-1. Note that the correlation of LAGGED LEVERAGE
with the residuals of the model is removed by including an Instrumental Variable; leverage lagged two periods (t-2).
The dummy variables are qualitative variables with the value 1 if the observation belongs to the group it represents.
Therefore, the shift dummy Western Europe has a value of 1 for a firm from a company in one of the following
countries: Ireland, the Netherlands or Belgium. It has the value 0 if the observation is from a company in any of the
other countries. Similarly, the slope dummy variables are computed by multiplying the shift dummy by the respective
independent variables.
The Target Adjustment Coefficient is derived from model [4] and is computed as: 1 – the coefficient of LAGGED
LEVERAGE.
R² indicates the coefficient of determination, or the explanatory power of the model as a whole. DW statistics show
whether the regression results are affected by autocorrelation. A DW statistic close to 2.0 indicates no autocorrelation.
The number of variables with a Tolerance level smaller than 0,1 indicates whether multicollinearity is apparent in the
regression model. F statistics and their significance show whether a linear relationship between the dependent
variable and any of the independent variables exists, depending what group of independent variables is included in
the F-test.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 56
Table 8 – White-heteroskedasticity adjusted 2SLS results of the Target Adjustment Model, comparing Eastern Europe vs. Western Europe. Eastern Europe serves as the base group.
TOTAL LEVERAGE SHORT TERM LEVERAGE LONG TERM LEVERAGE ADJUSTED TOTAL LEVERAGE
Total Liabilities / Total Assets Current Liabilities / Total Assets Non-Current Liabilities / Total Assets (Total Liabilities - Accounts Payable) / Total Assets
*, ** , *** = significant on the 0.1, 0.05 and 0.01 level of significance, respectively
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 57
The constant terms are highly significant in every regression, meaning that it takes
away variance which is not explained by the independent variables that are included.
From Table 8 and Appendix VII, it can be observed that the R-squared and adjusted
R-squared of all the regressions are very high, especially for the regressions with
Total Leverage and Short Term Leverage as dependent variables. R-squared is the
coefficient of determination, indicating the strength of the model. It is a calculation of
the ratio of the explained variation (called SSE, or the explained Sum of Squares) over
the total variation (called SST, or Total Sum of Squares). This indicates how good the
model predicts the observations. In this research study, the R-squared is the
coefficient that tests for the strength of the target adjustment model. An R-squared of
1 would mean that there is no variation that is not explained by the model. Therefore,
the observed R-squares of approximately 0.87 for the model on Total Leverage and
0.821 for the model on Short Term Leverage seem to indicate that the models explain
almost all of the variation in the data. The observed R-squares of approximately 0.35
for the model on Long Term Leverage and 0.53 for the model on Adjusted Total
Leverage are somewhat weaker, but are still considerably strong. These findings seem
to indicate that the target adjustment model explains capital structure determination of
SMEs in Eastern Europe and Western Europe very well. This seems to be a strong
input for validity of the model: since the model works well, the Tradeoff Theory
seems to hold, and therefore seems to be a valid underlying theoretical framework for
the research study.
Regretfully, one must be very careful when interpreting these relatively high R-
squares. Literature proves that R-squared is not a very useful indicator of the
goodness-of-fit in a Two-Stage Least Squares (2SLS) regression with one or more
instrumental variables. Since the 2SLS regression adjusts the variance of the
endogenous variable so that it does not correlate to the residuals of the model, the R-
squared as the ratio of SSE to SST is not useful, once the SSE has been adjusted.
Therefore, in 2SLS regressions, the R-squared is often left out of consideration, since
it is not a reliable estimator of the strength of the model (Woolridge, 2006). The next
reason for taking R-squares as an unreliable indicator is that in all regressions, the R-
squares is mainly so strong because of LAGGED LEVERAGE. This is shown by its
extreme high t-statistics. If this variable is not included in the regression, the R-
squares drop significantly. Thus, R-squared is not a reliable measure of the strength in
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 58
2SLS models, but rather an indication of the relationship between leverage and
LAGGED LEVERAGE.
Due to the fact that 2SLS regression methods have been applied, it is not possible to
test directly for the strength and applicability of the target adjustment model, hence,
the Tradeoff Theory. Literature suggests another way of indirectly testing whether the
target adjustment model holds. It can be observed that in all models, the target
adjustment coefficients are higher than zero, indicating that firms adjust toward target
debt ratios (Taggart, 1977; Jalilvand and Harris, 1984). The target adjustment
coefficients range from 15 percent in the models of Total Leverage and Short Term
Leverage, and 25 percent in the models og Adjusted Total Leverage, to as high as 73
percent in the models of Long Term Leverage. This indicates that SMEs from the two
regions seem to adjust much faster towards their long term target debt ratios.
The target adjustment coefficients imply that the Tradeoff Theory works. Another
way of testing whether the Tradeoff Theory is indeed a solid model for explaining
capital structure determination, is by analyzing the individual relations among
determinant variables and leverage. An in-depth analysis of these relations will be
presented in the following sections. The findings are concluded in the fifth section, by
controlling for the four hypothesis.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 59
4.2 Difference in Leverage between Eastern Europe and Western Europe
As it was indicated with the descriptive statistics in the data section of this paper, the
averages of the four proxies of leverage are lower in Eastern SMEs than in Western
SMEs. However, these differences are only an indication and do not show the real
significance of these differences.
In order to test the significant difference on the four proxies for leverage between the
Eastern and Western European SMEs, one should look at the constant term and the
slope of the regression model for both regions. The constant terms presented are the
constants for the model of Eastern Europe. These, in relation to the shift dummies for
Western Europe, indicate the constant terms for Western Europe. The shift dummies
indicate the correction to the constant for Western European SMEs, and, therefore,
these give an overview of the difference of constants between the Eastern and
Western European samples studied.
It can be observed that for the model of Total Leverage, the constant is higher in
Eastern than in Western Europe, since the shift dummy for Western Europe is
negative and significant. The same results are observed for the model of Short Term
Leverage. The shift dummies for Western Europe on the models of Long Term
Leverage and Adjusted Total Leverage are positive and significant. These findings
appear to indicate that if all variables have the value of zero, Total Leverage and Short
Term Leverage are significantly higher in Eastern Europe, and Long Term Leverage
and Adjusted Total Leverage are significantly higher in Western Europe. These
differences explain only a part of the differences between leverage in Eastern and
Western Europe. The condition that all other variables have a value of zero is very
unlikely, and, therefore, one should also look at the differences in the slopes of the
models.
Since the slopes exist of all independent variables together, partial F-tests need to be
conducted in order to calculate the cumulative difference of all slope dummy
variables of Western Europe compared to the full model, i.e., Western and Eastern
Europe together. The partial F-test statistics are shown on the bottom of Table 8.
These are measures of the significant difference between the original model and a part
of this model, consisting of multiple variables.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 60
The partial F-statistics are calculated as:
)]1(/[
/)()]1(,[
+−
−=+−
knSSE
rSSESSEF
U
UR
knr [19]
Here, the significance of the F-statistic is calculated on a F-distribution with r and
)1( +− kn degrees of freedom. r is the number of variables dropped (the restricted
part) from the unrestricted model, in this case, all slope dummies for the West. n is
the total number of observations in the model. k is the total number of independent
variables in the unrestricted (full) model. RSSE is the Sum of Squares for Error of the
Restricted model (the unrestricted model minus the r variables). USSE is the Sum of
Squares for Error of the Unrestricted (full) model.
When looking at the F-test statistics for slope dummies, one can see that, indeed, the
linear slopes of the regressions for Western Europe are significantly different from the
slopes of Eastern Europe, for all models (all four leverages). Similarly, F-tests were
computed to help explain the differences of the slope dummies and shift dummy
combined. It is found that the four leverages in Western and Eastern Europe are
highly different from each other indeed. Especially the Long Term leverage is highly
significantly different between the two sample regions.
One limitation of these F-tests is that it cannot be observed from the F-statistic which
region, Eastern or Western Europe, has a higher or lower leverage than the other. The
F-statistics are always positive, and, therefore, the same, whether Eastern Europe is
taken as base group or Western Europe is taken as base group, (see Table 8 and
Appendix VII).
In order to control for the F-tests and to see how the groups are different from each
other the distributions of data of the four proxies of leverage were compared to each
other. This was done by comparing the mean of the distributions of the Eastern
European leverage ratios with the total distribution of the Western European leverage
ratios, and vice versa. This was repeated for each proxy of leverage. T-tests were
calculated to estimate the probability that the leverage proxies of the West fit in the
distribution of leverage proxies of the East. Based on a 99 percent confidence interval,
each data distribution of the four leverages in the East were compared to the mean of
each data distribution of the four leverages in the West. In Appendix VIII the
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 61
outcomes of these T-tests are presented. The positive and significant difference
between all four proxies of leverage for the Western European sample compared to
the Eastern European sample, is confirmed. This indicates that, indeed, the findings of
the F-tests, as described above, are supported.
4.3 Differences in Proxies for Taxes between Eastern Europe and Western
Europe
Three tax proxies are used: KINK, STANDARDIZED KINK and EFFECTIVE TAX
RATE. In order to avoid multicollinearity effects, the three tax variables are used one
at a time. It can be observed that the estimated coefficients and significance levels of
other independent variables do not change much when different tax variable are used.
Also R-squares remain very similar.
Expectations for the Tax Effect
As stated in the hypotheses, it is expected that tax payments should be positively
related to leverage, in both Eastern Europe as well as Western Europe. However, this
relation is expected to be stronger in Western Europe. This is because in Eastern
Europe lower tax rates are observed, which would incline Eastern European managers
less to take on credit, compared to Western European managers. Lower amounts of
tax need to be shielded in Eastern Europe; hence, lower debt levels might be expected.
Besides, lower access to credits and stronger monitoring power by banks might result
in less willingness from banks to lend capital to Eastern European SMEs. Since
reliability on one bank is very high for an Eastern European firm, there are not many
different sources of credit for this firm. Thus, such firms might not have the luxury to
take on debt and optimize their capital structure.
This will mean that for both Eastern and Western Europe, the relation between the tax
variables and leverage are expected to be positive, but this relationship is likely to be
stronger in Western Europe as compared to Eastern Europe. The expected relationship
for the different proxies of leverage follows below.
The tax effect will only work on interest bearing liabilities such as loans, since these
are the liabilities that can shield taxes. The first and second proxy for leverage, Total
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 62
Leverage and Short Term Leverage, contain Accounts Payable, which do not bear
interest. As stated, Total Leverage in both Eastern and in Western Europe consist of
approximately one third of accounts payable. Especially for Short Term Leverage,
accounts payable make up a substantial amount: 43 percent in Western Europe and 37
percent in Eastern Europe, respectively. Besides, it is likely that total liabilities and
short term liabilities contain other non-interest bearing liabilities, such as accruals,
salaries payable and taxes payable etc. Obviously a large extent of Total Leverage and
Short Term Leverage is based on non-interest bearing liabilities.
Long Term Leverage is more likely to contain more interest bearing liabilities since
larger loans are expected to have timeframes of longer than one year. Mortgages are
just one example of such long term loan liability. The last proxy for leverage,
Adjusted Total Leverage, has been adjusted for accounts payable, and hence, contains
less non-interest bearing liabilities. Accordingly, it can be expected that the tax effect,
the relationship between the proxies for taxes and the proxies for leverage, will be
weaker for the proxies Total Leverage and Short Term Leverage, and stronger for the
proxies: Long Term Leverage and Adjusted Total Leverage.
Findings for KINK:
The first proxy for tax, KINK, is expected to be negatively related to leverage, since
the aggressive debt users shield more taxes by taking on extra debt and KINK
approaches 1.0, or for more aggressive debt users even lower than 1.0. Very
conservative users of debt rather take on less debt, even though there are marginal tax
benefits to be gained from taking on additional debt. Their KINK rates will be higher
than 1.0, and may go as high as 8.0. Hence, a firm with a low KINK is expected to be
aggressively shielding taxes by taking on a high degree of credit. Similarly, a firm
with a high KINK is considered to be a conservative tax shielder by having a
relatively lower leverage ratio.
Since the tax effect is expected to be stronger in Western Europe than in Eastern
Europe, a more negative and significantly different relationship between KINK and
leverage (especially Long Term Leverage and Adjusted Total Leverage) is expected
for Western European SMEs when compared to Eastern European SMEs. In Eastern
Europe, either a weak or no relation between KINK and leverage is expected to be
found.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 63
Further evidence from Table 8 and Appendix VII indicates that, indeed, the KINK
variable does not have much, if any, significance on the first two proxies of leverage,
i.e., Total Leverage and Short Term Leverage. For these two proxies of leverage, the
difference between Western and Eastern Europe seems to indicate a somewhat more
negative relationship, but the slope dummies that calculated this difference are far
from significant.
For Long Term Leverage, and to a higher extend Adjusted Total Leverage, one can
see that KINK is highly significant in Eastern Europe, regardless of the low amounts
of long term debt used in this region. However, the relationship is positive. In Western
Europe, one can see the opposite effect between KINK and Long Term Leverage and
Adjusted Total Leverage. In Western Europe, KINK is also highly significant, but
negative. The dummies indicate that the relationship between KINK and these two
proxies of leverage is significantly different between Eastern and Western Europe.
The outcomes for the Western SMEs are partly as expected. However, for the Eastern
SMEs the relationship is contrary to all expectations, and might seem awkward. This
outcome indicates that in Eastern Europe conservative debt users take on more debt
than more aggressive debt users. This finding is illogical and clearly does not make
sense. However, the relationship is highly significant, which means that statistically
this relationship is beyond all doubt. Apparently, it means that the variable KINK
captures effects of variance that it was not intended to test for. A possible explanation
might be found in Rajan and Zingales (1995). They tested several proxies of leverage,
among others the ‘flow’ measure of leverage which they called the interest coverage
ratio. The proxy was calculated as Earnings Before Interest and Taxes, divided by
Interest Expenses. This is the exact same calculation that was used to calculate KINK.
If the interest coverage ratio is indeed a good proxy for leverage, it might seem
obvious that one proxy of leverage is positively and significantly related to another
proxy of leverage, since they both capture part of the same variance.
Apparently KINK works better as a proxy for taxes in Western Europe, although this
relationship is not very strong. KINK and Short Term Leverage are not related,
because of the high amount of non-interest bearing liabilities in this measure of
leverage. The difference between Western and Eastern Europe is partly as expected,
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 64
since Eastern European SMEs not always seem to have the luxury to shield taxes,
simply due to a lack of available long term credits.
If indeed KINK better explains Rajan and Zingales’ (1995) ‘Interest Coverage Ratio’,
than the question might be posed: why does it not do so for Western European SMEs?
Findings for STANDARDIZED KINK:
The STANDARDIZED KINK is the second proxy for the tax effect and, as stated,
also predicts a firm’s aggressiveness or conservativeness in using interest payments as
a tax shield. A positive relation between STANDARDIZED KINK and leverage is
expected, for Western SMEs as well as Eastern SMEs. This, because a firm with low
earnings volatility can more easily be an aggressive debt user, without bearing the
downside risks of having a high leverage ratio and higher interest payments in a
consequent period. Similar to KINK, it is expected that STANDARDIZED KINK will
be more positively related to Long Term Leverage and Adjusted Total Leverage.
STANDARDIZED KINK is not expected to have any effect on non-interest bearing
liabilities, which are more apparent in the first two proxies for leverage. Since KINK
was expected to be lower in Western Europe than in Eastern Europe,
STANDARDIZED KINK is expected to be higher in Western Europe than in Eastern
Europe. That is, it is expected that the risk of volatility of earnings will be smaller in
Western Europe than in Eastern Europe, translating into a higher significant
relationship between STANDARDIZED KINK and leverage.
In Table 8 and Appendix VII one can observe that the STANDARDIZED KINK is
indeed positively related and significant at the highest level of significance with all
four measures of leverage. The coefficients of STANDARDIZED KINK are indeed
higher for Long Term Leverage and Adjusted Total Leverage in both regions. This
finding is exactly as expected. The coefficients of STANDARDIZED KINK on Total
Leverage and Short Term Leverage in Western Europe are not significantly different
from those of Eastern Europe. There is a difference on the 0.1 level of significance
between Eastern and Western Europe in the relationship of STANDARDIZED KINK
and Total Leverage, but this level is not high enough to prove or provide any real
significance. These findings contradict two expectations: STANDARDIZED KINK is
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 65
not weakly related to Total Leverage and Short Term Leverage and the relationship is
not stronger in Western Europe than in Eastern Europe.
What is more surprising, however, is that the relationship between STANDARDIZED
KINK and Long Term Leverage and Adjusted Total Leverage is significantly lower
for Western Europe compared to Eastern Europe. The relationship is positive and
significant in both regions, as expected, but less positive in the West than in the East.
This is contrary to the expectations.
It seems that the STANDARDIZED KINK proves a stronger indicator for the tax
effect in Eastern European SMEs. This means that the role that volatility in earnings
plays on a firm’s debt policy is larger for Eastern European SMEs than for Western
European SMEs. Thus, because Eastern European SMEs have more volatility in their
earnings, the STANDARDIZED KINK is more strongly related to leverage decisions.
Findings for the EFFECTIVE TAX RATE
The EFFECTIVE TAX RATE is the third and last proxy for the tax effect used here.
It is expected to be positively related to leverage. As in the case of KINK and
STANDARDIZED KINK, it is expected to be more positively and significantly
related to Long Term Leverage and Adjusted Total Leverage. Besides, the effect is
expected to be stronger for Western European SMEs than for Eastern European
SMEs.
From Table 8 and Appendix VII it is observed that the EFFECTIVE TAX RATE does
not properly capture the variance explained by taxes, if any exists. It never shows
significance for the Eastern European sample, and it hardly shows significance for the
Western European sample either. Only for Long Term Leverage there is some small
significance (on the 0,05 level), but not enough to base any strong conclusions on.
There is no significant difference between Eastern and Western Europe. For some
proxies of leverage the signs are positive and for some they are negative, but since no
real significance in these relationships exist, it can be concluded that the EFFECTIVE
TAX RATE is not a good indicator of the tax effect.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 66
4.4 Differences in proxies of Bankruptcy and Agency Costs between Eastern
Europe and Western Europe
TANGIBILITY
Expectations for TANGIBILITY
TANGIBILITY might proxy for different effects on leverage. From the Tradeoff
Theory, TANGIBILITY is expected to be positively related to leverage. As described,
firms with higher collateral value have lower potential bankruptcy costs: it would
seem to indicate that for such firms it is optimal to have a higher share of debt in their
capital structure.
Long term liabilities are more likely to be related to fixed assets, since fixed assets
give high relative collateral values to creditors. Also fixed assets normally are in use
for longer periods of time, and therefore act as better insurance for creditors. Property,
plants, equipment, etc. are long term investments and therefore, need long term
financing to match the investments. For these reasons, TANGIBILITY is expected to
be strongest and most positively related to Long Term Leverage. Also for Adjusted
Total Leverage the relationship is expected to be stronger and more positive than for
Total Leverage, since short- term Accounts Payable have been removed. Therefore,
the relation is expected to be weakest and least positive for Short Term Leverage.
The relationship between TANGIBILITY and leverage is expected to be different
between Eastern Europe and Western Europe. It was argued that for emerging
economies, secondary markets for tangible assets may not be deep enough to provide
good value for collateral (Cornelli, 1996). Besides, bankruptcy and liquidation
proceedings might be too slow for creating good value for collateral. Therefore, the
relationship between TANGIBILITY and leverage is expected to be less positive or
weaker in Eastern Europe than in Western Europe.
Findings for TANGIBILITY
From Table 8 and Appendix VII one may conclude that for Total Leverage and Short
Term Leverage a negative and highly significant relationship exists with
TANGIBILITY, in both Eastern as well as Western Europe. For Long Term
Leverage, a positive and significant relationship exists with TANGIBILITY in both
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 67
Eastern and Western Europe. For Adjusted Total Leverage, a significant and positive
relationship exists with TANGIBILITY only in Western Europe. In Eastern Europe,
this relation is not significant.
The findings for Total Leverage and Short Term Leverage are not according to the
expectations, since a weak and positive relationship was expected. The results indicate
a strong and negative relationship to exist. For Long Term Leverage and Adjusted
Total Leverage, the findings are more in line with the expectations, since the
relationship is positive and significant, especially for the Western sample.
The observed differences between Eastern and Western Europe can be summarized as
follows: even though Total Leverage and Short Term Leverage are negatively related
to TANGIBILITY, this relationship is less negative in Western Europe than in Eastern
Europe. Yet this difference is highly significant, especially for Total Leverage. For
Long Term Leverage and Adjusted Total Leverage, one can see that TANGIBILITY
is more positive and significantly different in Western Europe. That is,
TANGIBILITY in the Western European sample is always more positive or less
negative in relation to all proxies of leverage, when compared to the Eastern European
sample. This finding is exactly as expected.
Discussion of (unexpected) findings for TANGIBILITY
It can be observed that the relationship between TANGIBILITY and Long Term
Leverage is very positive and significant for SMEs in both regions. For Western
European SMEs, long term liabilities make up a greater part of Total Leverage than in
Eastern European SMEs. Therefore, it is logical that TANGIBILITY has a more
positive (or less negative) relationship with Total Leverage and Adjusted Total
Leverage. Besides, bankruptcy costs might be lower in Western Europe and therefore,
banks might be willing to lend more funds to Western European SMEs, leading to a
more positive relationship between TANGIBILITY and leverage.
The strong negative relationship between TANGIBILITY and Short Term Leverage is
rather similar in both regions. However, the difference in this relationship between
Eastern and Western Europe is weaker than for the other proxies of leverage. The
strong negative results are clearly not as expected, but have been explained by several
authors. Sogorb-Mira (2005) explained that this relation means that current liabilities
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 68
are used to finance non-fixed assets. Rajan and Zingales (1995) explained that a
possible negative relation might exist because TANGIBILITY can be a proxy for
operating leverage as well. Higher TANGIBILITY might indicate higher operating
leverage (the ratio of fixed to variable costs), which would indicate higher bankruptcy
costs. In this case, TANGIBILITY might be a negative as well as a positive proxy for
bankruptcy costs. This would not explain why TANGIBILITY is found to be
negatively related to Total Leverage and Short Term Leverage and positively related
to Long Term Leverage and Adjusted Total Leverage.
One explanation is that the variable TANGIBILITY catches multiple effects at the
same time. On Total Leverage and Short Term Leverage it works better as a positive
proxy for bankruptcy costs, while on Long Term Leverage and Adjusted Total
Leverage it works better as a negative proxy for bankruptcy costs. However, Booth et
al. (2001) came up with a more convincing argument. Similar to the findings of this
study, they found that for small firms, especially in developing countries, tangible
assets were negatively related to short term debt and positively related to long term
debt. They stated that it was often observed that the more tangible the asset mix, the
higher the long term debt ratio, but the smaller the short term debt ratio. This indicates
that the substitution of long-term for short-term debt is often less than one. That is, as
the tangibility of a firm’s assets increases, by say one percent, although the long-term
debt ratio also increases, the short-term debt ratio falls, and therefore, the total debt
ratio falls as well. This substitution effect of Long Term and Short Term Leverage
might very well be apparent in the two samples presented here, more so in the Eastern
European sample than in the Western European sample. Since it was observed from
the descriptive statistics (see Appendix IV) that Total Leverage consists mostly of
Short Term Leverage in both samples (but more so in Eastern Europe than in Western
Europe), this substitution effect also takes place on Total Leverage.
As previously explained, TANGIBILITY might also act as a (negative) proxy for
agency costs. This is not supported by the findings, since positive as well as negative
signs are identified. Consequently, TANGIBILITY must act as a positive cost
indicator of some kind. Hence, the identified positive relation with Long Term
Leverage and Adjusted Total Leverage can not be explained from the firm’s
perspective. Only from the banks’ perspective an explanation can be found; banks
would simply prefer giving long term loans to safer, more tangible, firms.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 69
TANGIBILITY seems to better capture bankruptcy costs than agency costs, indicating
that, as expected, agency costs between shareholders and managers do not seem to
matter much within SMEs.
The observed differences between the Eastern and the Western European samples in
this relation is quite constant, meaning that the relation is always either more positive
or less negative in Western Europe, compared to Eastern Europe. This indicates that
Cornelli’s (1996) argument might hold. In Western Europe, secondary markets for
collateral are deeper and, therefore, give better value for money. This leads to lower
bankruptcy costs in Western Europe and banks are more willing to lend to Western
European SMEs.
Hall, Hutchinson and Michaelas (2004) argued that in Eastern European countries, the
importance of collateral seemed to be more important in raising long-term debt; this
argument does not seem to be supported since the relations are both very significant
and positive. However, in the Western European sample they are more significant,
thus stronger, and more positive.
SIZE
Expectations for SIZE
Similar to TANGIBILITY, SIZE might be a proxy for several effects as well. From
the Tradeoff Theory perspective, SIZE is a negative proxy for bankruptcy costs. That
is, the bigger the size of the firm, the lower its probability of financial distress and the
lower its expected bankruptcy costs. Since the Tradeoff Theory expects a negative
relationship between leverage and bankruptcy costs, SIZE and leverage are expected
to be positively related.
Besides being a proxy for bankruptcy costs, SIZE might also be a negative proxy for
agency costs. Larger firms have, in general, more diluted ownership. The higher the
separation between ownership and management, the higher the agency costs.
Therefore, the owner(s) might be inclined to increase debt as a control mechanism, so
that management has fewer opportunities for exploiting free cash flow to its own
benefit. In this manner of reasoning, the larger SIZE, the higher the expected leverage,
and the expectation of a positive relation. Since SIZE is expected to be positively
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 70
related to leverage in two ways, it is hard, if not impossible, to distinguish between
both types of relationship from the findings. Note that the second proxy is less likely
to hold, since the analysis is on SME’s, for which most of the firms have relatively
low agency costs between owners and managers.
SIZE is expected not to have a similar impact on all four proxies of leverage. Similar
to TANGIBILITY, SIZE is expected to have the strongest positive impact on Long
Term Leverage. This is, since long term loans are more risky investments from the
banks’ perspective, and safer, bigger firms are preferred. Similarly, from the agency
cost perspective, long term liabilities are stronger control devices than short term
liabilities and therefore, will be most directly related to SIZE. Short Term Leverage is
expected to have a weaker and less positive relationship with SIZE, since SIZE is
expected to matter less for generating short term (lower risk) loans and payables. The
findings on the relationships between SIZE and Total Leverage and Adjusted Total
Leverage are expected to fall in between these two.
The expected differences for Eastern Europe and Western Europe are as follows.
Since the focus lies on SMEs, which are by definition relatively small, SIZE plays a
major role in attracting funds, in both regions. However, since the availability of
credits is expected to be smaller in East, SIZE is expected to be a more important
determinant of attracting credits from banks in this region. As indicated, a positive
relationship between SIZE and LEVERAGE is expected. However, since bankruptcy
and agency costs are expected to be lower in Western Europe, the coefficients of the
relationships on all four proxies of leverage are expected to be more positive for the
Western European sample (indicating lower bankruptcy and agency costs) than for the
Eastern European sample.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 71
Findings for SIZE
Table 8 and Appendix VII indicate that for Eastern European SMEs a negative and
significant relation exists between SIZE, Total Leverage and Short Term Leverage.
However, for Western European SMEs no significant relation among SIZE and these
two proxies of leverage is found.
For Long Term Leverage, a positive and highly significant relation exists for both
regions. For the Adjusted Total Leverage, only in Eastern Europe does a positive and
significant relation exist, while in Western Europe no relation is apparent with
Adjusted Total Leverage.
For the Western European sample, these findings are more or less in accordance with
expectations: the strongest and most significant relationship exists for Long Term
Leverage, while for the other proxies of leverage no clear relationship is observable,
since there is no significance in these findings.
For the Eastern European sample, only the positive and significant relationships
between SIZE and Long Term Leverage and the Adjusted Total Leverage are as
expected. However, the negative and significant relationships among SIZE, Total
Leverage and Short Term Leverage, are not as expected.
Another expectation that is supported by these findings is that the relationship
between SIZE and all leverages is stronger for the Eastern European sample. The t-
statistics and thus significance levels are always higher for the Eastern European
sample than those of the Western European sample. The difference in the relation of
SIZE on leverage between Eastern and Western Europe is highly significant on all
proxies of leverage. However, for Total Leverage and Short Term Leverage, the
relations are significantly more positive in Western Europe, while for Long Term
Leverage and Adjusted Total Leverage, the relationships are significantly more
negative in Western Europe. Yet, since most signs of coefficients in the Western
sample are not significant, the strong differences in relationships between Eastern and
Western Europe might be misleading.
Discussion of (unexpected) findings for SIZE
It has been demonstrated that SIZE matters more for Eastern European SMEs in order
to get credits. The relationships found are much more significant in Eastern Europe
than in Western Europe. However, for Short Term Leverage, the relationship with
SIZE proved negative. Since Total Leverage exists for the majority (around 90
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 72
percent) of Short Term Leverage, it is obvious that this same effect takes place on
Total Leverage as well. This negative relation is clearly not explained by the
bankruptcy cost and agency cost theory.
It can be further observed that for the Adjusted Total Leverage, the signs are positive
and significant, as expected. The only difference between the Adjusted Total
Leverage and Total Leverage is the Accounts Payable that have been removed from
Total Leverage. Since the signs of the relationship between both proxies of leverage
changes, it is certain that Accounts Payable have a profound influence on the
relationship. Indeed, one can observe that in both regions, accounts payables make up
a large part of Short Term Leverage and similarly Total Leverage. SIZE would
therefore be negatively related to Accounts Payable. This would indicate that small
firms rely more on trade credits (Accounts Payable) in their capital structure, and less
on other sources of credit. The bigger the size of the firm, the lower its reliance on
trade credits, and the higher its reliance on other (preferably longer term) sources of
credits, such as loans. Therefore, if a firm grows in size, it might want to lower its
accounts payables by substituting other types of debt. In that case, a negative
relationship would exist between SIZE and accounts payables, which is translated into
a negative relationship with Short Term Leverage and even into Total Leverage, due
to the heavy reliance on short term liabilities (and thus payables) of the Eastern SMEs.
This effect is present only in the Eastern European sample, and this unexpected effect
might further result in a lower availability of credit to small firms in Eastern Europe.
Since insufficient credits are available, small firms in this region might need to rely on
trade credits to a higher extent. Because of higher bankruptcy costs in Eastern Europe,
banks might be less willing to lend to firms with high amounts of trade credits. In this
case, Eastern European SMEs might seek to reduce their trade credits, relative to other
sources of debt, whenever possible, e.g. after growing in size.
In sum, the research results point toward SIZE being a good proxy for bankruptcy
costs (or agency costs) on long term debt in both regions, but in Western SMEs, SIZE
hardly plays a role on the other proxies for leverage. The differences in the
relationship of SIZE and leverage between Eastern and Western Europe are found to
be inconclusive.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 73
Z-SCORE
Expectations for Z-SCORE
In contrast to the variables described above, Altman’s general Z-SCORE is simply a
proxy for one effect, the bankruptcy effect. As previously noted the Z-SCORE is an
indicator of financial distress. The higher the Z-SCORE, the higher the chance of
bankruptcy, and the higher bankruptcy costs. Therefore, from the tradeoff perspective,
a negative relation between Z-SCORE and leverage is expected. Once again, this
relation is expected to be negative and strongest with Long Term Leverage since long
term debts are more risky investments from the banks’ perspective and require low
bankruptcy costs. The relationship is expected to be least negative for short-term
liabilities. Inasmuch as Total Leverage and Short Term Leverage contain a large
quantity of Accounts Payable, which are not expected to be related to the Z-SCORE,
the relationship for these proxies is expected to be weaker.
Also since bankruptcy costs in Western Europe are expected to be smaller than those
for Eastern Europe, the relationship is expected to be more negative in Western
Europe than in Eastern Europe.
Findings for Z-SCORE
The Z-SCORE is negatively and significantly related to all four proxies of leverage, in
Eastern Europe as well as in Western Europe. This is exactly as expected. The
relationship is very strong for all measures of leverage, indicating that the expectation
of the Z-SCORE being weaker when related to Short Term Leverage is rejected. Both
in Eastern and in Western Europe, the Z-SCORE’s are even stronger as related to
Short Term Leverage and Total Leverage. This finding is contrary to expectations.
The differences between Eastern and Western Europe in the relation of the Z-SCORE
and leverage are unanimous. In Western Europe, the relation is always more negative
than in Eastern Europe, and this difference is always highly significant.
Discussion of (unexpected) findings for Z-SCORE
The findings for the relation of the Z-SCORE and leverage are to a great extent in line
with expectations, in both Eastern and Western Europe. This demonstrates that the Z-
SCORE is a good proxy for bankruptcy costs for SMEs in both regions of this study.
The results are most negative with Total Leverage and Short Term Leverage in both
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 74
regions, indicating that the Z-SCORE proxies bankruptcy costs for Short Term
Leverage very well. The significant difference between Eastern and Western Europe,
indicating a more negative relationship between the Z-SCORE and all leverages in
Western Europe, clearly proves that bankruptcy costs are lower in Western Europe,
which makes creditors more willing to lend to SMEs in this region.
The strong results do not only indicate that bankruptcy costs matter for banks that
lend long term, but are an important determinant for banks in lending short term as
well. This conclusion is supported by the finding that the differences for the Z-
SCORE are also significant and negative for Short Term Leverage in the Western
European sample. Bankruptcy costs are clearly lower in Western Europe, as indicated
by the Z-SCORE.
OPERATING RISK
Expectations for OPERATING RISK
As stated prior, OPERATING RISK is a proxy for bankruptcy costs only. The higher
the OPERATING RISK of a firm, the higher the probability of distress. A firm with
high bankruptcy costs is most likely to receive lower or no credits from a bank, thus a
negative relation is expected between OPERATING RISK and leverage.
Similar to the other variables above, the relation is expected to be most negative and
strongest with Long Term Leverage, since banks are expected to be most reluctant to
lend long term to firms. Similarly, the relation is expected to be less negative for Short
Term Leverage.
The expected difference between Eastern and Western Europe is that in Western
Europe the relations are expected to be more negative than in Eastern Europe, since
bankruptcy costs in general are expected to be smaller, which might cause banks to be
less reluctant in financing risky firms in Western Europe.
Findings for OPERATING RISK
It can be observed that the coefficients of OPERATING RISK are all extremely low,
approaching zero, while being significant in relation to some of the proxies of
leverage. This might be due to the extreme values of OPERATING RISK, as depicted
in the descriptive statistics of Table 7. Contrary to all expectations, OPERATING
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MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 75
RISK is found to be positively related to all proxies of leverage in the Western
European sample. In Eastern Europe, only one negative and significant relationship is
found between OPERATING RISK and Long Term Leverage and one positive
significant relation with Adjusted Total Leverage. Most of the results are
contradictory to expectations. OPERATING RISK is in most cases positively related
to leverage, instead of negatively. This is especially so for the Western European
sample. Instead of finding a more negative relation in Western Europe, a significantly
more positive relation is found, compared to Eastern Europe.
Discussion of (unexpected) findings for OPERATING RISK
Even though most findings show positive relations between OPERATING RISK and
leverage, a negative relation is found with Long Term Leverage in Eastern Europe.
This finding is according to expectations, and indicates that indeed in Eastern Europe
bankruptcy costs are highest. It also shows that bankruptcy costs matter most on Long
Term Leverage. Besides, when looking at the differences between Eastern and
Western Europe, one can see that in Eastern Europe the relations are always
significantly less positive, indicating a stronger bankruptcy cost effect to exist, and
hence, higher bankruptcy costs.
The most striking finding is the positive relations of OPERATING RISK with all
proxies of leverage in Western Europe, and with some proxies of leverage in Eastern
Europe. These relations do not seem to indicate a bankruptcy cost effect and have not
been described in literature. A possible explanation is that volatile firms have a bigger
need for credits, as operational buffers, meaning that a firm might keep extra credits
in order to absorb shocks in its cash flows. If the explanation is indeed due to such
buffers, it seems that in Western Europe these are not or hardly based on short term
debt, nor on Accounts Payable. The most significantly positive relation is with
Adjusted Total Leverage, in both regions, which might indicate that a greater
preference exists for stable sources of credit.
It can be questioned how volatile firms are able to attract such credits, since banks
will not easily extend credits to a firm facing high financial distress. Because of more
positive relations between OPERATING RISK and leverage in Western Europe, it
seems that Western European firms have more ease in collecting such credits, thus
indicating that overall bankruptcy costs are lower in Western Europe.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 76
PROFITABILITY
Expectations for PROFITABILITY
PROFITABILITY can be a proxy for both bankruptcy and agency costs. Highly
profitable firms generate higher cash flows than less profitable firms. Probability of
default is expected to be lower in profitable firms, and thus bankruptcy costs are
lower. Banks are more willing to invest in profitable firms, and thus according to the
bankruptcy cost theory, the expected relationship between PROFITABILITY and
LEVERAGE is positive. As stated, according to Jensen (1986), PROFITABILITY
also serves as a proxy for agency costs between shareholders and managers.
Generations of high cash flows in the firm may encourage managers to invest in
negative Net Present Value projects or to “build empires”. In this case, higher levels
of debt serve as a control device and reduce the possibility of management abuse of
shareholders funds. This argument also suggests a positive relation between
PROFITABILITY and LEVERAGE. Another argument from the agency cost theory
is that PROFITABILITY is considered to be a proxy for information asymmetry.
Here, the firms prefer internal financing over external financing, as is explained by the
Pecking Order Theory. More profitable firms are expected to have lower amounts of
debt than less profitable firms, and thus a negative relation between
PROFITABILITY and leverage is expected.
Again, the relationship of PROFITABILITY to LEVERAGE is expected to be
strongest with Long Term Leverage for all proxies. From the bankruptcy cost point of
view, long term debt is the most risky investment for banks. From the agency cost
point of view, long term debt serves as the strongest control device over management,
and because of its duration, long term debt is a more risky commitment for the firm.
As already noted, agency costs in SMEs are expected to be weak, or not apparent.
Thus, the findings are expected to be in line with the bankruptcy cost theory and only
a positive relation of PROFITABILITY with leverage is expected. PROFITABILITY
is expected to be more positively related to leverage in Western Europe because
bankruptcy costs in general are expected to be lower in Western Europe than in
Eastern Europe.
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MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 77
Findings for PROFITABILITY
Contrary to the expectations, in the Western European sample the results indicate a
strongly negative relationship between PROFITABILITY and all types of
LEVERAGE. The same results are found in Eastern Europe, although only Long
Term Leverage is positively related to PROFITABILITY. The other three proxies of
LEVERAGE are negative and significant.
The relationship between PROFITABILITY, Total Leverage, and Short Term
Leverage is significantly more negative in Eastern Europe than in Western Europe.
However, the relationship between Long Term Leverage and Adjusted Total Leverage
proves significantly more positive in the Eastern European sample than in the Western
European sample.
Discussion of (unexpected) findings for PROFITABILITY
The findings in the Western European sample clearly contradict the expectations
based on the bankruptcy and agency costs, in light of the Tradeoff Theory. The
negative relation of PROFITABILITY with LEVERAGE are in line with the Pecking
Order theory, in which more profitable firms in Western Europe prefer internal
financing over external financing. A true Pecking Order, as described by Myers and
Majluf (1984) and Myers (1984) is very unlikely to exist in privately held SMEs,
since private firms cannot easily issue equity as a form of external capital. An
‘adjusted’ Pecking Order might, however, exist, in which the choice is merely
between internal funds and credit (Nguyen & Ramachandram, 2006). A negative
relationship between PROFITABILITY and LEVERAGE might thus indicate that a
firm prefers internal funds over external funds, since these are cheaper. Such ‘Pecking
Order’ findings are strongest in Eastern Europe for Total Leverage and Short Term
leverage. According to Cornelli (1996) the loan conditions in emerging markets are
not attractive and require high interest payments, especially for short term loans.
Thus, in Eastern Europe, cheap internal funds combined with expensive loan
conditions, often result in profitable firms becoming less likely to take external loans,
since they can afford to finance the investments from internal sources. Consequently,
only less profitable firms will use external financing (with high interest rates) as these
firms do not have the “luxury” of choosing between internal and external financing. It
seems that in Eastern Europe, PROFITABILITY also works as a proxy for bankruptcy
costs, since on Long Term Leverage the relation is positive. Apparently, banks in
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 78
Eastern Europe are only willing to lend long term loans to highly profitable firms, in
order to reduce their risks. This effect also seems to take place in Western Europe, but
to a smaller extent than in Eastern Europe. The relationship between
PROFITABILITY and Long Term Leverage is less negative than for the other three
proxies of LEVERAGE, indicating that the bankruptcy cost effect plays some role.
However, in Western Europe, the negative effect of internal financing is still stronger.
The findings clearly illustrate that bankruptcy costs play a bigger role in Eastern
Europe than in Western Europe.
GROWTH
Expectations for GROWTH
GROWTH is a proxy for bankruptcy costs as well as agency costs.
When looking at GROWTH as a proxy for bankruptcy costs, a positive relation with
all four proxies of LEVERAGE is expected. High growth firms are an indication of
safer investments to the banks, and, therefore, results in lower bankruptcy costs.
GROWTH might also indicate growth opportunities, which is considered a proxy for
agency costs between shareholders and management. Growth opportunities as a proxy
for agency costs has a relationship with leverage that is expected to be negative. Yet,
growth opportunities need to be financed by extra amounts of debt. Since more debt
requires higher amounts of interest payments, management may pass on profitable
investments, and use most of the firm’s cash flow for financing debt.
According to the agency costs theory, GROWTH might also be a good proxy for
information asymmetry between shareholders and creditors. Fast growing firms have
a bigger potential of risk shifting, thus a negative relation between LEVERAGE and
GROWTH is expected. From the bankruptcy cost theory perspective, GROWTH is
expected to be most strongly related to Long Term Leverage, and least related to
Short Term Leverage, for the reasons discussed above. Long Term Leverage is a more
risky investment for banks and, therefore, stronger growth is needed to offset this risk.
From the agency cost perspective, GROWTH might be strongest when related to
Short Term Leverage as well as Long Term leverage, depending on which agency
cost reasoning is applied. On average, interest costs are higher on short term debt
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 79
which would increase the probability of underinvestment. In this case, the strongest
negative relationship will be found between GROWTH and Short Term Leverage. On
the other hand, risk shifting might be possible with long term debt, which would
assume a stronger negative relationship between GROWTH and Long Term
Leverage.
There are different expectations for Eastern and Western European SMEs regarding
the relationship of GROWTH and LEVERAGE. As bankruptcy costs are expected to
be lower in Western Europe, when GROWTH works as a proxy for bankruptcy costs,
the relationship is expected to be more positive in Western Europe than in Eastern
Europe. In regards to agency costs, a less negative relationship is expected to be
observed in Western European SMEs. In general, agency costs are expected to be
lower in Western Europe. However, as agency costs and information asymmetries
between management and shareholders are less likely to exist in SMEs it is expected
that GROWTH as a proxy for agency costs will not be found or will not be
significant. Therefore, a relationship between GROWTH and LEVERAGE is
expected to be in line with the expectations from the reasoning of the bankruptcy cost
theory.
Findings for GROWTH
Looking at Table 8 and Appendix VII, one can see that the relationship of GROWTH
with all proxies of leverage is positive, in both Western and Eastern Europe. This
observation is consistent with the expectations based on the bankruptcy theory. In
Eastern Europe, the relations are significant to the highest extent in all four proxies of
LEVERAGE. In Western Europe, the relations also indicate high significance in Total
Leverage and Short Term Leverage, but lower significance in Long Term Leverage
and Adjusted Total Leverage. These weaker results in Western Europe may be due to
lower bankruptcy costs in this region and better access for SMEs to long term credits,
as compared to SMEs from Eastern Europe. SMEs in Western Europe do not
necessarily have to indicate high growth rates in order to receive long term credit. In
Eastern Europe, however, high significance between GROWTH and Long Term
Leverage and Adjusted Total Leverage confirms that growth firms are better able to
obtain external financing, and thus that banks are risk avoiding. This is a indication of
higher structural bankruptcy costs in Eastern Europe.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 80
Discussion of (unexpected) findings for GROWTH
The research expectations on Eastern and Western Europe suggest that a more
positive relationship between GROWTH and LEVERAGE is to be expected in
Western Europe because of lower expected bankruptcy costs. The results, however,
indicate just the opposite. Reasons for this are as follows: the importance of firm’s
growth rates for banks in Eastern Europe is higher than in Western Europe and thus
banks value growth rates more in Eastern Europe. Banks in Eastern Europe view
lending to growing firms as a safer investment: bankruptcy costs are expected to be
lower in Western Europe, and banks have a lower need for good growth figures as an
insurance of loan repayment. Besides, Serria-Allende and Zaidi (2006) concluded that
high growth firms need more external financing, especially long term credits in order
to keep on growing. The strong relationship between GROWTH and LEVERAGE
comes from the bankruptcy cost theory reasoning. Agency costs between management
and shareholders, and information asymmetry between shareholders and banks, do not
appear to exist in European SMEs. This is according to the expectations.
4.5 Conclusions of the Results in Eastern Europe and Western Europe
LEVERAGE IN EASTERN AND WESTERN EUROPEAN SMEs
Descriptive statistics in the data section gave an indication that all four proxies of
leverage are lower in Eastern than in Western European SMEs. In order to check
whether the differences between the proxies of leverage are indeed statistically
significant, F-tests were conducted. These indicated that indeed, all leverage ratios in
Western Europe are significantly different from the leverage ratios in Eastern Europe.
T-tests were calculated to test whether these differences occur in the predicted
direction. These clearly show that the four different leverage variables in Eastern
Europe are lower then in Western Europe.
Consequently, Hypothesis 1 is confirmed, since all four proxies of Leverage are
higher in Western European SMEs than in Eastern European SMEs.
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MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 81
INFLUENCE OF TAX ON LEVERAGE:
The research findings on the different proxies for the tax effect are not completely
conclusive. The findings on KINK indicate that in Western European SMEs, KINK
has a negative influence on Long Term Leverage and Adjusted Total Leverage. On
Total Leverage and Short Term Leverage, tax does not seem to have much influence
in this region, although it was expected that some, minor, relation would exist. In the
Eastern European SMEs, KINK does not seem to explain LEVERAGE in the
expected directions, and therefore, does not seem to work well. These findings do not
clearly demonstrate that KINK is a good proxy for tax, but they do show that KINK
works better as a proxy for tax in Western Europe than in Eastern Europe. Tax
shielding is more apparent in Western Europe than in Eastern Europe, especially with
long term credits and non-working capital items. This in turn, provides some evidence
that indeed in Western Europe, where corporate tax rates are higher, shielding taxes
with credit is a more profound activity.
The findings on STANDARDIZED KINK indicate that the risk of shielding taxes
plays a significant role on capital structures in both regions and on all proxies of
LEVERAGE. This relationship is similar in the two regions on Total Leverage and
Short Term Leverage, but different for Long Term Leverage and Adjusted Total
Leverage. The risks of tax shielding play a smaller role on longer term debt financing
in Western Europe, as compared to Eastern Europe. It can be concluded that, all else
equal, such tax shielding risks are just lower in Western Europe. Lower risk of tax
shielding explains the stronger activity of tax shielding in Western Europe, as
observed before. Namely, the relation between KINK and Long Term Leverage and
Adjusted Total Leverage indicates that tax shielding is only apparent in Western
Europe. Lower risk of tax shielding might give extra proof for tax shielding only to be
apparent in Western Europe.
The variable EFFECTIVE TAX RATE does not seem to play any role in SME’s
capital structures in neither the Eastern nor the Western European sample. Since
KINK and STANDARDIZED KINK do seem to indicate a relationship with leverage,
it is most likely that the construction of the variable EFFECTIVE TAX RATE is
weak. That is, this variable does not capture any variance explained by the tax effect.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl 82
From these conclusions, Hypothesis 2 is partly confirmed. Taxes have a positive
influence on (Long Term) Leverage in Western Europe, and the influence of taxes
is higher for Western European SMEs than for Eastern European SMEs. The tax
effect does play a clear role in Western Europe (but only on Long Term Leverage),
but not in Eastern Europe.
INFLUENCE OF BANKRUPTCY COSTS ON LEVERAGE:
The two variables that solely proxy for bankruptcy costs, the Z-SCORE and
OPERATING RISK, indicate bankruptcy costs to be an important determinant of
LEVERAGE in both Eastern European SMEs and Western European SMEs.
Particularly the Z-SCORE demonstrates a very strong and negative relationship with
all proxies of LEVERAGE, indicating that bankruptcy costs play a strong role on
SMEs capital structures in both regions. The findings on OPERATING RISK are
harder to interpret, since the signs are contradictory to expectations on most proxies of
LEVERAGE in both samples. However, as expected, OPERATING RISK is
positively and significantly related to Long Term Leverage in Eastern Europe. This is
not the case in Western Europe and thus indicates that bankruptcy costs play a bigger
role on Long Term Leverage in the Eastern European SMEs.
Other variables that can be proxy either for bankruptcy costs or agency costs prove to
be better proxies for bankruptcy costs in both samples. This is especially the case in
relation to Long Term Leverage, and to a lesser extent to Adjusted Total Leverage
(which consists mostly of Long Term Leverage).
TANGIBILITY is negatively related to Total Leverage and Short Term Leverage;
however, it shows positive relations with Long Term Leverage and Adjusted Total
Leverage in the Eastern European sample as well as in the Western European sample.
This relation, however, is stronger in Western Europe. Similarly for SIZE, even
though in Eastern Europe SIZE is negatively related to Total Leverage and Short
Term Leverage, SIZE indicates positive relationships with Long Term Leverage and
Adjusted Total Leverage. The same is true, but to a lesser extent in Western Europe.
PROFITABILITY is in both regions negatively related to all proxies of leverage,
except for Long Term Leverage in Eastern Europe. This, again, indicates higher
bankruptcy costs in Eastern Europe. Finally, GROWTH is found to be a much
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stronger proxy for bankruptcy costs than for agency costs, where it is always
positively related to all proxies of leverage, but strongest in the Eastern European
sample.
All above findings on bankruptcy costs clearly point out that bankruptcy costs matter
on capital structure determination of SMEs in both Eastern and Western Europe.
Bankruptcy costs, therefore, have a negative influence on leverage. Most variables
studied point towards bankruptcy costs being a more important issue in Eastern
European SMEs, further indicating that bankruptcy costs are considered to be
generally higher in Eastern Europe. Consequently, banks might be more reluctant to
lend to SMEs in this region. As expected, such reluctance holds particularly true in
the case of long term debt financing, as found in the study results.
From these conclusions, Hypothesis 3 is confirmed: bankruptcy costs are negatively
related to leverage, especially Long Term Leverage, in Western and Eastern
European SMEs. This relation is stronger in Eastern Europe where bankruptcy
costs are more negative.
INFLUENCE OF AGENCY COSTS ON LEVERAGE:
As described in the above section, most variables that might either proxy for agency
costs or bankruptcy costs seem to work better as bankruptcy cost indicators, since the
results have the expected bankruptcy proxy signs. For example, GROWTH works
better as a bankruptcy proxy for both Western and Eastern European SMEs. However,
some variables show relationships with proxies of leverage in the directions expected
from the agency costs theory. In all cases, other factors might explain these relations.
The positive relationship between TANGIBILITY and Long Term Leverage and
Adjusted Total Leverage in both Eastern and Western Europe, could be indicative of
agency costs working as a determinant of SME capital structure. This is unlikely
however, since these positive relations fit better with the bankruptcy cost theory, and
are supported by the stronger findings for other bankruptcy proxies on Long Term
Leverage and Adjusted Total Leverage.
The variable that clearly shows findings that are strongly in line with the agency cost
theory, is PROFITABILITY. The strong negative relationship between
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PROFITABILITY and most proxies of leverage is a possible confirmation of an
agency cost effect, from the information asymmetry perspective. However, as stated,
other external forces might be underlying this effect, making it appear that an
‘adjusted’ pecking order of financing exists. The negative relations between
PROFITABILITY and leverage are strongest in Eastern Europe, which might indicate
that the availability of credit is lower, and conditions of debt contracts are worse.
Instead of having a formalized ‘pecking order’, SMEs in Western Europe and
especially those in Eastern Europe might not have the luxury of choosing between
different sources of finance, and, therefore, they might need to primarily rely on
internally generated cash. This would not contradict the Tradeoff Theory, but would
only limit it to a certain extent. Since SMEs have mostly combined management and
ownership, severe agency costs are unlikely to be existent.
Except for PROFITABILITY, no variable shows any evidence of agency costs to be
apparent. This, in combination with the likelihood that the negative relation for
profitability is caused by other, institutional factors for SMEs, makes it appear that
agency costs are not strong in both samples, exactly as was expected.
From these conclusions, Hypothesis 4 is partly confirmed: no clear, undisputed,
effects for agency costs are found in either of the regions. Consequently, agency
costs seem to be non-existent for Small and Medium sized Enterprises.
Since the four hypotheses have been confirmed, it can be stated that the Tradeoff
Theory works well as an explanatory theory of capital structure on SMEs in Eastern
Europe as well as Western Europe. It was identified above that the target adjustment
coefficients already indicated this theory to be valid. The individual relations between
the determinants of leverage, and leverage itself, are in the directions as predicted by
the Tradeoff Theory. This strengthens the observations from the target adjustment
coefficients, and implies that the target adjustment model, hence the Tradeoff Theory,
is a good underlying theoretical model for testing the differences between Eastern and
Western European SMEs. This, in turn, adds strength to the conclusions as stated
above.
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4.6 Robustness Check
In Appendix IX an extensive Robustness Check is presented which serves to control
the approach that has been applied in this Chapter. Its purpose is to check for the
robustness of the results and conclusions of this study. In the previous section the
hypotheses have been controlled for. This was done by analyzing the differences
between Eastern and Western Europe based on leverage ratios and the relationships
between different proxies of leverage and independent variables of the model. These
findings have been linked to the expectations that were formalized. By comparing the
findings (relationships between variables) with the expectations, the hypotheses were
controlled for.
In a similar way country differences can be studied. This will yield numerous
interesting results to this research. Namely, it will be possible to check to what extent
SMEs from different countries are similar or different from each other, based on the
relationships between proxies for leverage, tax, bankruptcy costs and agency costs.
Since the focus of this research is to compare Eastern European SMEs with Western
European SMEs, such country comparisons are not a necessity to answer the Research
Question and to control the Hypotheses, as is done in the previous section. A very
important benefit of including this extra research is to see whether the methodology
which was applied to test the hypotheses, is valid. Namely, in a similar fashion
country differences can be detected, analyzed, and compared to expected country
specific factors. Such a country study therefore serves as a robustness check to the
research of Eastern European SMEs and Western European SMEs. A country specific
comparison will help to prove whether the resources that were used, the expectations /
hypotheses which were formalized, and the comparisons which were done, are valid.
The conclusions from the previous section, based on the expected regional differences
and regression results, are only valid if the results are indeed caused by such regional
differences, and not by possible other factors that have not been taken into account in
this study. It is not the purpose here to identify such possible other factors, but merely
to test whether the existence of possible other factors can be excluded.
The Robustness Check of Appendix IX is based on the exact same methodology as
was applied in the previous sections. SMEs from the three countries from the Western
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European sample (Ireland, the Netherlands and Belgium) are studied in comparison to
each other. Similarly, SMEs from the Eastern European sample (Poland, Hungary and
Ukraine) are studied and compared to each other. Data from SMEs in these six
countries is available, since the exact same data was used before, in the study of
Eastern Europe versus Western Europe.
All details of these country analyses are described in Appendix IX, including the
output of the regression analyses. The approach of testing is similar as was done for
the regional tests. First, expectations on findings for each country under study were
constructed, based on the country scores that are presented in Appendix II. Second,
the expectations regarding country differences were made, also based on these
country scores. Third, these expectations were compared to the actual 2SLS
regression results. The regression output is more extensive than for the study of
Eastern Europe and Western Europe, and therefore besides Appendix IX, further
output is presented in Appendix X and Appendix XI. This, since country comparisons
are again made by using dummy variables for countries. For this reason, basegroups
need to be changed, and since the analysis is on six countries instead of only two
regions, there is more output to be presented.
The last stage in the Robustness Check is to dicuss the findings, after they are linked
to expectations.
In the following part of this section, a short summary of the findings and the
implications of the Robustness Check are described.
In both the Western and Eastern European countries, the findings for proxies of tax
are, to a large extent, in line with expectations. None of the proxies for tax seem to
play a significant role in the Irish and Hungarian SMEs; the tax rates have been low in
these countries and it was expected that tax will not have an influence on leverage. In
the Netherlands and Belgium, where corporate tax rates are higher, KINK has an
influence on Long Term Leverage and Adjusted Total Leverage. STANDARDIZED
KINK was found to be the best proxy for tax and is highly significant on all four types
of leverage in the Netherlands and Belgium. Also, according to expectations, country
dummies did not detect significant differences between tax effects on leverage
between Belgium and the Netherlands but these differences exist when comparing
these two countries to Ireland. In Eastern European countries, the tax effect was found
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to be strong in Poland and Ukraine, especially while using the STANDARDIZED
KINK variable. The differences detected by country dummies among Eastern
European countries are not conclusive – this may be caused by factors that are not
included in country scores, for example weaker capital markets in Ukraine.
The analysis of the variables that proxy bankruptcy costs revealed that these costs are
a very important determinant on capital structure in every country studied in this
research. The findings were strong, especially for Long Term Leverage, which might
indicate that, indeed, bankruptcy costs are most important in lending and borrowing
for long periods of time. In Eastern European countries the findings on Z-SCORE,
GROWTH, TANGIBILITY and SIZE confirmed that bankruptcy costs are highest in
Ukraine and lowest in Hungary, especially on Long Term Leverage. In Western
European countries, Z-SCORE was negative and significant in every country and
dummy variables did not detect any difference among the countries.
Agency costs in SMEs from Eastern and Western European countries do not have any
strong impact on capital structure. This is in line with the expectations, since SMEs
often do not have dispersed ownership and are often owner-managed. Besides, banks
seem to solve agency costs themselves, by keeping close relations with SMEs and by
lending predominantly short term. The negative signs in GROWTH indicate that
agency costs do exist in Dutch SMEs, but only to a small extent. This is in line with
the country scores on corporate governance. The findings for Ireland and Belgium
indicate that agency costs are lower or nearly non-existent in leverage determination.
This is in line with the country scores as well. However, the country scores on
corporate governance are more applicable to large public firms; thus, findings are not
conclusive enough to state that agency costs exist within Dutch SMEs. In Eastern
European countries, none of the variables fully point towards expected signs for
agency costs.
From the above differences in corporate taxes, bankruptcy costs, agency costs and
access to credit, expectations were formed on differences in leverage ratios. These
expectations were compared to the F-tests and T-test statistics on observed differences
in leverage ratios. In Western Europe, it turned out that leverage ratios in Ireland were
considerably lower than in Belgium and the Netherlands, due to the much lower
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
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corporate tax rates, and hence lower marginal benefits to shield taxes. In Eastern
Europe, it was found that leverage ratios were highest in Hungary, followed by Poland
and lowest in Ukraine. This was because of low availability of credits in Ukraine and
better access to credits in Hungary.
It turned out that the tested differences in leverage ratios between the countries, are
perfectly in line with the expected, and tested differences in taxes, bankruptcy costs,
and access to credit. Agency costs did, indeed not play any significant role.
Since all the expectations were confirmed, the robustness check proved that the
approach that has been used in this research detects the main characteristics of SMEs’
leverage determination and country differences. This shows that country scores are
indeed a good basis for this research. It is therefore found that the methodology which
is applied, is valid for the analysis of all countries. Hence, it can be concluded that this
approach is also valid for testing differences and similarities between the two regions:
Eastern Europe and Western Europe, since the expectations are based on the country
scores. This Robustness Check thus presents more evidence that indeed the observed
differences between SMEs from Eastern Europe and Western Europe are due to
institutional differences in respect to credit availability, corporate tax rates and
bankruptcy costs. Agency costs are not found to have a clear impact on SME capital
structure in Eastern Europe as well as Western Europe.
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Conclusions
In this research paper, capital structures of Small and Medium sized Enterprises from
Eastern Europe and Western Europe were analyzed, based on leverage ratios and
determinants of capital structures that were found in literature. The methodology
applied was a comparative study, in which the emphasis relied on differences found
between Eastern Europe and Western Europe. These differences were computed by
applying multiple Two Stage Least Squares regression analyses including dummy
variables for both regions.
The research study followed a target adjustment model, based on the Tradeoff Theory
that analyzed the impact of corporate taxes, bankruptcy costs and agency costs on
changes in leverage. The Tradeoff Theory argues that firms will optimize their
leverage ratios based on a tradeoff between tax benefits from debt, and bankruptcy
costs and agency costs of debt.
The researchers specifically chose to analyze Eastern Europe and Western Europe,
since literature on intra-European comparisons is scarce, and country data studied
clearly identified differences between these two regions in regard to taxes, bankruptcy
costs and agency costs. The division between Eastern Europe and Western Europe
was not based specifically on the geographical positions of countries, but primarily to
identify differences in the state of development of economies or financial systems.
Eastern European countries, under the taxonomy that was applied, have a different
economic background than Western European countries, which was expected to
impact firms’ capital structures differently. Corporate tax rates were found to be
considerably lower in Eastern Europe, compared to Western Europe. Bankruptcy
laws, bankruptcy procedures and corporate governance systems were found to be
weaker in Eastern Europe than in Western Europe. From the Tradeoff Theory, the
hypothesis was made that firms’ capital structures have lower amounts of debt in
Eastern Europe. The reasoning was as follows: On one side of the tradeoff, lower tax
rates lead to lower marginal benefits of debt, inclining Eastern European firms less to
take on debt. On the other side of the tradeoff, a weaker bankruptcy system makes
creditors more reluctant in giving loans (and thus increasing bankruptcy costs), which
reduces the amount of debt in Eastern European capital structures. Weaker corporate
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governance systems in Eastern Europe were expected to increase agency costs
between management and owners and between management and creditors. This would
further reduce the amount of debt in firms capital structures. Moreover, it was
observed that credit availability was lower in Eastern Europe, reducing the access to
credit for firms and thus their leverage ratios.
Most literature has analyzed capital structures of large (public) firms. This study
distinguished itself from that, by solely focusing on private Small and Medium sized
Enterprises (SMEs). Since SMEs make up the biggest share of a country’s economy,
it is surprising that literature on SME capital structure is rather scarce. This is
especially so, since for capital structure decision making, the size of a firm and its
ownership structure clearly make a difference. Small and private firms are mostly
owner-managed, which leaves fewer reasons to expect agency costs between owners
and management to play a role on capital structure determination. Agency costs
between creditors and management were also not expected to play a role on SME
capital structures, since it can be argued that banks solve this information asymmetry
in their own way. SMEs do not have the size, nor access to issue any public debt, and,
therefore, need to rely on bank financing. Thus SMEs are often characterized as
having very strong ties with banks. Data on SME performance is scarce, thus by
having a close relationship with firms, banks can gather their own data on borrowing
firms. It was identified that in the capital structures of SMEs, debt is mostly short
term. This is more evident in Eastern Europe rather than in Western Europe.
Two reasons for such differences were found in literature. Firms from Eastern Europe
have shorter data histories and are more risky investments. From the banks
perspective, long term loans are more risky than short term loans, and banks prefer to
finance Eastern European firms with short term debt. Besides, short term financing
provides a tool to continuously renegotiate the debt contract forcing the firm to act on
the banks behalf. Another hypothesis on the relationships between SME leverage and
its determinants was that agency costs have no influence on leverage ratios, or a
smaller influence on leverage ratios than bankruptcy costs, for both Eastern and
Western Europe. Hence, bankruptcy costs were expected to have a relatively more
important influence on leverage ratios.
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Besides testing for the differences between Eastern and Western European firms, the
paper’s research also tested the effectiveness of the Tradeoff Theory in explaining
capital structure. Since it was impossible to test the strength of the target adjustment
model directly, the research showed that the tax effect, bankruptcy cost effect and
agency cost effect were related with leverage in the way that aligns with the Tradeoff
Theory.
The research was conducted by comparing several variables which proxied for the tax
effect, bankruptcy cost effect and agency cost effect on four different proxies of
leverage. The relationship among the proxies for the three effects on leverage and the
proxies for leverage itself, were computed by several multiple Two Stage Least
Squares regression analyses. The comparisons of these relations between Eastern
Europe and Western Europe were done by including dummy variables in the
regression analyses, which either represented Eastern Europe or Western Europe.
The data that was used to compute the variables and proxies, was limited to six
countries. For Western Europe the data was gathered from SMEs in Ireland, the
Netherlands and Belgium. For Eastern Europe this data came from SMEs in Poland,
Hungary and Ukraine.
The findings of this research clearly showed differences to exist between leverage
ratios from Eastern European SMEs and Western European SMEs. Because of
institutional differences such as corporate taxes, availability of credits, bankruptcy
laws and procedures, and corporate governance, leverage ratios were found to be
considerably lower in Eastern Europe as compared to Western Europe, for all four
proxies of leverage. The first hypothesis was supported, because of institutional
differences, firms have different financing patterns in both regions. The role of
corporate taxes on leverage was found to be considerably stronger in Western
European SMEs, indicating that the importance of shielding taxes with debt is lower
in Eastern Europe. This is the result of lower corporate tax rates which cause a much
smaller positive effect of adding debt to firm’s capital structures. The fact that
availability of credit is weaker, also limits firms from shielding taxes by debt. The
second hypothesis was accepted.
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It was difficult to distinguish between bankruptcy cost effects and agency cost effects
on leverage. Indeed, several variables could proxy for both effects simultaneously.
From those variables that were found to only proxy for bankruptcy effects, it became
clear that indeed bankruptcy costs play a profound role on SME capital structures, in
both Eastern Europe as well as Western Europe. However, this bankruptcy effect was
found to be more important in Eastern Europe. Higher bankruptcy costs in Eastern
Europe caused a more negative effect on leverage for firms that tried to attract credits,
and banks were more reluctant to lend to firms, especially when firms were seeking
long term loans. These findings clearly lead to the third hypothesis to be accepted.
The regression analysis employed by the researchers and the data results proved that
indeed agency costs did not play an important effect on leverage ratios of SMEs in
both regions. The fourth hypothesis was thus accepted as well.
By means of a robustness check, the approach and reasoning of this research paper
were controlled for. In a similar approach as with the central research, the robustness
check investigated the differences and similarities between SME capital structures on
a country specific level, instead of a regional level. Based on the country-specific
scores and literature, expectations were formed on country-specific SME leverage
ratios and on the relationships between the variables. It was identified that also for
the individual countries, the regression results were in line with the expectations. This
observation created extra robustness to the research findings of Eastern and Western
Europe, since it diminished the probability that the variation of results was due to
unexplained factors.
One of the implications of this research paper is that, to a certain extent, the
generalization of Eastern Europe and Western Europe works rather well in explaining
regional capital structure differences. Even though Eastern Europe contains many
different countries with different backgrounds, cultures etc., it seems that the
economic history of the last two decades creates a comparable playing field for firms
in which to operate. It might be questioned however, how long this differentiation
might last, since in Eastern Europe, in the last decade, the different financial and
economic markets have grown rapidly and have become stronger. It is expected that
economic and financial improvements will continue, and the weak institutional factors
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that were observed in the past years will improve, leading to more diversified and
stronger economies.
From this research it was argued that such improvements would directly lead to
changes in firms capital structures. It will be interesting to keep track on these
relationships over the next decade.
Another important implication from this research is that it clearly shows that a
country’s institutional settings, such as bankruptcy laws and availability of credit, are
directly translated into firms’ capital structures. In line with Booth et.al. (2001), it
proves that knowing a firm’s nationality, or regional origin, might explain a big extent
of its capital structure. The type, and availability of financial resources of the country,
or region, have a direct impact on firms’ investments and operations.
The last implication of this research paper is that the Tradeoff Theory works as an
explanatory theory behind debt-equity choices. Corporate taxes have a positive impact
on leverage ratios while bankruptcy costs have a negative impact on leverage ratios.
Capital structures thus seem to be the result of a tradeoff between these two effects.
Agency costs do not seem to play an observable role on SME capital structures, since
ownership and management are hardly dispersed, and banks solve the information
asymmetry themselves. This research showed that the Tradoff Theory is applicable
for smaller and private companies that do not have access to public markets. Besides,
the Tradeoff Theory works well across countries with a different stage of economic
development. This is an important input into the continuous Tradeoff Theory
discussion, namely it proves that the Tradeoff Theory is an applicable and useful
theory in explaining capital structure determination.
Another important implication from this research is that it clearly shows that a
country’s institutional settings, such as bankruptcy laws and availability of credit, are
directly translated into firms’ capital structures. The type, and availability of financial
resources have a direct impact on firms’ investments and operations.
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Limitations of the research
This research paper focused on SMEs and on the differences between Eastern Europe
and Western Europe. It might be questioned whether such a division can really be
made. In the last fifteen years, many countries have been going through political,
social and economic transitions, and, therefore, the consideration of Eastern Europe as
one block of countries with similar economies might not be valid. Besides, only six
countries where selected from both Western Europe and Eastern Europe, which
represented both regions. It is probable that the research findings would have been
different if different, or more, countries would have represented both regions. It can
be noted that one of the underlying reasons of this study was to prove the differention
between Eastern and Western Europe. For that purpose, these six countries were
selected, because they differed from each other in respect to institutional factors. If
selected countries would have been more in line with each other in respect to taxes,
legal systems, bankruptcy proceedings and credit availability, the study could have
resulted in very different findings for this research.
The expectations and hyphotheses of this research paper were based and solely
focused on country scores that are continuously updated by scientists that cooperate
with the International Bank for Reconstruction and Development, which is part of the
World Bank. This resource was considered to be valid for the research, but resulted in
rather unilateral expectations. More objective expectations would have been created,
if multiple resources that compare institutional factors were available. Within the
timeframe and objectives of this research paper, more resources unfortunately were
not found.
Due to endogeneity in the original model, the target adjustment model had to be
computed by 2SLS regressions, instead of OLS regressions. Due to endogeneity in the
regression model, an Instrumental Variable had to be introduced, which caused the R-
squares to be unreliable in interpreting the strength of the model. This introduced
another limitation to the study.
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The target adjustment model consists of three parts: taxes, bankruptcy costs and
agency costs. It is possible that slightly different results would have been obtained if
different variables would have been chosen as proxies for taxes, bankruptcy and
agency costs. Especially one of the tax variables included in this research study, the
EFFECTIVE TAX RATE, proved to be a weak explanator of the tax effect.
Another important point of limitation in this research was the availability of useful
data. Many firms and firm/year observations had to be deleted from the final data
samples, since certain data items were missing or incomplete. As can be observed in
the collected data for the sample countries in Chapter Three, and especially for
Ireland, the Netherlands, and Poland, the majority of original firm/year observations
had to be deleted. Regretfully, this made the research findings weaker than if data
availability would have been better, or consistent from country to country. Certain
variables had to be adjusted, because of data weaknesses, in order to make them
useful for this research. For the variables KINK and STANDARDIZED KINK,
bottom and ceiling values were created in order for the variation not to get too
extreme. From the descriptive statistics in Table 7, it can be seen that even after
adjusting for the most extreme 0,5 percent, still many extreme observations are found.
This is most observable for the variables OPERATING RISK and EFFECTIVE TAX
RATE. It seems that also for the four dependent variables still quite extreme values
have been used. These extreme outliers are especially apparent in Eastern Europe. A
possible solution could have been to delete more than the suggested 0,5 percent of the
outliers on both sides of the distributions, but this would have biased the results by
selecting only expected data values.
The data weaknesses limited the validity of the conclusions on these variables and on
the relationship between these variables and the measures of leverage.
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Recommendations for further research
Central to this research paper is the state of development of a country’s economy, and
hence its financial system. This was shown to have a direct impact on firms capital
structure decisions. Since the state of development of Eastern European countries, and
Western European countries, does not stand still, it will be very interesting to see how
changes in countries legal systems, credit markets, tax policies etc. will impact the
development of the firms’ capital structures in these countries. Growth figures from
Eastern European economies indicate the rapid pace in which these economies are
changing. The more an economy grows, the more likely it is to get stronger and
improve in its financial climate. The conclusions of this research might be very
different in the future. It is, therefore, that researchers should continue to further study
the relationships between economy-specific factors and firms capital structures. Such
studies are important not only because they can yield interesting results, but more so
because they might indicate to policy makers how and in which way economic growth
might lead to improvements for national companies, and help to attract additional
foreign direct investments into the countries.
In contrast to most existing literature in the field of corporate finance, this study has
specifically focused on Small and Medium sized Enterprises. The share of the
economic activity in Europe that is provided by SMEs is far bigger than that of large
public firms. However, we still do not know much about SME financing which
suggests further research is needed. This research paper showed that the Tradeoff
Theory is a very useful and applicable theoretical framework to study and compare
SMEs from different regions and countries. Yet, it also identified many aspects of
SME leverage ratios that can not be typically explained by the Tradeoff Theory and
the target adjustment model. The focus of this research has been to test relationships
between SME leverage ratios and expected determinants of those leverage ratios, ex
post. Perhaps as economic growth hastens in Europe, information technology and
knowledge exchange will make financial data for new studies more readily available
to our understanding of capital markets, tradeoffs, debt leverage, etc. Indeed, such
new technology and data availability might yield more insights into SME financing
patterns and specific SME financing decisions. This is yet another recommendation
for future research.
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Appendices – Table of Contents
Appendix I Generalized overview of corporate governance systems in Western
Europe __________________________________________________________ i
Appendix II Comparison between Eastern and Western Europe on institutional
factors __________________________________________________________ ii Development of capital markets in Eastern Europe __________________________________ ii Access to Credit _____________________________________________________________ iv Corporate Taxes ____________________________________________________________ vii Bankruptcy _________________________________________________________________ ix Corporate Governance _______________________________________________________ xii
Appendix III Overview of Industries ___________________________________________ xv
Appendix IV Descriptive Statistics for the individual countries ______________________xvi IV.I) Descriptive Statistics for Ireland, the Netherlands and Belgium___________________ xvi IV.II) Descriptive Statistics for Poland, Hungary and Ukraine _______________________ xvii
Appendix V Hausman tests_________________________________________________ xviii
Appendix VI Correlation Matrices____________________________________________ xix
Appendix VII 2SLS Regression Results for Eastern Europe versus Western Europe_____ xx
Appendix VIII T-test results for comparing the four proxies of Leverage_____________ xxii VIII.I)T-test Results of the four proxies of Leverage between the Western European
sample and the Eastern European sample _______________________________________ xxii VIII.II) T-test Results of the four proxies of Leverage among Ireland, the Netherlands
and Belgium ______________________________________________________________ xxiv VIII.III) T-test Results of the four proxies of Leverage among Poland, Hungary and
Appendix IX Robustness Check – Within the Western and Eastern European samples xxviii IX.I Within the Western European sample: Ireland, the Netherlands and Belgium ________ xxx IX.II Within the Eastern European Sample: Poland, Hungary and Ukraine _______________ xl
Appendix X Regression results for Ireland, the Netherlands and Belgium ____________ xlix
Appendix XI Regression results for Poland, Hungary and Ukraine __________________ liii
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl i
Appendix I
Generalized overview of corporate governance systems in Western Europe
System Countries
example
Authors Stakeholder orientation
Ownership Type of Law Role of Legal system in cases of
bankruptcy
External Market for corporate
control
Shareholder /
Creditor Protection
Relation between
stakeholders and Mgmt
Anglo-Saxon
UK, Ireland
Shleifer and Vishny (1997) Rajan and Zingales (1995) LaPorta et al (1997, 1998, 1999) Weimer and Pape (1999
Market
/ Shareholders
Dispersed
Common
law
Highly
Important
Yes
Shareholder
Short term
Germanic
Germany,
Netherlands, Switzerland,
Sweden, Austria,
Denmark, Norway and
Finland
Shleifer, Vishny (1997) Rajan and Zingales (1995) LaPorta et al (1997, 1998, 1999) Weimer and Pape (1999
Bank
/ Employees
(Unions)
Moderately to
highly concentrated
(German) civil law
Less important
No
Creditor
Long term
Latin
France, Italy, Spain, and
Belgium
Weimer and Pape (1999)
Family / bank /
Government
Highly
Concentrated
(French) civil
law
Not important
No
Creditor
Long term
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl ii
Appendix II
Comparison between Eastern and Western Europe on institutional factors
The observed differences between Eastern and Western Europe are broadly
categorized and supported by country scores from several resources. In order to find
general differences between Western and Eastern Europe, the country scores were
developed into two samples: one based on several Western European countries, and
the other based on several Eastern European countries. This section will conclude
with a short review of determinants of capital structure mostly found in existing
literature.
The development of capital markets in Eastern Europe started only after the fall of
communism, while in Western Europe well developed capital markets were far longer
in place. The financial circumstances under which firms operate are, therefore,
different in both geographic regions. Capital markets provide financing sources, and
as will be discussed later, the access to credit is important for most Small and Medium
sized Enterprises. Credit is the sole form of external financing for most small firms,
and consequently, it has a big impact on firms abilities to optimize investments and
capital structure. Before discussing the concrete differences between Western and
Eastern Europe in respect to credit access, corporate taxes, bankruptcy laws and
corporate governance laws, one must first discuss and understand the development of
capital markets in Eastern Europe.
Development of capital markets in Eastern Europe
A clear taxonomy that generalizes different capital markets and legal systems, as
presented for Western Europe in Appendix I, does not exist for Eastern Europe. Many
Eastern European countries that were under transition from centrally planned
economies introduced reforms to implement a Western style market economy
(Svejnar, 2002). Until the late 1990’s, many of these reforms proved to be
unsuccessful, because they lacked supportive legal structures. The importance of the
legal system was underestimated. Even though most Eastern European countries have
law systems based on the German and French jurisdiction, i.e. civil law codes, the law
systems were often old-fashioned and the enforcement of laws was weak. Gradually
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl iii
most countries started modernizing their law system in which property rights and
shareholder protection were crucial (Svejnar, 2002). The most successful countries in
implementing effective legal systems were Estonia, Latvia, Lithuania, Poland,
Hungary and Slovenia (Svejnar, 2002). Such legal reforms and protection were crucial
to the future development of financial markets.
In the absence of an effective financial market, the major supply of finance came from
banks. To offset the sole reliance on bank financing, in the early 1990s Eastern
European governments introduced plans to implement Anglo Saxon style capital
markets, in which ownership of public firms is more widely dispersed. These plans
proved to be disappointing because ownership ratios of public firms were actually
concentrated, as a result of high agency costs. Large investors concentrated their
block holdings in order to have a stronger influence on a company’s decision making,
to decrease abuse of funds. This resulted in minority shareholders getting smaller
influence, and hence, their agency costs rose.
Another development in the 1990’s was that the large former state-owned banks of
many Eastern European countries accumulated non-performing loans because of slow
economic improvements. In order to prevent a banking crisis, the governments of
Poland, Hungary and the Czech Republic privatized virtually all major banks and sold
them off to large Western banks in the late 1990’s. Since then, the role of the banking
sector in the Eastern European economies has grown significantly, especially with the
expertise and size of the new Western banking players. The first Eastern European
countries that joined the European Union (Estonia, Czech Republic, Hungary, Latvia,
Lithuania, Poland, Slovakia, and Slovenia) have made the largest progress in
reforming their banking systems. Banks in most of the region now enjoy better legal
protection, courts are better at enforcing laws, and banking supervision and regulation
have become more effective (Svejnar, 2002).
Bank lending is the major source of financing in Eastern Europe and contributes
largely to the high economic growth rates in this region. Even though banks dominate,
the financial sector is also broadening because of growing stock markets. This is due
to improvements in disclosure rules, private equity and pension funds promoting long
term saving (Berglof, 2006).
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl iv
Below, differences are analyzed between Western and Eastern European economies
on credit access, corporate tax rates, bankruptcy laws and proceedings and issues
related to corporate governance. Findings for the more economically developed
Western Europe are based on nine countries: Austria, Belgium, Denmark, France,
Germany, Ireland, Italy, the Netherlands and the United Kingdom. Findings for
Eastern Europe are based on seven countries: Czech Republic, Hungary, Poland,
Romania, Russia, Slovak Republic and Ukraine. Even though clear differences can be
observed when studying Eastern and Western Europe, the countries that determine the
Western and Eastern European samples differ with each other as well.
Access to Credit
A firm’s access to finance involves several institutional issues that firms face when
trying to attract investors. The focus here is on creditors, and the index used for the
analysis is called the “Access to Credit” index, developed by Djankov, McLiesh and
Shleifer (2006). This index explores three indicators of credit access for firms. The
first indicator deals with legal rights of creditors and borrowers. This measure shows
the degree of effectiveness of bankruptcy laws in facilitating lending by creditors, on
a scale of 0 to 10, where 10 indicates highest effectiveness. The second indicator is a
credit information index. This index measures accessibility and quality of credit
information available through credit registries. The third indicator shows the
availability of current credit information of individuals and firms from private and
public credit registries and bureaus. This indicator is expressed as a percentage of
registered adults with credit history (Djankov, McLiesh and Shleifer 2006).
Credit registries such as the UK Credit Registry, are institutions that collect and share
information on credit histories of firms and individuals. The information that is
provided helps creditors to assess risks and allocate credit most efficiently. Access to
credit is better in countries where credit registries have higher coverage and better
quality of information. In such countries, firms need not rely on personal relations
with lending institutions when trying to obtain credit. Countries with stronger legal
rights and more credit information about firms are associated with deeper credit
markets and lower default rates (Djankov, McLiesh and Shleifer, 2006).
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl v
In Table II.1 and Figure II.1 below, different legal rights, credit information and
coverage scores for Eastern and Western European countries under study are shown.
In Western Europe, it appears that the United Kingdom (UK), Ireland and Germany
score very high on all three indicators, meaning that creditors have more and better
information in these markets as such, and about companies specifically. Companies
from these countries are likely to have easier access to credit. This in turn might
translate into more favorable interest rates. Countries in Western Europe that score
lower on the legal rights index are Italy, followed by Austria, France and Belgium. In
terms of the availability and quality on credit information, France and Denmark score
considerably low.
In Eastern Europe, it appears that Czech Republic scores best on all three indicators
followed by Slovak Republic and Poland. Even though Ukraine scores very high on
the legal rights index, it has very weak quality and quantity of credit information
available. Overall, Russia scores worst on all three indicators in this region.
Table II.1 – Access to Credit in Western and Eastern European countries
Legal Rights
Index
Credit
Information
Index
Coverage (%
adults)
WESTERN EUROPE
Austria 5 6 41,1
Denmark 8 4 11,5
The Netherlands 7 5 68,9
Belgium 5 4 56,2
Germany 8 6 94,4
Ireland 8 5 100
Italy 3 5 74,8
France 5 4 12,3
United Kingdom 10 6 86,1
EASTERN EUROPE
Poland 4 4 38,1
Ukraine 8 0 0
Czech Republic 6 5 54,5
Hungary 6 5 5,9
Romania 4 5 8,1
Slovakia 9 3 46,3
Russia 3 0 0 Source: The International Bank for Reconstruction and Development / World Bank: www.doingbusiness.org
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl vi
Figure II.1 – Average Access-to-Credit scores in Western and Eastern Europe
Access to Credit
1
10
100
Legal Rights Index Credit Information Index Coverage (% adults)
Western Europe
Eastern Europe
Source: The International Bank for Reconstruction and Development / World Bank: www.doingbusiness.org
When comparing Western Europe with Eastern Europe, the following trends are
observable. First, Eastern and Western European countries score similar on legal
rights, on average. Even though legal systems in the Eastern transition economies are
often weaker compared to the Western standards, it may seem surprising that the legal
rights index appears to be similar for both blocks. There might be a logical reason for
this. Under weak legal systems, creditors are often found to have large monitoring
power. This larger power makes the role of courts less necessary. Creditors
monitoring power comes from a variety of control rights. They receive these control
rights when firms default or violate debt covenants and because they typically lend
short term. Therefore borrowers have to come back at regular, short intervals for more
funds (Shleifer and Vishny, 1997). The second observed trend is that Eastern
European countries score worse on credit information and coverage indexes,
compared to Western Europe. Indeed, the quality and availability of credit
information needs to be improved in the Eastern European market in order to decrease
the gap between Western and Eastern Europe.
Implications from these findings are as follows: in Eastern Europe banks have less
credit information available about firms. This is because companies in transition
economies usually have shorter credit histories due to the fact that keeping track of
credit started later than the actual transition itself. Also accounting standards changed
which lead firms having to rebuild their data history from scratch. For example, only
in 1995 Poland introduced an accountancy act that requires minimum record-keeping
(Gottlieb, 1999). These shorter and less qualitative credit histories make banks and
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl vii
other creditors more reluctant to extend credit while making lending decisions to
Eastern European firms. This leads to banks giving smaller loans and demanding
higher compensation, i.e., higher interest rates. Moreover, higher interest rates lead to
lower demand for loans. This in turn gives a reason to expect leverage ratios to be
lower in this region, when compared to Western Europe. A last implication of low
public credit information availability is that banks have to build up credit registries of
firms themselves. They will build up stronger personal relations with firms in order to
stay up-to-date with company records. Because of the competitive sensitivity of such
information, banks are not likely to share this information, and therefore will remain a
major stakeholder in the firms financial decision making. A strong hands-on approach
to borrowing is expected to be the end result.
Corporate Taxes
A wave of international corporate tax competition has been taking place around the
whole continent. The European countries have been decreasing corporate tax rates in
order to attract and keep investments. The recent tax rivalry has been referred to as a
“race to the bottom” or “predatory practices” (Erdilek, 2007). It started especially
after Ireland and new European Union member states from Eastern Europe succeeded
in attracting investment and irking their biggest competitors with tax rates below
twenty percent, which are among the world’s lowest (Kennedy, 2007). The larger
Western European countries were forced to follow this trend in order not to loose
investments, especially from multinational companies and to be able to compete with
other European countries. In 1993 the EU had an average corporate tax rate of 38
percent, while in 2006 the EU average had dropped to 25,8 percent (Erdilek, 2007).
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl viii
Table II.2 – Corporate Tax Rates in Western and Eastern European countries in % - over time
YEAR 2000 2001 2002 2003 2004 2005
WESTERN EUROPE
Austria 34,00 34,00 34,00 34,00 34,00 25,00
Denmark 32,00 30,00 30,00 30,00 30,00 28,00
The Netherlands 35,00 35,00 34,50 34,50 34,50 31,50
Belgium 40,17 40,17 40,17 33,99 33,99 33,99
Germany 51,60 38,36 38,36 39,58 38,29 38,31
Ireland 24,00 20,00 16,00 12,50 12,50 12,50
Italy 41,25 40,25 40,25 38,25 37,25 37,25
France 36,66 35,33 34,33 34,33 34,33 33,83
United Kingdom 30,00 30,00 30,00 30,00 30,00 30,00
Russia N/A 35,00 24,00 24,00 24,00 24,00 Source: KPMG's Corporate Tax Rate Survey, an international analysis of corporate tax rates from 1993 to 2006, KPMG Audit – Tax and Advisory, 2006
Table II.2 is based on the yearly corporate tax rates reports of KPMG Audit – Tax and
Advisory (2006), and indicates that Austria, Germany and Ireland had the highest
drop in corporate tax rates in the period 2000 - 2005 in Western Europe. This amounts
to nine, thirteen, and twelve percent, respectively. Similarly, Poland, Slovakia and
Russia decreased their rates in the same period with eleven, ten and eleven percent
respectively.
Figure II.2 – Average Corporate Tax Rates in Western and Eastern Europe - over time
Source: KPMG’s Corporate Tax Survey, and international analysis of corporate tax
rates from 1993 to 2006, KPMG Audit - Tax and Advisory, 2006
Average Corporate Tax Rates in Europe - %
15,00
20,00
25,00
30,00
35,00
40,00
2000 2001 2002 2003 2004 2005
Year
Ra
te
Western
Europe
Eastern
Europe
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl ix
From Figure II.2 one can see that both regions have been following a similar trend of
decreasing corporate tax rates during years 2000-2005. This trend is expected to
continue into the future (Erdilek, 2007). Nevertheless, research for Eastern Europe
indicates much lower average tax rates than Western Europe. This is due to the fact
that emerging economies in the Eastern region are in a bigger need of attracting
foreign investors and are offering very competitive tax rates. Besides, the heavy tax
cuts should be seen as an incentive for firms to invest, in order to offset the higher
risks in these emerging economies, and the higher costs of short-term bank borrowing
at high interest rates.
Looking at the European corporate tax trends, it can be expected that the role of taxes
in setting capital structures, is declining in both the Western and Eastern regions.
Since the percentage of payable taxes is lower than in previous years, the relative
amount of tax shields is also lower. Thus, in the light of the Tradeoff Theory, present
day leverage ratios are expected to be lower in both regions than a decade ago.
Besides, the importance of taxes in determining leverage ratios seems to be declining.
Looking at the relative tax rates between Eastern and Western Europe, the same
reasoning would indicate lower leverage ratios in Eastern Europe. What is more, since
in both regions the role of taxes is decreasing, the role of bankruptcy and agency costs
is expected to be higher in setting a target leverage ratio, under the Tradeoff Theory.
Bankruptcy
The methodology followed here is based on Djankov, Hart, McLiesh and Shleifer
(2006). In the table below three indicators of a country’s bankruptcy enforcement are
depicted. The first indicator shows the number of months required to complete a
typical bankruptcy case. The more efficient the bankruptcy proceedings, the shorter
the time it takes for an investor to receive his dues. The second indicator illustrates the
costs of the bankruptcy proceedings as a percentage of the estate’s value. These costs
include costs of courts, fees for insolvency practitioners, independent assessors,
lawyers and accountants. The third indicator measures the efficiency of foreclosure of
bankruptcy procedures. It estimates the percentage of the value that can be recovered
by creditors, tax authorities and employees from an insolvent firm. It should be
mentioned that the second and third indicator presented below are related: the higher
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl x
the costs of bankruptcy proceedings, the lower the recovery rate, since the bankruptcy
costs are incurred from the estate’s value (Djankov, Hart, McLiesh and Shleifer,
2006).
Table II.3 – Bankruptcy Scores for Western and Eastern European countries
Cost
% of estate
WESTERN EUROPE
Austria 13,2 18 73,7
Denmark 36 4 70,5
The Netherlands 20,4 1 86,3
Belgium 10,8 3,5 86,4
Germany 14,4 8 53,1
Ireland 4,8 9 87,9
Italy 14,4 22 39,7
France 22,8 9 48
United Kingdom 12 6 85,2
EASTERN EUROPE
Poland 36 22 27,9
Ukraine 34,8 42 8,7
Czech Republic 110,4 14,5 18,5
Hungary 24 14,5 39,7
Romania 55,2 9 19,9
Slovakia 48 18 48,1
Russia 45,6 9 28,7
Months Recovery Rate
Source: The International Bank for Reconstruction and Development / World Bank: www.doingbusiness.org based on Djankov, Hart, McLiesh and Shleifer (2006)
Figure II.3 – Average Bankruptcy Scores for Western and Eastern Europe
Average Bankruptcy Scores
0
10
20
30
40
50
60
70
80
Months Cost = % of estate Recovery Rate
Western Europe
Eastern Europe
Source: The International Bank for Reconstruction and Development / World Bank: www.doingbusiness.org based on Djankov, Hart, McLiesh and Shleifer (2006)
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xi
From Table II.3 and Figure II.3 it can be observed that the duration of bankruptcy
proceedings takes over three times longer in the countries of Eastern Europe as
compared to those of Western Europe- 50 months to 18 months respectively.
Bankruptcy costs are on average twice as high in the East compared to the West- 19
percent to 9 percent. Partly because of these two weaknesses, the recovery rates of
only 28 percent are much lower in the Eastern region as well. Moreover, while
looking at the costs and recovery rates together, one can notice that in Eastern Europe
more value of the firm is lost from bankruptcy then in Western Europe. Ireland and
Belgium have the shortest bankruptcy durations in the Western sample, taking less
than one year. The Czech Republic has bankruptcy proceedings that can take up to
nine years.
The Netherlands and Belgium have the lowest costs, amounting to 1 and 3,5 percent,
respectively. These costs in Ukraine amount to 42 percent. Recovery rates are very
high in Western Europe, amounting to 70 percent on avarege. Ireland, Belgium and
the Netherlands perform especially very well: more than 85 percent of the firm’s
value is recovered after bankruptcy. In Eastern Europe, recovery rates are much
lower, with Ukraine showing the worst recovery rate of 8,7 percent. Such low
recovery rates tend to create higher financial risk for all investor groups.
The outdated bankruptcy laws in Eastern Europe are a possible explanation for the
observed differences. Nevertheless, the countries are improving their law systems by
introducing new Bankruptcy and Insolvency Acts, e.g. Poland and Estonia introduced
new Acts in 2003 and Czech Republic is replacing its bankruptcy law in 2007. The
previous bankruptcy laws in Czech Republic dated from before 1950, while in Poland
they dated from 1934 (Warsaw Voice Online, 2003).
The scores on the three bankruptcy indicators clearly suggest that bankruptcy costs
are higher in Eastern Europe than in Western Europe. Creditors lending capital to
Eastern European firms need to wait longer for repayment in case of bankruptcy.
Besides, they will have to pay more to the legal practitioners and afterwards will find
that they recover a smaller portion of their initial investment. When applying these
findings to capital structure theory, specifically the Tradeoff Theory, there are some
implications. Creditors in East will be more reluctant to give credits in the first place,
due to bigger risks and higher bankruptcy costs. Besides, they will ask for higher
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xii
interest rates in order to offset these risks and costs. Thus, higher bankruptcy costs
and higher credit risk may lead to lower leverage ratios in Eastern Europe.
Corporate Governance
There are significant differences across countries in the degree of investor protection
(Demirguc-Kunt, 2002). The Investor Protection index, developed by Djankov, La
Porta, Lopez-de-Silanes and Shleifer (2006), measures such country differences. The
Investor Protection Index measures the strength of investor protection against
directors’ misuse of corporate assets for personal gain. This index is composed of
three dimensions and mainly focuses on legal issues. The first is a disclosure index
which indicates the transparency of transactions. The second indicates the extent to
which a director can be held liable or brought to court for mismanagement of the
investors’ funds. The third dimension indicates the extent to which the legal system
supports shareholders in case of disputes with management. The corporate governance
index ranges from 0 to 10, with higher values indicating better corporate governance
in the country.
Looking at the data in Table II.4 below one can notice that the average investor
protection index in Eastern Europe is slightly lower then in Western Europe, equal to
almost 5 and 6 points, respectively. Ireland and the U.K. represent the highest scores
from the two samples. This could be expected, as these countries have a common law
system in place in which high emphasis is put on investor protection. Surprisingly,
Austria and Ukraine indicate a similar, low score of 3,7. In Eastern Europe Poland
and Romania indicate the highest corporate governance equal to 6 points.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xiii
Table II.4 – Investor Protection Index for Western and Eastern European countries
Disclosure
Index
Director
Liability
Index
Shareholder
Suits Index
Investor
Protection
Index
WESTERN EUROPE
Austria 2 5 4 3,7
Denmark 7 5 7 6,3
Netherlands 4 4 6 4,7
Belgium 8 6 7 7
Germany 5 5 5 5
Ireland 10 6 9 8,3
Italy 7 2 6 5
France 10 1 5 5,3
United Kingdom 10 7 7 8
EASTERN EUROPE
Poland 7 2 9 6
Ukraine 1 3 7 3,7
Czech Republic 2 5 8 5
Hungary 2 4 7 4,3
Romania 9 5 4 6
Slovakia 2 4 7 4,3
Russia 7 2 7 5,3 Source: The International Bank for Reconstruction and Development / World Bank: www.doingbusiness.org developed by Djankov, La Porta, Lopez-de-Silanes and Shleifer (2006)
Figure II.4 – Average Investor Protection Index for Western and Eastern Europe
Source: The International Bank for Reconstruction and Development / World Bank: www.doingbusiness.org developed by Djankov, La Porta, Lopez-de-Silanes and Shleifer (2006)
It is worth noticing that the corporate governance scores presented above differ from
other available sources. For example, the report of Heidrick and Struggles (2006)
indicated that the Netherlands had the second strongest corporate governance scores
in Western Europe during the years 2003-2006. Italy and Germany, on the other hand,
scored relatively lower then the scores presented above. The differences in these
scores are most likely due to the assumptions that need to be made in calculating the
scores. Regretfully, the Heidrick and Struggles (2006) report did not include country
Investor Protection Index
4,4 4,6
4,8 5
5,2 5,4 5,6
5,8 6
Western Europe Eastern Europe
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xiv
scores for Eastern Europe. Since the focus here lies on comparing Eastern with
Western Europe, the Heidrick and Struggles (2006) scores are not presented.
The differences observed in corporate governance scores between Western and
Eastern Europe are very diverse and country specific. Therefore, it is hard to
generalize between West and East. The variation between East and West mainly
comes from the first two indicators, the disclosure index and the director liability
index. They indicate that most of the Eastern European law systems are still
underdeveloped in comparison to Western standards, indicating weak shareholder
protection. A possible reason for the shareholder suits index not to under perform the
Eastern sample is a strong investor concentration in firms. LaPorta et al (1999) found
that in economies with weak shareholder protection, relatively few firms are widely
held. Dzierzanowski and Tamowicz (2004) found that in Poland and other Eastern
European transition economies, voting control in listed corporations is remarkably
concentrated. Shleifer and Vishny (1997, pp. 753) stated “in cases where legal
protection does not give enough control rights to small investors, investors can get
more effective control rights by being large or concentrated.” By being concentrated,
investors have much higher influence on management and solve disputes before they
occur. A legal system is not needed in such cases. In effect, concentrated ownership
provides the needed legal protection to investors. So, even though the investor
protection index only shows small deviations between Eastern and Western countries,
the problems concerning weak law systems in Eastern Europe might be bigger than
they seem to be.
On a country-specific basis one can infer that agency costs seem to be lowest for
Ireland, the UK and Belgium, due to strong and effective corporate governance.
Similarly in Eastern Europe, Ukraine, Slovak Republic and Hungary are likely to have
higher agency costs than the other countries presented, due to weak corporate
governance. One would expect higher agency costs in Eastern Europe, due to lower
transparency and less effective legal systems. When connecting corporate governance
to capital structure there are some implications on leverage. In light of the Tradeoff
Theory, countries with low corporate governance, and hence, high agency costs are
expected to have lower leverage, since creditors are less inclined to lend to companies
from these countries. The general assumption is that this is another reason to expect
lower leverage ratios in Eastern European countries.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xv
Appendix III
Overview of Industries
The industry classification used is the European Union’s NACE Rev.1.1. This classification is identical to the UK SIC (2003) industry
classification. At the left, the industry codes are shown. At the right it is displayed which generalization was applied to reduce the number
of industries used in testing for an industry effect. Firm data was collected from firms that are active in the following industries.
NACE Rev.1.1 Code Industry Name Industry classification used
- 1000 – 1450 Mining and Quarrying
- 1500 – 3720 Manufacturing Manufacturing
- 4000 – 4100 Electricity, Gas and Water
- 4500 – 4550 Construction
- 5000 – 5274 Wholesale and Retail
- 5500 – 5552 Hotels and Restaurants
- 6000 – 6420 Transport, Storage, Communication
- 7100 – 7499 Renting, Computer Business, R&D, Other Business
- 7500 – 7530 Public Administration and Defence Services
- 8000 – 8042 Education
- 8500 – 8532 Health and Social Work
- 9000 – 9305 Other Community, Social and Personal Service Activities
- 9500 – 9700 Activities and Households
- 6500 – 6720 Financial Intermediation Excluded from this research
- 7000 – 7032 Real Estate
- 0100 – 0202 Agriculture, hunting and forestring
- 0500 – 0502 Fishing Other
- 9900 – 9999 Extra-territorial Organizations and Bodies
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xvi
Appendix IV
Descriptive Statistics for the individual countries
IV.I) Descriptive Statistics for Ireland, the Netherlands and Belgium
Observations Minimum Maximum Mean Std. Deviation
Total Leverage 1780 0,0247 1,6188 0,5434 0,2449
Short Term Leverage 1780 0,0052 1,1688 0,4398 0,2331
Long Term Leverage 1780 0,0000 0,9778 0,1037 0,1440
Adjusted Total Leverage 1780 0,0054 1,3306 0,3927 0,2363
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xviii
Appendix V
Hausman tests
Lagged Total Leverage
Lagged Short Term Leverage
Lagged Long Term Leverage
Lagged Adjusted Total Leverage
Eastern Europe vs. Western Europe -0,0455 [-10,9148]***
-0,0962 [-11,5136]***
-0,0204 [-1,9836]**
-0,1501 [-15,8942]***
Within the Western European sample, testing differences between Ireland, the Netherlands and Belgium
-0,042 [-6,5987]***
-0,0857 [-6,9391]***
-0,038 [-3,4392]***
-0,0759 [-4,8274]***
Within the Eastern European sample, testing the differences between Poland, Hungary and Ukraine
-0,038 [-3,1812]***
-0,1022 [-9,4427]***
-0,04 [-2,6699]***
-0,1361 [-12,9317]***
*, ** , *** = significant on the 0.1, 0.05 and 0.01 level of significance, respectively
Hausman tests were conducted in order to test for endogeneity of the LAGGED LEVERAGE variable. The LAGGED LEVERAGE variables represent the leverage of period t-1, which is included in the target adjustment model. All measures of lagged leverage are found to be endogenous, indicating that the Ordinary Least Squares regression method is not the proper method of testing the regression model. Hence, an instrumental variable (IV) needs to be calculated which replaces lagged leverage in the model. This model then can be tested by a 2-Stage Least Squares regression method. The Hausman test scores are calculated as follows:
• First, normal OLS regressions are run, where the suspect endogenous variable is used as the dependent variable and all independent variables (except the suspect endogenous variable) are included, including the Instrumental variable for the suspected endogenous variable. In this case, the endogenous variable is leverage lagged by one period, and the instrumental variable is leverage lagged by two periods.
• Second, the residuals of the OLS regression are used as an independent variable for the original OLS regression.
• Third, the original OLS regression is run, with the normal dependent variable on the left, and all independent variables (including the instrumental variable) plus the residuals of the first regression on the right.
• Fourth, the coefficients of the residuals are presented in the table below. In case these are significant, which they are, the suspected variable is indeed endogenous.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xix
Appendix VI
Correlation Matrices
Correlation Matrix for the Western European Sample
Total
Leverage
Short Term
Leverage
Long Term
Leverage
Adjusted Total
Leverage KINK
STANDARDIZED
KINK
EFFECTIVE
TAX RATE TANGIBILITY SIZE Z-SCORE
OPERATING
RISK PROFITABILITY GROWTH
Total Leverage 1,0000
Short Term Leverage 0,7580 1,0000
Long Term Leverage 0,4090 -0,2850 1,0000
Adjusted Total Leverage 0,7440 0,3960 0,5400 1,0000
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xx
Appendix VII
White-heteroskedasticity adjusted 2SLS results of the Target Adjustment Model, comparing Eastern Europe vs. Western Europe. Western Europe serves as the base group.
Total Leverage Short Term Leverage Long Term Leverage Adjusted Total Leverage
Total Liabilities / Total Assets Current Liabilities / Total Assets Non-Current Liabilities / Total Assets (Total Liabilities - Payables) / Total Assets
*, ** , *** = significant on the 0.1, 0.05 and 0.01 level of significance, respectively
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxi
Appendix VII Continued
Explanatory Notes to the table in Appendix VII:
White-heteroskedasticity adjusted 2SLS regressions, conducted in E-VIEWS, for years 2000 to 2005 on the complete sample of all observations from Eastern Europe and
Western Europe. In order to compare both regions, Western Europe is the base group. Twelve tests on the following four different dependent variables have been done: Total
Leverage, Short Term Leverage, Long Term Leverage and Adjusted Total Leverage.
Total Leverage is calculated as: Total Liabilities / Total Assets, Short Term Leverage is calculated as Current Liabilities / Total Assets, Long Term Leverage is calculated as
Non-Current Liabilities / Total Assets and Adjusted Total Leverage is calculated as (Total Liabilities – Payables) / Total Assets.
LAGGED LEVERAGE, and shift DUMMY and slope DUMMY variables for Eastern Europe and shift dummy variables for Industries.
KINK is calculated as EBIT in year t / Interest Expenses in year t. STANDARDIZED KINK is computed as (KINK in year t x Interest Expenses in year t) / Standard deviation of
KINK over all years. The EFFECTIVE TAX RATE is calculated as the observed Tax Expenses in year t / Earnings Before Taxes in year t. Note that only one tax variable is used
at a time.
SIZE is proxied by the natural logarithm of Total Assets in year t. Z-SCORE is Altman’s Z-SCORE for General use, which is calculated for every year t as:
OPERATING RISK is calculated as the standard deviation of Earnings Before Taxes over all years observed until year t. PROFITABILITY is calculated as Earnings Before
Taxes / Total Assets. GROWTH is calculated as the percentage change of Total Assets in year t-1 to year t. LAGGED LEVERAGE is calculated as the respective leverage ratio
(the dependent variable of the model), in year t-1. Note that the correlation of LAGGED LEVERAGE with the residuals of the model is removed by including an Instrumental
Variable; leverage lagged two periods (t-2).
The dummy variables are qualitative variables with the value 1 if the observation belongs to the group it represents. Therefore, the shift dummy Eastern Europe has a value of 1
for a firm from a company in one of the following countries: Poland, Hungary or Ukraine. It has the value 0 if the observation is from a company in any of the other countries.
Similarly, the slope dummy variables are computed by multiplying the shift dummy by the respective independent variables.
The Target Adjustment Coefficient is derived from model [4] and is computed as: 1 – the coefficient of LAGGED LEVERAGE.
R² indicates the coefficient of determination, or the explanatory power of the model as a whole. DW statistics show whether the regression results are affected by autocorrelation.
A DW statistic close to 2.0 indicates no autocorrelation. The number of variables with a Tolerance level smaller than 0,1 indicates whether multicollinearity is apparent in the
regression model. F statistics and their significance show whether a linear relationship between the dependent variable and any of the independent variables exists, depending
what group of independent variables is included in the F-test.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxii
Appendix VIII
T-test results for comparing the four proxies of Leverage.
VIII.I) T-test Results of the four proxies of Leverage between the Western European
sample and the Eastern European sample
By calculating a T-test of one sample’s average (mean) leverage ratio over another
sample’s leverage data distribution, the T-test scores indicate whether the two samples
are statistically different from each other in respect to their leverage ratios. In case the
T-test scores are significant, the leverage ratios in the two samples are statistically
different from eachother. The higher the significance, the more certain one can be
about the statistical difference. The signs (positive or negative) in front of the T-test
scores indicate in which direction the leverage ratios of both samples are different.
Table VIII.1 T-test results for comparing the four proxies of Leverage between the
Western European sample and the Eastern European sample
Total Leverage
data distributions Western Europe mean Eastern Europe mean
data Western Europe --- [153,1327]***
data Eastern Europe [-99,1787]*** ---
Short Term Leverage
data distributions Western Europe mean Eastern Europe mean
data Western Europe --- [97,1876]***
data Eastern Europe [-64,0818]*** ---
Long Term Leverage
data distributions Western Europe mean Eastern Europe mean
data Western Europe --- [88,9762]***
data Eastern Europe [-94,4755]*** ---
Adjusted Total Leverage
data distributions Western Europe mean Eastern Europe mean
data Western Europe --- [92,9498]***
data Eastern Europe [-71,9686]*** ---
*, ** , *** = significant on the 0.1, 0.05 and 0.01 level of significance, respectively
Note that the T-tests are repeated, in both directions. This means that e.g. the data
distribution of leverage from Western Europe is tested on the average leverage ratio of
Eastern Europe, as well as the data distribution of the Eastern Europe is tested on the
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxiii
average leverage ratio of Western Europe. This is done in order to test for validity of
the results. The T-test scores are different in both directions, since the size of the
tested data samples differ. However, from this validity test it can be seen that if the
difference is positive in one direction, then, the difference must be negative in the
other direction.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxiv
Appendix VIII Continued (1)
T-test results for comparing the four proxies of Leverage.
VIII.II) T-test Results of the four proxies of Leverage among Ireland, the Netherlands
and Belgium.
By calculating a T-test of one sample’s average (mean) leverage ratio over another
sample’s leverage data distribution, the T-test scores indicate whether the two samples
are statistically different from each other in respect to their leverage ratios. In case the
T-test scores are significant, the leverage ratios in the two samples are statistically
different from eachother. The higher the significance, the more certain one can be
about the statistical difference. The signs (positive or negative) in front of the T-test
scores indicate in which direction the leverage ratios of both samples are different.
Table VIII.2 T-test results of comparing the four proxies of Leverage between the
three countries: Ireland, the Netherlands and Belgium.
Total Leverage
data distributions Ireland mean Netherlands mean Belgium mean
data Ireland --- [-21,5914]*** [-24,8615]***
data Netherlands [48,6615]*** --- [2,16441]**
data Belgium [104,0485]*** [-2,5646]*** --
Short Term Leverage
data distributions Ireland mean Netherlands mean Belgium mean
data Ireland --- [-29,2974]*** [-18,1099]***
data Netherlands [34,2625]*** --- [1,2162]
data Belgium [76,4419]*** [-1,6953]* --
Long Term Leverage
data distributions Ireland mean Netherlands mean Belgium mean
data Ireland --- [-14,7431]*** [-12,9293]***
data Netherlands [21,4439]*** --- [1,3594]
data Belgium [45,7651]*** [-1,9244]** --
Adjusted Total Leverage
data distributions Ireland mean Netherlands mean Belgium mean
data Ireland --- [-32,7709]*** [-6,6527]***
data Netherlands [50,6381]*** --- [40,3581]***
data Belgium [28,3227]*** [-111,2462]*** --
*, ** , *** = significant on the 0.1, 0.05 and 0.01 level of significance, respectively
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxv
Note that the T-tests are repeated, in both directions. This means that e.g. the data
distribution of leverage from Ireland is tested on the average leverage ratio of the
Netherlands, as well as the data distribution of the Netherlands is tested on the
average leverage ratio of Ireland. This is done in order to test for validity of the
results. The T-test scores are different in both directions, since the size of the tested
data samples differ. However, from this validity test it can be seen that if the
difference is positive in one direction, then, the difference must be negative in the
other direction.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxvi
Appendix VIII Continued (2)
T-test results for comparing the four proxies of Leverage.
VIII.III) T-test Results of the four proxies of Leverage among Poland, Hungary and
Ukraine.
By calculating a T-test of one sample’s average (mean) leverage ratio over another
sample’s leverage data distribution, the T-test scores indicate whether the two samples
are statistically different from each other in respect to their leverage ratios. In case the
T-test scores are significant, the leverage ratios in the two samples are statistically
different from eachother. The higher the significance, the more certain one can be
about the statistical difference. The signs (positive or negative) in front of the T-test
scores indicate in which direction the leverage ratios of both samples are different.
Table VIII.3 T-test results for comparing the four proxies of Leverage between the
three countries: Poland, Hungary and Ukraine
Total Leverage
data distributions Poland mean Hungary mean Ukraine mean
data Poland --- [-15,5392]*** [33,5796]***
data Hungary [18,5036]*** --- [58,4557]***
data Ukraine [-34,5012]*** [-50,4739]*** --
Short Term Leverage
data distributions Poland mean Hungary mean Ukraine mean
data Poland --- [-13,2049]*** [29,1005]***
data Hungary [14,5877]*** --- [46,7536]***
data Ukraine [-30,4317]*** [-44,2246]*** --
Long Term Leverage
data distributions Poland mean Hungary mean Ukraine mean
data Poland --- [-6,6935]*** [12,7719]***
data Hungary [6,6263]*** --- [19,3148]***
data Ukraine [-16,3413]*** [-24,8072]*** --
Adjusted Total Leverage
data distributions Poland mean Hungary mean Ukraine mean
data Poland --- [-101,3011]*** [17,1153]***
data Hungary [90,8382]*** --- [106,1844]***
data Ukraine [-18,9374]*** [-131,0397]*** -- *, ** , *** = significant on the 0.1, 0.05 and 0.01 level of significance, respectively
Note that the T-tests are repeated, in both directions. This means that e.g. the data
distribution of leverage from Poland is tested on the average leverage ratio of
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxvii
Hungary, as well as the data distribution of Hungary is tested on the average leverage
ratio of Poland. This is done in order to test for validity of the results. The T-test
scores are different in both directions, since the size of the tested data samples differ.
However, from this validity test it can be seen that if the difference is positive in one
direction, then, the difference must be negative in the other direction.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxviii
Appendix IX
Robustness Check – Within the Western and Eastern European samples
In chapter Four of this research paper the differences between capital structures of
Western and Eastern European SMEs were analyzed. Each sample consisted of three
countries; each country was partly selected based on differences in credit scores,
corporate tax rates, bankruptcy and corporate governance scores, as identified in
Appendix II. The differences in these country indicators were shown to determine the
differences in capital structure of SMEs in the two tested samples.
The differences in capital structure between the two inter-country samples do not
necessarily indicate that country-specific results are similar within each sample. Since
the selected countries in each sample differ with each other based on the country
scores presented in Appendix II, it is expected that their capital structure and its
determinants are also different. In this Appendix, a review on country specific
differences within both samples is presented, similar to the prior analysis examined
between the Eastern and Western European samples in Chapter Four. Regression
analyses were conducted with country-specific dummy variables to identify the
country differences. This section will serve as a Robustness Check to the previous
analysis, in order to test the validity of the concluded relationships between regional
institutional differences and SME capital structures. Findings of differences between
the countries’ leverage ratios and independent variables can be related to the country
scores of Appendix II in a similar fashion as was performed in Chapter Four.
It was stated that a causal relationship exists between the institutional differences of
Eastern and Western Europe and SME leverage ratios and the relationship between
tax variables, bankruptcy cost variables and agency cost variables with SME leverage
ratios.
If this relationship is truly valid, similar conclusions should be found when comparing
institutional country differences with country specific SME capital structures.
Given that the expectations on country differences will hold, the evidence on a causal
relationship between the differences in country indicators and differences in capital
structure seem to be valid. The similarities found among the studied countries may
confirm that the generalization of Eastern and Western Europe holds. This analysis
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxix
will provide more insight into the strength of the observed and discussed differences
as well as the similarities in capital structure in the Eastern and Western European
SMEs.
The regression results are presented in separate tables, one for each country used as a
base group. Hence, six different tables can be found. Table IX.1 presents the results of
the Western European sample, with Ireland as basegroup. Table IX.2 presents the
results of the Eastern European sample, with Poland as basegroup. The other four
tables are presented in Appendix X and Appendix XI. The regression analyses provide
insight into country specific variance on capital structure based on the effects of taxes,
bankruptcy costs and agency costs. The country effects were tested on expectations
based on the country scores and indicators from Chapter One.
The independent variable EFFECTIVE TAX RATE appeared not to be significant for
Eastern and Western Europe. The country specific regressions also did not show any
significance on this variable. Therefore, the country analysis in this Appendix will not
include this variable and thus only two tax variables, KINK, and STANDARDIZED
KINK are included.
Simlar to the previous regression analyses, the regressions in this Appendix were
adjusted for industry effects. However, in addition, the regressions were also adjusted
for year effects. Since the focus here lies on country differences, there might be
macro-economic variables which are not included in the regression model, but which
might explain an extensive part of the variance in the data. Many macro-economic
effects take place on a country specific level, such as the interest rates, employment
figures, gross domestic product and the state of the economic cycle. By adjusting for
a year effect, as well as an industry effect, and by including shift dummies, such
unexplained variance is greatly removed.
Similar as in the central research, R-squares of the presented models for the individual
country comparisons, as presented in Table IX.1, Table IX.2, and Appendix X and XI,
cannot be interpreted without keeping in mind that they are biased. However, when
comparing the R-squares for the models within Western Europe and within Eastern
Europe, it still becomes visible that the target adjustment model is overall strong,
except for the tests on Long Term Leverage within Eastern Europe. This clearly
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxx
shows what was concluded before: small firms in Eastern Europe have great
difficulties in attracting long term debt, due to higher bankruptcy costs and greater
control from banks, who typically lend short term.
These R-squares cannot be used in controlling for the effectiveness of the target
adjustment model itself, nor the Tradeoff Theory. Target adjustment coefficients,
however, prove that all firms, in Western Europe as well as Eastern Europe, adjust
their leverage ratios towards some ‘target’. This works as indirect evidence for the
Tradeoff Theory to hold. The individual relationships between determinants and
leverage ratios, as will be presented in the following sections, show that the directions
and significance of the relations, once again prove that the Tradeoff Theory is a valid
underlying theoretical framework for this study.
An interesting observation from these target adjustment coefficients of the Western
European and Eastern European samples is that firms in Western Europe clearly
adjust their leverage ratios much faster towards their targets, especially on long term
debt. Once again, this proves the availability and access to (long term) credits to be
much stronger in Western Europe.
IX.I Within the Western European sample: Ireland, the Netherlands and
Belgium
Leverage
From the country scores in Appendix II it can be seen that corporate tax rates were
fairly similar between The Netherlands and Belgium, while considerably lower in
Ireland. This leads to the expectation that leverage ratios are lower in Irish SMEs, as
compared to Dutch and Belgian SMEs. Bankruptcy costs in the three countries are
low, and very similar, in spite of clear differences in law systems. These observed
similarities are therefore expected not to create any significant difference in leverage
ratios of SMEs in the three countries. Agency costs are somewhat different, but as
argued before, are not expected to play an important role on SME capital structures.
These three different aspects are discussed below in much greater detail. It is expected
that capital structures in the three Western European countries are mostly determined
by the tax effects, and to smaller extent by the bankrupty effect. Since the tax effect is
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxxi
expected to be the most dominant effect, Irish SMEs are expected to have lowest
leverage ratios, while Dutch and Belgian SMEs have higher, but rather similar
leverage ratios.
From the descriptive statistics (in Appendix IV.I) it seems that, indeed, leverage ratios
in the Netherlands and Belgium are very similar and only a few percentage points
higher in the Netherlands, as compared to Belgium. Leverage ratios for Ireland seem
to be substantially lower than in the other two countries. The F-tests in Table IX.1 and
Appendix X demonstrate that indeed the full models, (F-tests for shift dummies plus
slope dummies), are different from each other, thus leverage ratios are statistically
different, between the three countries. The F-tests do not detect the directions in
which the models are different. Therefore, T-tests were conducted between one
country’s data set on leverage and another country’s average (mean) leverage (see
Appendix VIII.II). The T-tests show how leverage ratios in two countries are
significantly different from each other; the tests were conducted in both directions to
control for validity. It can be further observed that on all proxies of leverage, Irish
SMEs have significantly lower leverage in their capital structure. The T-test statistics
indicate that no differences exist between Short Term Leverage and Long Term
Leverage between the Dutch and Belgian SMEs. On Total Leverage, only a small
significant difference is found. This proves that indeed the leverage ratios of the
Netherlands and Belgium are similar. When controlling by conducting the T-test the
other way around, that is, by comparing the mean leverage ratio from the Netherlands
to the data set from Belgium, it appears that the differences between the Netherlands
and Belgium are slightly bigger. However, these findings are rather a confirmation
that the data sample of the Belgian SMEs is bigger than the Dutch sample. If the
Belgian leverage ratios would be increased by less than one percent, the significant
differences between two countries are completely removed.
Thus, leverage ratios are hardly different between the Netherlands and Belgium and
they are significantly lower in Ireland. This confirms the expectations, but does not
yet prove the theoretical causes of these differences.
The next sub-sections of this appendix will therefore investigate whether this
difference in capital structure originates in the expected manner, commencing with a
discussion of taxes.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxxii
Explanatory Notes to Table IX.1:
White-heteroskedasticity adjusted 2SLS regressions, conducted in E-VIEWS, for years 2000 to 2005 on the country-
samples from Western Europe: Ireland, the Netherlands and Belgium. In order to compare the three countries, Ireland
is the base group. Eight tests on the following four different dependent variables have been done: Total Leverage,
Short Term Leverage, Long Term Leverage and Adjusted Total Leverage.
Total Leverage is calculated as: Total Liabilities / Total Assets, Short Term Leverage is calculated as Current
Liabilities / Total Assets, Long Term Leverage is calculated as Non-Current Liabilities / Total Assets and Adjusted
Total Leverage is calculated as (Total Liabilities – Payables) / Total Assets.
OPERATING RISK is computed as the standard deviation of Earnings Before Taxes over all years observed until
year t. PROFITABILITY is calculated as Earnings Before Taxes / Total Assets. GROWTH is calculated as the
percentage change of Total Assets in year t-1 to year t. LAGGED LEVERAGE is calculated as the respective
leverage ratio (the dependent variable of the model), in year t-1. Note that correlation of LAGGED LEVERAGE with
the residuals of the model is removed by including an Instrumental Variable; leverage lagged two periods (t-2).
The DUMMY variables are qualitative variables with the value 1 if the observation belongs to the group it represents.
Therefore, the shift dummy for the Netherlands has a value of 1 for a firm from the Netherlands. It has the value 0 if
the observation is from a company in any of the other countries.
The Target Adjustment Coefficient is derived from model [4] and is computed as: 1 – the coefficient of LAGGED
LEVERAGE.
R² indicates the coefficient of determination, or the explanatory power of the model as a whole. DW statistics show
whether the regression results are affected by autocorrelation. A DW statistic close to 2.0 indicates no autocorrelation.
The number of variables with a Tolerance level smaller than 0,1 indicates whether multicollinearity is apparent in the
regression model. F statistics and their significance show whether a linear relationship between the dependent
variable and any of the independent variables exists, depending what group of independent variables is included in
the F-test.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xxxiii
Table IX.1 – White-heteroskedasticity adjusted 2SLS results of the Target Adjustment Model, comparing the three countries of the Western European sample: Ireland, the Netherlands and Belgium. Ireland serves as the base group.
OPERATING RISK is computed as the standard deviation of Earnings Before Taxes over all years observed
until year t. PROFITABILITY is calculated as Earnings Before Taxes / Total Assets. GROWTH is calculated as
the percentage change of Total Assets in year t-1 to year t. LAGGED LEVERAGE is calculated as the respective
leverage ratio (the dependent variable of the model), in year t-1. Note that correlation of LAGGED LEVERAGE
with the residuals of the model is removed by including an Instrumental Variable; leverage lagged two periods
(t-2).
The DUMMY variables are qualitative variables with the value 1 if the observation belongs to the group it
represents. Therefore, the shift dummy for Hungary has a value of 1 for a firm from Hungary. It has the value 0
if the observation is from a company in any of the other countries.
The Target Adjustment Coefficient is derived from model [4] and is computed as: 1 – the coefficient of
LAGGED LEVERAGE.
R² indicates the coefficient of determination, or the explanatory power of the model as a whole. DW statistics
show whether the regression results are affected by autocorrelation. A DW statistic close to 2.0 indicates no
autocorrelation. The number of variables with a Tolerance level smaller than 0,1 indicates whether
multicollinearity is apparent in the regression model. F statistics and their significance show whether a linear
relationship between the dependent variable and any of the independent variables exists, depending what group
of independent variables is included in the F-test.
Capital Structure Determination of Small and Medium Sized Enterprises in Eastern and Western Europe
MSc Thesis in Finance & International Business A.K. Chudzinska & S.L.van der Bijl xlii
Table IX.2 – White-heteroskedasticity adjusted 2SLS results of the Target Adjustment Model, comparing the three countries of the Eastern European sample: Poland, Hungary and Ukraine. Poland serves as the base group.