The Optimal Capital Structure
Considering Firm Specific Factors:
An Empirical Analysis
Lars E. W. van der Weij
Student number: 0171522
March 30th, 2009
Master Thesis
Caput Corporate Finance
Dr. Armin Schwienbacher
Finance Group
Amsterdam graduate Business School (UvA)
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
Table of contents
Table of contents
2
1. Introduction
3
2. Firm Specific Factors
5
2.1. Uniqueness
6
2.2. Earnings Volatility
8
2.3. Past Profitability
8
2.4. Tangibility of Assets
9
2.5. Non-debt Tax Shield
10
2.6. Theoretical Model
11
2.7. Relationship between Firm Specific Factors
12
3. Empirical Research
14
3.1. Data
15
3.2. Results
18
4. Conclusion
21
5. References
22
Page 2 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
1. Introduction
‘What is the optimal capital structure?’’
This is a question often asked by financial managers, and although the corporate finance
literature covers several aspects of this question, a clear answer is yet to be found. For
instance Vojislav Maksimovic 1 argues that there are two schools of thought, which we
can call ‘’solid-financial-footing’’ and ‘’debt-makes-you-tough’’. Solid-financial-footing is
based on the fact that firms with low level of debt have the financial flexibility to respond
to competitive challenges. Debt-makes-you-though on the other hand argues that
leverage sharpens incentives and makes firms stronger competitors. It is clear that
Maksimovic focuses on the relationship between capital structure and competitiveness of
a firm. This relationship can also be translated to the type of industry and therefore also
to certain firm specific factors.
There are also other theories who address the choice of capital structure. One of
them is the ‘’trade of theory’’. This theory states that the optimal capital structure has an
amount of debt for which the marginal cost of using €1,- more or less debt financing is
equal to the marginal benefit. Therefore it is important to determine the costs and
benefits of using debt financing. In order to do this it is important to identify certain firm
specific factors that influence the amount of debt a firm should use according to the
theory. These factors are widely researched in several papers. In their paper, Titman
and Wessels (1988), introduce eight different firm specific factors that determine the
capital structure. Bradley, Jarrel and Kim (1984) even provide empirical evidence that
shows there is indeed a difference in capital structure between industries.
Another
theory is the ‘’pecking order theory’’. This theory states that companies prefer to use the
sources of finance in the following order: internal funds first, debt second and equity last.
This theory also implies that the optimal amount of debt for a firm is influenced by certain
firm specific factors.
1
V. Maksimovic, D. Brounen, A. de Jong and K. Koedijk, 2004 ‘’Topics in Corporate Finance /
Perspectives on the theory and practice of corporate finance’’
Page 3 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
The above mentioned theories all suggest that the optimal amount of debt is
influenced by certain firm specific factors. The question is what these firm specific factors
are and how they are determined within the firm. Section two outlines the firm specific
factors I will use in my thesis. In this section each firm specific factor and its theoretical
relationship with the capital structure of a firm is discussed in a subsection. Section three
describes the empirical research to control for the theoretical relationships proposed in
section two. In this section I will also describe and discuss the outcome of my research.
Finally, in section four I will present my conclusions and also propose further research.
Page 4 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
2. Firm Specific Factors
In the introduction I already mentioned the firm specific factors which in theory determine
the optimal capital structure for a firm. The diversity of corporate finance literature has
discussed several of these firm specific factors in theory, but also provided empirical
research. From this literature several factors are proven to be important. I decided to
incorporate four of these firm specific factors in my thesis, these factors are: uniqueness,
earnings volatility, past profitability, tangibility of assets and non debt tax shield.
Each of these firm specific factors will be discussed in a subsection. In this
discussion I will describe the firm specific factor and how it should influence the amount
of debt a firm chooses in its capital structure according to corporate finance theory.
Figure 1 shows the implied relationship of each firm specific factor to the amount of debt
in a firm’s capital structure.
Figure 1: Relationship between Firm Specific Factors and Capital Structure
Past
Tangibility of
Profitability
Assets
Amount of Debt
in the
Capital Structure
Earnings
Non-debt
Volatility
Tax Shield
Uniqueness
Negative Relationship
Posititve Relationship
Page 5 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
Figure 1 shows that four of the firm specific factors should have a negative
relationship with the amount of debt in a firm’s capital structure according to the theory.
This implies that when the value of the firm specific factor increases the amount of debt
in the firm’s capital structure will decrease. Only when the tangibility of the firm’s assets
increases, the amount of debt in the firm’s capital will increase as well. This positive
relationship is indicated by the green arrow, whereas the negative relationship of the
other firm specific factors is indicated by a red arrow. In the remainder of section two I
will discuss each firm specific factor and its implied relationship to the firm’s capital
structure in a separate subsection. In the final subsection I will present the theoretical
model which shows the relationship between the amount of debt in the firm’s capital
structure and each firm specific factor.
2.1. Uniqueness
The extent to which a firm is unique could influence the amount of debt a firm chooses in
its capital structure. This relationship is based on the liquidation costs imposed on
customers, employees and suppliers when the firm liquidates 2 . These liquidation costs
will be higher when a firm is more unique. This is explained by the fact that a more
unique firm produces unique products, therefore the firm needs employees with specific
skills and knowledge to produce them. The suppliers of this firm also need to be
specialized and customers will find it hard to find the same type of product or providers
of future servicing for their unique product. Therefore when a unique firm goes bankrupt
it will impose higher costs on its customers, suppliers and employees than a less unique
firm. This explains the positive relationship between the uniqueness of a firm and its
liquidation costs, and since a firm will use less debt when the liquidation costs are higher
it also indicates a negative relationship between uniqueness and the amount of debt a
firm chooses in its capital structure. In their paper, Michael Alderson and Brian Betker
(1995), provide evidence that a firm with high liquidation costs use less debt than firms
with low liquidation costs. The relationship described above can be translated to the
‘’trade off theory’’ which incorporates the benefits and costs of debt and states that a firm
will choose an optimal amount of debt considering these costs and benefits.
2
Since the liquidation costs are higher when a firm is more unique I do not incorporate the
liquidation costs as a separate firm specific factor.
Page 6 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
As mentioned above the uniqueness if a firm is related to the type of product the
firm produces. The type of product is often categorized as either a differentiated / unique
product or a commodity. In their paper, Stefan Arping and Gyöngyi Lóránth (2002),
indicate that a firm who manufactures a unique good should use less debt in its capital
structure. When this type of firm uses too much debt and faces bankruptcy potential
customers will not buy the product since they are not certain the company is able to
provide future service of deliver add-on products. This relationship is not important when
a firm produces a commodity since this type of product does not require after sale
service. The relationship between the type of product and the amount of debt a firm
should use in its capital structure is also discussed by Titman (1984), in his paper Titman
provides a figure which shows this relationship. I have used this figure in a different way
to illustrate the relationship between the uniqueness of a firm and the amount of debt in
a firm’s capital structure.
Figure 2: The amount of debt compared to the uniqueness of a firm 3
Operating value
Amount of debt
d*
Net liquidation value
(less unique firm)
d**
Net liquidation value
(more unique firm)
n**
#
n*
States of nature
Net liquidation value = liquidation value – liquidation costs
Figure 2 shows that the optimal amount of debt for a unique firm (d**) is lower than the
optimal amount of debt for a less unique firm (d*),
When a company produces a more unique product the firm will make higher
expenses such as selling, salaries, R&D and cost of goods sold in order to sell their
product compared to a firm with a less unique product.
3
Source: Titman,S ‘The effect of capital structure on a firm’s liquidation decision’ (1984) page 147
Page 7 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
2.2. Earnings Volatility
As mentioned in the introduction the amount of debt chosen by a firm could be
influenced by the thought that a firm prefers financial flexibility. In the introduction this is
explained by the ‘’solid-financial-footing theory’’. The degree to which the earnings of a
firm vary from year to year, referred to as earnings volatility, is an important determinant
of financial flexibility. This suggests that earnings volatility is of influence when a firm
determines the amount of debt in its capital structure. That this relationship exists has
already been proven by Michael Bradley, Gregg Jarrel and Han Kim (1984). In their
research they find that the volatility of earnings is an inverse determinant of the amount
of debt in a firm’s capital structure, which means that an increase in the volatility of
earnings will cause a decrease in the amount of debt. Also John Graham and Campbell
Harvey (1999) find evidence for this relationship in their paper.
This negative relationship can be explained by the following theory. When a firm
has to deal with volatile earning it is very difficult to budget the earnings for upcoming
years, therefore it will be difficult to issue new debt since there is no security of
repayment of debt and payment of interest. A firm that has steady revenues has more
certainty of the level of earnings in upcoming years, therefore it will be easier for this firm
to issue new debt, since this firm is able to provide certainty regarding payment of
interest and repayment of the loan. It is clear to see that this implies that a firm with
volatile earnings should use less debt than a firm with steady earnings. This relationship
is not only connected to the ‘’solid-financial-footing theory’’ but also to the ‘’trade off
theory’’ mentioned before. Higher volatility of earnings means that a firm is less likely to
be able to repay the loan and pay the interest, therefore increases the possibility of
bankruptcy. Therefore the costs of debt are higher for a firm with more volatile earnings,
forcing the firm to issue less debt than a firm wit less volatile earnings.
For a firm with less volatile earnings the deviation of the earnings divided by
sales from the average amount of earnings divided by sales over a period of time is
lower than for a firm with more volatile earnings.
2.3. Past Profitability
A firm specific factor which gives the impression to be the same as volatility of earning is
past profitability. Although figure 1 shows this firm specific factors also has a negative
relationship with the amount of debt the underlying theory and explanation differs
Page 8 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
compared to volatility of earnings. Whereas the relationship of earnings volatility can be
referred to the ‘’trade of theory’’ the relationship of past profitability is explained by the
‘’pecking order theory’’. Donaldson (1961) states that according to the ‘’pecking order
theory’’ a firm prefers internal funds for investments and financing to external funds.
Within external funds issuing debt is preferred to issuing equity.
Therefore a more profitable firm has more earnings to use for financing and
accordingly needs less debt in her financing needs, often these firms also use their
earnings to pay down debt and therefore have less debt in their capital structure than
firms who are less profitable. As mentioned before Donaldson found evidence in his
paper that firms prefer retained earnings to fund new investments rather than debt, but
prefer debt to equity financing. This finding implies that firms accumulate retained
earnings and therefore will have less debt in their capital structure when they are
profitable and more debt in their capital structure when they are unprofitable or at least
less profitable. A firm with high past profitability will have a higher net revenue compared
to sales in the previous year than firm who has a lower past profitability.
There could also be another explanation why firms that are more profitable have
less debt in their capital structure. Since a more profitable firm is valued higher its stock
price will also be higher, making it more attractive for the firm to issue new equity.
Although this seems like a good explanation research shows that firms prefer to issue
debt to equity for financing purposes. This is mainly caused by the costs associated with
issuing equity, such as asymmetric information and transaction costs.
2.4. Tangibility of Assets
Another firm specific factor that influences the amount of debt in a firm’s capital structure
is the asset structure, or better said, the tangibility and thus collateral value of assets.
Theory suggests that when a firm has more tangible assets it can use these assets as
collateral for issuing debt. Since these assets will have a certain known value, banks are
more willing to provide loans to firms who have more tangible assets in place. Because
of this advantage it is expected that firms with more assets that can be used as collateral
will issue more debt than firms who have less assets that can be used as collateral.
Therefore the tangibility of assets is positively related to the amount of debt in a firm’s
capital structure as shown by figure 1. A firm that has more tangible assets will have
Page 9 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
more property, plant and equipment compared to total assets than a firm with fewer
tangible assets.
Erasmo Giambona and Armin Schwienbacher (2007) proved in their paper that
there is indeed a positive relationship between tangibility of assets and the amount of
debt a firm uses in its capital structure. Gambiona and Schwienbacher only incorporate
property, plant and equipment as tangible assets. Their research goes further and also
proves that for financially constrained firms only hard tangible assets, namely land an
buildings, are suitable as collateral when issuing debt. The most important conclusion
however is that when firm’s assets are more tangible it is able to issue more debt and
will use this advantage, leading to a higher amount of debt in its capital structure. The
opposite also holds, namely that a firm with less or almost no tangible assets will have a
lower amount of debt.
In their paper, Sheridan Titman and Roberto Wessels (1988), discuss the effect
of debt on managerial behaviour. According to their paper higher debt levels may
prevent managers from consuming more perquisites than is desirable. This is caused by
the fact that firms with high levels of debt are closely monitored by banks and
bondholders. For firms with less collateralizable assets it is more difficult to monitor,
therefore firms with less tangible assets might choose higher amounts of debt in order to
limit their managers consumption of perquisites. According to this theory the relationship
between the tangibility of assets and the amount of debt in a firm’s capital structure could
be negative. I do not expect this theory to be significant and therefore expect this
relationship to be positive as shown in figure 1. I also expect this because previous
research has proven that this relationship is indeed positive.
2.5. Non-debt Tax Shield
One of the benefits of debt is the tax shield of debt: due to the interest payments on debt
which are tax deductible, debt has an advantage over equity since dividend payments
are not tax deductible. A firm that has more debt also haa higher tax shield advantage,
but since the corporate tax rate is the same for firms in a country this does not explain
the difference in capital structure between firms in the same country.
Besides the debt tax shield there are also other tax shields, these tax shields are
related to non-debt items and therefore they are called non-debt tax shields. Examples
of non-debt tax shields are depreciation and amortization. Firms who have high amounts
Page 10 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
of investments or depreciation benefit from the tax shields on these expenditures since
they pay less taxes due to the lower taxable income, therefore these firms are less
interested in the tax benefit of debt and thus have a lower amount of debt in their capital
structure. The degree of this non debt tax shield is determined by the amount of
depreciation and amortization compared to the elements that cause the depreciation and
amortization.
The theory described above implies that the relationship between the amount of
non-debt tax shield and the amount of debt in a firm’s capital structure should be
negative, as illustrated in figure 1 at the beginning of section two.
2.6. Theoretical Model
According to the theoretical discussion in the previous subsections the model should
look like this:
ML = X + β1U + β2EV + β3PP + β4TA + β5NdTS
Where:
ML
= Market Leverage
X
= The amount of debt beneficial for every firm
U
= Uniqueness
EV
= Earnings Volatility
PP
= Past Profitability
TA
= Tangibility of Assets
NdTS = Non-debt Tax Shield
Considering the theoretical discussion in the previous subsections regarding the firm
specific factors I expect the values of β1, β2, β3, and β5 to be negative and the value of β4
to be positive.
In section three I will present the empirical research done to control the
theoretical relationships described above and to obtain values for X and each β in order
to indicate how much debt is beneficial for each firm and how the relationship is for each
firm specific factor.
Page 11 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
2.7. Relationship between Firm Specific Factors
The model above describes the relationship between each firm specific factor and the
amount of debt in the firm’s capital structure. However the firm specific factors also have
a relationship with each other. If firm specific factor A has a negative relationship with the
amount of debt in the firm’s capital structure but also a negative relationship with another
firm specific factor B and factor B also has a negative relationship with the amount of
debt, the relationship between the two factors will have an opposite effect on the amount
of debt compared to the effect factor A will have. In the figures below I will graphically
describe the above mentioned relationships.
Figure 3: Legend to explain the figures below
Negative relationship
B
Variable decreases
Debt
Debt decreases
A
Variable increases
Debt
Debt decreases
Figure 4: Both factors have a negative relationship with debt and a negative relationship
with each other
Debt
Debt
Factor A
A
B
Factor B
Debt
Debt
B
A
Debt
It is obvious that the described situation is also valid for two negative
relationships after each other and a positive and negative relationship after each other.
In the empirical research it is therefore important to exclude the relationship between the
firm specific factors when the relationship between each firm specific factor and the
optimal amount of debt is determined. It is therefore necessary to perform a multivariable
regression analysis on the complete data set.
Page 12 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
Section three will describe the empirical research I have done. First I will
explain how I will calculate the different firm specific factors, in line with the theoretical
discussion of the firm specific factors in section 2. After that I will describe how I
collected the data and how I determined the values for the model described in section
2.6. Finally I will present my conclusions and propose ideas for further research.
Page 13 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
3. Empirical Research
For my empirical research I will collect the financial data – balance sheet and profit and
loss account – from 121 different firms for the past 13 years from the Dutch industry. I
will also collect the number of shares outstanding and the stock price for these firms for
each year. I will need this in order to calculate the market value of equity which is
needed to calculate the market leverage of each firm in each year.
From this data set I will select the data types I need to calculate the variables as
described in the model from section 2.6. Below I indicate how I will calculate each
variable:
Table 1: Description and calculation of variables.
Variable Description
Calculation
Y
Book value of debt / Market value of assets
Market Leverage
Where; Market value of assets = Book value of assets
- Book value of equity + Market value of equity
Where: Market value of equity = #shares * stock price
U
Uniqueness
R&D costs and diverse costs to generate sales
divided by sales.
EV
Earnings Volatility
Earnings divided by sales compared to average
earnings divided by sales for the complete period.
PP
Past Profitability
NOPAT previous year divided by sales previous year.
TA
Tangibility of Assets
Property, Plant and Equipment divided by total assets.
NdTS
Non-debt Tax Shield
Depreciation, depletion and amortization divided by
the total amount of assets that cause the depreciation,
depletion and amortization.
After I have calculated these variables I will perform a multivariable regression analysis
to determine the relationship between each firm specific factor and the amount of debt.
The regression analysis will also show the optimal amount of debt for each firm, which is
represented by the value of Y when the firm specific factors are all zero. These
calculations will lead to values for X and all the β’s, as mentioned in the model described
in section 2.6.
Page 14 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
3.1. Data
As mentioned above I selected data types from the complete DataStream data set in
order to calculate the variables mentioned in table 1 above. Table 2 outlines the data
types I selected to calculate the variables, table 3 shows how I used the data types to
calculate the variables.
In table 2 on the next page, I have also calculated two data types from the data
types collected from data stream in order to calculate the variable EV: Earnings Volatility.
I have calculate the earnings divided by sales and the average earnings divided by sales
for the entire period, these are represented by the coloured parts of the table and
calculated as described below:
EARNINGS BEFORE INTEREST AND TAXES (EBIT)
Earnings divided by sales =
NET SALES OR REVENUES
Average earnings divided by sales = average of calculated variable for entire period
I used the data types from table 2 to calculate the variables I need for my model.
How I used the data types to calculate the variables is presented in table 3 on page 17.
Page 15 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
Table 2: Data types selected for the different variables
Data type
Description
For variable
WC03255 TOTAL DEBT
Y:Market Leverage
WC02999 TOTAL ASSETS
Y:Market Leverage
WC03998 TOTAL CAPITAL
Y:Market Leverage
(NOSH)
Number of shares outstanding
Y:Market Leverage
(P)
Price per share
Y:Market Leverage
SELLING, GENERAL & ADMINISTRATIVE
WC01101 EXPENSES
U: Uniqueness
WC01084 SALARIES AND BENEFITS EXPENSES
U: Uniqueness
COST
OF
GOODS
SOLD
(EXCL
WC01051 DEPRECIATION)
U: Uniqueness
WC01201 RESEARCH & DEVELOPMENT
U: Uniqueness
WC01001 NET SALES OR REVENUES
U: Uniqueness
PROPERTY, PLANT AND EQUIPMENT WC02501 NET
TA: Tangibility of Assets
WC02999 TOTAL ASSETS
TA: Tangibility of Assets
DEPRECIATION,
DEPLETION
AND
WC01151 AMORTIZATION
NdTs: Non-debt Tax shield
WC01149 AMORTIZATION OF INTANGIBLES
NdTs: Non-debt Tax shield
WC01150 AMORTIZATION OF DEFERRED CHARGES
NdTs: Non-debt Tax shield
PROPERTY, PLANT AND EQUIPMENT WC02501 NET
NdTs: Non-debt Tax shield
WC02649 TOTAL INTANGIBLE OTHER ASSETS - NET
NdTs: Non-debt Tax shield
EARNINGS
BEFORE
INTEREST
AND
WC18191 TAXES (EBIT)
EV: Earnings Volatility
WC01001 NET SALES OR REVENUES
EV: Earnings Volatility
earnings divided by sales
EV: Earnings Volatility
avg. earnings divided by sales
EV: Earnings Volatility
WC01751 NET INCOME AVAILABLE TO COMMON
PP: Past Profitability
WC01001 NET SALES OR REVENUES
PP: Past Profitability
Page 16 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
Table 3: Calculation of variables for model
Variable
Calculation
Y:Market Leverage
TOTAL DEBT / ( TOTAL ASSETS - TOTAL CAPITAL +
Number of shares outstanding * Price per share)
U: Uniqueness
(
SELLING,
GENERAL
&
ADMINISTRATIVE
EXPENSES + SALARIES AND BENEFITS EXPENSES
+ COST OF GOODS SOLD (EXCL DEPRECIATION) +
RESEARCH & DEVELOPMENT ) / NET SALES OR
REVENUES
TA: Tangibility of Assets
PROPERTY, PLANT AND EQUIPMENT - NET / TOTAL
ASSETS
NdTs: Non-debt Tax shield
( DEPRECIATION, DEPLETION AND AMORTIZATION
+
AMORTIZATION
OF
INTANGIBLES
+
AMORTIZATION OF DEFERRED CHARGES ) /
( PROPERTY, PLANT AND EQUIPMENT - NET +
TOTAL INTANGIBLE OTHER ASSETS - NET )
EV: Earnings Volatility
Absolute value of [ ( earnings divided by sales - avg.
earnings divided by sales ) / avg. earnings divided by
sales ]
From the calculated variables I excluded all the calculations which involved
dividing by a data type with value zero since dividing by zero will result in an error. The
resulting variables represent a complete data set of 8130 variables which is the basis for
the regression analysis. The complete set of variables is included in appendix A.
Page 17 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
3.2. Results
After performing a regression analysis with a 95% reliability level on the complete data
set the information presented in table 4 is given. Translating this data into the model
presented in my thesis results in the information in table 5.
Table 4: Regression analysis
Results from regression analysis
Intersection point
U: Uniqueness
EV: Earnings Volatility
PP: Past Profitability
TA: Tangibility of Assets
NdTs: Non-debt Tax shield
Coefficients
P-value
0,1073348806
0,0134603336
-0,0020954392
0,0106332965
0,6011505525
0,0000006167
0,0000000019
0,0000000000
0,1754970981
0,0004699439
0,0000000000
0,9998540495
Table 5: Values for model
Values for model
X = 0,10733488
U: Uniqueness
β
= 0,01346033
EV: Earnings Volatility
β
= -0,00209544
PP: Past Profitability
β
= 0,01063330
TA: Tangibility of Assets
β
= 0,60115055
NdTs: Non-debt Tax shield
β
= 0,00000062
Conclusion
Theory
Positive
relationship
Negative
relationship
Positive
relationship
Positive
relationship
Positive
relationship
Negative
relationship
Negative
relationship
Negative
relationship
Positive
relationship
Negative
relationship
The information from table 4 and 5 suggests the model should look like this:
ML = 0,1073 + 0,0135 U – 0,0021 EV + 0,0106 PP + 0,6012 TA + 0,0000 NdTS
However, since the p-values for each variable presented in table 4 indicate that the
implied values for β in table 5 are more likely to be zero for variables EV: Earnings
Volatility and NdTs: Non-debt Tax shield, these variables should be left out of the
regression analysis. After performing a second regression analysis, but without
incorporating the above mentioned variables, the information and variables for the model
are as presented in table 6 and 7.
Table 6: Regression analysis without variables EV and NdTs
Page 18 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
Results from regression analysis
Coefficients
P-value
Intersection point
U: Uniqueness
PP: Past Profitability
TA: Tangibility of Assets
0,0000000043
0,0000000000
0,0004573799
0,0000000000
0,1016843815
0,0134180403
0,0106195755
0,6058783574
Table 7: Values for model without variables EV and NdTs
Values for model
X = 0,10168438
U: Uniqueness
β
= 0,01341804
PP: Past Profitability
β
= 0,01061958
TA: Tangibility of Assets
β
= 0,60587836
Conclusion
Theory
Positive
relationship
Positive
relationship
Positive
relationship
Negative
relationship
Negative
relationship
Positive
relationship
The p-values from table 6 indicate that the implied relationships as presented by the
values for β in table 7 are not likely to be zero. Therefore it is not necessary to leave any
of these variables out of the regression analysis. I also preformed a correlation analysis
on the complete dataset. The results form this analysis is presented in table 8.
Table 8: Correlation analysis
Y
U
TA
NdTs
EV
PP
Y
U
TA
NdTs
EV
PP
1,00000
0,27029
0,33134
-0,03158
-0,05108
-0,02434
1,00000
-0,04341
-0,00726
0,03281
-0,43784
1,00000
-0,05834
-0,08066
0,06899
1,00000
0,08149
-0,07197
1,00000
-0,01536
1,00000
This correlations analysis shows that the variables U: Uniqueness and TA:
Tangibility of Assets have a significant positive relationship with Y:Market Leverage
compared to the other variables. Furthermore, the analysis shows that only U:
Uniqueness has a significant relationship with another variable, PP: Past Profitability. All
the other variables have a relatively weak and therefore insignificant relationship with the
other variables. Since only variables U: Uniqueness and TA: Tangibility of Assets have a
significant positive relationship with Y:Market Leverage it seems obvious to perform a
Page 19 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
regression analysis with only these two variables, However, since U: Uniqueness and
PP: Past Profitability have a significant relationship with each other I can not leave PP:
Past Profitability out of the regression analysis. But since TA: Tangibility of Assets has
the strongest relationship with Y:Market Leverage in terms of correlation, β and p-value
and has no significant relationship with the other variables, I wanted to see what a
regression analysis with only the variable TA: Tangibility of Assets would show. The
results are presented in table 9 and 10.
Table 9: Regression analysis with only variable TA
Results from regression analysis
Coefficients
P-value
Snijpunt
TA: Tangibility of Assets
0,0000000000
0,0000000000
0,1249515460
0,5922815373
Table 10: Values for model with only variable TA
Values for model
X = 0,12495155
TA: Tangibility of Assets
β
= 0,59228154
Conclusion
Theory
Positive
relationship
Positive
relationship
The p-value in the regression analysis shows that it is not likely for β to be zero,
therefore we can assume that the value for β is significant. The same reasoning holds
for the value of X, the intersection point reresenting the value of Y:Market Leverage
when the variable TA: Tangibility of Assets is zero.
However, regarding the results from the regression analysis presented in table 6
and 9 and the correlation analysis presented in table 8, it is best to use the results from
table 6 for the model presented earlier. The values for this model are already presented
in table 7, translated into the model this leads to:
ML = 0,1017 + 0,0134 U + 0,0106 PP + 0,6059 TA
Page 20 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
4. Conclusion
The model presented in the previous section suggests the following conclusions;
1. For each firm a Market Leverage (ML) of 0,1017 should be beneficial.
2. For each increase of Uniqueness (U) by 1, the Market Leverage (ML)
increases by 0,0134.
3. For each increase of Past Profitability (PP) by 1, the Market Leverage (ML)
increases by 0,0106.
4. For each increase of Tangibility of Assets (TA) by 1, the Market Leverage
(ML) increases by 0,6059.
The first conclusion is easy to understand and even reasonable compared to the
average Market Leverage of 0,3016 and the fact that the variable with the strongest and
biggest positive relationship with the Market Leverage, the Tangibility of Assets, will
either be zero or higher. Given the high value of the average Market Leverage it could
be interesting for further research to conduct a survey among financial managers or
CFO’s whether they have a fixed amount of debt they hold in their capital structure
regardless of the other financial data and resulting firm specific factors. In this survey it is
also possible to investigate the different motivations for financial managers or CFO’s to
use more or less debt as a financing tool.
The second and third conclusion is more puzzling. The empirical research
indicates that the relationship of Uniqueness and Past Profitability with Market Leverage
is, although small, positive. Whereas the theory predicts that this relationship should be
negative. Perhaps a more unique company needs to invest more and therefore needs
more financing, which leads to a higher market leverage. The relatively strong positive
correlation might prove this conclusion to be correct, further research could be done to
explain this relationship. Past Profitability is more difficult to understand since the
correlation of this variable is negative and small, indicating a weak negative relationship,
therefore I can not prove the third conclusion mentioned above.
The fourth and last conclusion is expected according to the theory and also very
understandable in light of the found regression and correlation coefficients, therefore the
main conclusion of my empirical research is that there is a relatively strong and high
positive relationship between the Tangibility of Assets and the Market Leverage of a firm.
Page 21 of 22
Lars E. W. van der Weij:
The Optimal Capital Structure Considering Firm Specific Factors: An Empirical Analysis
5. References
Alderson, M. J., and B. L. Betker, 1995, “Liquidation Costs and Capital Structure,”
Journal of Financial Economics, 39, 45-69.
Arping S.,and G. Loranth, 2002, “Corporate Leverage and Product Differentiation
Strategy,” Discussion Paper No. 3451, July 2002.
Bradley, M., G. Jarrell, and E. Han. Kim., 1984, “On the Existence of an Optimal
Capital Structure: Theory and Evidence.” Journal of Finance 39, 3, 857-878.
Chevallier, J. A., 1995b, “Capital Structure and Product-Market Competition: Empirical
Evidence from the Supermarket Industry,” American Economic Rev. 85, 415-435.
Giambona, E. and Schwienbacher, A., 2007, “Debt Capacity of Tangible Assets: What
is Collateralizable in the Debt Market?”
Graham, John R. and Harvey, Campbell R., 2001, “The theory and practice of
corporate finance: evidence from the field,” Journal of Financial Economics, 60,
187-243.
Hovakimian, A., Opler, T. and Sheridan, T., 2001, “The Debt-Equity Choice”, The
Journal of Financial and Quantitative Analysis, 36, 1-24.
Lang, L. H. P., E. Ofek, and R. Stulz, 1996, “Leverage, Investment, and Firm Growth,”
Journal of Financial Economics 40, 3-30.
Maksimovic V., Brounen D., de Jong A. and Koedijk K, “Topics in Corporate Finance
(8) Perspectives on the Theory and Practice of Corporate Finance” 2004,
ISBN 90-805728-8-8
Miao, J., 2005, “Optimal Capital Structure and Industry Dynamics,” The Journal of
Finance 6, 2621-2659.
Modigliani, F., and M. Miller, 1958, “The Cost of Capital, Corporation Finance and the
Theory of Investment,” American Economic Review 48, 261-297.
Phillips, G. M., 1995, “Increased Debt and Industry Product Markets: An Empirical
Analysis,” Journal of Financial Economics 37, 189-238.
Titman, S., 1982, “Determinants of Capital Structure: An Empirical Analysis.” Working
Paper, UCLA.
Titman, S., 1984, “The Effect of Capital Structure on the Firm’s Liquidation Decision.”
Journal of Financial Economics 13, 137-151.
Titman, S., and R. Wessels., 1988, “The Determinants of Capital Structure Choice.”
Journal of Finance 43, 1-20.
Page 22 of 22