Modeling the Relationship between Capital Structure and Company
Value in the Perspective of Agency and Trade-Off Theory
WAWAN ICHWANUDIN1*, ENOK NURHAYATI1, CEP JANDI ANWAR2
1Department of Management,
Sultan Ageng Tirtayasa University,
INDONESIA
2Department of Economics,
Sultan Ageng Tirtayasa University,
INDONESIA
*Corresponding Author
Abstract: - This study is carried out to investigate the link between capital structure and company value from
the perspective of agency and trade-off theory. This model formulates that the use of debt can increase
profitability through monitoring mechanisms and disciplining by creditors. Profitability can reduce and increase
financial distress and company value. The sample consists of companies in the LQ45 index for the period 2017-
2020 and model testing uses path analysis. The results show that (i) there is a positive influence of capital
structure on profitability, (ii) profitability significantly increases company value (iii) profitability affects the
decrease in financial distress (iv) Financial distress significantly increases company value, (v) profitability and
financial distress do not mediate capital structure on company value, (v) profitability mediates the influence of
capital structure on company value (vi). These results have important implications, where an increase in debt
positively affects company value due to the supervisory mechanism and discipline from the debtor. Meanwhile,
the theoretical implication is to confirm agency theory and trade-off theory.
Key-Word: - Agency Theory, Trade-off Theory, Capital Structure, Profitability, Financial Distress.
Received: September 27, 2022. Revised: August 19, 2023. Accepted: September 17, 2023. Published: October 9, 2023.
1 Introduction
Studies on company value are vital for investors and
companies because the concept is related to
investment decisions and the sustainability of the
capital market. Several theories explain different
views on the correlation between company value
and capital structure.
According to, [1], there is no optimum capital
structure (irrelevance theory), meaning that the
variable does not affect company value. However,
[2], revised previous results, where capital structure
has a significant impact on company value because
of market inefficiencies. The reduction of company
tax liabilities leads to a positive impact and the
modification of the Modigliani and Miller (MM)
theory is commonly referred to as the MM
Irrelevance Theory.
Considering the weakness of MM Irrelevance
Theory MM, optimum capital structure is conducted
by using debt, which influences the likelihood of the
company becoming bankrupt. trade-off theory is
designed to consider the risk of bankruptcy.
According to, [3], the decision to use debt is
dependent on the degree of advantages to be
obtained. Conversely, the use may not be deemed
necessary when the associated drawbacks and
potential losses outweigh the benefits. The use of
debt increases and decreases company and company
value to a certain percentage.
Agency theory in, [4], explains that debt
financing reduces managers who try to maximize
their profits by using free cash flow. Debt financing
increases agency costs, but lenders include loan
terms in the contract as a monitoring tool. The
covenants are designed to restrict managers from
overinvesting in risky projects.
Numerous studies show that the use of debt in
capital structure enhances company value, [5], [6],
[7], [8]. However, other results report a detrimental
impact because increasing debt is considered a risk
that will reduce company value and the benefits are
smaller than the costs of financial difficulties, [9],
[10], [11], [12].
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Previous studies showed that Debt Equity Ratio
directly impacted Company Value, [4], [6].
According to optimum capital structure, [5], capital
structure can have positive and negative effects on
company value. Previous results have not explained
the mechanism of the link between the two
variables, hence this study is conducted to fill the
gap.
The current study aims to examine the impact of
Capital Structure on company value from the
perspective of agency and trade-off theory. To
realize the objective, a model that formulates capital
structure to increase company value is built.
The novelty is to develop a model from the
perspective of agency theory and trade, where the
optimum capital structure can be obtained from the
use of debt. Optimum capital structure from the use
of debt can increase company value. The model
built will then be tested to explain the effects of
capital structure on company value. Therefore, this
study explains trade-off and agency theory
concerning the use of debt.
2 Theoretical Review
The theoretical basis used is agency and irrelevance
theory for building models that explain the use of
debt. Agency theory shows that principals and
agents have different interests. Conflicts of interest
arise due to information asymmetry between owners
and management, [13]. Meanwhile, management
possesses a deeper understanding of company
operations and activities due to their direct
involvement in its day-to-day management,
surpassing the knowledge of the owner. Conflicts of
interest can arise between shareholders and
bondholders within the company ownership
structure, [14], [15].
The use of debt in capital structure can
overcome agency costs arising from conflicts of
interest related to free cash flow. In addition, [4],
explains that agency problems associated with free
cash flow can be controlled by increasing the use of
debt in capital structure. Debt is used as a control
mechanism where lenders and shareholders become
the main parties in company governance structure
and, [16], states the point of view in agency theory.
Moreover, [17], explains that company value is
higher than those without debt.
Agency theory states that the optimum capital
structure with the use of debt can increase company
value. The study, [2], argues that companies with
leverage have more value than those without
leverage. Furthermore, [17], reports that the value of
companies with greater debt is higher than those
without debt.
MM created the trade-off theory and, [1],
reports that the use of equity or debt as a trade-off
between the expense of bankruptcy and the interest
tax shield is determined by the trade-off hypothesis.
According to, [2], [18], [19], the risks presented by
future bankruptcy are exchanged by the company
for the tax advantages of debt financing. The
company stands to benefit from the tax advantages
associated with interest payments when financing an
investment using debt.
2.1. Effect of Capital Structure on
Profitability
The use of debt in capital structure may enhance the
profitability of the company, [20]. This is in line
with agency theory that a company financed by
most of the debt in its capital structure will make
managers have less power in decision-making. Debt
can be used as a control mechanism in company
governance and this is supported by, [14], where a
company reduces the risk of bankruptcy to make
optimal business decisions. In addition, [21],
proves that long-term debt is a strong disciplinary
tool against company governance allowing a
company to generate positive profitability, [22],
[23], [24]. The study, [25], explains the other side
of the use of debt in capital structure, where
companies with more debt financing in their capital
structure avoid the tendency of managers to misuse
free cash flow. Therefore, the first hypothesis states
that capital structure has a positive effect on the
profitability of the company.
2.2 Effect of Profitability on Financial
Distress
Increased profitability as an impact of the use of
debt in capital structure as explained in the
formulation of hypothesis 1, strengthens other
financial performance. Improved financial
performance is also needed to keep the company
from financial distress. Meanwhile, [26], explains
that a company gains high confidence from its
stakeholders by producing strong financial results,
conveying favorable information, and attracting
investors and creditors.
An increase in profitability shows that the
company has a better financial condition and can
avoid the possibility of difficulties. The study, [27],
suggests the significance of profitability ratios in
identifying financial difficulties and argues that
companies with high profitability face less
likelihood of financial distress. According to, [28], a
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company with high profitability has a large profit
devoid of financial distress. In addition, [29], reports
that companies experiencing financial distress
generate low profitability. The second hypothesis
states that the increase in profitability decreases
financial distress.
2.3 Effect of Profitability on Company Value
Continuing the first hypothesis, the model built from
agency theory is that the use of debt can increase
profitability and company value. Agency theory
explains that the conflict between agents and
creditors can be resolved by the ability to generate
profits, [26]. The company has a good financial
condition and will be responded to by increasing
company value with high productivity. According
to, [30], profitability with ROE and ROA indicators
shows positive and statistically significant
regression results on company value. Meanwhile,
[31], explains that the benefits of using debt can
increase expectations of higher future profitability
due to low financial difficulties. As stated by, [32],
the benefit of using external financing in the form of
debt can result in good future investment projects
with positive NPV. Future profitability resulting
from the benefits of using debt can provide positive
sentiment on the stock market, [33]. In trade-off
theory, [3], the variable is generated from the ability
to use sources of funds from debt to increase share
value. Therefore, the third hypothesis states that
profitability has a positive effect on company value.
2.4 Effect of Financial Distress on Company
Value
The first and second hypotheses with the agency
theory perspective show that the use of debt has the
potential to enhance profitability. Increased
profitability serves as a safeguard against the
occurrence of financial distress. Consequently, a
lower incidence of financial distress contributes
positively to company value. To assess financial
distress, the Alman Z-score model is used, where a
higher value indicates a reduced risk of financial
distress. The increased Z-score correlates with an
augmentation in company value, as shown by an
increase in the PBV ratio. There exists a positive
relationship between the Z-score and PBV, implying
a positive relationship between the Z-score value
and PBV ratio. However, the risk of financial
distress has a detrimental impact on the valuation of
shares, potentially leading to a decrease in share
value. According to, [19], companies with high
levels of financial distress tend to carry out accrual
earnings management and have less real income.
The study in, [34], reports that financial distress is a
systematic risk of reducing asset prices. The study,
[35], states that the risk of financial distress puts
pressure on falling stock prices.
Another study conducted by, [36], examines the
other side of financial distress, where businesses use
restructuring methods including lowering dividends
or modifying capital structure in facing difficulties.
In recovering financial conditions, investment and
dividends are reduced to impact market confidence
and company value. Therefore, the fourth
hypothesis states that the avoidance of financial
distress increases company value.
2.5 Mediation Profitability and Financial
Distress on Company Value
Agency Theory put forward by, [4], postulates that
the control of excessive use of free cash flow by
management is achieved through the use of debt.
This method avoids risky investments, [25], but the
use of debt also makes management more careful
because the impact increases bankruptcy. Trade-off
and agency theory state that capital structure can
increase the use of debt functioning as a control
mechanism for the tendency of managers to behave
opportunistically. The use of debt needs to be
accompanied by the principle of prudence resulting
from the risk of using debt to improve profitability
performance exceeding the risk of financial distress.
Therefore, the fifth hypothesis states that
profitability and financial distress mediate the effect
of capital structure on company value.
3 Methodology
3.1 Sample
This study was conducted to prove agency theory on
how the use of debt has a positive effect on
company value. The sample used was a company in
the LQ-45 index during 2017-2020 which
consistently remained listed in LQ-45. The reason
for selecting a company in the LQ-45 index was
because the stocks included in the index had
financial conditions, growth prospects, and high
transaction value. Therefore, the use of debt was not
due to financial problems because of the growth
prospects. The sorting of the study years 2017-2020
ensures that the results are tested under any
conditions.
3.2 Variable
The variables used together with their abbreviations
and definitions are provided in Table 1.
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Table 1. Variable Definition
Variable
Abbreviation
Definition
Dependent Variable
Debt To Equity Ratio
DER
Total debt to total equity ratio
Intervening Variables
Profitability
ROA
Net income to total assets ratio
Financial Distress
Z
Z-Score of company
Dependent Variable
Price Book Value
PBV
The ratio of market price per share to
book value per share
3.3 Data and Analysis Methods
This study aims to answer the problem of a path
analysis model derived from four sub-structure
models, which is a regression equation using panel
data. Therefore, panel data analysis is used for each
sub-structure to obtain path coefficients. The
following is a sub-structure model based on the
study model.
ROA = a1 + b1 DER + e1 (sub-structure 1)
Z-Score = a2 + b1 ROA + e2 (sub- structure 2)
PBV = a3 + b1 Z-score + e3 (sub- structure 3)
PBV = a4 + b1 DER + b2 ROA + b3 Z-score + e1
(s4b- structure 4)
The pooled ordinary least squares (pooled-
OLS), fixed effects model (FEM), and random
effects model (REM) for four regression models
were used in this investigation. To select the most
suitable, the Chow test was used to verify a better
model between OLS and FEM. The basis for the
Chow test decision is seen from the cross-section
chi-square probability value, with the H0 criterion:
Common Effect Model or CEM. H1: Fixed Effect
Model or FEM.
Breusch and Pagan Lagrange multiplier to
check the most suitable model between REM and
CEM. The basis for decision-making in the
Lagrange multiplier is seen from the critical value of
the chi-squares statistic with the criterion H0:
Random Effect Model. H1: Common effect.
The Hausman test is used to determine which
model between REM and FEM is more appropriate.
The random cross-section probability value provides
the framework for the decision-making of the
Hausman test. Furthermore, with the criteria H0:
Random Effect Model or REM. H1: Fixed Effect
Model is FEM.
The multicollinearity test is required to
determine when there is a correlation between the
independent variables. There is a need to check for
multicollinearity due to the presence of more than
two independent variables in the fourth substructure.
In this study, The multicollinearity test includes
assessing the correlation between independent
variables, and a value exceeding 0.8 is considered
an indicator.
In the context of conducting a linear regression
analysis, it is important to ascertain the level of
heteroskedasticity or homoskedasticity. In the case
of the OLS method, the model adheres to the
assumption of homoscedasticity. Conversely, when
an individual opts for the FEM or REM, it becomes
essential for the model to exhibit heteroskedastic
characteristics.
Hypothesis testing is conducted through the t-
statistic and probability values. The intervening
variable is proven to mediate and can be determined
by the comparison between the magnitude of the
direct and indirect effects. The indirect effect is
calculated from the sum of the multiplication of the
path coefficients between parameters. The
intervening variable acts as a mediator when indirect
effects outweigh the direct. However, the variable
does not perform a mediating role when the indirect
effects outweigh the direct effects.
4 Data Analysis and Interpretation
4.1 Descriptive Statistik
Descriptive statistics of the variables used in the
model are presented in Table 2.
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Table 2. Descriptive Statistik
DER
ROA
Z-Score
PBV
1.0146
0.1846
4.9696
5.0680
0.7253
0.1207
4.0680
1.6992
3.3134
1.4508
12.3721
82.4444
0.1447
-0.0730
-1.3350
0.5671
The capital structure of the company
incorporated in JCI has an average DER of 1.01
during the study period, hence the average company
funding is 101% using debt compared to capital.
The maximum and minimum values are 331% and
14.47%, with a median DER of 0.72%. Sampling
with a large debt-use ratio is relevant to the
objectives of this study. In the context of agency
theory, the use of increased debt causes the
company to be more supervised in its operations to
produce good company profitability.
The profitability of the company incorporated
in JCI has an average ROA of 18.48 during the
study period, meaning that every one rupiah of total
assets generates 18.38 rupiah of net income. This
ROA ratio is quite good when compared to the
average risk-free rate with an average of 7% per
year. The minimum and maximum profits are -
0.07% and 145% with a median ROA of 12.07%,
meaning that some samples have a ROA value
above 12.07%. This ratio causes the company to
have sufficient cash flow used to increase retained
earnings and develop business.
Financial Distress incorporated in JCI has an
average Z score of 4,969 during the study period,
meaning that companies are categorized as avoiding
financial distress. This z-score value indicates that
the company has a low risk of bankruptcy. The
minimum and maximum z-score values are -1.335
and 12.3712 with a median value of 4.068, meaning
that some samples have a score of 4.068.
Company value proxied by the average price
book value is 5.068 during the study period,
meaning that the company is categorized as having a
market price exceeding its book value. The market
has trust in the shares of a company or shows the
investor assessment. The minimum and maximum
PBV values are 0.5671 and 8.244 with a median of
1.992, meaning that some samples have values
above 1.992.
4.2 Hypothesis Testing
Model Selection Estimation with Chow test,
Hausman test, and Lagrange Test obtained the
results in Table 3.
Table 3. Model Selection Estimation
Hypothesis
Test
P-Value
Model Preferred
Path 1 : ROA = a1 + b1 DER + e1 (p<0,05, Ho : ditolak)
Null: Common Effect Alternative: Fixed Effect
Chow Test
0.1020
CEM
Null: Random Effect Alternative: Common Effect
Lagrange multiplier testMultiplier
0.000
CEM
Null: Random Effect Alternative: Fixed effect
Hausman Test
0.2444
FEM
Path 2 : Z-Score = a1 + b1 ROA + e1 (p<0,05, Ho : ditolak)
Null: Common Effect Alternative: Fixed Effect
Chow Test
0.0000
FEM
Null: Randamo Effect Alternative: Common Effect
Lagrange multiplier testMultiplier
0.0000
CEM
Null: Random Effect Alternative: Fixed effect
Hausman Test
0.8710
FEM
Path 3 : PBV = a1 + b1 Z-Score e1 (p<0,05, Ho : ditolak)
Null: Common Effect Alternative: Fixed Effect
Chow Test
0.0000
FEM
Null: Randamo Effect Alternative: Common Effect
Lagrange multiplier testMultiplier
0.0000
CEM
Null: Random Effect Alternative: Fixed effect
Hausman Test
0.7855
REM
Path 4 : PBV = a1 + b1 DER + b2 ROA + e1 (p<0,05, Ho : ditolak)
Null: Common Effect Alternative: Fixed Effect
Chow Test
0.0013
FEM
Null: Randamo Effect Alternative: Common Effect
Lagrange multiplier testMultiplier
0.0572
CEM
Null: Random Effect Alternative: Fixed effect
Hausman Test
0.0039
FEM
Based on the estimation model, paths one,
four, and three are CEM, FEM, and REM,
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respectively. Furthermore, classical assumption
testing is carried out and the multicollinearity test is
only performed for path four in Table 4.
Table 4. Multicolinierity Test
Variable
DER
ROA
DER
1
0.3067
ROA
0.3067
1
The independent variables have a correlation
coefficient below 0.08. Therefore, the variables are
not correlated with each other and there is no
significant multicollinearity between the
independent variables.
The heteroscedasticity test is carried out using
the Glejser test, as shown in Table 5.
Table 5. Heteroskedastic Model Test
Dependent Variable
Independent Variables
Prob
Conclusion
Path 1 : ROA = a1 + b1 DER + e1 (Prob > 0,05, There is no problem
Heteroscedasticity)
ROA
DER
0.0813
There is no problem
Heteroscedasticity
Path 2 : Z-Score = a1 + b1 ROA + e1
Z Score
ROA
0.7605
There is no problem
Heteroscedasticity
Path 3 : PBV = a1 + b1 Z-Score + e1 (Prob > 0,05, There is no problem
Heteroscedasticity)
PBV
Z Score
0.4539
There is no problem
Heteroscedasticity
Path 4 : PBV = a1 + b1 DER + b2 ROA + e1 (Prob > 0,05, There is no problem
Heteroscedasticity)
PBV
DER,
ROA,
0.7476
0.7858
There is no problem
Heteroscedasticity
After passing the classical assumption test on
each substructure, the following are the regression
estimation results for testing the hypothesis as
shown in Table 6.
Table 6. Summary Output
Variable
Coefficient
t-statistic
Prob
Path 1 : ROA = a1 + b1 DER + e1 (Estimasi Common Effect Model)
Intercept
0.0086
1.9971
0.0490
DER
0.0971
2.988
0.0037
Path 2 : Z-Score = a1 + b1 ROA + e1 (Estimasi Fixed Effect Model)
Intercept
3.5778
18.0640
0.0000
ROA
7,5376
7.190
0.0000
Path 3 : PBV = a1 + b1 Z-score + e1 (Estimasi Fixed Effect Model)
Intercept
2.7815
7.6196
0.0000
Z-score
0.4600
6.3098
0.0000
Path 4 : PBV = a1 + b1 DER + b2 ROA + e1 (Estimasi CEM)
Intercept
-4.0056
-4,0707
0.0000
DER
0.9486
1,7844
0.0779
ROA
43.9209
26.1469
0.000
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The path_1 regression equation where DER is
the independent variable affecting ROA as the
dependent variable is as follows:
ROA = 0.08615 + 0,0917 DER + ei
The constant value of 0.08615 indicates that
DER (Z) will remain at 0.08615 units even though
DER is zero. DER regression coefficient is 0.0917,
hence each increase in DER by one unit will
increase ROA value by 0.0917 units. The P value
of DER on ROA is 0.0037 smaller than 0.05, Ho is
rejected, meaning that DER has a significant effect
on ROA at a significance level of 5%.
The Path_2 regression equation where ROA is
the independent variable affecting Z-Score as the
dependent variable is as follows:
ROA = 3.5778 + 7,5376 Z-Score + ei
The constant value of 3.5778 indicates that the
Z-score will remain at 3.5778 units even though the
ROA is zero. The regression coefficient of the Z-
score is 7.5376, hence each increase in ROA by
one unit positively affects the Z-score by 7.5376
units. The P value of ROA on the Z-score is 0.0000
smaller than 0.01, Ho is rejected, meaning that
ROA has a significant effect at a significance level
of 1%.
The Path_3 regression equation where Z-score
is the independent variable that affects PBV as the
dependent variable is as follows:
PBV = 2.7815 + 0.4600 Z-score + e1
The constant value of 2.7815 indicates that
PBV will remain at 2.7815 units even though the Z-
score is zero. The regression coefficient of the Z-
score is 0.4600, hence each increase in Z-score by
one unit will positively affect PBV by 0.4600 units.
The P value on PBV of 0.0000 is smaller than 0.01,
Ho is rejected, meaning that Z-score has a
significant effect on PBV at a significance level of
1%.
The Path_4 regression equation where DER
and ROA as independent variables affect PBV as
the dependent variable is as follows:
PBV = 0.7502+1.1600 DER+3.9732 ROA +0.4843
Z_score+ei
The constant value of -4.0056 indicates that
PBV will remain at -4.0056 units even though DER
and ROA are zero. The regression coefficient of
DER is 0.9486, hence each increase in DER by one
unit has a positive effect on PBV value by 0.9486
units with ROA at a fixed value. The Regression
Coefficient of ROA is 43.9209, meaning that each
increase by one unit positively affects the PBV
value by 43.9209 units with DER at a fixed value.
The P value of DER and ROA of 0.0779 and
0.0000 is smaller than 0.05 and 0.01, Ho is
rejected, hence DER has a significant effect on
PBV at a significance level of 1%.
The mediation hypothesis test is shown by
comparing the direct and indirect effects as shown
in Table 7.
Based on the calculation in Table 4,
concerning the mediation of ROA on the
relationship between DER and PBV, when the
DER variable directly affects PBV, the estimated
coefficient value obtained is 0.8998. The indirect
influence of DER on PBV through ROA shows an
estimated coefficient value of 4.2647. Therefore,
the value of the indirect effect is greater than the
direct through the mediation variable since ROA
mediates the relationship between DER and PBV.
Concerning the mediation of ROA and Z-score
on the relationship between DER and PBV, when
the DER variable directly affects PBV, the
estimated coefficient value obtained is 0.8998. The
indirect influence or the effect of DER on PBV
through ROA and Z-score shows an estimated
coefficient value of 0.3667. It can be concluded
that the value of the indirect effect is smaller than
the direct through the mediation variable since
ROA and Z-score do not mediate the relationship
between DER and PBV.
Table 7. Mediation Test
Path
Direct Effect
Indirect Effect
Conclusion
DER PBV
0.9486*0.9486= 0.8998
DERROAPBV
0.0971 X 43,9209
= 4.2647
Mediation
DERROAZ Score PBV
0.0971 X 7.5376
X 0.4600 =
0.3667
No Mediation
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4.3 Discussion and Result
The result shows a significant and positive impact
of DER on ROA, meaning that a rise in capital
structure increases the ability to generate profits.
The use of debt results in increased control
mechanisms in the company governance structure.
Furthermore, it avoids the tendency of managers to
abuse free cash flow and makes financial managers
more disciplined in managing the company. These
results are consistent with agency theory and
studies conducted by, [14], [21], [22], [24], [25].
ROA has a positive and significant influence
on the Z-score, meaning that an increase in
profitability significantly reduces the risk of
financial distress. In the context of agency theory, a
company with high profits resulting from the use of
capital sourced from debt can be interpreted that
the management is successful in achieving the
interests of the agent and the principal, [4].
Furthermore, an increase in profit makes it easier to
settle obligations and avoid financial difficulties,
[26], and the company has all obligations with its
profitability, [28], [29]. The increase in z-score
value indicates a decrease and increase in
bankruptcy risk and company value, [27]. This
result confirms agency and trade-off theory where
debt can provide benefits in the form of profits.
Profitability has a positive and significant
influence on company value and the hypothesis is
proven. Based on a model built from agency and
trade-off theory, debt, profitability, and company
value are directly related. The profitability of a
company serves as an indicator of successful
company management, mitigating conflicts
between agents and principals, [26]. High
profitability is emblematic of favorable financial
circumstances, leading to increased trust among
stakeholders, such as investors, creditors, and
shareholders, [30]. In the context of trade-off
theory, the strategic employment of debt to enhance
profitability underscores the ability to yield greater
benefits relative to the associated risks of the use,
[3]. The situation attests to a high-performing
company, eliciting a positive response from
investors. Moreover, heightened prospective
profitability holds the potential to generate positive
sentiment, [33].
There exists a positive correlation between
financial distress and company value. The z-score
and PBV are directly related, signifying a reduced
risk of bankruptcy and an augmented company
value. The rationale is that companies characterized
by minimal financial distress tend to exhibit greater
real income, lower systematic risk, and a
diminished likelihood of bankruptcy. In the
absence of financial difficulties, such a company
possesses the potential for heightened investment.
Under these favorable circumstances, the company
is poised to maintain an upward trajectory,
providing dividends to shareholders and proffering
the promise of continued growth, [19], [34], [35],
[36].
The mediation test results show that ROA can
mediate DER to PBV, and this is evidenced by the
magnitude of the indirect effect. The results are in
line with the perspective of agency and trade-off
theory, where the use of debt can produce an
optimum capital structure. The use is related to the
supervisory mechanism carried out by the lender,
making financial managers more disciplined in
managing the company, avoiding the tendency to
misuse free cash flow, and making optimal
business decisions, [14], [21], [22], [24], [25].
The mediation test results of profitability and
financial distress in the link between capital
structure and company value are not proven. This is
because the magnitude of the indirect effect is
smaller than the direct effect. Capital structure
affects profitability, financial distress, and
company value, without a proven mediation. The
explanation lies in the dual influence of debt,
including both profitability and financial distress.
The optimal deployment of debt leads to
heightened profitability and simultaneously
introduces financial risk. Therefore, the growth of
company value may be hindered when the
increment in profitability resulting from the use of
debt surpasses the magnitude of financial risk
incurred.
The use of debt increases profitability, which
can reduce financial distress. The lack of
significance in mediation testing can be attributed
to profitability levels. This is due to the Altman
model's consideration of debt as a weight,
contributing to the risk profile of the company. The
mediation test outcomes tend to exhibit significant
results when the profitability generated exceeds the
risk associated with debt use.
5 Conclusion
Capital structure decision was important for the
sustainability of the company because the
performance of the company was affected. This
study aimed to prove a proposed model of the
relationship between capital structure and company
value from the perspective of agency theory. The
samples used were companies in the LQ45 Index
on the Indonesia Stock Exchange (IDX) with a
sample period between 2017 and 2020. Company
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DOI: 10.37394/232018.2023.11.39
Wawan Ichwanudin,
Enok Nurhayati, Cep Jandi Anwar
E-ISSN: 2415-1521
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Volume 11, 2023
value was measured using PBV and there were
independent and intervening variables based on the
development of the model. The independent
variable was capital structure measured using DER,
and the intervening variable was profitability and
Financial distress measured by ROA and Z-score
value.
The hypothesis testing showed that DER had a
positive and significant effect on PBV. An increase
in the use of debt caused ROA to increase with
PBV and Z scores, indicating a low risk of
bankruptcy. ROA significantly mediated the effect
of DER on PBV, while ROA and Z-score did not
mediate the effect of DER on PBV.
The interesting result was based on the
mediation test, where profitability significantly
mediated the effect of capital structure on company
value. Profitability and financial distress proved to
be insignificant in mediating capital structure to
company value. This result showed that the model
proposed using the agency theory perspective was
proven. The increased use of debt in the
perspective of agency theory increased the
supervision of the lender. Therefore, the company
worked more effectively and carefully in every
decision making as evidenced by the increase in
profitability and value of the company. The capital
structure presented a paradox, enhancing
profitability while elevating financial challenges.
The observed rise in profitability fell short of
reaching an optimal level necessary to offset
financial risks stemming from debt use. Therefore,
the mediation effect of profitability and financial
distress on the relationship between capital
structure and company value did not attain
statistical significance.
This result had important implications for
academics and managers. First, the use of debt
could positively affect company value within the
model. Previous studies examined the association
between capital structure and company value.
However, the results omitted an evaluation of how
the deployment of debt was harnessed as a
mechanism for regulating the operational
undertakings of the company. This omission
potentially yielded inadequate conclusions
regarding the impact of capital structure on
company value. Second, management needed to
consider the use of debt in its use because the
concept had positive and negative impacts on
company performance. Company value was
increased by optimizing the use of funds from debt,
hence the resulting profitability was higher than the
risk. Third, the decision of the company was
focused on risk minimization and supervising
debtors prevented managers from engaging in risky
operational activities, leading to a reduction in
company value.
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Contribution of Individual Authors to the
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Scientific Article or Scientific Article Itself
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Conflict of Interest
The authors have no conflict of interest to declare
that is relevant to the content of this article.
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