the effect of capital structure on the performance …

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INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS

COPY RIGHT © 2014 Institute of Interdisciplinary Business Research 502

JANUARY 2014

VOL 5, NO 9

THE EFFECT OF CAPITAL STRUCTURE ON THE PERFORMANCE OF THE FIRMS LISTED ON THE TEHRAN STOCK EXCHANGE BASED

ON THE COMPETITIVE ADVANTAGE

ForoughHeirany

Department of Accounting, Islamic Azad University, Yazd Branch, Yazd, Iran

Safaiieh, Shohadegomnam Road, Zip code: 89195/155, Yazd, Iran

ShahnazNayebzadeh

Department of Management, Yazd Branch, Islamic Azad University, Yazd, Iran

Safaieeh, Shohadegomnam Road, Zip code: 89195/155, Yazd, Iran

HosseinEsmailkhani

Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran

Safaieeh, Shohadegomnam Road, Zip code: 89195/155, Yazd, Iran

The Author to whom we should address our correspondence: HosseinEsmailkhani, M.A student of Accounting,

Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, IRAN.

Abstract

This study seeks to examine the relationship between capital structure and firm performance based on the

competitive advantage in the firms listed on the Tehran Stock Exchange. Using lagged leverage, square of lagged

leverage, relative leverage, square of lagged relative leverage, as the independent variables and Herfindahl-

Hirschman as the mediator variable, the research model has been formed. The sample is composed of 202 firms

selected among 13 different industries over a period from 2006 to 2011. The findings of this study document the

positive significant relationship between leverage and the financial performance. However, it is found that there is

an inverse significant relationship between squareleverage and firm performance. It is also shown that there is no

significant association between Herfindahl-Hirschman index and firm performance. To examine the impact of

leverage of the competitors in the firm performance, the relationship between the relative financial performance and

firm performance has been tested and it is found that the leverage of the competitors has negative effects on the

firm performance. The results finally indicated that the relative leverage might improve the firm performance in

balance with Herfindahl-Hirschman index.

Keywords: Capital Structure, Competitive Advantage, Firm Performance, Herfindahl- Hirschman Index

1. Introduction

As a significant source of decision making, the equities might belong to the owner or to the others. The difference

in the ownership introduces the debts or owner’s equity. A combination of these two elements is known as the

financial knowledge. This is a dynamic situation and changes under different circumstances, such as cost of capital,

capital market, managerial perceptions, organizational strategies, firm size and firm growth. In doing so, the capital

is one of the most significant fields of financial management and finance. Most decision making processes related

to the capital structure are the elements at the time of determining capital structure. Some of these elements are

related to different taxes, tax rate and interest rate, which are used in explaining the changes in the leverage. In

terms of the taxable income and cost of capital, it is argued that the market value is positively associated with the

long-term debts used in the capital structure. In modern business environments, the organizations work in a very

complicated and competitive environment. Therefore, the empirical and theoretical studies about the leveragefound

some results which lead firms achieve the optimum value. When analyzing the operational functions, the capital

structure should be interpreted with caution. The behavior is very effective in many fields aimed at making a profit

(Bei and Wijewardanab, 2012). This study seeks to examine the relationship between capital structure and firm

performance based on the competitive advantage of the Tehran listed firms. This study also collects the real data to

bridge the gap between the research fields and provide useful information for the principals and stakeholders.

2. Theoretical Bases and Hypotheses

2.1 Capital Structure

Any of the definitions provided for the capital structure represent a dimension of the methods of finance. The

capital structure is a combination of debts and capital identified to be necessary for financing a corporation. After

comparing the internal and external factors related to the operational environment and the specific characteristics of

the finance, the appropriate level of capital and debt is determined (Bei and Wijewardanab, 2012, 710).

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2.2 The Relationship between Capital Structure and Firm Performance

Modigliani and Miller (1958) predicted that there is no significant relationship between the capital structure and its

intrinsic value on the perfect competition market. Due to various reasons, the capital structure is significant and this

is derived from the tax effect of the debts and agency theory (Fosu, 2013, 2). Modigliani and Miller (1963)

reasoned that the high debt level in the capital structure leads to lower tax debts and more cash flows after tax,

which would finally increase the market value (Shahedani et al, 2012, 25).

Based on the literature review of the agency theory, using more debts in the capital structure is a way to mitigate

the agency theory, because the high level of debts in the capital structure mitigates the conflict of interest among

the directors and shareholders (Setayesh et al, 2011, 56).

Bei and Wijewardanab (2012) conducted a study aimed to examine whether the leverage has a positive or negative

impact on the firm’s growth. They found that the leverage has a positive association with the financial growth and

power. Similarly, Park and Jang (2013) investigated the internal relationship between capital structure, free cash

flows, diversification and performance. They showed that the debt leverage is an effective way to reduce the free

cash flows and might improve the firm performance. Based on the prior studies, it can be argued that increasing

finance through debts could improve the firm performance. The debts, however, transfer a portion of the investment

benefits to the holders of the securities. Under certain circumstances, the leverage firms might reject the valuable

investment opportunities and this results in reducing the market value (Myers, 1977, 147). The existing literatures

suggest that the agency costs are extended to the conflict of interest among the firms and the stakeholders. The

bankruptcy probability is low for the firms with facilities or the firms working with lower debt ratio (Verwijmeren

and Derwall, 2009, 956). Similarly, Hong Bae et al (2010) examined the relationship between stakeholder theory

and employees. Their findings revealed that those firms which behave fairly with their employees have lower debt

ratios. Maksimovic and Titman (1991) believe that under certain circumstances, the customer might put the product

quality of the very leveraged firms at risk and this shows that the high leverage level might be detrimental for the

performance. Mixed evidences are found based on these theories. The various studies document the negative

impacts of the leverage on the firm performance; however, the other studies suggested positive or insignificant

effects. Coricelli et al (2012) examined when the leverage damages the growth of the productivity. Specifically, it

can be concluded that financing methods have negative impacts on the growth. They tested the economic

foundations of this argument and assumed that there is an inconsistent relationship between leverage and

productivity growth in terms of the interaction theory of capital structure. They documented inconsistent

relationships between leverage and the characteristics of the firm value. The results also supported a positive

(negative) relationship between profitability and optimum leverage. Finally, they indicated that the ratio of the

firms with excess leverage are higher among those firms with less profitability (Coricelli et al, 2012, 1674). Based

on these findings, the first hypothesis is formed:

The first hypothesis: There is a relationship between leverage and firm performance.

Based on the Porter competitive advantage model (1980), the competitiveness is defined as conducting aggressive

operations to create a defensive position for the successful confrontation with the competing forces and high return

on investment. Porter considers that the competitiveness relies on the productivity, which is derived from human

resources, capital and natural resources (Mahdi Zadeh, 2011, 128). Various changes occur by the evolutions of the

market (Werker, 2003, 281). Competition is defined as the operations conducted to win the business operations in

comparison with the competitors (Karuna, 2007, 275).

2.3 The Relationship between Capital Structure and Competition on the Product Market

Titman (1984) found that the unique productions and those products with mutual relationships with the customers

and suppliers have lower leverage (Hong Bae et al, 2010, 130). Brander and Lewis (2986) represented that

leveraging allows firms to become more competitive in the product market and this is because of the limited

liability. The strategic effect of this behavior might offset the costly agency theory. The theories and literature

review show that the high leveraged firms suffer from the potential competitive advantages in the product market.

The leveraged firms are more vulnerable in the concentrated markets (Fosu, 2013,1). Guney et al (2010) examined

the association between capital structure and market competition. They showed that there is a non-linear

relationship between leverage and competition of the product market. It was also found that this association

depends on firm size and growth opportunities.

The firms without debts behave aggressively by increasing production or reducing prices (Setayesh and

KargarFard, 2011, 13). Clayton and Jorgensen (2011) found that the firms are inclined to select long-term capital

positions when their products are supplemented. In comparison, the firms have sufficient incentives to select short-

term positions when their products are alternatives. These positions lead firms in aggressive product markets, which

increase the capital expenditures. Based on the prior studies, it is expected that the firms in the competitive situation

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(non-concentrated) get attacked by debt financing through the firms with lower leverage. The second hypothesis is

developed as follows:

The second hypothesis: The competitive advantage impacts the agency advantages of leverage.

2.4 The Finance Decisions and Leverage Level of the Competitors

Debts of the investment models cause lower investments and this is because of the effect of the alternative assets.

Increasing assets is an indicator of the future investment because the cash flow percentage improves (Guney et al,

2010, 41). Huang and Lee (2012) investigated the market competitiveness and credit risk and empirically examined

the effects of the product market competition on the credit risk. The structural model is examined in a

homogeneous model of oligopoly and it was found that the credit dispersion has a positive association with the

number of the firms in an industry. The different firm sizes in an industry depend on the competition of the product

market and credit risk (Huang and Lee, 2012, 324). The leverage firms might face withmore financial limitations in

comparison with the competitors with the lowestleverage in the product markets; that is why, their sensitivity to the

market signs is probably higher (Fudenberg and Tirole, 1986, 366). In doing so, the third hypothesis is formed as

follows:

The third hypothesis: There is a relationship between relative leverage and firm performance.

3. Measurement Methods

This is an applied study classified as a descriptive correlation survey. The population is composed of the firms

listed on the Tehran Stock Exchange over a period from 2006 to 2011. The following criteria are considered in

selecting the sample:

Their end of the fiscal year is consistent with the calendar year. They should be listed on the Tehran Stock Exchange during the examination period. The required data should be available for the selected firms. The investment, insurance and credit firms are excluded from the sample. The industry should include at least five firms.

Considering the above criteria, 202 firms from 13 different industries are selected as the sample. To collect the

required data about the theoretical discussions, the prior literature is investigated. The information about the

variables are gathered from different databases and the financial statements of the selected firms. Using EXCEL

and Eviews, the statistical data is analyzed. The variables are defined in terms of four groups, including dependent,

independent, mediator and control variables.

3.1 Return on Assets

The return on assets is one of the measures used to evaluate the firm performance and is used as the dependent

variable. This ratio is computed by dividing net income by the total assets. This variable has been previously used

by Guney et al (2010), Cohw et al (2011), Hall (2011), Chen et al (2012) Fosu (2013).

The independent variable of the study is the capital structure measured by the following criteria:

3.2 Leverage

The leverage of the prior period (LEVi,t-1) is calculated by dividing total debts to the total assets. This variable has

been used by Manous et al (2007), Guney et al (2010), Paya and Spicial (2011), Bei and Wijewardanab (2012),

Park and Jang (2013), Fosu (2013).

3.3 Relative Leverage

This variable is defined as the difference between the leverage of each firm from the average leverage of the

industry. This variable is used to control the leverage level of the competitors. This is the variable used by Fosu

(2013).

3.4 Competitive Advantage

This variable is used as the mediator variable. To measure the competitiveness, the Herfindahl - Hirschman index

has been used.

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3.5 The Herfindahl-Hirschman

This variable is a commonly accepted measure of market concentration. The index of Herfindahl-Hirschman has

been used by the studies of Chen et al (2012), Fosu (2013), Setayesh and KargarFard (2011), Namazi and Ebrahii

(2012). This variable is calculated by the squared market share of all entities in an industry:

si = Market share of firm i

xj= Sale of firm j

i= Industry type

The Herfindahl-Hirschman index is used to measure the market concentration. The higher value of this index shows

the higher concentration and lower competition in the industry (Setayesh and KargarFard, 2011, 15). To control the

other effective factors of the capital structure, some characteristics of the sample are considered as the control

variables. These variables include: 1. Size (the natural logarithm of total assets), 2. Size2 (squared firm size). 3.

Growth which is calculated by dividing the difference between the sales in year t and the sales of one prior period

by the latter item (Salesi,t− Salesi,t−1)/Salesi,t−1; wherein, i and t are indicators of firm i in year t). 4. MROA

which is measured by the simple mean of the two years of profitability.

The present study seeks to examine the relationship between capital structure and firm performance. As the first

step, the impact of the capital structure on the firm performance is examined. Using relative leverage, the

hypotheses are retested. To estimate the impact of the leverage on the firm performance, the following model is

developed (Fosu, 2013):

(1)

Where in;

ROAi,t، is the return on assets of fir i in year t; β is the intercept of the regression; LEVi,t-1 is the leverage of firm i in

year t-1; sizei,t is the firm size; Growthi,t is the growth rate of the sales.

Including the square of the lagged leverage in the model results in considering the nonlinear effect of the leverage

on the firm performance (Fosu, 2013).

(2)

The variables of the model have been defined in the previous section; however, this model includes the squared

lagged leverage (leverage of the prior period). Adding the interactive effects of leverage and competition, model 1

is retested (Fosu, 2013).

….(3)

is the interactive effect of leverage and the Herfindahl-Hirschman index. In addition, the squared of

the lagged leverage is added to the model and it is again tested (Fosu, 2013).

(4) Finally, a combined hypothesis is developed according to which the leverage impacts are affected by the competitors. To test the third hypothesis, the relative leverage (RLEVi,t-1)is substituted by the leverage (LEVi,t-1) and the hypothesis is again tested. Relative leverage= Lagged leverage- mean leverage of the industry

4. Conclusion Remarks

After selecting panel data based on Chaw test, it is examined whether to use cross-section fixed effect or period

fixed effect model. Tables 1 and 2 show the results of F test to determine the fitness of the regression in model 1. In

panel data, the period fixed effect and cross-section effects and their simultaneous effects are tested. Based on the

model of fixed effects, one intercept is provided for each year; however, one intercept is provided for each firm

based on the cross-section model. To test the significant difference between these intercepts, Chaw test has been

used. Accordingly, H0 and H1 are developed as follows:

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H0: All intercepts are equal ↔pooled

H1: Intercepts are different ↔ Cross-section or fixed effect or both

The intercepts of the model are as follows:

Pooled↔

1. Fixed effect panel ↔ 2. Cross-section panel ↔ 3. Fixed effect of cross-section↔

The probability lower than 0.05 shows that H0 for equating intercepts is rejected and the fixed effect model is

preferred.

Table 1. The results of the cross-section fixed effects

Redundant Fixed Effects Tests

Test cross-section fixed effects

Effects Test Statistic d.f. Prob.

Cross-section F 2.8493 (201.990) 0

Cross-section Chi-square 546.8558 201 0

Table 2. The results of the period fixed effect

Redundant Fixed Effects Tests

Test period fixed effects

Effects Test Statistic d.f. Prob.

Period F 1.2338 (5.186) 0.2956

Period Chi-square 6.16514 5 0.2951.

Based on Chaw statistics, the probability of crosss-section is lower than 0.05 and the probability of the period fixed

effect is higher than 0.05; therefore, H0 is rejected and it is found that the cross-section fixed effects model is

preferred. The descriptive statistic is first provided and the hypotheses are then tested.

Table3. Descriptive Statistics

Title HHI ROA MROA Growth Lagged

leverage Size

Lagged

relative

leverage

Mean 0.012741 0.167397 0.182469 0.250013 0.667711 13.34761 0.015374

Median 0.001201 0.083625 0.090315 0.137677 0.653837 13.2005 -0.01

Maximum 0.352463 80.39012 40.2593 69.73694 5.673509 18.43763 4.61

Minimum 2.52E-10 -0.76156 -0.69682 -0.99806 0.096415 8.43685 -0.58

Std.

deviation 0.038717 2.324685 1.681279 2.095428 0.311805 1.466114 0.29286

Generally, the descriptive statistics indicate that the selected sample is very diversified. For example, the statistics

on ROA show that the minimum and maximum of ROA are -0.07615 and 80.39012, respectively. The standard

deviation of ROA is also found to be 2.324685. This characteristic is similar to the other variables and it shows that

the selected firms are diversified and the findings might be generalized to the population.

5. Results of Hypotheses

In terms of the first hypothesis, two models have been tested and the findings are represented in table4. To test the

relationship between leverage and performance, the first model is used.

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Table4. Results of testing model 1

Cross-section fixed (dummy variables)

Adj. R2

0.9506

F 112.1823

(Prob( 0

Durbin-Watson 2.311756

Explanatory variable Coefficient t Prob. Confidence level

C 1.157458 7.330193 0 99%

LEV 0.132386 11.15758 0 99%

SIZE -0.18381 -7.35303 0 99%

0.006559 6.645625 0 99%

GROW 0.002431 2.326734 0.0202 95%

MROA 1.193695 28.15172 0 99%

HHI -0.01668 -0.26192 0.7934 -

Based on F statistics and its probability, it is found that all regression models are significant at the 99 percent of

confidence. The results of Durbin-Watson statistics confirm the relative independence of the data. In addition,

adjusted R2 of the model describes the relevancy of the independent variables and the dependent variables. Based

on table 4, adjusted R2 for all models is 95 percent and it is concluded that 95 percent of changes in the dependent

variable are explained by these models. According to the probability of the leverage (LEVi,t-1) which is lower than

0.01, it is found that this variable is significant at the 99 percent level. On the other hand, the coefficient of this

variable is positive and it can be concluded that there is a positive significant relationship between leverage and

performance.

Adding Levi,t-12 , the first model is retested (model 2). By including the square of lagged leverage, the non-linear

impact of leverage on the performance is tested.

Table5. Results of the nonlinear impact of leverage on the performance


Adj. R2

0.94936

F 108.7965

(Prob( 0



C 1.101716 9.178245 0 99%

LEV 0.192899 6.798945 0 99%

SIZE -0.1788 -9.06364 0 99%

0.006331 8.277802 0 99%

GROW 0.002513 1.532413 0.1257 -

MROA 1.197708 27.77917 0 99%

HHI 0.003336 0.070423 0.9439 -

-0.02042 -2.35187 0.0189 95%

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By adding the squared leverage (model 2), the coefficients of the leverage are found to be significant at the 95

percent and the negative coefficient also indicates that the excess level of the leverage might have an inverse impact

on the performance. Based on the probabilities of the control variables and their significance in the model, it is

found that most of the control variables are significantly associated with the performance. The relationship between

firm size and performance is significant at the 99 percent. Furthermore, the relationship between growth rate and

firm performance in models 1 and 2 is positive. The growth rate is measured by the changes in the sales in

comparison with the prior year; therefore, increasing the rate of sales growth shows an increase in the sales which

finally leads to better performance. The probability of HHI is higher than 0.05 and shows that this variable is not

significant at the 95 percent level. As a result, it can be argued that the competition has no significant impact on the

firm performance. It must be noted that the leverage might have a considerable effect on this relationship because

the excessive use of the leverage might impose high interest costs. The higher interest cost is effective in the final

cost and the price. On one hand, using leverage might lead to financing the resources needed for increasing

investments in the market and increasing profit. Therefore, it seems necessary to examine the interactive role of

leverage and market competition. In doing so, the second hypothesis is developed and tested by using model 3.

Table6. Results of the third model for the second hypothesis


Adj. R2

0.950443

F 110.4493

(Prob( 0


Explanatory

variable Coefficient t Prob. Confidence leve

C 1.046248 6.099399 0 99%

LEV 1.046248 6.099399 0 99%

SIZE -0.17242 -6.4928 0 99%

0.006164 6.046102 0 99%

GROW 0.002506 2.483057 0.0132 95%

MROA 1.225546 58.61105 0 99%

HHI -0.31812 -1.7314 0.0837 -

LEV*HHI 0.420198 1.888967 0.0592 -

As stated before, the market competition is a significant element in analyzing the firm performance and leverage.

To examine the interactive effect of leverage and competition, is used in the model. Based on the

findings of table 6, HHI*LEV is not significant at the 95 percent level and it can be concluded that the interactive

effect of leverage and HHI are not significantly associated. As mentioned in the prior literature, HHI is a

concentration measure used for measuring competitive advantage. The higher ratio of HHI indicates more

concentrated and noncompetitive industry.

The second hypothesis is tested by considering the square of the lagged leverage in model 4 in which the interactive

effects of the leverage and competition are both tested in one model.

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Table7. Results of testing model 4 for the second hypothesis


Adj. R2

0.94946

F 108.5054

(Prob( 0



C 1.109436 7.590972 0 99%

LEV 0.18885 9.614798 0 99%

SIZE -0.1798 -7.54622 0 99%

0.006376 6.670553 0 99%

GROW 0.00252 2.288378 0.0223 95%

MROA 1.198355 25.62585 0 99%

HHI -0.27878 -1.54182 0.1234 -

LEV*HHI 0.376106 1.610486 0.1076 -

-0.01952 -2.24646 0.0249 95%

As shown in the table above, it is concluded that there is a positive association between leverage and performance

and the coefficient of the leverage is negative and significant. Similar to the previous model, HHI has no significant

relationship with the performance.

The third hypothesis examines whether the impact of the leverage, at least in part, is related to the competitors.

Using relative leverage, the difference between leverage and the mean of the industry leverage is measured.

Therefore, the regression equations are revised so that the leverage is substituted by the relative leverage. The

findings are shown in the table below.

Table8. Results of testing model 5 for the third hypothesis

Adj. R2

0.946044

F 102.3062

(Prob( 0


Explanatory

variable Coefficient t Prob. Confidence level

C 1.606403 8.489679 0 99%

RLEV -0.0487 -4.49825 0 99%

SIZE -0.22292 -7.8457 0 99%

0.00758 7.119109 0 99%

GROW 0.002172 2.911131 0.0037 99%

MROA 0.983509 19.12996 0 99%

HHI 0.016141 0.237717 0.8121 -

According to table8 and the probability of (RLEVi,t-1), it is found that this variable is significant at the 99 percent.

The coefficient of this variable in the model is negative and it shows that there is a negative association between

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relative leverage and performance. The impact of the excessive relative leverage on the performance is tested

below.

Table 9: Results of testing model 6 for the fourth hypothesis

Adj. R2

0.945938

F 101.6085

(Prob( 0



C 1.573849 7.310365 0 99%

RLEV -0.05475 -4.9392 0 99%

SIZE -0.21829 -6.79495 0 99%

0.007412 6.214902 0 99%

GROW 0.002277 1.74143 0.0819 -

MROA 0.981059 46.11894 0 99%

HHI 0.015677 0.203614 0.8387 No mean

0.016523 1.79818 0.0725 -

The squared coefficients of the relative leverage is not significant at the 95 percent and it is concluded that the

relative leverage is the difference between the financial leverage and the mean leverage of the industry. As a result,

the relative leverage is not related to the firm performance. The findings also reveal that most of the control

variables are significantly associated with the performance. This relationship is similar to the explanations of the

prior model.

To examine the behaviors of the competitors in selecting the level of the leverage, the interactive relationship

between relative leverage and the competition with the performance has been tested.

Table10. Results of model 6, the interactive relationship between relative leverage and competition with the

performance


Adj. R2

0.946753

F 103.2371

(Prob( 0



C 1.684168 8.920492 0 99%

RLEV -0.05186 -5.05723 0 99%

SIZE -0.2352 -8.20488 0 99%

0.008055 7.406842 0 99%

GROW 0.002386 3.005582 0.0027 99%

MROA 0.985695 18.75792 0 99%

HHI 0.055231 0.764487 0.4448 -

RLEV*HHI 1.753269 5.515891 0 99%

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Based on table 10, the results of the relationship between relative leverage and performance and the relationship

between HHI and performance are similar to the previous model. The interactive relationship of relative leverage

and HHI at the 99 percent has positive and significant relationship with the performance. By increasing the leverage

of the competitors, the low leveraged firms might use the benefits to increase their market shares. Finally, the

interactive relationship of excessive relative leverage and HHI with the performance has been examined.

Table11. Results of testing model 8 for the third hypothesis


Adj. R2

0.946535

F 102.3099

(Prob( 0


Explanatory

variable Coefficient t Prob. Confidence level

C 1.638695 9.005645 0 99%

RLEV -0.05968 -5.84203 0 99%

SIZE -0.22856 -8.16408 0 99%

0.00781 7.270394 0 99%

GROW 0.002554 2.970151 0.003 99%

MROA 0.981535 18.37175 0 99%

HHI 0.055289 0.765272 0.4443 -

RLEV*HHI 1.793971 5.536854 0 99%

0.018597 1.860873 0.0631 −

According to table 11, the interactive relationship between relative leverage and HHI with the performance is

positive and significant at the 99 percent level of significance. It is concluded that by considering the leverage level

of the competitors, the firms might improve their performance through leverage-based finance. The coefficient of

the squared relative leverage is insignificant at the 95 percent. In addition, the interactive relationship of squared

relative leverage and HHI is also insignificant in the model.

6. Conclusion and Discussion

The results of the first model confirm the positive significant relationship between leverage and performance.

Therefore, the first hypothesis of the study is confirmed. In other words, the findings confirm that the higher

leverage of the capital structure results in better firm performance. This advantage is attributed to the tax benefits

proposed by Modigliani and Miller (1963) and also attributed to the lower agency costs based on the agency theory.

This finding of the study is consistent with the results of Bei and Wijewardanab (2012), Park and Jang (2013) and

Fosu (2013).

The second model aimed to examine the nonlinear relationship between the leverage and performance. The results

of this model represent that the excessive leverage might have an inverse impact on the performance. Consistent

with Myers (1977), the valuable investment opportunities might be rejected by the leveraged firms and this results

in underinvestment and reduction of the market value. Furthermore, the conclusions are consistent with

Maksimovic and Titman (1991) and Coreicelli et al (2012). The findings of the first hypothesis denote the specific

attention that should be paid to the trade-off theory. Based on this theory, the optimum level of the leverage

reflects the balance between tax advantages and bankruptcy costs derived from debts. Because of the high

concentration of the sample firms, HHI has no effects on the firm performance and it is concluded that HHI does

not affect the firm performance in the non-competitive market. The findings of the third model document the

positive relationship between leverage and performance. Furthermore, it is found that the leverage interacted with

HHI has no significant association with the performance.

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The findings of the fourth model are consistent with the prior results. The results of the model (5) indicate that the

relative leverage and performance are negatively associated. As stated before, relative leverage represents the

leverage level of the competitors (market leverage). The higher level of the relative leverage indicates lower

leverage. Based on the findings of the first hypothesis, increasing the leverage improves the performance and

reducing the relative leverage improves the performance (at the optimum level). The results of the model(6)

represent that the squared relative leverage has no significant association with the performance. This finding is

consistent with the conclusions of Fosu (2013).

The results of the model (7) confirm the positive significant relationship between the relative leverage and

competition. In other words, by increasing the leverage of the competitors, the lower leveraged firms might use

higher leverage benefits to increase their market shares. This is consistent with the results of Brander and Lewis

(1986).

The strategic effect of this behavior might offset the costly agency problem. Increasing leverage results in the

entrance of more firms into the market and increase of the competition. Stated another way, the competitive

advantages in the competitive markets will reinforce the discipline effect of leverage and relative leverage or will

mitigate the agency problems. In fact, for the leveraged firms in the concentrated industries, the default risk limits

the ability to invest in the market share; however, the firms are seeking to increase leverage in the competitive

industries. Based on the findings, it is found that the Tehran listed firms should pay attention to the leverage of the

competitors and the competition level of the industry. These firms should mitigate the agency costs of debts to

increase their market share and provide a chance for the entrance of new businesses and the creation of the

competitive markets. Generally, the firms might improve their performance by considering the competition and

leverage level of the competitors.

7. Directions for the Future Studies

Based on the significant role of the financial institutions in financing the firms through loans, it is suggested to

conduct a study about the impact of interest rate on the capital structure and competition of the product market.

ijcrb.webs.com



JANUARY 2014

VOL 5, NO 9

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