The impact of credit ratings on capital structure (the case of listed companies on hose)

THE IMPACT OF CREDIT RATINGS
ON CAPITAL STRUCTURE
(THE CASE OF LISTED COMPANIES ON HOSE)

In Partial Fulfillment of the Requirements of the Degree of

MASTER OF BUSINESS ADMINISTRATION

In Finance

By
Ms: Nguyen Thi Tuong Van
ID: MBA06044
Advisor: Dr. Nguyen Kim Thu

International University - Vietnam National University HCMC

August 2014

i


THE IMPACT OF CREDIT RATINGS
ON CAPITAL STRUCTURE

In Partial Fulfillment of the Requirements of the Degree of
MASTER OF BUSINESS ADMINISTRATION
In Finance
By
Ms: Nguyen Thi Tuong Van
ID: MBA06044

International University - Vietnam National University HCMC

August 2014

Under the guidance and approval of the committee, and approved by all its members, this
thesis has been accepted in partial fulfillment of the requirements for the degree.
Approved:

---------------------------------------------Chairperson

---------------------------------------------Committee member

---------------------------------------------Committee member

---------------------------------------Committee member

---------------------------------------Committee member

---------------------------------------Committee member

ii


Acknowledge
To complete this thesis, I have been benefited from the following people:
First of all, I would like to express my sincere gratitude to my advisor, Dr. Nguyen Kim
Thu, who inspired and recommended me the research idea and always instructed me
dedicatedly and enthusiastically during the time I conducted this thesis. Whenever I meet
difficulty, she always gives me the solutions, provide me the necessary documents and
raise up my knowledge to continue doing my thesis.

Secondly, I want to show my gratefulness to the professors and lecturers for giving us
their valuable knowledge during the study period. This is the foundation for this thesis
completion.

Next, a sincere thank you is sent my family who always stand beside me. Thanks for their
continuously encouraging and supporting me to follow and complete the MBA program
of International University. I cannot finish my thesis on time without their contribution.

Last but not least, I want to thank all my friends in MBA06 and MBA07, especially Ms.
Tran Hong Quynh, Ms. Do Thi Hoang Anh, Mr. Nguyen Thanh Tuan, Mr. Tran Le Duy,
Ms. Le Tran Nguyen Nhung, Mr Nguyen Quy Vu for your share and encouragement.
Ho Chi Minh City, August 2014,
Nguyen Thi Tuong Van

iii


Plagiarism Statements
I would like to declare that, apart from the acknowledged references, this thesis either
does not use language, ideas, or other original material from anyone; or has not been
previously submitted to any other educational and research programs or institutions. I
fully understand that any writings in this thesis contradicted to the above statement will
automatically lead to the rejection from the MBA program at the International University
– Vietnam National University Hochiminh City.

iv


Copyright Statement

This copy of the thesis has been supplied on condition that anyone who consults it is
understood to recognize that its copyright rests with its author and that no quotation from
the thesis and no information derived from it may be published without the author‘s prior
consent.
© Nguyen Thi Tuong Van/ MBA 06044/ 2014

v


Table of Contents
CHAPTER I: INTRODUCTION .....................................................................................1
1.1. Background and research problems .................................................................1
1.2. Research Questions .............................................................................................2
1.3. Contributions of the research ............................................................................3
1.4. Research Methodology .......................................................................................3
1.5. Scope and Limitation ..........................................................................................4
1.6. Structure of Research .........................................................................................4
CHAPTER 2: LITERATURE REVIEW ........................................................................5
2.1.

Credit ratings .....................................................................................................5
2.1.1. Introduction of credit ratings .......................................................5
2.1.2. Credit ratings agencies ..................................................................7
2.1.2.1.Foreign market ...................................................................7
2.1.2.2.Vietnam market .................................................................9

2.2.

Capital structure ...........................................................................................11
2.2.1. Theories of capital structure .......................................................11

2.2.1.1.The Irrelevance Theory of Capital Structure ...............11
2.2.1.2.The Taxes theory of Capital Structure ..........................12
2.2.1.3.The Trade-off Theory ......................................................13
2.2.1.4.Pecking Order Theory .....................................................15
2.2.1.5.Agency Cost Theory .........................................................16
2.2.2.

Previous empirical studies of determinant of capital structure17
2.2.2.1. Size....................................................................................17
2.2.2.2.Growth Opportunities .....................................................18
2.2.2.3.Tangibility.........................................................................19
2.2.2.4.Profitability .......................................................................19
2.2.2.5. Industry level factor........................................................20

2.3. The impact of credit ratings on capital structure ......................................23
2.3.1. Foreign researches .......................................................................23
2.3.1.1. Kisgen Darren J. (2003, 2006, 2009) ...............................23

vi


2.3.1.2. Berlekom, Bojmar and Linnard (2012)and Kemper and
Rao (2013) .........................................................................25
2.3.1.3. Agha (2011) ......................................................................25
2.3.1.4. Helene and Hårstad (2012) ..............................................26
2.3.1.5. Drobetz and Heller (2014) ................................................29
2.3.1.6. Naeem, Shammyla (2012) .................................................30
2.3.2. Vietnam researches .......................................................................33
CHAPTER 3: COLLECTION AND RESEARCH METHODOLOGY .....................40
3.1. Data collection ...............................................................................................40

3.2. Reason for selecting CRVC credit ratings ...................................................40
3.3. Choosing Variable and Description ..............................................................41
3.3.1. Dependent variable ...........................................................................41
3.3.2. Credit ratings ....................................................................................43
3.3.2. Control variable ................................................................................43
3.4. Methodology ..................................................................................................47
3.4.1. Model 1: The Impact of Credit rating score on Capital Structure47
3.4.2.Model 2: The impact of Credit Rating changes on Capital
Structure ...........................................................................................................................48
3.4.3. Rung regression model ......................................................................49
CHAPTER 4:DATA ANALYSIS ...................................................................................52
4.1Descriptive Analysis .......................................................................................52
4.2. Result analysis ...............................................................................................53
4.2.1. Correlation Matrix.............................................................................53
4.2.2. Test for Heteroskedasticity ...............................................................54
4.2.3. Panel regression model analysis .......................................................54
4.2.4. Empirical Results ...............................................................................56
CHAPTER 5: CONCLUSION........................................................................................59
5.1. Main finding of the thesis .............................................................................59
5.2. Limitations of The Thesis .............................................................................60
5.3. Recommendations .........................................................................................60

vii


5.4. Suggestion for future research .................................................................................61
REFERENCE ...................................................................................................................62
APPENDICES ..................................................................................................................70

viii

List of Abbreviation

ACRC

Absolute credit rating changes

CIC

Credit Information Center

CR

Credit rating

CRAs

Credit rating agencies

CRVC

Credit Ratings Vietnamnet Center

FEM

Fix Effect Model

HNX

Hanoi stock exchange

HOSE

Hochiminh stock exchange

M&M

Modigliani and Miller

REM

Random Effect Model

S&P

Standard & Poor's

Vietnam Credit

Vietnam Credit Information and Rating Company

WACC

Weighted Average Cost Of Capital

ix


List of Tables

Table 1: The Credit Ratings description ..............................................................................6
Table 2: Credit Rating Definition by the Big Three CRAs .................................................9
Table 3: Classification criteria1 .........................................................................................11
Table 4: M&M (1963): A correction of irrelevance model of capital structure ................12
Table 5: Summary of previous empirical studies ..............................................................20
Table 6: Summary of previous empirical studies .............................................................34
Table 7: Credit ratings transform .......................................................................................43
Table 8: Industry level factor for each industry .................................................................46
Table 9: Fixed Versus Random Effect ...............................................................................50
Table 10: Model 1 summary statistics ...............................................................................52
Table 11: Model 2 summary statistics ...............................................................................52
Table 12: Correlation Matrix .............................................................................................53
Table 13: The result of test for Heteroskedasticity ............................................................54
Table 14: Analysis result of Pool OLS. FEM, REM .........................................................54
Table 15: The result of F-test .............................................................................................55
Table 16: The result of Hausman test ................................................................................56

x


List of Figures
Figures 1: : Market share of credit ratings agencies ........................................................ 8
Figures 2: Trade-off theory‘s Capital structure (The Optimal Capital Structure, the Value
of the Firm and the Cost of Capital) ...............................................................................14

xi


Abstract
This research aims to examine the impact of credit ratings influencing the capital

structure of listed enterprises on Hochiminh Stock Exchange. The research data were
collected from 239 listed enterprises over the period of 4 years in the period between
2009 and 2012 to use for Panel data method. The research would conduct test
assumptions to define the optimal regression model among Pooled OLS, Fixed Effects
Models and Random Effect Model.
The thesis has two empirical models :
- The first empirical model investigates whether the firm which has a higher credit
rating, have lower financial leverage than those with lower credit ratings. The study finds
that credit ratings are an important determinant of the capital structures of firms and that
there is a strong relationship between credit ratings and capital structures.

- The second empirical model examines the influence of the change of credit
ratings between each year on the short term debt to equity of listed firms on Hochiminh
stock exchange. Consistent with the predictions, the results indicate that firms‘ change of
credit rating significantly influenced on the following year‘s short term debt of the firm.
Keywords: credit ratings, capital structure

xii


xiii


CHAPTER 1: INTRODUCTION
This section provides the content of the study, section 1.1 discusses research’s
background and research problems. Based on that, section 1.2, 1.3 and section 1.4
present the research questions, contribution of the research and research methodology
are specified. Next, the scope and significance are as well listed out in section 1.4.
Finally, section 1.5 provides the organization of the thesis

1.1 Background and research problems
Credit ratings is a terminology that has become a widely accepted measure of firms‘
creditworthiness in financial markets. They like a tool that has established credit
standards in the market, which have received regulatory attention in several countries as
well (Pinto, 2006). For corporations that need to raise funds in the financial market, credit
ratings have important implications, since lower ratings lead to higher funding costs, and
vice versa (Boot and Milbourn, 2002). Moreover, credit ratings are also an important part
of investment decisions of institutional investors. Cantor & Packer (2007) state that 86%
of fund managers explicitly use ratings in their investment guidelines. Similarly, the
research of Graham and Harvey (2001) demonstrates that the credit rating is one of the
most important factors affecting capital structure decisions. Kisgen & Strahan (2010)
argued that the credit ratings matter because it serves as a signal of firm quality for
investors and therefore affects the company‘s capital structure.

Despite a continuous reliance on rating agencies by regulators, investors and firms along
with the significant growth of rating agencies globally, academic studies generally tend to
underestimate the relevance of credit ratings for firms‘ financial structure decisionmaking. After the recent financial crisis of 2008, it becomes imperative to investigate the
role and significance of their output for the firms‘ financing decisions to assess the
importance of credit rating agencies in the financial markets. (Naeem, Shammyla, 2012).
A recent study by Bacon, Grout & O‘donovan. (2009) of 43 senior treasury professionals
from nonfinancial UK firms, indicates that ratings have become more important during
the recent crisis, while the firms without ratings sought to obtain them during this period.
This suggests that the credit ratings could possibly be an important supply-side factor and
1


necessitates further exploration of how this factor can be influential in determining the
financial structure of firms.

The number of previous studies exploring the relationship between credit ratings and

capital structure are limited. Kisgen is said to be a pioneer in the study of this
relationship. Kisgen et al. (2006, 2009, 2010) Michelsen and Klein (2011), Kemper and
Rao (2013) used credit ratings – capital structure model to test the relevance of credit
ratings with capital structure in the US market. However, the result of Kemper and Rao
(2013)‘s study contrast to two previous studies. Sundheim and Hårstad (2012) used
multiple regression models to test the effect of credit ratings, among other factors , on
capital structure in the Norwegian market. The study had the same result with Kisgen
(2006), Michelsen and Klein (2011). To our knowledge, there has been a research on the
effect of credit rating changes in stock returns and capital structure of listed companies in
Vietnam by Ms. Pham Quynh Chau (2011). Her data base on Credit Information Center
and the model‘s variable are different from this research and she choose long-term
debt/total assets as her model‘s proxy. Moreover, she did not examine the impact of
credit ratings on capital structure. Base for some reasons above, this opens a new
direction for determining the impact of credit ratings on capital structure.

1.2 Research questions
Research questions As stated earlier, this research aims at examining the relationship
between credit ratings and capital structure for listed firms on HOSE. In particular, the
research examines if the firms that have high credit ratings will have lower financial
leverage than those with low credit ratings. In addition, the thesis will verify if firm has a
positive change of credit rating will borrow less than others.
Based on the research objectives, the following two questions will be answered in the
research:
--Do firms with higher credit ratings have lower financial leverage than those with lower
credit ratings ?
The firm have a high credit ratings that providing them with a higher incentive to
maintain their credit ratings than other rated firms in the market. Therefore, high rated
2

firms are expected to have a high concern for benefits enjoyed by their credit ratings
and thus have low levels of gearing.

- Is there a negative relationship between the range of credit ratings changes of the firm
and the following short term debt to equity ratio?
The implications of the credit rating – capital structure hypothesis are tested by
examining whether firms follow a pattern of leverage change behavior after they have
been changed in credit ratings.

1.3 Contributions of the research
Capital structure remains one of the most well researched topics in finance literature,
where several key aspects of the subject have already been explored. Currently, in
Vietnamese market, there have been a number of researches on capital structure and the
determinants of capital structure. However, there is little research on credit ratings in
general as well as on the relationship between credit rating and capital structure. Kisgen
(2006) stated that ―future capital structure research would benefit from including credit
ratings as part of the capital structure framework, both to ensure correct inferences in
capital structure empirical tests, and more generally, to obtain a more comprehensive
depiction of capital structure behavior‖ (p.1069). This thesis offers, an in depth analysis
of the relevance of credit ratings to the financial structure of HOSE firms, and thus makes
a number of contributions to finance literature. The findings of this study suggests that
credit ratings are important for firms in getting access to the Vietnamese debt markets.
For the rated firms specifically, credit ratings are one of the important factors in
determining the level of leverage.
1.4. Research methodology
This research uses quantitative research methods to examine the relationship between
credit ratings and capital structure. Literature review with relating theories and empirical
researches provide orientation for the study and determine factors to investigate in the
regression model. Quantitative methods with the support of analyzing tools including
Eviews, Stata and Excel are applied for the regressions, and statistical tests. Data sources

3


of this thesis are from financial statements of listed firms on Hochiminh Stock Exchange
and credit rating results of Credit Ratings Vietnamnet Center (CRVC)

1.5

Scope and limitation

This study focuses on testing the relationship between credit ratings and capital structure
of companies listed on HOSE within 4 years, from 2009 to 2012. Therefore, this study
has just conducted research on listed companies in HOSE, so the results cannot be
applied to all unlisted companies and companies listed on HNX.

1.6

Structure of research

Besides the Introduction, the thesis has four more chapter:.
-

Chapter 2 provides details of the general background of the rating agencies in the
world and Vietnam credit rating agencies, their operations and their significance.
This chapter also reviews the important theories of capital structure and presents
the relevant empirical evidence about the relationship between credit rating and
capital structure.

-

Chapter 3 discusses the methodology adopted in the present study. Specifically, it
presents the data collection procedures, models and the variables for the two
empirical chapters of the thesis.

-

Chapter 4 investigates the relationship between the level of credit ratings and the
leverage structure of listed firm on HOSE. Specifically, it presents the descriptive
statistics of the sample used in the analysis and the empirical results. The section
applies quantitative method with the support of analyzing tools including Excel
2007, Eviews 8.0 and Sata 12.0.

-

Finally, Chapter 5 concludes the thesis by summarizing the key findings,
discussing the limitations of the study and offers recommendations for future
research.

4


CHAPTER 2: LITERATURE REVIEW
2.1.Credit ratings
2.1.1. Introduction of credit ratings
According to Naeem, Shammyla (2012), credit rating is an economic term, which
estimates the credit worthiness of a borrower in general terms or with respect to a
particular debt or financial obligation. A credit rating helps in the assessment of the
solvency of the particular entity that seeks to borrow money such as an individual,
corporation, state or provincial authority, or sovereign government. Regulatory bodies

and rating agencies define themselves in their own ways. These ratings based on detailed
analysis of various credit rating agencies (CRAs). CRAs does not rely on mathematical
formulas to evaluate credit rating, instead, they use their judgment and experience in
determining what public and private information should be considered in giving a rating.
In other words, credit rating analysis of a corporate issuer typically considers many
financial and non-financial factors, both qualitative and quantitative. Credit ratings
evaluation base on economic, regulatory, and geopolitical influences; management and
corporate governance attributes; key performance indicators; competitive trends; productmix considerations; R&D prospects; patents rights; and labor relations (Meinna G –
2013).
Credit ratings are a set of alphabetic codes assigned in descending order according to the
rising likelihood of default. They may also include numerical codes or symbols,
depending on the rating agencies, to show the relative standing within each set of broad
category of alphabetic codes (Naeem, Shammyla,2012). For example, Standard and
Poor‘s assigns alphabetic codes such as AAA, AA, A, BBB, BB and so on, with ‗+‘ or ‗-‘
modifiers (AAA, AA+, AA, AA-, A+, A, A-, BBB+, BBB, BBB- and so on) to show the
respective creditworthiness within the broad rating category, whereas Moody‘s assign
numerical modifiers (Aaa, Aa1, Aa2, Aa3, A1, A2, A3, Baa1, Baa2, Baa3 and so on) to
the alphabetic codes (Aaa, Aa, A, Baa and so on).
Nguyen Duc Huong (2012) claim that credit ratings represent riskiness of the companies
and bonds, thus they have been extensively used by bond investors, debt issuers, and
government officials. Lower credit ratings result in higher borrowing costs because the
borrower face a higher risk of default. Similarly, Yoko Ogimoto (2008) asserted that
5


corporate credit ratings play a critical role in the provision of information to evaluate and
decide the credit problems, when enterprises want to have a frequent need for loans and
want to set up a long-term relationships with banks or investors. Thus building a
corporate credit rating system is not only helpful for the banks and investors in evaluating
the possibility of loan recovery, but also helpful for enterprises in evaluating its position

compared with other businesses. Despite the importance of credit ratings Vietnam has not
promulgated in any legal documents regarding corporate credit rating.

Moody’s

S&P

Fitch

Rating description

Aaa

AAA

AAA

Aa1

AA+

AA+

Aa2

AA

AA

Aa3

AA-

AA-

A1

A+

A+

A2

A

A

A3

A-

A-

Baa1

BBB+

BBB+

Baa2

BBB

BBB

Baa3

BBB-

BBB-

Ba1

BB+

BB+

Non-investment grade

Ba2

BB

BB

speculative

Ba3

BB-

BB-

B1

B+

B+

B2

B

B

B3

B-

B-

Caa1

CCC+

Caa2

CCC

Caa3

CCC-

Prime

High grade

Upper medium grade

Investment grade

Lower medium grade

Highly speculative

Speculative
grade,
High yield

Substantial risks
CCC

Extremely speculative
Default imminent with little
6


CC

prospect for recovery

Ca
C
C

D

DDD

In default

Table 1: The Credit Ratings description
Source: Boehm Kristina (2013)

2.1.2. Credit ratings agencies.
Sylla (2002) presented that credit rating agencies originated in the US market, in the early
20th century, due to the expansion of financial activities in the US and globally, apart
from investors, financial regulators were also demanding wider disclosure in terms of
firms‘ financial standings. Moody‘s, recognizing the need, formed the first formal rating
agency in 1909 (Sinclair, 2005). Following Moody‘s, Standard Statistics Company and
Fitch Publishing Company also emerged in this period. Since their inception, credit rating
agencies gradually became an important intermediary specializing in the provision of
reliable appraisals of the creditworthiness of the firms and countries. Due to the desired
attributes and general acceptability of credit rating agencies within the financial markets,
they soon gained recognition from regulatory bodies (Naeem, 2012).

According to Jacob de Haan and Fabian Tenbrink (2011) CRAs essentially provide two
services. First, they offer an independent assessment of the ability of issuers to meet their
debt obligations, thereby providing ―information services‖ that reduce information costs,
increase the pool of potential borrowers, and promote liquid markets. Second, they offer

―monitoring services‖ through which they influence issuers to take corrective actions to
avert downgrades via ―watch‖ procedures.
A Moody‘s research in 2002 said that in the case of upgrades, that can mean greater
capital market access and interest cost savings for issuers, and improved securities prices
for investors. In the case of downgrades, it can mean higher capital costs for issuers, and
portfolio turnover and losses for investors; most dramatically, however, it can terminate
an issuer‘s access to capital, possibly even leading to default. Especially in the case of

7


downgrades, the potentially self-fulfilling nature of ratings requires that CRAs
particularly endeavor to avoid ―false‖ negative predictions (Jerome S. Fons, Richard
Cantor and Christopher Mahoney – 2002)

2.1.2.1 Foreign market
In an analysis by Claire A. (2002), The World Big Three of credit rating agencies (CRA)
are Standard & Poor‘s (S&P), Moody‘s, and Fitch Group. They cover approximately
96% of the world market. S & P and Moody‘s are the United State companies and
account for 44.82% and 38.25% market share respectively. Meanwhile, Fitch Group is
operated by a French and accounts for about 13.25% of market share.
Other
4%
Fitch
Group
13%

Standard
& Poor's
45%

Moody's
38%

Figure 1: Market share of credit ratings agencies
Source: US Securities and Exchange Commission (SEC) website,
(Accessed 18 Apr. 2011)

8


Table 2: Credit Rating Definition by the Big Three CRAs
Source: Boehm Kristina (2013)
Moody‘s Ratings Definition

Fitch Ratings Definition

Standard & Poor Ratings
Definition

―Fitch

Ratings‘

credit Moody‘s

rates

ratings provide an opinion publishes

and ‖ a forward-looking opinion

independent about the creditworthiness

on the relative ability of an credit opinions on fixed of an obligor with respect to
entity to meet financial income securities, issuers of a
commitments
ratings,

as

relative

specific

financial

Credit securities and other credit obligation, a specific class
opinions

on obligations

ranking

of Investors

of financial obligations, or a
use

Moody‘s specific financial program.‖

vulnerability to default, do ratings to help price the (Standard & Poor‘s 2013a).
not imply or convey a credit risk of fixed income
specific

statistical securities or debts they may

probability

of

default, buy, sell or lend.‖ (Moody‘s

notwithstanding

the 2013).

agency‘s published default
histories

that

may

be

measured against ratings at
the time of default. Credit
ratings

are opinions

on

relative credit quality and
not a predictive measure of
specific

default

probability.‖ Fitch, 2013)

2.1.2.2 Vietnamese market
According to Nguyen Duc Huong (2012), Vietnam CRAs are still very young, they are
still in the process of building database and the credit rating system. Theirs credit rating
system are borrowed from other CRAs around the world and have not been unified for
9


Vietnamese market yet. Moreover, the lack of expert is also a weak point for the credit
rating industry in Vietnam. Currently, there are several CRAs in Vietnam, including :

Credit Information Center (CIC) is a credit rating agency of the State Bank of Vietnam.
The CIC‘s database is a unique database in Vietnam, which contains more than 600,000
business records and 20 million individual records. CIC mainly provides credit ratings of
non-financial companies and their reports are used by both the State Bank of Vietnam
and financial institutions.

Vietnam Credit Information and Rating Company (Vietnam Credit) is the first rating
agency in Vietnam. They have worked with corporate credit profile since 1996. Their
reports based on the standards of the world‘s major institutions such as Standard &

Poor‘s, Moody‘s, Fitch … VietnamCredit is a member of Asian Credit Information
Gateway (ASIAGATE).

Credit Ratings Vietnamnet Center (CRVC) started operations from June 2005. CRVC are
sponsored by government offices and they refer to the evaluation process of the Big
Three to build a consistent credit rating system in Vietnam. The Center recruits
professional, researchers deep understanding of credit ratings. According to CRVC, on
09/08/2012 CRVC has signed an agreement with Risk Management Institute of the
National University of Singapore (RMI), which is the leading research and training
organization within the region in the fields of risk management, including credit ratings.

To estimate credit ratings,: CRVC use 54 financial indicators, calculated from financial
statements of the company. After that, they choose the most significant indicator and base
on discriminant function and classification criteria to make CRVC‘ Credit ratings. For
example they use the following function to determine the credit rating (the Z score) of
firms:
Z= -0,352 – 3,118X4 + 2,763 X 8 – 0,55X22 – 0,163X24 + 6,543X29 + 0,12X53
In which:


X4 is the ratio of total loans / total assets
10




X 8 is the ratio of working capital / total assets



X22 is the ratio of receivables / net sales



X24 is the ratio of receivables / liabilities



X29 is the ratio of profit before interest and taxes / total assets



X53 is the ratio of profit after tax / equity
Table 3: Classification criteria
Source:CRV.com.vn
DISTINGUISHES

TYPE

Z> 1.7

AAA

0.85
AA

0
A

-0.85
BBB

-1.7
BB

2.2. Capital structure
2.2.1. Theories of capital structure
To date, capital structure remains one of the most chosen research topics in the finance
literature. Most researches base on several outstanding theories which explain the
relevance of capital structure, including tax related theories (Modigliani and Miller, 1963;
Miller, 1977; DeAngelo and Masulis, 1980), trade-off theories (Kraus and Litzenberger,
1973; Scott, 1976; Kim, 1978), pecking order theory (Myers, 1984; Myers and Majluf,
1984) and agency cost theories (Jensen and Meckling, 1976; Jensen, 1986). This section
will discuss the major theories of capital structure and some factors that have impacts on
capital structure.
2.2.1.1.The Irrelevance Theory of Capital Structure
Before Modigliani and Miller (MM) (1958), there was no accepted theory of capital
structure. They argued that the choice of debt or equity to finance assets does not impact
on firm value, shareholders can replicate the firm‘s capital structure without incurring

11


any additional costs and any change in the firm‘s capital structure is irrelevant to the
shareholders. Hence, according to this theory, the optimal capital structure of the firm
does not exist. Noted that this theory was based on a set of assumptions including perfect

and frictionless markets with perfect substitution of financing types, where there was no
transaction cost, constraining regulation, default risk, taxation or information asymmetry
and the firms are homogeneous in nature (Naeem, Shammyla, 2012).
2.2.1.2.The Taxes theory of Capital Structure
In 1963, Modigliani and Miller loosened the assumption of no corporate income tax.
Accordingly, they recognized the value of the tax deductibility of the interest payments
for the capital structure. Modigliani and Miller (1963) argue that given the value of the
tax shield, an optimal decision for firms would be to use as much debt as the firm can get,
as this would lead to increased value of the firm. This would imply a near exclusion of
equity financing. The value of the levered firm would therefore be equal to that of the
unlevered firm plus the value of the debt tax shield, thus, the value of corporation can be
maximized value when it has 100% debt. In reality, personal taxes, bankruptcy costs,
information asymmetry and agency costs can be quite onerous and can be incurred,
especially firm that are experiencing bankruptcy issues have high legal and accounting
related expenses, costs of debt covenants as well as the potential loss of clients or
suppliers, impaired ability to conduct business (Tran Thanh Huy, 2013).
Without Taxes

Value of the Firm

Cost of Equity

VL = VU

With Taxes

VL = VU + TC

( )

( )

Table 4: M&M (1963): A correction of irrelevance model of capital structure
Source: Corporate Finance (Ross, Westerfield, Jaffe and Jordan, 2008)
Where
12