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International Journal of Accounting & Business Management
www.ftms.edu.my/journals/index.php/journals/ijabm
Vol. 5 (No.2), November, 2017
ISSN: 2289-4519 DOI:24924/ijabm/2017.11/v5.iss2/131.148
This work is licensed under a
Creative Commons Attribution 4.0 International License.
Research Paper
THE IMPACT OF CAPITAL STRUCTURE ON FIRMS PERFORMANCE:
EVIDENCE FROM MALAYSIAN INDUSTRIAL SECTOR –A CASE BASED
APPROACH
Abdul Basit Lecturer
School of Accounting & Business Management
FTMS College, Malaysia
Nur Fasirah Irwan BSc(Hons) Accounting & Finance Student
Lord Ashcroft International Business School
Anglia Ruskin University, UK
ABSTRACT This research aim to identify the impact of capital structure on firm performance of Malaysia listed
industrial product company. Convenience sampling technique was using in this research to select 50
industrial product companies listed in Bursa Malaysia main exchange market based on available of
2011 to 2015 annual report. The independent variables used in this research are debt to equity ratio,
total debt ratio and total equity ratio. Return on asset (ROA), return on equity (ROE) and earning per
share (EPS) are used as dependent variable to measure firm performance. Descriptive statistics and
multiple regression are used in this research to analyses the data. This research found industrial
product company are heavily rely on equity finance in their capital structure. Besides that, the
regression result found debt to equity has negative impact on ROA, total debt ratio and total equity
ratio has insignificant impact on ROA. Debt to equity has negative impact on ROE, total debt has
positive impact on ROE and total equity has insignificant impact on ROE. Besides that, debt to equity
has negative impact on ROE, total debt has positive impact on ROE and total equity has insignificant
impact on ROE. Finally, debt to equity has a negative significant impact on EPS, total debt ratio has
positive significant impact on EPS and total debt has insignificant impact on EPS. In conclusion,
industrial product company raise debt finance can reduce agency problem and enjoy tax advantage,
but debt level over the optimum capital structure will bring a negative impact on firm performance.
This research will benefit for the industry, manager, shareholder, investor and future researcher.
Future researchers are recommending to use large sample size and other variable to identify the
impact of capital structure on firm performance.
Key Terms: Capital Structure, Debt to Equity, Total Debt, Total Equity, Firm Performance, ROA,
ROE, EPS
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1. INTRODUCTION
The purpose of this research is to identify the impact of capital structure of firm
performance in listed company of the Bursa Malaysia exchange on the industrial product
sector. Started from 1980, Malaysia to be a new industrialized country and focus on produce
and export manufacture goods (Bank Negara Malaysia, 2011). Manufacture export occupy
80.2 % of Malaysia 2015 total export (Economic Planning Unit, 2016). From the 2016 total
export, industrial product such as technical, machinery, plastics product, rubber product and
chemical good were ranking in to the top 10 of Malaysia Export (Workman, 2017). Summary
of the above information, industrial product sector is an important part of Malaysia economic.
Capital structure is a mixture of the debt and equity securities used to finance real investment
(Myers, 2000). The beginning of capital structure study was introduced by Modigliani and
Miller in 1958 (Tailab, 2014). After Modigliani and Miller, many research have developed to
investigate capital structure and argue with the Modigliani and Miller theorem. So, there are
many capital structure theories were developed such as Myers (1984) introduced tradeoff
theory to argue that the optimum capital structure is exists, Myers and Majluf (1984)
introduce a pecking order theory which indicated manager more prefer using internal funds,
Jensen and Meckling (1976) introduce agency theory which indicated principle-agent
problem can reduce by raising debt level and so on.
A significant number of research were identified the impact of capital structure on
firm performance in developed and developing countries. In the developed countries aspect,
Tailab (2014) did research on American energy, Tifow and Sayilir (2015) did research
Turkey manufacturing firm and Abeywardhana (2016) did research on United Kingdom
manufacturing sector small and medium enterprise (SME). From 2013 forward, most of the
research done in capital structure was carried on developing countries. Ogebe, et al (2013)
did research on Nigeria firm performance. Kajananthan and Nimalthasan (2013) did research
on Sri Lankan manufacturing firm, Hasan, et al (2014) did research on Bangladesh food, fuel
and power, pharmaceuticals and miscellaneous sectors companies, Mwangi, et al (2014) did
research on Kenya non-financial listed companies performance, Zeitun and Tian (2014) did
research on Jordanian non-financial listed companies, Leonard and Mwasa (2014) did
research on Kenya listed companies and Akeem, et al (2014) did research on Nigeria
manufacturing companies performance.
In empirical Malaysia capital structure studies, San and Heng (2011), did a research
on Malaysia listed construction companies performance. While Salim and Yadav (2012) did a
research on several sectors construction, consumer product, industrial product, plantation,
property, trading and service sector, Malaysia. In addition, Foo et al (2015) did a research on
Malaysian public listed oil and gas companies and Hadi et al (2015) did a research on
Malaysia property companies. Furthermore, Shahara and Shahar (2015) did a research on
Malaysia Shariah compliant and Non-Shariah compliant listed companies while Sabin and
Miras (2015) did a research on low capitalized firm. Finally, Ahmad et al (2012) did a
research on consumers and industrials sectors. However, none of these past researcher did a
study on Malaysian industrial product sector which is why this study is important.
Therefore, this research will help author to understand the impact of capital structure
on industrial product companies’ performance. Moreover, this research will help company
manager and stakeholder know more about the impact of capital structure and the sensitive of
debt and equity in the industrial product sector. It will provide a guide to financial manager to
design a better capital structure to reduce cost of capital, raise firm performance and
maximize shareholder wealth. Besides that, this research can lead the investor to know more
about the effect of capital structure choice on their return, it will give a guide to help them to
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create their investment portfolio. Finally, this research can rich the following capital structure
researcher literature and given a guideline in their future research.
Research Objectives
To identify the impact of capital structure on ROA.
To identify the impact of capital structure on ROE.
To identify the impact of capital structure on EPS.
2.0 LITERATURE REVIEW
According to Myers (1984), capital structure is choose of debt, equity or hybrid
securities for firm to finance their business while Harris and Raviv (1991) indicated capital
structure as a part of solution problem overinvestment and underinvestment. Myers (2000)
defines the capital structure is a mixture of the debt and equity securities used to finance real
investment. Roshan (2009) indicated that capital structure is a financial structure of an entity,
is combines of debt and equity fund maintained by an entity. Finally, Brendea (2011), stated
that capital structure is the long term financing used by entity while Nirajini and Priya (2013)
added that capital structure refer to the way which the entity financed a mixture of long term
capital and short term liabilities.
The first theory established from capital structure is the Modigliani and Millers (1958)
which the research found that capital structure has no brought any impact to the firm’s market
value and average cost of capital. M&M 1958 theory is based assumption of perfect capital
market with no tax, no transaction cost and risk free debt (Modigliani & Miller, 1958).
M&M’s 1958 has been supported by Cole, et al (2015) research, capital structure had no
relationship with companies’ stock price. In year 1963, Modigliani and Millers have
published a new research paper to correct their previous error and indicated debt finance
given tax advantage to firm (Modigliani & Miller, 1963). Hence, the capital structure is
relevant to the firm value and firm able to maximize firm value by raise debt level in their
capital structure (Sabin and Miras, 2015). Nirajini and Priya (2013) research show support to
this theory, a positive relationship between debt and firm performance. M&M theory (1858
and 1963) was criticized as unrealistic due to the impractical assumption (Sabin & Miras,
2015). Imperfect capital market, transaction cost and bankruptcy cost exist in real world lead
the M&M’s theory to be limited applicability (Foo, et al., 2015). Deeds, et al (1995) also
indicated M&M’s theory only suitable to explain the capital structure decision in small firm
only. Even M&M theorem have some weakness, but it provided a basis concept for the
capital structure and a foundation of other theories (Ahmad, et al., 2012). Ahmeti and Prenaj
(2015) also supported MM theory goes beyond the propositions themselves.
Trade-off theory was develop by multi research paper and grew up from the M&M
relevant theory (Myers, 1984). Tradeoff theory indicated each financial source has own
benefit and cost (Awan & Amin, 2014). The firm’s optimum capital structure is identified
by the tradeoff of the benefit and the cost of debt finance (Myers, 1984). Trade-off theory
indicated higher profitability firm will be able to take more tax advantage by increases
borrowing without risking financial distress and apply a higher portion of debt finance in
capital structure (Kausar, et al., 2014). Several studies such as Goyal (2013), Javed and
Akhtar (2012), Salawu (2009), Coleman (2007) and Negasa (2016) provided empirical
evidence to supporting tradeoff theory, a positive relationship between debt level and
profitability. However, trade-off theory were criticizes that it is correct under the assumption
of no cost of adjustment (Myers, 1984). Besides that, trade-off theory has ignored the effect
of retain earning in the capital structure, retain earning is no cost and no risk (Frank &
Goyal, 2005). Pettit and Singer (1985) criticize that trade-off theory is not suitable for small
firms, because small firms don’t have enough earning to trade-off cost of debt.
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Pecking order theory was introduced by Myers and Majluf (1984) to explain that
optimum capital structure does not exist and firm manager are more prefer to use internal
fund to finance their business activities (Hasan et al, 2014). Asymmetric information arisen
between manager and stakeholder, manager know more information than outsides investor
about the firm performance (Nirajini and Priya, 2013). This theory connote an existence of
financial hierarchy with fist is an internal fund, second is debt and lastly is equity (Jamal et
al, 2013). Saputra et al (2015), Foo et al (2015), Mohammadzadeh et al (2013) research used
pecking order theory to test the capital structure and found capital structure has a negative
impact on firm performance. Acaravci (2015) indicated pecking order theory is widely
applicable, large company and small company also can apply. Butt and Khan (2013)
indicated pecking order theory has considers the motivation of firm. Liesz (2011) also
supported this theory have observe and reported managerial actions. However, this theory is
few to consider the tax shield effect (Acaravci, 2015). More than that, pecking order theory
also ignore the problem of too much financial slack and long term does not issue security
may led to the low security price (Liesz, 2001). Saputra, Achsani and Anggreani (2015), Foo
et al (2015), Mohammadzadeh et al (2013) research found capital structure has a negative
impact on firm performance, consistent with the pecking order theory.
Agency cost theory developed by Jensen and Meckling in year 1976. Agency cost is a
cost arisen from the interest conflict between principal and agent (Ahmad, et al., 2012).
Jenson (1986) develop a free cash flow hypothesis, manager and shareholder have different
expected to use the free cash, so interest conflict and agency problem arise. Principle – agent
problem and free cash flow problem can dealt with some extent of capital structure by
increasing debt level (Roshan, 2009). High debt encourage manager invest in profitable
project that benefit of shareholder wealth to ensure company able to paid the interest (Berger
& Patti, 2002). Hence, high debt will reduce agency cost and lead to firm performance
increase (Chinaemerem & Anthony, 2012). Chinaemerem and Anthony (2012) research show
support to this theory. In order hand, this theory can considered as a version of trade-off
theory (Brendea, 2011). Agency cost theory states that the optimum capital structure is at the
point which the benefit of debt finance offset agency cost of debt (Brendea, 2011). Agency
cost are real exist in the world, level of agency problem is depend on the law, regulation and
human ingenuity in devising contracts (Jensen & Meckling, 1976). However, agency theory
only applicable when the agent and shareholder goal incongruence (Arthurs & Busenitz,
2003). Agency theory was criticize is well in explain the concept of human being, but does
not accurately reflect the diverse motivation for individual behavior (Baumüller, 2007).
Besides that, the agency theory only consider about principle’s perspective, principals
behavior, responsibilities and their influence on the relationship with agent has been ignore
(Baumüller, 2007).
In Malaysia capital structure studies, San and Heng (2011) did a research on
investigating the relationship of capital structure and performance for the period 2005-2008.
49 listed construction companies were taken as sample of the research and divided into big,
small and medium sizes companies. Dependent variable of the research is corporate
performance, measure through ROC, ROE, ROA, EPS, operating margin (OM) and net
margin (NM). Long term debt to capital (LTDC), debt to capital (DC) , debt to asset (DA),
debt to equity market value (DEMV), debt to common equity (DCE) and long term debt to
common equity (LTDCE) were employed as independent variable (capital structure). Pooling
regression model was employed to test the impact of capital structure on corporate
performance. San and Heng found that in big companies, ROC with DEMV and EPS with
LTDC have a positive relationship, but EPS and debt to capital has a negative relationship.
For medium companies, OM has a positive relationship with LTDCE. For small companies,
negative relationship between EPS and DC. The author only observes three years data, the
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observation is fewness. Increase in sample size or the years’ observation cam improve the
result. For example, Salim and Yadav (2012) research taken 237 companies as sample and
observed over 1995 until 2011 period. The result of research shows firm performance
measure through ROA, ROE and EPS has a negative relationship with capital structure, but
Tobin’s Q has a significant positive relationship with short term debt and long term debt.
Besides that, companies’ sale growth has positive relationship with firm performance for all
sector.
Table 1: Summary of Variables
Capital structure Financial performance
Variables Source Variables Source
Debt to equity Hadi et al (2015), Goh et
al (2016), Nawaz et al
(2011)
Return on Asset Foo et al (2015), San and
Heng (2011), Ahmad et
al (2012), Salim and
Yadav (2012)
Total debt Foo et al (2015), San and
Heng (2011), Ahmad et
al (2012), Salim and
Yadav (2012)
Return on Equity Foo et al (2015), San and
Heng (2011), Ahmad et
al (2012), Salim and
Yadav (2012)
Total equity Githire & Muturi (2015),
Idode et al (2014),
Sivathaasan & Rathika
(2013)
Earnings per share San and Heng (2011),
Hadi et al (2015), Salim
and Yadav (2012)
Based on Table 1 the variables adopted in this research for capital structure are debt to
equity, total debt and total equity. The three variables adopted for the financial performances
are return on asset (ROA), return on equity (ROE), and earning per share (EPS).
Debt to equity formulate is total debt divided by total equity, increase debt will raise
debt to equity (Hitchner, 2003). Based on trade off theory, debt provide tax advantage to
company (Obim, et al., 2014). Hence, increase company debt level able to reduce tax
expense and raise firm performance. Therefore, debt to equity has a positive significant
impact on ROA. Goh et al (2016), Nawaz et al (2011) and Nirajini and Priya (2013) finding
show support to this view. Numerous studies was found a difference result and indicate debt
to equity has negatively significant impact on ROA (Mwangi, et al., 2014; Saputra, et al.,
2015; Sabin & Miras, 2015; Abeywardhana, 2016; Pratheepkanth, 2011; Leonard & Mwasa,
2014; Akeem, et al., 2014; Mohamad & Abdullah, 2012; Muhammad, et al., 2014).
H1: Debt to equity has positive significant impact on ROA
Total debt ratio formula is using total debt divided by total asset Invalid source
specified.. Based on agency cost theory, agency problem can reduce through raising
company debt level (Roshan, 2009). High debt level encourage manager to work for
company interest (Berger & Patti, 2002). Hence, total debt ratio has positive significant
impact on ROE. Negasa (2016) and Idode et al (2014) research finding show support to this
view.
H2: Total debt ratio has positive significant impact on ROA
Equity is another important element of capital structure, equity finance dos not require
fixed repayment and interest (Saad, et al., 2014). So, raising equity finance will bring a
positive impact on firm performance (Boateng, 2004) Githire and Muturi (2015) and Idode et
al (2014) research result show support to this hypothesis and indicated total equity ratio has a
positive significnat impact on ROA.
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H3: Total equity ratio has a positive significant impact on ROA
According to Modigliani & Miller (1963) relevent theory, debt provide huge tax
shield effect and it able to reduce cost of capital. Hence, raising debt to equity ratio able to
reduce cost of capital and led the manager able to produce more efficiency ROA. Saputra et
al (2015) and Nirajini & Priya (2013) research finding show support to this view. However,
numerous empirical studies has found debt to equity has significant negative impact on ROE
(Mohamad & Abdullah, 2012; Sabin & Miras, 2015; Mwangi, et al., 2014; Pratheepkanth,
2011; Leonard & Mwasa, 2014; Akeem, et al., 2014; Chadha & Sharma, 2015; Muhammad,
et al., 2014).
H4: Debt to equity has positive significant impact on ROE
Based on tradeoff theory, debt able to raise firm performance through the tax shield
effect (Myers, 1984). Besides that, it also indicated high profitability firm will be able to take
more tax advantage by increases borrowing without risking financial distress (Kausar, et al.,
2014). Hence, total debt ratio has a positive impact on ROE. Saputra et al (2015) Nirajini and
Priya (2013) and Abor (2005) finding show support to this view. However, some of the
empirical research found an adverse result and indicate total debt ratio has a negative
significant impact on ROE (Awais, et al., 2016; Foo, et al., 2015; Chinaemerem & Anthony,
2012; Tailab, 2014)
H5: Total debt ratio has positive significant impact on ROE
Large external equity holders can mitigate agency conflicts because of they have
strong incentives to monitor manager and ensure resource are allocate appreciate (Booth, et
al., 2001). Hence, this research assume total equity has significant positive impact on ROE.
Ferati and Ejupi (2012) research support to this hypothesis and indicated total equity has a
significant positive impact on ROE.
H6: Total equity ratio has positive significant impact ROE
High debt to equity means a high debt or low equity. High debt encourage firm
manager work for company interest and hence has a positive effect on firm performance
(Berger & Patti, 2002). Therefore, this research assumes that debt to equity ratio has
significant positive impact on EPS. Ebrati et al (2013) discover debt to equity has a
significant negative impact on EPS.
H7: debt to equity has positive significant impact on EPS
Based on Modigliani and Miller (1963), debt finance provide tax advanatege for
company and hence the cost of capital reduce. It impose a positive impact on firm
performance. Hence, this research assume total debt ratio has a positive impact on EPS.
Numerous research discover total debt has a significant negative impact on EPS (Awais, et
al., 2016; Umar, et al., 2012; Ebrati, et al., 2013; Salawu, 2009; Salim & Yadav, 2012).
Hasan et al (2014) found that total debt ratio has no significant impact on EPS.
H8: Total debt ratio has positive significant impact on EPS
High equity finance mean company are less borrowing, interest payment and financial
risk (Saad, et al., 2014). Hence, company can reserve the profit and invest in profitable
project. Therefore, this research assume that total equity ratio has a significant positive
impact on EPS. Saad et al (2012) research show support to this view, total equity is
significant positive correlation with earning per share.
ISSN: 2289-4519 Page 137
Total Equity ratio
(Githire and Muturi,
2015)
H9: Total equity ratio has positive significant impact on EPS
Conceptual Framework
Capital structure Firm’s performance
Figure 1: Conceptual Framework
3.0 RESEARCH DESIGN AND METHODOLOGY
Explanatory research design is applied in this research to identical whether capital
structure brought impact to firm performance. Compare to exploratory and descriptive
research, explanatory research design able to provide more intellectual satisfaction and clear
conclusion though eliminate puzzles (Blaikie, 2009). It because, explanatory research used
hypotheses testing to identify whether the variable (capital structure) cause another (Blanche,
et al., 2006). Besides of the explanatory research design, time series design also using in this
research. Time series data refer to the data collect from containing series time (Hsiao, 1995).
This research taken the data from 50 companies 5 year annual report. It can provided a more
accurate data compare to cross-sectional design (Shukla, 2008). It because time series design
able monitors the change over a period and capturing the complexity of human behavior
(Hsiao, 1995; Shukla, 2008). Data provides from difference firm annual report might
different, the time series data able to solve this problem. For example the company has
restates the 2012 financial statement, the correction will be clear state in 2013 annual report.
Data collection methods: This research has employed secondary data collective
method. Secondary data mean data that are already collected by someone for a different
purpose (Johnston, 2014). Secondary data can collected from book, company annual report,
journal article, social report, organization statistics and others (Kothari, 2004). In this
research, author is direct take research require data such as company net income, total debt ,
total equity and others from company annual report without any cost.
Population and sample size: Based on the information available from Bursa
Malaysia, a total of 268 industrial product companies are listed in Bursa Malaysia main stock
exchange market. This research taken 50 listed industrial product companies and observe
over 2011 to 2015. Totally 250 observation taken as a research sample, the sample size is
excess the minimum sample size require (Cridland, n.d.). This research is using convenience
Return on asset
(Hasan, et al., 2014)
Return on equity
(Akeem, et al., 2014)
Earnings per Share
(Ebrati, et al., 2013)
Debt to equity ratio
(Sabin and Miras,
2015)
Total Debt ratio
(Salim and Yadav,
2012)
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sampling technique. Convenience sampling technique is non-probability sampling method,
sampe are selected if they are meet particular certain criteria (Farrokhi & Hamidabad, 2012)
Convenience sampling technique is appreciate for this research because many of the
companies were not available of 5 year data that was require for this study. Hence, 50
companies which has publish 2011 to 2015 annual report in official website or Bursa
Malaysia website have meet the criteria and taken as research sample.
Accessibility and ethical issue: In this research paper, all of the data is direct access
from the companies’ annual report. Listed companies are requiring publishing their annual
audited report and financial statement to Bursa Malaysia, so the access is easy (Crowe
Horwath , 2015). The ethical issue in this research is quite less, only has copyright issue and
legal assess should be taken into consider. In order to solve copyright issue, this research will
have proper citation of the fact. Besides that, companies’ annual report was downloaded from
Bursa Malaysia webpage. Hence, the legal assess is not an issue for this research.
Data analysis method: E-view was used in this research paper to interpretation of the
data into statistical information because it is the best software to deals with the cross-
sectional and time series data compare to Statistical Package of Social Sciences (Richard,
2015). Three data analysis method ware used in this research paper which are descriptive and
multiple liner regression analysis. Descriptive statistic is a set of coefficient that summarizes
data provided by sample (Wyllys, 1978). It able shows the data into graphically and
numerically (Jaggi, 2016). It will be easy to understand and discuss of the data. However,
descriptive statistics only provided a summary of what the research already measure, unable
to find out the causality (Xie, 2011). In order to overcome this limitation, correlation and
multiple regression analysis have used to find out causality. Multiple liner regression are
main data analysis in this research. It’s able to identify the associated between variety
variable (Bewick, et al., 2003). For example to measure the impact of capital structure on
ROA, ROE and EPS. Sykes (1993) also supported multiple regression analysis provided a
helpful statistic data to qualify the impact of various independent influence upon a single
dependent variable.
4.0 DATA ANALYSIS
Descriptive analysis Table 2: Descriptive Statistics
Variable Mean Median Maximum Minimum Std. Dev.
Debt to equity 0.368 0.097 7.001 0.0003 0.743
Total Debt Ratio 0.170 0.088 0.843 0.0003 0.211
Total Equity Ratio 0.836 0.913 1.449 0.116 0.219
ROA 0.082 0.071 0.813 -0.901 0.133
ROE 0.077 0.080 0.858 -3.661 0.293
EPS 0.124 0.091 1.173 -3.963 0.382
According to Table 2, equity ratio has a higher mean value of 0.836 with the standard
deviation of 21.9%. It value indicated that the selected 50 company are average relies 83.6%
on equity finance in their capital structure. Secondly, debt to equity has mean value of 0.368
with the standard deviation of 74.3%. It mean that the average company gearing level is
lower, debt finance is 36.8% of the company total equity. However, the high standard
deviation value show that the mean value of debt to equity is not reliable. Lastly, debt ratio
has a mean value of 0.170 with the standard deviation value of 21.1%. It show that 50
company are relies 17% on debt finance in their capital structure. The standard deviation
value is higher than 0.17 show that the mean value of total debt ratio is not reliable.
ISSN: 2289-4519 Page 139
Based on the table 2, earning per share has a higher mean value of 0.124 with
standard deviation of 38.2% in among of dependent variable. It indicates the industrial
product companies shareholder are enjoy average of 12.4% return on each common share
from the period 2001-2015. Secondly, companies are enjoying average return on total asset
on 8.2% with standard deviation of 13.3%. Lastly, the industrial product companies are enjoy
average value of 7.7% of return on equity with standard deviation of 29.2%. However, value
of standard deviation for dependent variable (EPS, ROA, ROE) is higher than the mean
value. It indicated the mean value of dependent variable is not reliable.
Regression analysis
Table 3: Regression analysis of Return on Asset (ROA)
Model R-squared Adjusted R-
squared
Prob (F-statistic) Durbin-Watson
stat
1 0.535 0.400 0.000 2.588
Variable Coefficient Std. Error t-Statistic Prob.
Debt to equity -0.064 0.023 -2.765 0.006
Total debt ratio -0.136 0.167 -0.823 0.411
Total equity ratio 0.048 0.134 0.357 0.721
According to the Table 3, R-squared value is 0.535 which indicated 53.5% of ROA
can be elaborated by the debt to equity ratio, total debt ratio and total equity ratio. A good fit
model arisen when the adjusted R-squared value is more 0.6, this model is not a good fit
because it value only 0.4 (Zygmont & Smith, 2014). The probability of F-statistics is 0.000
show that this model is significant. Durbin-Watson value is 2.588 indicated there
autocorrelation among the 50 selected sample company as the value out in the range of 1.5-
2.5 (Folarin & Hassan, 2015).
As for the dependent variables as according to table 4.2.1, debt to equity ratio beta
coefficient value is -0.064 with a probability value of 0.006 which is lower than 0.05 (Hadi,
et al., 2015). It show that debt to equity has negative significant impact on ROA. This result
supported by the Mwangi et al (2014) and Saputra et al (2015). However, Goh et al (2016),
Nawaz et al (2011) found adverse result and indicated debt to equity has a significant positive
impact on ROA. Based on this result, hypothesis 1 is rejected.
Total debt ratio beta coefficient value is -0.136 with a probability of 0.411. Its show
that total debt ratio has negatively insignificant impact on ROA. Foo et al (2015) found a
same result. However, Negasa (2016) and Idode et al (2014) found a different result and
indicated total debt ratio has a positive significant impact on ROA. Based on this result,
hypothesis 2 is rejected.
Total equity ratio beta coefficient value is 0.048 with a probability of 0. Its mean total
equity ratio has positive insignificant positive impact on ROA. However, Githire and Muturi
(2015) and Idode et al (2014) discover total equity ratio has a significant positive impact on
firm performance measure by ROA. Based on this result, hypothesis 3 is rejected
Table 4: Regression analysis of Return on Equity (ROE)
Model R-squared Adjusted R-
squared
Prob (F-statistic) Durbin-Watson
stat
2 0.713 0.629 0.000 2.296
Variable Coefficient Std. Error t-Statistic Prob.
Debt to equity -0.658 0.040 -16.495 0.000
Total debt ratio 1.332 0.289 4.617 0.000
Total equity ratio -0.103 0.232 -0.453 0.651
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According to the table 4, R-squared value is 0.713 which indicated 71.3% of ROE can
be elaborated by the debt to equity ratio, total debt ratio and total equity ratio. This model is
good fit because it adjusted R-squared value is higher than 0.6 (Zygmont & Smith, 2014).
The probability of F-statistics is 0.000 shows that this model is significant. Durbin-Watson
value is 2.296 indicated there no autocorrelation among the 50 selected sample company as
the value fall in the range of 1.5-2.5 (Folarin & Hassan, 2015).
As for the dependent variables as according to Table 4, debt to equity ratio beta
coefficient value is -0.658 with a probability value of 0.000 which is lower than 0.05 (Hadi,
et al., 2015). Hence, debt to equity has significant negative impact on ROE. Sabin and Miras
(2015) and Akeem et al (2014) found a same result. However, Nirajini and Priya (2013)
argue that debt to equity has a significant positive impact on ROE. Based on this result,
hypothesis 4 is rejected.
Secondly, total debt ratio beta coefficient value is 1.332 with a probability of 0.000
(Hadi, et al., 2015). Hence, debt ratio has a significant positive impact on ROE. This result
are supported by Abor (2005) and Saputra et al (2015). However, Mohamad and Abdullah
(2012) argue that total debt ratio has a significant negative impact on ROE. Based on this
result, hypothesis 5 is accepted.
Lastly, total equity ratio beta coefficient value is -0.103 with a probability of 0.
Hence, the equity ratio has insignificant negative impact on ROE. This research Based on this
result, hypothesis 6 is rejected.
Table 5: Regression analysis of Earnings per Share (EPS)
Model R-squared Adjusted R-
squared
Prob (F-statistic) Durbin-Watson
stat
3 0.617 0.505 0.000 2.157
Variable Coefficient Std. Error t-Statistic Prob.
Debt to equity -0.658 0.060 -11.410 0.000
Total debt ratio 1.279 0.434 2.946 0.004
Total equity ratio 0.099 0.349 0.283 0.777
According to the Table 5, R-squared value is 0.617 which indicated 61.7% of EPS can
be elaborated by the by the debt to equity ratio, total debt ratio and total equity ratio. This
model is not good fit model because it adjusted R-squared is lower than 0.6 (Zygmont &
Smith, 2014). The probability of F statistics is 0.000 shows that this model is significant.
Durbin-Watson value is 2.157 indicated there no autocorrelation among the 50 selected
sample company as the value fall in the range of 1.5-2.5 (Folarin & Hassan, 2015).
As for the dependent variables as according to Table 5, debt to equity ratio beta
coefficient value is -0.685 with a probability value of 0.000 which is lower than 0.05 (Hadi,
et al., 2015). Hence, debt to equity has significant negative impact on EPS. Ebrati et al (2013)
found a same result. However, Sivathaasan & Rathika (2013) argue that debt to equity ratio
has insignificant positive impact on EPS. Based on this result, hypothesis 7 is rejected.
Secondly, total debt ratio beta coefficient value is 1.279 with a probability of 0.000.
Hence, total debt ratio has a significant positive impact on EPS. This research is opposite
with the Ebrati et al (2013), Salawu (2009) and Awais et al (2016). They found that total debt
ratio has a negative significant impact on EPS. Based on this result, hypothesis 8 is accepted.
Lastly, total equity ratio beta coefficient value is 0.099 with a probability of 0.099
which is higher than 0.05 (Hadi, et al., 2015). Hence, the equity ratio has insignificant
positive impact on EPS. Sivathaasan and Rathika (2013) found a same result. Based on this
result, hypothesis 9 is rejected.
ISSN: 2289-4519 Page 141
4.3. DISCUSSION AND FINDING
Impact of capital structure on ROA
According to Table 3, debt to equity has negative significant impact on ROA. It mean
company heavily depend on debt finance will cause a high cost of capital and lead the
company performance fall. This result show support to agency theory, company are trend to
overhang debt finance to reduce agency problem and it leads the ROA fall (Leonard &
Mwasa, 2014). Mwangi et al (2014) and Saputra et al (2015) found a same result. However,
Goh et al (2016) and Nawaz et al (2011) found difference result. The different result arise
because the difference industrial characteristic and behavior.
Secondly, total debt ratio has negative insignificant impact on ROA. The insignificant
value indicate any change on total debt does not impose impact on ROA. It result show
support to Modigliani and Miller (1958) irrelevent theory. Negasa (2016) and Idode et al
(2014) found a different result and indicated total debt ratio has a positive significant impact
on ROA. The different result arise because this research does not taken the control variable
into research framework, different country and industry has difference characteristic and
behavior
Lastly, total equity ratio has positively insignificant impact on ROA. Equity finance
does not require company to have fixed monthly or annually interest payment. Hence,
company more equity finance able to retain their earning and raise ROA. However, the
insignificant value indicated change in total equity ratio does not inflict any impact on ROA.
It result show support to Modigliani and Miller (1958) irrelevent theory. Githire and Muturi
(2015) and Idode et al (2014) found a different result. The difference result arise because this
research only focus on industrial product sector.
Impact of capital structure on ROE.
.According to table 4, debt to equity has negatively significant impact on ROE. It mean
company heavily depend on equity finance enjoy more return on equity compare to company
heavily depend on debt finance. This result show debt to equity increase will cause firm
performance fall, it show opposite with the Modigliani and Miller (1958) relevant theory.
Sabin and Miras (2015) and Akeem et al (2014) found a same result with this research.
Nirajini and Priya (2013) and Saputra et al (2015) found a difference outcome with this
research. The different result arise because this research does not taken the control variable
into research concept and the different industry has difference characteristic and behavior.
Secondly, total debt ratio has positively significant impact on ROE. It indicate
company debt level increase given more tax advantage to company and hence company ROE
will increase. It show support to Modigliani and Miller (1958) relevant theory. Saputra et al
(2015), Nirajini and Priya (2013) and Abor (2005) found a same result. Mohamad and
Abdullah (2012), Chinaemerem and Anthony (2012), Muhammad et al (2014), Muritala
(2012), Tailab (2014) and Akeem et al (2014) found opposite result. The different result
arise because this research does not taken the control variable into research framework,
different country and industry has difference characteristic and behavior.
Lastly, total equity ratio has negatively insignificant impact on ROE. Transaction
cost, asymmetric information problem and other issue cost lead the equity fund become
expenses. However, the insignificant impact indicated change in total equity ratio does not
inflict any impact on ROE. . It result show support to Modigliani and Miller (1958) irrelevent
theory.
ISSN: 2289-4519 Page 142
Impact of capital structure on EPS
According to Table 5 debt to equity has negatively significant impact on EPS. It
means the high gearing company are trend to use proportion of income to repay the interest
Invalid source specified.. Hence, the high debt to equity ratio will lead the company EPS
decline. This research show support with the tradeoff theory which indicated the debt level
over the optimum point will cause cost of capital increase. Ebrati et al (2013) found a same
result but Sivathaasan & Rathika (2013) found a different result. The different result arisen
because different industry has difference characteristic and behavior. Sivathaasan & Rathika
(2013) research is focus on financial institution, this research is focus on industrial product
company.
Secondly, total debt ratio has positively significant impact on EPS. The high debt
level require high fixed interest payment, it motivate manager to invest in profitable project
(Berger & Patti, 2002). Hence, the high debt level can reduce agency problem and lead the
company performance raise, it show support to agency theory. Salim and Yadav (2012),
Ebrati et al (2013), Salawu (2009) and Awais et al (2016) found a different result with this
research. The different result arisen because this research does not taken the control variable
into research framework and different country has difference characteristic and behavior.
Lastly, total equity ratio has positively insignificant impact on EPS. Company more
trend to used equity finance encourage shareholder to have a direct control to the firm
manager to ensure company resource are allocated appropriate. However, the insignificant
impact indicate change in total equity does not inflict any impact on EPS. It result show
support to Modigliani and Miller (1958) irrelevent theory. Sivathaasan and Rathika (2013)
found a same result.
Summary of hypothesis Table 6: Summary of hypothesis
Hypothesis Beta
coefficient
Significant Result
H: Debt to equity has positive
significant impact on ROA.
-0.064
0.006
Rejected
Debt to equity has a negative
significant impact on ROA.
H2: Total debt ratio has positive
significant impact on ROA
-0.136
0.411
Rejected
Total debt ratio has a negative insignificant impact on ROA.
H3: Total equity ratio has positive
significant impact on ROA
0.048
0.721
Rejected
Total equity ratio has positively
insignificant impact on ROA.
H4: Debt to equity has positive
significant impact on ROE.
-0.658 0.000 Rejected
Debt to equity has a negative
significant impact on ROE.
H5: Total debt ratio has positive
significant impact on ROE
1.332 0.000 Accepted
H6: Total equity ratio has positive
significant impact ROE
-0.103 0.651 Rejected
Total equity ratio has negatively insignificant impact on ROE.
H7: Debt to equity has positive
significant impact on EPS.
-0.685 0.000 Rejected
Debt to equity has negative significant impact on EPS
H8: Total debt ratio has positive
significant impact on EPS
1.279 0.004 Accepted
H9: Total equity ratio has positive
significant impact on EPS
0.099 0.777 Rejected
Total equity ratio has positive
insignificant impact on EPS.
ISSN: 2289-4519 Page 143
5.0 CONCLUSION
For the impact of capital structure on return on asset (ROA) which is based on
descriptive statistics, sample companies more trend to using equity finance, average equity
ratio is in 0.836. Further, the regression result show total equity ratio has positive
insignificant impact on ROA. The selected sample companies with more equity finance will
no imposes significant impact on ROA. It show support to Modigliani and Miller (1958)
irrelavent theory. In conclusion, debt to equity has a negatuve significant imapct on ROA,
total debt ratio and total equity ratio has no significant impact on ROA.
For the impact of capital structure on return on equity (ROE) which is based on
descriptive statistics, sample companies more trend to using equity finance, average equity
ratio is in 0.836. Further, the regression result show total equity ratio has negative
insignificant impact on ROA. The selected sample companies with more equity finance will
no imposes significant impact on ROA. It show support to Modigliani and Miller (1958)
irrelavent theory. In conclusion, debt to equity has negtaive significant impact on ROE, total
debt ratio has positive significant impact on ROE and total equity has indignificant impact on
ROE.
For the impact of capital structure on return on earning per share (EPS) which is
based on descriptive statistics, sample companies more trend to using equity finance, average
equity ratio is in 0.836. Further, the regression result show total equity ratio has positive
insignificant impact on EPS. The selected sample companies with more equity finance will
no impose significant impact on EPS. It show support to Modigliani and Miller (1958)
irrelavent theory. In conclusion, debt to equity has a negative significant impact on EPS,
total debt ratio has positive significant impact on EPS and total debt has insignificant impact
on EPS.
Recommendation
Based on the research result, total debt ratio has a positive significant on ROE and
EPS. Increasing debt finance is able to reduce agency problem and tax payment. Hence, firm
manager can raising their company debt level to taken the advantage of debt finance.
However, this research also found debt to equity has a negative impact on firm performance
which measure of ROA, ROE and EPS. It means debt increasing over optimum level will
raise cost of capital and bring negative impact on firm performance. Hence, firm manager
should cautious while using debt finance. Firm manager should consider the impact of debt
finance on firm performance before making capital structure decision. They are supported to
identify the optimum debt level and ensure that they are no use excessive amount of debt in
capital structure. In order to maximize firm performance and shareholder wealth, firm
manager must move their real capital structure to optimum capital structure level and
maintain it level as much as possible.
Limitation
This research is focus on the industrial product sector. Hence, the result cannot be
representative for the overall Malaysia situation. Secondly, this research only study the
overall debt effect only, the impact of long term debt and short term debt does not cover.
Long term debt and short term debt has different characteristic and so the impact on firm
performance also different. Lastly, this research only taken 50 company, the sample size is
quite less. It’s unable to represent all industrial product companies
ISSN: 2289-4519 Page 144
Further research
Firstly, future researcher is advised to identify the impact of capital structure on other
sector such as consumer, technology, financial institution. It’s because this research only
focus on industrial product sector, the result cannot represent overall industry in Malaysia.
Secondly, this research only using 50 company and 5 year data, future researcher are
recommend using long time series data and large sample size to obtain a more accurate result.
Thirdly, future researcher can do comparative research to compare the different between
Malaysia and Singapore capital structure trend and the impact of capital structure. Lastly,
future researcher can use other independent variable such as company market share, Tobin’s
Q, growth opportunity in their research paper. Furthermore, future researcher also can
included control variable such as size, sale growth, asset turnover rate into the research
framework.
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