Truong Hanh Duyen

7/24/2019 Truong Hanh Duyen

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UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

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TRUONG HANH DUYEN

DEBTS AND PROFITABILITY

AN EXAMINATION OF

MANUFACTURING FIRMS LISTED

ON VIETNAM STOCK EXCHANGE

MASTER OF BUSINESS (Honours)

SUPERVISOR: Dr. PHAM QUOC HUNG

Ho Chi Minh City Year 2012


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Debts & Profitability: An examination of manufacturing firms listed in Vietnam

By Truong Hanh Duyen Mbus 1 2 of 44

TABLE OF CONTENT

6TAcknowledgement6T ..................................................................................................................... 3

6TAbstract6T ...................................................................................................................................... 4

6TCHAPTER 1: INTRODUCTION6T............................................................................... 56T1.16T 6TVietnam Context:6T ............................................................................................................................ 56T1.26T 6TManufacturing firms in Vietnam:6T ................................................................................................. 66T1.36T 6TResearch Objective:6T ........................................................................................................................ 76T1.46T 6TResearch structure:6T ....................................................................................................................... 10

6TCHAPTER 2: LITERATURE REVIEW 6T................................................................. 116T2.1 The concept of debts: 6T ....................................................................................................................... 116T2.2 The concept of profitability:6T ............................................................................................................ 126T2.3 Relationship between debts and profitability:6T ............................................................................... 146T2.4 Theoretical Framework:6T .................................................................................................................. 176T2.5 Hypotheses Development:6T ................................................................................................................ 18

6TCHAPTER 3: RESEARCH METHODOLOGY6T..................................................... 206T3.1 Research Design: 6T .............................................................................................................................. 206T3.2 Variables Definition:6T ........................................................................................................................ 216T3.3. Samples Collection: 6T ......................................................................................................................... 226T3.4. Methods of Data Analysis: 6T .............................................................................................................. 24

6TCHAPTER 4: EMPIRICAL RESULTS & DISCUSSION 6T..................................... 26

6TCHAPTER 5: IMPLICATIONS & CONCLUSIONS6T............................................ 306T5.1. Implication:6T ...................................................................................................................................... 306T5.2. Limitation:6T ....................................................................................................................................... 316T5.3. Conclusion:6T ...................................................................................................................................... 32

6TReferences6T ................................................................................................................................ 33

6TAppendix 1: Outliners6T............................................................................................................. 36

6TAppendix 2: Normality and Heteroskedasticity6T................................................................... 37

6TAppendix 3: MLR between Net margin and independent variables6T.................................. 39

6TAppendix 4: MLR between ROE and independent variables6T............................................. 42


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Acknowledgement

I would like to gratefully acknowledge the enthusiastic supervision of Dr. Pham QuocHung during this work. I thank Prof. Nguyen Dinh Tho for the technical discussions on

the spectral response model, optical measurements and relevant discussions. Staff of

International School of Business (ISB) University of Economy Ho Chi Minh is thanked

for numerous supports. I am grateful to all my friends and classmates from Mbus 1 ISB

for sharing science materials and knowledge during the years I study there and for their

continued moral support there after. From the staff, Mr. Duong Minh Toan and Mr. Ho

Sze Ming are especially thanked for their care and attention. Finally, I am forever

indebted to my husband for his understanding, endless patience and encouragement when

it was most required.


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Abstract

The ability of companies in determining suitable financial policies to make investment

opportunities is one of the most principal factors for the companies growth and

progression. Adopting a debt policy or a capital structure is considered as a momentous

decision that influences the companies value. The determination of a companys capital

structure constitutes a difficult decision, one that involves several and antagonistic

factors, such as risk and profitability. That decision becomes even more difficult, in times

when the economic environment in which the company operates presents a high degree of

instability. Therefore, the choice among the ideal proportion of debt and other resourcescan affect the value of the company, as much as the return rates can. In this study, I tried

to examine the influence of debts from Vietnam manufacturing firms regarding the factor

profitability. The necessary data, which are used in this work are the 3 consecutive years

financial reports provided by the 200 respective firms. The Ordinary Least Squares

(OLS) method was employed in the estimation of a function relating the net margin and

return on the equity (ROE) with the indexes of long-term, short-term and total debts, and

also with the total of owners equity. The results indicate that short-term debt presents a

negative impact on net margin. The study recommends that managers should be careful

while using short term debts as a source of finance.


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CHAPTER 1: INTRODUCTION

This chapter includes three sections. The first section introduces Vietnam Context in

recent years, which is also the background of the research. The second is some briefs of

manufacturing firms in Vietnam and its vital role in the whole economy, thus the research

is to focus on this sector. The third section goes straightly to research objective as a

conclusion for two sections above and an opening for following chapters.

1.1Vietnam Context:

Vietnams transition, from a centrally planned economy to a market economy and from

an extremely poor country to a lower-middle-income country in less than 20 years, is

now a case study in many development textbooks. But Vietnams other transition, tobecoming an industrialized and modern economy by 2020, has barely begun. The latest

Socio-Economic Development Strategy (2011-2020) goes on to identify the countrys

key priorities to meet this ambitious target: stabilize the economy, build world-class

infrastructure, create a skilled labor force, and strengthen market-based institutions.

Meeting these aspirations will not be easy. The country has experienced bouts of

macroeconomic turbulence in recent years: double-digit inflation, depreciating currency,

capital flight, and loss of international reserves eroding investor confidence. Rapidgrowth has revealed new structural problems. The quality and sustainability of growth

remain a source of concern, given the resource-intensive pattern of growth, high levels of

environmental degradation, lack of diversification and value addition in exports, and the

declining contribution of productivity to growth. Vietnams competitiveness is under

threat because power generation has not kept pace with demand, logistical costs and real

estate prices have climbed, and skill shortages are becoming more widespread.

Until a few years ago, Vietnam was one of the world's hottest emerging markets. Now itfaces an urgent task: fix a beleaguered banking system or watch its economy continue to

slip behind faster-growing neighbors. Piles of bad loans following the financial crisis

have dragged down growth in Vietnam and left banks weakened and reluctant to lend,

lending interest rate sometimes climbed up to exceedingly 21% per annually in crisis

period. Economists warn that Vietnam has entered a dangerous cycle where banks,


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saddled with bad debts, are unwilling to lend, making it harder for businesses to invest.

That feeds into slower growth, which in turn makes it harder for companies to pay back

loans, again harming the banks. In a report of government in July 2012, from early 2012

Vietnam recorded about 30,000 of firms are in financials difficulties, temporarily

stopping business and declaring bankruptcy.

1.2Manufacturing firms in Vietnam:

Vietnams manufacturing sector grew at a compound annual growth rate (CAGR) of

9.3 percent from 2005 to 2010, and labor productivity in the sector increased at

3.1 percent a year. Because this sector accounts for around 30 percent of overall GDP,

this rapid growth made a substantial contribution to Vietnams expansion during this

period. Within manufacturing, some subsectors performed especially well. Motor vehicleproduction grew at an annual rate of 16 percent during these five years, ready-made

clothes by 12.9 percent, and electrical equipment by 12.0 percent.

The manufacturing industry plays a vital role in Vietnams economy by providing

employment opportunities and accelerating its growth. Simultaneously, liberalization,

removal of investment restrictions, and semi-privatization of the economy have greatly

boosted the country's industrial growth rate. The main manufacturing sectors in Vietnam

are textiles and garments, food and beverages and leather and wood. The Government hasimplemented various programs to transform Vietnams economic structure from

agriculture-driven to industry-driven and reduce its import dependency. The development

of export processing and industrial zones is just one of the initiatives that bolstered the

country's industrial growth. The Government has also offered incentives to investors in

social sectors such as health and education. However, since liberalization, the

Governments share in the overall industrial investment has been declining, thereby

enabling higher participation of private and foreign companies.

Financial and R&D (research and development) support, as well as the allotment of land

in industrial zones, are likely to encourage stakeholders in the manufacturing industry to

increase their investments. While sectors such as textiles, leather, food and beverages,

automobiles, chemicals and energy were resilient even during the economic downturn, a

booming food processing sector, an unsaturated pharmaceuticals market and a dynamic


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garments sector are expected to add value to the industrial production in Vietnam. The

Government has retained the majority of the stake in energy, finance, banking and

telecom and shielded the agriculture, food and automobiles sectors from international

competition. Higher private and foreign investment had enhanced the growth rate of

sectors such as transportation, real estate, communication and mining. However, the

country does not permit foreign investments in national defense, security, and health and

it places conditional restrictions on investments in telecommunications, postal network

and airports. The Vietnamese Governments initiatives and specific incentives for the

industrial sector are likely to increase exports and drive the economic growth.

Liberalization and the removal of various restrictions generating sector-specific

investment opportunities are expected to attract more private and foreign participants to

manufacturing industry.

Overall, with an aim to become industrialized country by 2020, Vietnams manufacturing

industry has been undergoing major changes as a result of government initiatives, WTO

commitments and industrial liberalization. Industrial development strategy for the period

2011-2020 to focus on the development of Textiles, Leather, Chemicals, Agro

processing, Electronics, Automotive, Information and Communications technologies are

expected benefit from the industrial development strategy. Due to improving business

climate, increased trade and investment cooperation, low labor cost and Vietnam is

expected to emerge as a major manufacturing hub in the ASEAN region. Hence, the

vitalization of firms in this industry is very important for the growth of country. During

crisis period, many firms in sector have been badly affected resulted from high leverage

in capital structure. The companies, well overcome such bad cycle of economy, generally

do not only well prepare for business operation to maintain profitability, but also less

involve in debts by optimal capital structure.

1.3

Research Objective:

Which the relationship between debts and profitability? Does the fiscal benefit makes

debt more attractive than other funding resource? Does the risk associated to the increase

of the debt can, or should, be taken by the firm? Should the financing decisions of the

firms follow a single pattern, irrespective of the country where it operates? Those are


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frequently asked questions that are significantly present in the processes related to

decision of capital structure of any firms.

Decisions of that type tend to become even more difficult when the economic conditions

of the country where the firm operates already are typically more uncertain. In theVietnamese case, specifically, the presence of two aggravating factors is observed: first is

the high interest rates practiced in the financial market, and second is the instability of the

economy before the international conjuncture. Those two factors play distinct roles;

however, they produce similar effects under the scope of uncertainty.

Any firm finances its operation and investment by either debt or equity and mostly both.

The firms might like to raise finance from their internal resources, instead of the bank

loans and debt issues. Thus the external equity financing is their last option. Conversely,many organizations use debt financing to reduce their cost of capital so that they can

lower the Weighted Average Cost of Capital (WACC)P0F1

P as it will allow the firms to

have wider extent of acceptance for capital budgeting options.

Theres many argument on the relationship of leverage (ratios of debts in asset structure)

and business performance before. As a point of departure, the Modigliani and Miller

(M&M) (1958) stated: With perfect capital markets and no taxes or information

asymmetry, debt financing has no effect on value. However, in a subsequent paper,M&M (1963) eased the conditions and showed that under capital market imperfection

where interest expenses are tax deductible, firm value will increase with higher financial

leverage. Later, Miller (1977), elaborated a new revision, analyzing the subject of the

taxes paid by the investors, concluding that the corporate tax benefits of debt are reduced

by the tax penalty due to personal taxation. Models based on impact of tax, suggest that

profitable companies should have more debts. However, increasing debt results in an

increased probability of bankruptcy. Hence, the optimal capital structure represents a

level of leverage that balances bankruptcy costs and benefits of debt finance.

1A calculation of a firm's cost of capital in which each category of capital is proportionately weighted. All capital sources - common stock, preferred stock,bonds and any other long-term debt - are included in a WACC calculation. All else equal, the WACC of a firm increases as the beta and rate of return onequity increases, as an increase in WACC notes a decrease in valuation and a higher risk.


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Since all firms managers try to get the optimal capital structure with least possible cost,

this led in 1984 for the pecking order theory to emerge. The theory began from Myers

(1984) states that there is no optimal capital structure for a firm, according to this theory,

since there is asymmetric information between managers and shareholders. Therefore to

minimize this asymmetric information, firms prioritize their sources of finance (from

internal financing to equity) according to the principle of least effort or of least

resistance, retained earnings are better than debt and debt is better than equity. But there

is another suggestion for case of asymmetric information; managers, directly involve in

daily operations of business, thus could master detailed positions of businesses and what

are actually being happened in the firms; whilst shareholders mainly rely on the reports

from managers, and could be disguised by the beautiful and vivid wordings of those

reports. Hence, to make manager be more responsible for their jobs, the firm owners

prefer to get more debts rather than equity; repayment obligation of debts and interest

occurred push managers work harder to get more profitability in the bottom line of

income reports.

Due to the importance of the issue and the impact of the financial structure or choice of

funding sources on the performance of companies, there are many previous studies and

various researches lead us to verify the relationship between capital structures or debts

and the performance of companies in different markets generally, but not many for

emerging markets and particularly for Vietnam financial market which is characterized as

small and unstable. Furthermore, management of capital structures in Vietnam is

typically different from others due to components such as high cost of debt, unstable

policy and political issues of a social republic country.

Unlike previous studies, this paper focuses deeply in the relationship between debts and

profitability of listed manufacturing firms on Vietnam Stock Exchange. Specifically, it is

aimed at: examining the relationship between Short-term debt, Long-term debt, Total

debts, and Net Profit Margin (NM) and Return on Equity (ROE). This study will be

significant to managers and shareholders in deciding proportion of debts and each debt

types to finance their operations and to maximize firm value which then contributes to the

economic development of Vietnam.


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1.4Research structure:

This thesis comprises five chapters.

Chapter 1: Introduction generally introduces the subject area interest with defined

problems, research questions, research objectives, and sources of information to be

collected for the research.

Chapter 2: Literature Review summarizes concepts and theories relating to debts,

profitability and the relationship between them. From such reviews, basic theories for

studying will be synthesized to develop an initial research model and hypotheses used for

the research.

Chapter 3: Research Methodology introduces the approach method of this research

through four sub-sessions including research design, variables definition, samples

collection and method of data analysis.

Chapter 4: Empirical Results & Discussion reports the analysis results and meaningful

figures.

Chapter 5: Implications & Conclusions discusses the implications of the results and

findings in session four, limitations are also drawn; based on which conclusions and

recommendations are provided.

Some appendix for detailed outputs from SPSS will be put at last papers for references.


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CHAPTER 2: LITERATURE REVIEW

In this chapter, theoretical background and review on previous studies are presented,

including 5 sections. The first and second section is some popular definitions of debts and

profitability. The third presents the relationship of debts and profitability. The forth istheoretical framework, whilst the last describes the hypotheses development for this

research.

2.1 The concept of debts:

There are various measures of debts, which can be classified as accounting based

measures, market-value measures and quasi-market value measures. Since market values

of leverage may be difficult to obtain, accounting based measures are often applied as

proxies. The use of debt, or a loan, in business operation is to increase sales and profit.

Companies have to be careful with their use of financial leverage as too much can lead to

serious financial problems and even bankruptcy.

Debt includes the firm's current liabilities which are the obligations the firm intends to

pay off in one year or less, generally seen as current liabilities in balance sheet like short

term bank loan, accounts payables and accruals. Debt also includes long-term debt which

has a maturity of more than one year such as mortgages, long-term loans for other

purposes or even long-term prepaid amounts etc, and recorded in non-current liabilities of

balance sheet.

Thedebt ratio compares a company's totaldebt to its totalassets,which is used to gain a

general idea as to the amount of leverage being used by a company. Total debts might be

replaced by short term or long term debts in the ratio or total assets might be replaced by

current or non current assets to get different views of how debts fund the firms assets,

the portion of debts in constitution of assets. The lower the percentage, the less leverage a

company is using and the stronger its equity position. In general, the higher the ratio, the

more risk that company is considered to have taken on, but could be compensated by

higher return.

Another measure of a company's financial leverage is calculated by dividing its total

liabilities by stockholders' equity indicates what proportion of equity and debt the
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company is using to finance its assets, called debt to equity ratio. Sometimes

only interest-bearing, short-term or long-term debt is used instead of total liabilities in the

calculation.

Rajan & Zingales (1995) suggest that the choice of measure should be based on theobjective of the analysis. In their view, the ratio of total debt to capital, where capital is

defined as total debt plus equity i.e. ratio of total debts to total assets can be seen as the

best accounting based proxy for leverage.

2.2 The concept of profitability:

Profitability ratios are a class of financial metrics that are used to assess a business's

ability to generate earnings as compared to its expenses and other relevant costs incurred

during a specific period of time. For most of these ratios, having a higher value relative to

a competitor's ratio e.g. comparison between company A and company B or the same

ratio from a previous period or comparison profit of year 2010 with year 2011 is

indicative that the company is doing well.

Every firm is most concerned with its profitability. One of the most frequently used tools

of financial ratio analysis is profitability ratios which are used to determine the

company's bottom line and return to its investors. Profitability measures are important to

company managers and owners alike. Any business has outside investors who have put

their own money into the company; the primary owner certainly has to show profitability

to those equity investors. Popularly, listed firms have to publicly announce the business

performance periodically.

Profitability ratios show a company's overall efficiency and performance. We can divide

profitability ratios into two types: margin ratios and return ratios. Ratios that show

margins represent the firm's ability to translate sales dollars into profits at various stages

of measurement. Ratios that show returns represent the firm's ability to measure the

overall efficiency of the firm in generating returns for its shareholders.


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Margin Ratios:

Gross Profit Margin looks at how well a company controls the cost of

itsinventory and the manufacturing of its products and subsequently passes on the

costs to its customers.

Operating Profit Margin is a measure of overall operating efficiency, incorporating all

of the expenses of ordinary, daily business activity.

Net Profit Margin shows how much of each sales dollar shows up as net income after

all expenses are paid. For shareholders and investors, this ratio might be the most

important, as it give them a tough view of how well their businesses are at the last.

Cash Flow Margin is an important ratio as it expresses the relationship between cashgenerated from operations and sales; measures the ability of a firm to translate sales

into cash.

Returns Ratios:

Return on Assets (also called Return on Investment) measures the efficiency with

which the company is managing its investment in assets and using them to generate

profit.

Return on Equity is perhaps the most important of all the financial ratios to investors

in the company. It measures the return on the money the investors have put into the

company.

Cash Return on Assets ratio is generally used only in more advanced profitability

ratio analysis. It is used as a comparison to return on assets since it is a cash

comparison to this ratio as return on assets is stated on an accrual basis.

Grout and Zalewska (2006) indicated some other measures of profitability including NPV

(net present value), IRR (internal rate of return), ARR (accounting rate of return), ROS

(return on sales), and concluded that IRR and ARR can be used to identify whether a

company is earning an excess return. Although in the context of the ARR the necessary

adjustments to asset values are not usually made, at least in principle, the ARR is able to
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identify excess returns and will be exactly equal to the IRR in some cases. However these

measures are more suitable to measure returns of project rather than normal business

operations, thus they will not be focused in this study.

2.3 Relationship between debts and profitability:

Studies showed contradictory results about the relationship between debts in capital

structure and firms performance (profitability).

In a study of listed firms in Ghana Stock Exchange (GSE) during a five-year period, Abor

(2005) examined the relationship between capital structure and profitability, and found

that Short-term and Total Debt are positively related with firm's ROE, whereas Long-

term Debt is negatively related with firm's ROE. Then in 2007, Abors research on small

and medium-sized enterprises in Ghana and South Africa again indicated that long-term

and total debt level is negatively related with performance.

Similarly, Arbabiyan and Safari (2009) investigated the effects of capital structure on

profitability by using 100 Iranian listed firms from 2001 to 2007 and found that Short

term debts and Total debts are positively related to profitability proxy by ROE which

indicate a negative relation between Long term debts and ROE.

While examining the relationship between capital structure and performance of 167

Jordan firms during 1989 - 2003, Zeitun and Tian (2007) found that capital structure have

a significant and negative impact on the firms performance measures in both the

accounting and market measures, debt level is negatively related with performance. It

means higher debts causes lower profits.

In a similar study on microfinance institutions in sub-Saharan Africa, Coleman (2007)

found that high leverage is positively related with performance proxy by ROA and ROE.

Husnan (2001) described that the use of debt statistically significant to the change in the

value of non-multinational companies ROE, while it is not significant to the

multinational companies.

However, the research made by Harjanti and Tandelilin (2007) to all manufacturing

companies listed in Jakarta Stock Exchange from 2000 to 2004 indicated that profitability


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which was proxy by ROE, basic earning power (BEP), and gross profit ratio had negative

significance to leverage.

Based on Ebaid (2009) research, capital structure choice decision, in general terms, has

weak-to-no influence on the financial performance of listed firms from 1997 to 2005 inEgypt as one of emerging or transition economies. By using three accounting-based

measurements of financial performance which are return on assets (ROA), return on

equity (ROE), and Gross Margin, the empirical tests come with the result that capital

structure (particularly Short term debts and Total debts) have a negative impact on an

organizations performance which is measured by ROA. Apart from that, capital structure

(including short-term debt, long-term debt and total debt) have no significant impact on

an organizations performance which is measured by ROE and Gross margin.

Jensen and Meckling (1976) argued that the conflict between shareholders and lenders

has the effect of shifting risk from shareholders to lenders and of appropriating wealth in

their favor as they take on risky investment projects (asset substitution). Hence,

shareholders, and managers as their agents, are prompted to take on more borrowing to

finance risky projects. Lenders receive interest and principal if projects succeed, and

shareholders appropriate the residual income; however, it is the lender who incurs the

loss if the project fails. Shareholders, though, while enjoying increased wealth in good

periods, tend to ignore a decline in profitability in bad times. This is due to the fact that

unfavorable consequences are passed onto lenders because of shareholders' limited

liability status. Therefore, the oligopolistic firms, in contrast to firms in competitive

markets, would employ higher levels of debt to produce more when opportunities to earn

higher profits arise. In corporate finance, the agency costs theory supports the use of high

debts, and it is consistent with the prediction of the output maximization hypothesis.

Valeriu and Nimalathasan (2010) pointed out capital structure and its impact on

profitability: a study of listed manufacturing companies in Sri Lanka. The result shows

that debt to equity ratio is positively and strongly associated to all profitability ratios

(gross profit ratio; operating profit ratio; and net profit ratio) except return on capital

employed and return on investment (ROI).


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Pratheepkanth (2011) tested the relationship of capital structure (ratios of debt and equity

over fund) with financial performance of firms listed on Sri Lanka Stock Exchange from

2005 2009, indicated that there is a weak positive relationship between gross profit and

capital structure and at the same time, there is a negative relationship between net profit

and capital structure.

Luper and Isaac (2012) examined the impact of capital structure on the performance of

manufacturing companies in Nigeria. The annual financial statements of 15

manufacturing companies listed on the Nigerian Stock Exchange were used for this study

which covers a period of five years from 2005-2009. Multiple regression analysis was

applied on performance indicators such as Return on Asset (ROA) and Profit Margin

(PM) as well as Short-term debt to Total assets (STDTA), Long term debt to Total assets

(LTDTA) and Total debt to Equity (TDE) as capital structure variables. The results show

that there is a negative and insignificant relationship between STDTA and LTDTA, and

ROA and PM; while TDE is positively related with ROA and negatively related with PM.

STDTA is significant using ROA while LTDTA is significant using PM. The work

concludes that statistically, capital structure is not a major determinant of firm

performance.

Nour (2012) investigated the impact of capital structure on firm performance. The study

used fifth performance measures (including return on equity ROE, return on assets -

ROA, earning per share - EPS, market value of equity to the book value of equity -

MBVR and Tobins Q) as dependent variables and four capital structure measures

(including short term debt to total assets - SDTA, long term debt to total assets LDTA

and total debt to total assets - TDTA, and total debt to total equity - TDTE) as

independent variable. The investigation is performed using panel data procedure for a

sample of 28 listed companies the Palestinian Stock Exchange (PSE) over the period of

2006 - 2010. The results showed that firms capital structure had a positive impact on the

firms performance measures, in both the accounting and markets measures, and

statistically significant with TDTA except MBVR was significant with TDTA and with

SDTA. Finally, the study findings suggest equations to determine the impact of the

various debts on the firm performance.


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A study of Nima, Mohammad, Saeed, & Zeinab (2012) examined the relationship

between capital structure and firm performance of Tehran Stock Exchange Companies is

investigated between the years 2006 to 2011. The study uses three performance measures

(including Gross Profit Margin, Return on Assets and Tobins Q) as dependent variable

and three capital structures (including long term debt short term debt and total debt ratios)

as independent variable. The study reported a significant relationship between dependent

and independent variable, except long term debts with gross profit margin.

2.4 Theoretical Framework:

The theoretical framework is constructed subsequent to the literature review. Derived

from the literature surveyed, the following theoretical framework is designed to facilitate

the research. It depicts the relationship between profitability and its explanatoryvariables.

Variables used for the analysis include profitability and leverage ratios. Dependent

variable in this study is profitability, which is measured by profit ratios including return

on equity (ROE) and net margin ratio (NM). The independent variables, which are the

explanatory variables, are measured by ratios of short-term debt to total assets (SDTA),

long-term debt to total assets (LDTA), total debts to total assets (TDTA) and total debts

to total equity (TDSE).

Short-term debts

(Current liabilities)

Long-term debts(Non-current liabilities)

Total debts

(Total liabilities)

Profitability


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2.5 Hypotheses Development:

From literature review above, we see there are many different arguments on relationship

between debts and profitability, or different debt types cause different relationship. The

object of this study is to indentify the impact of respective debt types to the profitabilityof manufacturing firms listed on Vietnam Stock Exchange. If the debts influence the

firm's profitability, the correlation between debt and firm's profitability can be expected.

Hypotheses for this study are developed based on the literature review and the actual

concepts in Vietnam financial market.

As a result of a rapid growth but bad control in the past, Vietnam faced the crisis with

high inflation (double digits) and weakened banking system. The increase in key interest

rates resulted in a sharp decrease in money market and credit growth; high cost of capitalalso slowed down both domestic production and consumption. In the market, race in

mobilization and breaking cap interest rates happened popularly and frequently. Though

the state bank require commercial banks to comply with the cap rates, but exceeding cap

interest rates still exist. Liquidity troubles in banking system also affected lending

capacity of banks; its really difficult and costly for firms to source funds for business

operation. Consequently, lending rate sometime climbed up to 25% per annual, an

unimaginable rate in any other markets.

Compared to ideal return on investment/ equity ranging from 10% - 20% or net profit

margin of around 5%, sourcing fund from external is the last options of business owners/

managements. Bearing such high interest rate absolutely deteriorates profitability. So, we

argue that debts influences profitability negatively. Thus, the hypotheses are:

HR1R: Theres negative relationship between Short-term Debt and Net Margin

HR2R: Theres negative relationship between Long-term Debt and Net Margin

HR3R: Theres negative relationship between Total Debt and Net Margin

HR4R: Theres negative relationship between Short-term Debt and ROE

HR5R: Theres negative relationship between Long-term Debt and ROE


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HR6R: Theres negative relationship between Total Debt and ROE

From the hypothesis recruited, 2 models for dependent variables to be described as

NM = R0 RRR R1RSDTARRRR R2RLDTAR R R3RTDTA R4RTDSERR+RRRi

ROE = R0 RRRR1RSDTARRRRR2RLDTAR R R3RTDTA R4RTDSERR+RRRj


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CHAPTER 3: RESEARCH METHODOLOGY

Chapter 2 reviewed literature and proposes hypotheses and research model. Chapter 3

will present how the research was implemented. It discusses the methodology used to

identify the impact of debts and profitability of listed manufacturing firms in Vietnam. Itoutlines the research design adopted, identification of variables, sampling method and

procedure of data analysis.

3.1 Research Design:

This research work adopted an ex-post facto design (also called Causal Comparative

Research) and used data from financial statements of manufacturing companies listed on

the Vietnam Stock Exchange from 2009 - 2011. This type of design was used because of

the availability of audited financial statements of the sampled companies. Audited

financial statements are reliable as auditors certify them.

In this experimental research, the impact of debts on profitability was tested through

regression model.


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Figure 3.1: Research Process Inflow Chart

3.2 Variables Definition:

The idea of writing this research was to know the impact of the use of debt to companies

profitability. However, if the data collected from audited reports of different firms with

different size, debt and profit of these firms can not be compared directly. To make data

in every sample corresponding to each other, the ratios of debts and profitability was used

instead of raw figures of debts and return amount.

(1)Ratio of Short Term Debts to Total Assets (SDTA)

(2)Ratio of Long Term Debts to Total Assets (LDTA)

(3)Ratio of Total Debts to Total Assets (TDTA)

(4)Ratio of Total Debts to Shareholders equity (TDSE)

(5)Ratio of Return to Shareholders equity (ROE)

(6)Net Profit Margin (NM/ Net Margin)

Define research problem

Review concepts and theories

Review previous research findings

Formulate hypotheses

Analyze data

Literature Review

Design research

Collect data

Interpret and report


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Dependent variables:

Return on equity (ROE) measures the rate of return on the ownership interest

(shareholders' equity) of the common stock owners. It measures a firm's efficiency at

generating profits from every unit of shareholders' equity (also known as net assets orassets minus liabilities). ROE shows how well a company uses investment funds to

generate earnings growth.

ROE = Net income/ Shareholders Equity

Net margin (NM), the ratio of net profits to revenues for a company or business segment,

typically shows how much of each dollar earned by the company is translated into profits.

NM = Net income/ Revenue

Both ROE and NM have numerator is net income. Net income stands in the bottom line

of income statement, is the profit after being deducted by all costs and popularly denoted

as net profit after tax (NPAT).

Independent variables:

SDTA = short - term debt (current liabilities) to total assets. The portion of debt

that is payable within one year. This data falls under current liabilities on

the company balance sheet;

LDTA = long - term debt (fixed/ non - current liabilities) to total assets: Liabilities

those are due to be repaid after more than one year. This is inclusive of

bonds and long-term loans;

TDTA = total debt (total liabilities) to total assets: It is the combined amount of

current liabilities and long-term liabilities. It can be found on the balance

sheet as "Total Liabilities; and

TDSE = total debt (total liabilities) to total equity.

3.3. Samples Collection:

This research paper investigates the relationship between debts in various types including

short term debts, long term debts and total debts and the firms profitability including
http://en.wikipedia.org/wiki/Shareholders%27_equityhttp://en.wikipedia.org/wiki/Shareholders%27_equity


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return on equity and net margin of manufacturing firms listed on Vietnam Stock

Exchange. This research was limited to the analysis to manufacturing companies given

the important role of this sector in the economy. In addition, firm in same sector have

homogeneity in terms of financial structure.

In this aim, the population of the study was made up of the 223 manufacturing companies

with industry code between 10 and 31 listed on Vietnam Stock Exchange as below table.

Industry (manufacturing sector) Code Number of firms

Food 10 45

Beverage 11 7

Tobacco 12 3

Textiles 13 3

Costumes 14 6

Wood 16 1

Paper & paper products 17 14

Coke & refined petroleum 19 1

Chemical 20 9

Drugs, chemical & medicinal products 21 15

Rubber & plastic products 22 18Mineral & non metal products 23 47

Metal 24 14

Casted metal products 25 7

Computer & electronic product 26 4

Electrical equipments 27 17

Other machineries & equipments 28 3

Motor vehicles & trailer 29 3

Furniture 31 6

Total 20 223


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In this study, audited financials in last 3 consecutive years (2009, 2010 and 2011) from

223 firms classified in manufacturing sector of economy was collected. The necessary

data, which are used in this work, are the financial figures including current liabilities,

non-current liabilities, total liabilities, total assets, total equity and net profit provided by

the respective firms, and availably updated on almost stock trading websites. These

figures are trusted to be audited by recognized audit firms, and to make sure they were

correctly input on websites, random checks against firms audited reports were

performed.

3.4. Methods of Data Analysis:

There are three types of data available for an empirical analysis: time series data, cross-

sectional data, and pooled data (i.e., combination of time series and cross-sectional).Since the variables are selected from various companies between 2009 and 2011, the type

of data for this study can be considered as pooled. There are two approaches to analyze

pooled data which include classical linear regression model and panel data regression

model. In order to use the classical linear regression model, all firms data should be

considered as homogeneous; otherwise the panel data should be applied. Thanks to

homogeneity of the data in this research, the average of 3 years date was taken to put in

classical linear regression model.

This study uses descriptive statistics, correlation matrix, and multiple linear regressions

to test the average of debts and profits, how the debts correlated to profits and each other,

and the influences of debts on the companies profitability. Method of Ordinary Least

Square (OLS) is used to estimate the regression line. OLS is used because it minimizes

the error between the estimated points on the line and the actual observed points of the

estimated regression line by giving the best fit. All the dependent and independent

variables are pooled into cross-section data.

The process of data analysis could be described as below:

- Detecting outliers: all outliers suggested by SPSS were re-checked manually to retain

samples with insignificant difference. After detecting 23 outliners, there are 200 rows

got from average of 3 years figures (see Appendix 1).


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- Checking normality and heteroskedasticity: results showed that dependent variables

(ROE and Net margin ratio) are not perfectly normal distributions, but still acceptable

(see Appendix 1).

-

Descriptive statistic for all variables

- Correlation matrix among variables

- Multi linear regression between Net margin and independent variables

- Multi linear regression between ROE and independent variables

The results of these processes were detailed in the next chapter.


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CHAPTER 4: EMPIRICAL RESULTS & DISCUSSION

This chapter presents the results of data analysis and the discussion on these results.

There are 4 main tables presenting descriptive statistic, correlation matrix between

variables, and multiple linear regressions between 2 dependent variables and independent

variables.

Table 4.1: Variable descriptions

Category Symbol Description Hypothesis

Debts

SDTA Short-term debt to total assets

Independent variablesLDTA Long-term debt to total assets

TDTA Total debts to total assets

TDSE Total debts to shareholders equity

ProfitabilityNM Net margin ratio

Dependent variablesROE Return on equity ratio

Table 4.2: Descriptive Statistics

N Range Minimum Maximum Mean Std. Deviation Variance

SDTA 200 68.45% 8.44% 76.89% 42.24% 16.26345% 264.500LDTA 200 41.43% .00% 41.43% 6.94% 8.32683% 69.336

TDTA 200 78.53% 8.66% 87.19% 49.18% 18.18884% 330.834

TDSE 200 722.57% 9.56% 732.13% 134.99% 104.54326% 10929.293

Net Margin 200 27.71% -3.46% 24.25% 7.20% 5.12322% 26.247

ROE 200 60.56% -17.53% 43.03% 17.57% 9.66926% 93.495

Table 2 reported summary statistics for 200 variables used in the study. The table showed

that all of the variables had a positive mean. Moreover, mean statistics provided some

interesting evidence.

First, the mean structures proxies (SDTA Short term debt to total assets, LDTA Long

term debt to total assets, and TDTE - Total debts to total assets) were about 42%, 6.9%,

and 49% respectively, which indicated Vietnamese manufacturing companies in general,


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financed their assets by debts, especially by short-term debts. This means they operated

in a risky manner.

Second, the mean of return to equity (ROE) for a sample as a whole was 17.57% which

was acceptable for business purpose as whole but still lower than popular lending rate inVietnam in period of 2009-2011 which was fluctuated around 20% per annual. However,

the average net margin of 7.2% could be considered as an ideal figure for any bottom line

of income statement.

Noticeably, mean of TDSE (Total debts to shareholders equity) was 135%, whilst mean

of TDTA (Total debts to total assets) was 49% only which implicated assets in balance

sheets of these firms in general were financed by not only by debts and equity but other

resources such as contribution of minority interest.

The range and Standard deviation of all variables were quite high which indicated the

data was spread out over a large range of values; it means though samples collected in

same industry (manufacturing), the homogeneity of capital structure and performance

was still low.

Table 4.3: Correlation Matrix

SDTA LDTA TDTA TDSE Net Margin ROE

SDTA 1

LDTA -.011 1

TDTA .889P** .448P** 1

TDSE .752P** .450P** .879P** 1

Net Margin -.528P**

.028 -.459P**

-.376P**

1

ROE -.041 .045 -.016 .018 .545P** 1

**. Correlation is significant at the 0.01 level (2-tailed).

Table 3 established according to Pearson Matrix; it showed the correlation between the

explanatory variables. With significant level of 0.01 (2 tailed), there was medium

negative correlation between 3 independent variables (SDTA, TDTA, TDSE) with net

margin, but LDTA almost had no correlation with dependent variable (NM); whilst all

explanatory variables had no correlation with return on equity (ROE). Among correlation


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matrix, SDTA showed a slight high negative correlation with net margin (-0.528),

subsequently followed by TDTA (-0.459) and TDSE (-0.376).

As shown in table above, there was strong positive relationship among independent

variables which may lead to multicollinearity problem which will affect the model powerand its ability in explaining the results. Variance Inflation Factor (VIF) was used which

refers to actual disparity percentage to total disparity, and this will be shown in Table 4

below.

Table 4.4: MLR between Net Margin and independent variables

Variable Coefficient T-stat VIF Adjusted R-square Sig.

Constant 14.384 12.608 - .268 .000Pa

SDTA -.178 -4.932 3.564

LDTA .000 -.002 1.941

TDSE .002 .382 4.470

Table 4 represented the result of multi linear regression used to verify the relationship

between SDTA, LDTA, TDSE and Net margin (TDTA was excluded in this model due to

multicollinearity). The results could be interpreted into main points as below:

The result indicated a negative relationship between SDTA and Net Margin as an

increase in SDTA by one will reduce Net Margin by 17.8%, whilst a unit change in

TDSE will increase Net Margin by 0.2 %; and LDTA have no impact on Net Margin

(coefficient of LDTA was .000).

The theoretical model here is:

Net Margin = R0 RRR R1RSDTARRRR R2RLDTAR R R3RTDTA R4RTDSERR+RRRi

The estimated model here is:

Net Margin = 14.384 - 0.178 SDTA + 0.002 TDSE

The independent variables were barely related with Net margin ration based on

Adjusted R square of model (0.268) which means approximately 26.8 % of variation

in net margin could be explained by independent variables.


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Sig. < 0.05 indicated that the model, as a whole, was significantly fit to the data.

VIF was less than 5 and this means the independent variables including SDTA,

TDTA and TDSE were not too inter-correlated. Fox (1991) proved that VIF factor is

less than five (5) this means that there is no multicollinearity problem.

Please see appendix 3 for more details.

Table 4.5: MLR between ROE and independent variables

Variable Coefficient T-stat VIF Adjusted R-square Sig.

Constant 19.499 7.715 - -.008 .702Pa

SDTA -.080 -1.004 3.564

LDTA -.015 -.126 1.941

TDSE .012 .832 4.470

Table 5 represented the result of multi linear regression used to verify the relationship

between SDTA, LDTA, TDSE and ROE. Given Sig. = 0.702 > 0.05 (significant level)

indicated that the model, as a whole, did not fit to the data. The independent variables

were almost non-related with ROE based on the Adjusted R-square value (-0.8% only).

Consequently, the null hypothesis was accepted that debts did not significantly affect

ROE.

ROE though is also indicator of profitability, but mostly not affected by debts; could be

subjectively explained that interest occurred by debts lower profit at the bottom line of

income statement which is a directly lower net margin, whilst ROE is resulted by both

profit and equity amount i.e. increase of debts may lower profit but increase of debts

means less use of equity, thus ROE is almost not changed since both numerator and

denominator change in same direction.

Please see appendix 4 for more details.


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CHAPTER 5: IMPLICATIONS & CONCLUSIONS

This research assesses the impact of debts on profitability of manufacturing firms in

Vietnamese through financials from 200 selected firms listed on Vietnam Stock

Exchange. Methods of data collection, data analysis and results have been elaborated inChapter 3 and 4.

This chapter is to drawn important implication and conclusion about the research.

Managerial implications will be discussed first, then will be followed by limitations, and

will be finished by conclusions which also include recommendations for further research.

5.1. Implication:

The finance decision of the company is characterized as being of extreme difficult,

involving the analysis of many other factors. In the specific case of the Vietnamese

economy, the difficulties are enlarged due to the instability, a common feature of an

economy that recently went through a process of monetary adjustment and that still very

dependent on instruments of monetary politics, especially interest rate, and external

relations.

The present work just tried to examines the impact of debts on profitability of

manufacturing firms in Vietnam. Based on the selected sample size and using debts

indicators like Short-term Debt to Total assets (SDTA), Long-term Debt to Total assets

(LDTA), Total Debts to Total assets (TDTA) and Total debts to Total shareholders

equity (TDSE) as well as Return on equity (ROE) and Net margin ratio as profitability

indicators, the study concludes that statistically debts represented by short-term debt to

total assets (SDTA) have a negative significant impact on net margin, whilst long-term

debts to total assets (LDTA), total debts to total assets (TDTA) and total debt to equity

(TDSE) are not major determinants of firms profitability. These findings imply that an

increase in short-term debt position is associated with a decrease in profitability;

thus, the higher the short-term debt, the lower the profitability of the firm.

The results from this research were not totally matched any previous studies, but

somehow partially matched with the works of Zeitun and Tian (2007) that debt level is

negatively related with performance; Pratheepkanth (2011) that there is a negative


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relationship between net profit and capital structure (ratios of debt and equity over fund);

Husnan (2001) that the use of debt is not significant to the multinational companies

ROE; Ebaid (2009) that capital structure (including short-term debt, long-term debt and

total debt) have no significant impact on an organizations performance which is

measured by ROE.

On the contrary, prior empirical studies showed different results compared to my research

are Abor (2005), Arbabiyan and Safari (2009), Harjanti and Tandelilin (2007), Valeriu

and Nimalathasan (2010), Luper and Isaac (2012).

5.2. Limitation:

Although this research was carefully prepared, I am still aware of its limitations and

shortcomings.

The research was conducted in a limited population of 200 manufacturing firms listed on

Vietnam Stock Exchange. It would be better if it was done in a larger sample including

not only listed but also non-listed companies. Furthermore, though manufacturing firms

is one of countrys main industry sectors, but not represent the majority of firms in

Vietnam. In fact there are many other sectors. Therefore, the result may not represent the

result on other sectors in Vietnam; and implication from this result can not be applied to

the whole.

Apart from that, there is problem with the firms in the sample set which adopt different

accounting policies. In addition, the period for annual closing account is different among

the companies. Different accounting policies and period for annual closing account for

comparison will influence the accuracy of the result.

In order to get the more convince and precise result, the time-series data collected should

covered longer period.

In addition, more and new variables of debts and profitability should be captured in the

model in order to obtain more comprehensive results. In addition, it is important to

conduct the study for the period within consistent economic predicament by specify the

accurate time period before and during the crisis in order to avoid biases in the analysis.


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5.3. Conclusion:

Corporations need capital in order to improve and grow. A part of the capital can be

provided from internal resources of a corporation such as retained earnings which is

obtained from corporations profit and is not divided among shareholders. The rest of thecapital can be borrowed or be provided from capital markets. Managers have to develop

efficient debt policies in order to suitably face financial issues. Debt policies are related

to the corporations value and a change in financial leverage will lead to a change in total

cost of a capital and the corporations total value. In brief, short-term loans have

negative relationships with firms profitability.The study recommends that managers

should be careful while using short term debts as a source of finance since a negative

relationship exists between debts and profitability variables used in this work. They

should try to finance their activities with retained earnings and use debt as a last option as

supported by the pecking order theory.

Based on the result mentioned above, the following recommendations are suggested:

1. The optimal capital structure for manufacturing firms in Vietnam should be

constituted of less short-term debts (current liabilities) than other resources. In other

words, its better to maintain portion of current liabilities to total assets is less than

portions of non-current liabilities and equity.

2. This study is limited to the sample of 200 manufacturing firms listed on Vietnam

Stock Exchange. Future research should investigate generalizations of the findings

beyond the manufacturing sectors.

3. There are some other ways in which this study could be further extended. First,

employing other performance measures may provide supplementary results. Second,

in this study we use Short-term debt, Long-term debt and Total debts to measure of

debts, but its better to detail into short-term bank loan, Long-term bank loan and

Total bank loan.

4. The banks/ lenders/ creditors are recommended to more cautiously examine the ratio

of short-term debt to total assets from borrowers/ debtors before any financing

decisions to control and reduce bankruptcy costs.


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Appendix 1: Outliners

Case Processing

Summary Valid Missing Total

SDTA 223 100.0% 0 .0% 223 100.0%

LDTA 223 100.0% 0 .0% 223 100.0%

TDTA 223 100.0% 0 .0% 223 100.0%

TDSE 223 100.0% 0 .0% 223 100.0%

Net Margin 223 100.0% 0 .0% 223 100.0%

ROE 223 100.0% 0 .0% 223 100.0%


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Appendix 2: Normality and Heteroskedasticity


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Appendix 3: MLR between Net margin and independent variables

Variables Entered/RemovedPb

Model Variables Entered Variables Removed Method

1 TDSE, LDTA,

SDTAPa

. Enter

a. Tolerance = .000 limits reached.

b. Dependent Variable: Net Margin

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .529Pa .279 .268 4.38190%

a. Predictors: (Constant), TDSE, LDTA, SDTA

ANOVAP

Model Sum of Squares df Mean Square F Sig.

1 Regression 1459.819 3 486.606 25.343 .000Pa

Residual 3763.409 196 19.201

Total 5223.227 199



CoefficientsPa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant

)

14.38

4

1.141 12.60

8

.000

SDTA -.178 .036 -.565 -4.932 .000 .281 3.564

LDTA .000 .052 .000 -.002 .998 .515 1.941

TDSE .002 .006 .049 .382 .703 .224 4.470

a. Dependent Variable: Net Margin


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Excluded VariablesP

Model Beta In t Sig. Partial Correlation


Tolerance VIFMinimumTolerance

1 TDTA

.P

a

. . . .000 . .000

a. Predictors in the Model: (Constant), TDSE, LDTA, SDTA


Collinearity DiagnosticsPa

Model

Dimen

sion Eigenvalue

Condition

Index

Variance Proportions

(Constant) SDTA LDTA TDSE

1 1 3.305 1.000 .01 .00 .02 .012 .477 2.631 .01 .01 .47 .00

3 .197 4.099 .16 .00 .06 .23

4 .020 12.734 .82 .98 .46 .76


Residuals StatisticsPa

Minimum Maximum Mean Std. Deviation N

Predicted Value 1.7631% 12.9061% 7.1957% 2.70846% 200Residual -11.71090% 17.43534% .00000% 4.34875% 200

Std. Predicted

Value

-2.006 2.108 .000 1.000 200

Std. Residual -2.673 3.979 .000 .992 200



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Appendix 4: MLR between ROE and independent variables

Variables Entered/RemovedPb

Model Variables Entered Variables Removed Method

1 TDSE, LDTA,

SDTAPa

. Enter

a. Tolerance = .000 limits reached.

b. Dependent Variable: ROE

Model Summary

Model R R Square Adjusted R Square Std. Error of the Estimate

1 .085Pa .007 -.008 9.70801%


ANOVAP

Model Sum of Squares df Mean Square F Sig.

1 Regression 133.338 3 44.446 .472 .702Pa

Residual 18472.101 196 94.245

Total 18605.440 199



CoefficientsPa

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

Collinearity

Statistics

B Std. Error Beta Tolerance VIF

1 (Constant

)

19.49

9

2.528 7.715 .000

SDTA -.080 .080 -.135 -

1.004

.317 .281 3.564

LDTA -.015 .115 -.013 -.126 .900 .515 1.941

TDSE .012 .014 .125 .832 .407 .224 4.470

a. Dependent Variable: ROE


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Excluded VariablesP

Model Beta In t Sig. Partial Correlation


Tolerance VIFMinimumTolerance

1 TDTA

.P

a

. . . .000 . .000

a. Predictors in the Model: (Constant), TDSE, LDTA, SDTA


Collinearity DiagnosticsPa

Mode

l

Dimensio

n Eigenvalue

Condition

Index

Variance Proportions

(Constant) SDTA LDTA TDSE

1 1 3.305 1.000 .01 .00 .02 .012 .477 2.631 .01 .01 .47 .00

3 .197 4.099 .16 .00 .06 .23

4 .020 12.734 .82 .98 .46 .76


Residuals StatisticsPa

Minimum Maximum Mean Std. Deviation N

Predicted Value 16.4439% 23.7008% 17.5737% .81856% 200

Residual -34.14282% 24.60652% .00000% 9.63455% 200Std. PredictedValue

-1.380 7.485 .000 1.000 200

Std. Residual -3.517 2.535 .000 .992 200



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