







































Asian Finance& Banking Review; Vol. 2, No. 2; 2018 

ISSN 2576-1161E-ISSN 2576-1188 

Impact Factor: 3.3  

Published by Centre for Research on Islamic Banking & Finance and Business 

 

 

42 

 

Determinants of Firm’s Leverage and Theoretical Examination: A 

Study on the Food and Allied Companies in Bangladesh 

 

Saptarshi Chakma 

Lecturer 

Department of Management 

Rangamati Science and Technology University, Rangamati 

 

 

 

Received: December 7, 2018             Accepted: December 16, 2018              Online Published: December 23, 2018 

 

 

 

Abstract 

Leverage helps to understand how much debt and equity employed by a firm to funds its operation and asset. 

Modigliani and Miller are the path breaker in this sector. In 1958 identified irrelevancy proposition of Firm 

Leverage decision. In 1963 they came with their new explanation to incorporate the effect of tax. There are some 

other popular theories. Jensen and Meckling agency cost theory, Scott trade off theory, Ross signaling theory, Myers 

and Majluf pecking order theory are the most popular one. There are several determinants in Firm Leverage used in 

different studies. In this study, we used some most popular determinants. They are profitability, tangibility, growth, 

operating leverage, liquidity, size. In this study, nine DSE listed food and allied companies’ data are used to analysis 

the relation between determinants and leverage and Firm Leverage theories are also tested for those companies. 

Food and allied sector is a constant growing sector and good option for the investors. Nine A category companies’ 

data are used for this study. For the data analysis descriptive data, hypothesis, correlation and regression method is 

used. Leverage mean of last seven-year data is 48.5%. That means there is a good combination of debt and equity. In 

the hypothesis, T-test: paired two sample for means is used. Null hypothesis only accepted for the tangibility 

determinants. That indicates there is a relationship between tangibility and leverage. In correlation matrix, it also 

showed that, leverage and tangibility have the strongest relation and the relation is negative. In regression model, 

only tangibility result is significant and the coefficient is negative. According to the result, pecking order theory, 

trade off theory and signaling theory play an important role in food and allied companies in Bangladesh. The 

analysis showed that, companies with high tangibility ratio try to finance their operations by internal finance rather 

than debt finance and supported theories also refer the same result. 

 

Keywords: Capital structure, Profitability, Leverage, Tangibility and Liquidity.  

 

1. Introduction 

Nowadays Bangladesh is well known as a developing country with rapid growth economics. It has an ample scope 

for industrial development which would bring about positive outcome in the economy of our country. Industry 

development is necessary for the development of infrastructure development. Firm Leverage is one of the most 

common and important theory in the field of finance. It is the most essential element to establish a company. Firm 

Leverage theory refers the amount of debt and equity used by a firm to finance its operations and assets. It indicates 

how firms finance their overall operations and growth by using debts like long-term notes payable and equity like 

common stock. The main components of Firm Leverage are debt and equity. A manager always looks to find out the 

optimal Firm Leverage to maximize the value of the firm and minimize the cost of capital. The purpose of this study 

is to examine the relation between leverage and determinants of Firm Leverage decision of food and allied 

companies in Bangladesh.  

Required data collected from 9 firms’ financial statement from consecutive seven years, from their audited 

balance sheet and income statement. The purpose of the study is to analyzes the result both descriptive and 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

43 
 

 

statistical analysis. Firm Leverage become one of the most controversial issue in the field of corporate finance 

since the phenomenal work of Modigliani & Miller. Most of the popular firm leverage researches are done under 

developed countries like Rajan and Zingales, 1995. Only a few popular works done in Bangladesh like 

Chowdhury, 2004; Lima, 2010; Sayeed, 2012. But the numbers are increasing. 

 

3. Objective of the study 

To get a better output, several hypotheses (HP) were tested. The tested hypotheses are given below:  

 

These hypotheses will determine the Firm Leverage of food and allied firms in Bangladesh: - 

 

Table 1. Hypothesis table 

 

Null Hypothesis Alternative Hypothesis 

HP0: Leverage ratios and profitability are associated. HP 1: Leverage ratios and profitability are not associated. 

HP0: Leverage ratios and growth are related. HP1: Leverage ratios and growth are not related. 

HP0: Leverage ratios and tangibility are linked. HP1: Leverage ratios and tangibility are not linked. 

HP0: Leverage ratios and liquidity are associated. HP1: Leverage ratios and liquidity are not associated. 

HP0: Leverage ratios and operating leverage are related. HP1: Leverage ratios and operating leverage are not 

related. 

HP0: Leverage ratios and size are corelated. HP1: Leverage ratios and size are not corelated. 

 

 

4. Literature Review 

There are several empirical studies regarding Firm Leverage decisions have been concisely reviewed here in terms 

of two segments both International evidence and Evidence from Bangladesh. 

 

In the year 1995, Rajan and Zingales had a rigorous study in this area where they came with an outcome that the 

various factors of Firm Leverage of US companies are size, growth, profitability and tangible assets.  

 

Lima (2010) likewise guaranteed that development rate, substantial quality, working influence, obligation 

administration limit, administrative proprietorship age and size have huge impact on Firm Leverage choices. They 

additionally reasoned that the organization cost hypothesis and static exchange off hypothesis are pertinent for the 

organizations in Bangladesh. 

 

5. Methodology of the study 

 

5.1 Data collection 

The number of inhabitants in the examination is the nourishment and associated firms in Bangladesh. For this 

investigation, sequential seven-year information will be considered. Along these lines 9 firms which have seven 

fiscal reports are fused right now. The organizations are browsed the rundown of Dhaka Stock Exchange (DSE) 

Food and Allied segment A classification firms. The organizations which used to gather the information are: 

 

▪ Agricultural Marketing Company Ltd. (Pran) 

▪ Apex Foods Limited 

▪ British American Tobacco Bangladesh Company Limited 

▪ Fu Wang Food Ltd. 

▪ Gemini Sea Food Ltd. 

▪ Golden Harvest Agro Industries Ltd. 

▪ National Tea Company Ltd. 

▪ Olympic Industries Ltd. 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

44 
 

 

▪ Rangpur Dairy (RD) & Food Products Ltd. 

 

5.2 Analysis of data 

The gathered information through audit are utilized to broke down to both distinct and exact insights. Graphic 

examination race to dissect the essential highlights of the information in the example. Connection network is 

utilized to distinguish the relationship of every factor among them. Various relapses are likewise used to decide 

the most significant informative factors influencing the Firm Leverageof nourishment and united firms in 

Bangladesh. In association with this, the general model for this examination, as is for the most part found in the 

current writing is spoken to by 

 

Yi,t= α + βXi,t + εi,t 

The subscript (i) representing the cross-sectional dimension and (t) denote the time-series dimension. The left-

hand variable which is the firm’s debt ratios represents the dependent variable in the model. (Xi,t) includes a 

number of independent variables estimated by the model. 

  Table 2. Variables and indicators 
 

Measurement of variables 

Variables Indicators 

Depended variable  

Leverage Total debt/Total asset 

Independent variable  

Profitability EBIT/Total asset 

Tangibility Fixed asset/Total asset 

Growth Annual change in total asset 

Operating leverage EBIT/operating revenues 

Liquidity Total current asset/Total current liabilities 

Size Natural logarithm of total asset 

 

6. Scope of the study 

The study mainly focuses on finding out the relationship between the leverage and the determinants of Firm 

Leverage (profitability, tangibility, growth, operating leverage, liquidity, size) of a specific sector food & allied 

sector nine listed A categorized company. Seven consecutive year financial data are used. Different statistical 

method used to find out the relation like hypothesis, correlation, regression. 

 

7. Limitations of the Study 

There is always a predetermined system-imposed limitation of time, exists in any research work. But with the 

cooperation of my supervisor, it has become possible to complete the research work satisfactory within the time 

limit. The limitation of the study is given bellow: 

 

▪ The study is restricted to a sample of only nine food & allied companies. 

▪ This study is limited to seven fiscal years for the analysis. 

▪ Theories of books are for efficient market. These theories are not completely applicable for an 

inefficient market like Bangladesh. 

▪ All data are secondary data. 

 

8. Firm Leverage Theories 

Firm Leverage refers that how a firm used different source of funds to finance its overall operations and growth. 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

45 
 

 

There are two components of Firm Leverage– debt and equity. Debt collected in the form of bonds, note-payable 

etc. and equity is classified in the form of common stock, preferred stock or retain earnings. It helps us to 

understand how much debt and/or equity employed by a firm to fund its operations and asset. It also helps us to 

understand the risk level of the firm. In general, high debt finance companies consider high risk exposure. 

 

8.1 Theories of Capital structure 

Modigliani & Miller (M&M) path breaking article in 1958 which identified irrelevancy proposition of Firm 

Leverage decision to firm value on an assumption of perfect world with no taxes, no transaction costs, no 

bankruptcy costs, equivalence in borrowing costs for both companies and investors, symmetry of market 

information, meaning companies and investors have the same information, no effect of debt on a company's 

earnings before interest and taxes. The article showed that the benefit from debt financing –financing at a low rate 

will be offset by the increase in cost of equity derived from high financial risk perceived by the shareholders and 

individual project risk has no relation to the sources of fund it uses. So market value of a company and cost of 

capital are independent to the extent of debt in the capital structure. In M&M they came with their new 

explanation to incorporate the effect of tax in the model is that value of the firm would be maximized if it uses 

100% debt in its Firm Leverage since interest payments are tax deductible. In 1977 Miller new version of 

irrelevance theory reveals that Firm Leverage decision of a firm has no effect in real world of corporate and 

personal tax. 

There are some other popular theories come into light after a wide array of research conducted. They are- agency 

cost theory, trade-off theory, signaling theory and pecking order theory. 

 

8.1.1 Agency cost theory 

Agency cost theory developed by Jensen and Meckling in 1976, refers that optimal Firm Leverage can be found 

by minimizing agency cost arising from conflict of interest among managers, owners and debt holders. First 

conflict between firm managers and shareholders. Firm manager directly deals with the agent on behalf of major 

shareholder interest. Most of the firm manager wants to run large with high probability of risk. This tends to 

undertake negative NPV projects. However, without a reward firm manager do not involve large and risky 

project even if they expect the project give positive NPV. This problem creates a conflict of interest between 

managers and shareholders. As a consequence, the agency cost problem arises. Sometime manager consumes 

firm valuable resources used their power (Jensen and Meckling, 1976). Second conflict between firm managers 

and debt holders. Managers are working for shareholders and they want to give priority shareholders interest. 

Manager invests risky project that will benefit for major shareholder not better for the bondholder. Bondholders 

also expect the manager invest safe and low return project that probability of risk is very low. Thus, firm can pay 

their debt on time. But firm manager chooses risky projects that indicated a high probability of losing capital. If 

they lose, no cash available to paid their loan. Most of the cases, shareholders prefer a firm manager invest risky 

project with high probability of success that they repaid their loan quickly and keep their ownership safe. If the 

risky project gave negative NPV, then shareholder has possibility of defaulter. They can’t repay their loan on 

time. 

Two ways are suggested to align managers interest with owners and debt-holders interest- 

▪ The first one is to increase the participation of the owners so that they can equally influence the 

decision taken by the manager. 

▪ The second one is to increase the use of debt financing to minimize consumption in the perk. 

 

 

8.1.2 Trade-off theory 

Trade-off theory developed by Sco, refers that firms seek to have an optimum debt– equity ratio where marginal 

rise in tax benefit equals to the marginal increase of agency and bankruptcy cost generated from an extra use of 

leverage. Financial manager taking firm debt- equity decision based on a trade-off between cost of financial 

distress and interest tax shields. But there is a controversy arises in the firm. Firm manager does not sure about 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

46 
 

 

how valuable interest tax shield. And they do not predict what types of financial problem are harmful for 

companies. According to the trade-off theory assume that debt ratio will vary from firm to firm. Firm with 

protected, tangible assets and high taxable income to shield indicate a high target ratio. 

 

8.1.3 Signaling Theory 

Signaling Theory introduced in 1977, based on asymmetric information, refers that managers use leverage 

decision to give signal to the market because investors treat debt financing as a signal of high future performance 

and high future cash flows of the firm. Therefore, the type of financing a company uses can provide a signal of the 

firm’s financial position and project prospects. When a company uses debt to fund a project, it could indicate 

that the company believes the project will provide returns quickly and sufficient enough to repay the debt so its 

current investors retain the benefits. If a company uses new equity to fund a capital project, it could be interpreted 

as either a signal that the company has no internal profits or is unable to raise any debt. 

 

8.1.4 Pecking order theory 

 

Pecking order theory introduced in 1984, states that there is no optimal Firm Leverage and managers follow a 

hierarchy of preferences for the issuance of new capital based on the cost of capital. They prefer retained 

earnings as the main source of financing due to its zero cost and then debt financing, followed by equity 

financing, because cost of debt is less than that of equity. 

 

Profitable firm borrow less amount debt because they have a low target ratio. This firms prefer internal finance 

when internal fund is sufficient to maximize the firm value and firm do not indicate any adverse signal that may 

lower the share price. 

 

Less profitable firm issue more debt because they have not enough internal funds to regulate the companies 

smoothly. So, they relied on external financing. This firms prefer external finance when internal fund is 

insufficient to run the firm. In such case, firm issue debt financing first. Then they go for equity finance. 

 

Pecking order theories do not neglect taxes and cost of financial difficulties in case of determined capital structure. 

However, this theory assumes, those factors are less significant than firm managers’ decision about internal and 

external finance to issue more new capital structure. 

 

9. Determinants of Capital Structure 

There are several determinants used in different studies on determinants of capital structure. But we choose the 

most popular and common six determinants to find out the relationship between the determinants and the 

leverage. The determinants we used in this study are: 

▪ Profitability 

▪ Tangibility 

▪ Growth 

▪ Operating leverage 

▪ Liquidity 

▪ Size 

 

9.1 Profitability 

Profitability is one of the most important determinants of Firm Leverage but there are different views in the 

relationship between leverage and profitability. Trade off theory and signaling theory, have showed positive 

relation with the leverage. In trade off theory managers try to increase their leverage to raises their profitability 

by achieving the tax shield. In signaling theory managers use debt financing to finance their profitable 

investments. On the other hand, pecking order theory referred negative relation between leverage and 

profitability. They think, profitable firms borrow fewer amounts of debt and internal financing as a first choice. 

The profitability of a firm calculates as a ratio: 

Profitability=EBIT/total asset 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

47 
 

 

 

9.2 Tangibility 

One of the vital determinants of Firm Leverage is tangibility. Trade off theory showed a positive relation 

between leverage and tangibility. It used as collateral of borrowed fund. In agency cost problem suggest that 

tangibility has negative correlation with information asymmetry problem. Lower information asymmetry problem 

has lower dependence on debt and equity is more preferable. High tangibility capable firms high borrowing 

ability. Tangibility calculates as: 

 

Tangibility=Fixed asset/total asset 

 

9.3 Growth 

Growth is the determinants which are related with all the four theories we used in this study. Singling theory and 

pecking order theory conclude a positive relationship in growth and leverage. They determine in their theories 

that companies with high growth have high debt capacity and tend to use external finance for their companies’ 

growth. Jensen and Meckling 1976, agency cost theory and trade off theory provides different opinion about 

growth. They think there is a negative relation between growth and leverage. High growth firm tend to use low 

external finance to reduce agency cost between firm managers and debt holders. In trade off theory high growth 

companies used low debt ration because their target ratio is low. Growth ratio calculates as: 

Growth=Annual change in total asset 

 

9.4 Operating leverage 

Operating leverage is the determinants which influence trade off and pecking order theory. In trade off theory, 

there is a positive relation between operating leverage and leverage ratio. Higher operating leverage indicates 

higher risk of the firms. Since the managers does not sure about how valuable interest tax shield and they do not 

predict what types of financial problem are harmful for companies. They take more risk and used debt finance. 

In pecking order theory show negative relation between operating leverage and leverage because high risk firm 

use low leverage to reduce risk. Operating leverage ratio calculate as: 

Operating leverage =EBIT/operating revenues 

 

9.5 Liquidity 

Liquidity is one of the most important determinants of capital structure. But there is a controversy about the 

relation between liquidity and leverage ratio. Trade off theory refers that there is a positive relation between 

liquidity and leverage ratio. Firms with high liquidity are more capable to pay their debt. So highly liquid firm tend 

to use high debt finance. On the other hand, pecking order theory refers that there is a negative relation between 

liquidity and leverage. Highly liquid firms used internal finance rather than external finance. Liquidity ratio 

calculate as: 

Liquidity=total current asset/total current liabilities 

 

9.6  Size 

Size of the firm is a determinant of capital structure. According to trade off theory there is a positive relation 

between size and leverage. Large size firms have low bankruptcy cost and high capacity to get external finance. 

Because of diversification large firms maximize their tax benefits form debt. In signaling theory, firm with high 

debt finance provide signals to the investors that the firm is in a profitable position and has the ability to quick 

repay of the loan. So it also refers that, there is a positive relation between size and leverage. But according to 

pecking order theory, there is a negative relation between size and leverage. Because large firms prefer internal 

finance first than external finance. Size calculates as: 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

48 
 

 

Size=Natural logarithm of total asset 

 

In the table below summarize the relations among the determinants of Firm Leverage (independent variables) 

and the theories of capital structure. Most popular four Firm Leverage theories are used in this table and the six 

mostly used determinants of Firm Leverageare used in this table. In this table (+) sign uses to indicate positive 

relation and (-) sign used to indicate negative relation. 

 

Table 3. Theoretical expectation of variables 

 

Theoretical Expectation 

Independent 

variables 

Agency 

cost 

Trade-off Signaling Pecking 

order 

Profitability  + + - 

Tangibility +/- +  - 

Growth - - + + 

Operating 

leverage 

 +  - 

Liquidity  +  - 

Size  + + - 

 

 

10. Food and Allied Sector of Bangladesh 

 

Food and allied sector is a growing sector in our country. This sector considers as one of the constant growth 

sectors in Dhaka Stock Exchange (DSE). The price return and change in turnover is positive in this sector for the 

last year. The foreign investment is increasing in this sector. There are eighteen (18) companies listed in DSE 

food & allied sector. In this eighteen companies nine companies are A category one is B category and the rest 

eight companies are Z category. In our study we use only the A category companies’ information. The list is: 

▪ Agricultural Marketing Company Ltd. (Pran) 

▪ Apex Foods Limited 

▪ British American Tobacco bangladesh Company Limited 

▪ Fu Wang Food Ltd. 

▪ Gemini Sea Food Ltd. 

▪ Golden Harvest Agro Industries Ltd. 

▪ National Tea Company Ltd. 

▪ Olympic Industries Ltd. 

▪ Rangpur Dairy & Food Products Ltd. 

 

10.1  Agricultural Marketing Company Ltd. (Pran) 

Program for Rural Advancement Nationally (PRAN) group was born in 1980. They are the largest processors of 

fruits and vegetables in Bangladesh and well known for diversify activities. The main purpose is to enrich the 

agricultural sector since our economy is agricultural based and develop our native farmers. They are also one of 

the biggest exporter in our country. PRAN listed in DSE in 1996 and now their market category is A. 

 

10.2  Apex Foods Limited 

Apex foods limited incorporated their business on 1979. Apex sea food is the single largest processor and 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

49 
 

 

exporter of frozen sea food of Bangladesh. They are well known in the worldwide for their high quality products. 

They export their product in North America, EU countries, Australia and Russia. Apex foods limited listed in 

DSE in 1981 and now their market category is A. 

 

10.3 British American Tobacco Bangladesh Company Limited 

In 1998 Bangladesh Tobacco Company change their name as a British American Tobacco Bangladesh company 

limited and aligning the corporate identity with other operating companies in the British American Tobacco 

group. It is one of the world largest international business and sold their products more than 200 markets all over 

the world. They are well known for their quality tobacco and diversification according to consumer choice. They 

listed in DSE in 1977. 

 

10.4 Fu Wang Food Ltd. 

Fu Wang food ltd. start their business in 1997 and certified in 1998. They introduce variety of products to cover 

the market. They have different food items like bred, biscuit, cake, toast, chocolate, instant noodles, drinking 

water, energy drink etc. Fu Wang food listed in DSE in 2000. 

 

10.5 Gemini Sea Food Ltd. 

Gemini sea food ltd. start their business in 1982. The main target this firm is to provide quality product 

according customer requirement. They believe that “Hygienic Product Healthy Trade”. They export our quality 

products to U.S.A & EU countries like U.K, Germany, Denmark, Netherlands, Belgium and Russia etc. They 

listed in DSE in 1985. 

 

10.6 Golden Harvest Agro Industries Ltd. 

Golden harvest Agro Industries ltd. is a company of Golden Harvest group. It is one of the pioneer frozen food 

manufacturing companies in our country. They are well known for their good quality and tasty frozen foods both 

locally and internationally. They export their product in USA, Canada, Australia, Middle East and the European 

countries. They listed in DSE in 2014. 

 

10.7 National Tea Company Ltd. 

National tea company ltd. starts their business in 1978 as a joint venture and government and its financial 

organization holds majority of the share (51%) and the rest are owned by the general public. This company 

owned 12 tea estates which cover almost fifty percent of the total tea cultivation area. It sold 5.20 million kg. tea 

through Chittagong auction market annually. National Tea Company ltd. listed in DSE in 1979. 

 

10.8 Olympic Industries Ltd. 

Olympic industries ltd. incorporates their business in 1979 as a battery manufacturer but later they diversify their 

business by manufacturing biscuits and confectionary items in 1996. Today they are the largest biscuit 

manufacturer in Bangladesh. They think quality of their products and loyalty to their customers make Olympic so 

popular. Olympic listed in DSE in 1989. 

 

10.9 Rangpur Dairy & Food Products Ltd. 

They collect the raw milk from the northern part of our country and processed the raw milk in Ultra High 

Temperature (UHT). It also reduces the risk of infection. They use high quality packaging system to maintain the 

milk for long time. Rangpur Dairy & Food Products Ltd. listed in DSE in 2011. 

 

 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

50 
 

 

11. Analysis of the Study 

11.1 Descriptive statistics 

In this study we examine the nine food and allied listed companies’ seven-year data. Here we showed the mean, 

standard deviation, maximum and minimum value of the ratios. 

Table 4. Data descriptions 

 

Variable Mean Max Min Standard deviation 

Leverage 0.485113 1.022036 0.047937 0.252917 

Profitability 0.134335 0.514757 -0.03007 0.126493 

Tangibility 0.445406 0.843248 0.046722 0.213776 

Growth 0.159228 1.129147 -0.27103 0.229247 

Operating leverage 0.127053 0.449611 -0.01945 0.112153 

Liquidity 3.132551 77.13767 0.678286 9.592806 

Size 20.58751 22.93377 16.39201 1.542438 

 

Leverage means is 48.5% which indicates equity used in this sector as 51.5%. That means leverage and equity 

portion almost equal in this sector which indicates a good combination of debt and equity. Standard deviation is 

25% in leverage ratio. 

Profitability in these companies is positive and it is 13% which refers profitability of those companies is 13%. It 

is good sign for food & allied companies in Bangladesh. In profitability minimum value is -3% and maximum 

value is 51.5%, there is huge gape in these two values and that’s why the standard deviation is 13.5%. 

Tangibility is the fixed asset portion of a firm. Here the average is almost 44%. That means the firms have a 

large portion of fixed assets. In tangibility minimum value 4.7% and maximum value 84%. The standard 

deviation is 21%. 

Growth is 16% which means that the firms growth last seven years is 16% which is positive and good enough. It 

refers that firms in this sector growing year to year. Standard deviation is 23%. 

Operating leverage calculate as a EBIT to operating revenues. Operating leverage mean is 12.7% which means 

earnings of the firms after basic costs. So the earnings ratio of the firm over last seven years is positive and quiet 

satisfactory. Standard deviation is 11%. 

Liquidity is 3.13 which means firms are not use their liquid asset efficiently and their performance is not 

satisfactory. They should use more their liquid asset in their business activities. Standard deviation is 9.6. 

Size of the firm is another determinant of Firm Leverage calculates as a natural logarithm of total asset. The 

mean of the firm’s total asset natural logarithm over last seven years is 20.58 and the standard deviation is 1.54. 

     

11.2 Hypothesis 

T-test: Paired two samples for means is used. Significance level is 5%. 

 

 

 

 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

51 
 

 

 

Table 5. Hypothesis result 

T-test: Paired two samples for means is used. Significance level is 5%. 

Null Hypothesis Alternative Hypothesis Result 

HP0: Leverage ratios and 

profitability are associated. 

HP 1: Leverage ratios and 

profitability are not associated. 

HP0 hypothesis rejected 

HP0: Leverage ratios and growth are 

related. 

HP1: Leverage ratios and growth are 

not related. 

HP0 hypothesis rejected 

HP0: Leverage ratios and tangibility 

are linked. 

HP1: Leverage ratios and tangibility 

are not linked. 

HP0 hypothesis accepted 

HP0: Leverage ratios and liquidity 

are associated. 

HP1: Leverage ratios and liquidity 

are not associated. 

HP0 hypothesis rejected 

HP0: Leverage ratios and operating 

leverage are related. 

HP1: Leverage ratios and operating 

leverage are not related. 

HP0 hypothesis rejected 

HP0: Leverage ratios and size are 

corelated. 

HP1: Leverage ratios and size are 

not corelated. 

HP0 hypothesis rejected 

 

H0 accepted or rejected based on the P value and the t-stat value of the result. If P value is lower than .05 than 

reject the null hypothesis and if P value is greater than or equal .05 than accept the null hypothesis. If t-stat value 

is greater than t critical value than reject the null hypothesis otherwise we accept the null hypothesis. According 

to these two conditions only tangibility and leverage null hypothesis is accepted. That means there is relationship 

between leverage ratios and tangibility. All other determinants relation with leverage is rejected because of lower 

P value and higher t-stat value. 

 

11.3  Correlation 

In this correlation matrix, showed the relation between the dependent variable (leverage) and independent 

variables (Profitability, tangibility, growth, operating leverage, liquidity, size). It also showed the internal 

relations among the independent variables. 

 

Table 6. Correlation matrix 

 

  

Leverage 

 

Profitability 

 

Tangibility 

 

Growth 
Operating 

leverage 

 

Liquidity 

 

Size 

Leverage 1       

Profitability 0.162528711 1      

Tangibility -0.637004421 -0.100731037 1     

Growth 0.089690154 0.117833829 -0.17938 1    

Operating 

leverage 
 

-0.5237648 

 

0.002155883 

 

0.597904 

 

0.159278 

 

1 

  

Liquidity 0.12614236 0.046138026 -0.09529 -0.06436 -0.08701 1  

Size -0.252793763 -0.655249788 0.151824 0.072891 0.314651 -0.09575 1 

 

The correlation matrix showed that leverage has positive relation with profitability. It indicates that firms which 

have high profitability ratio have preference to use debt finance. Leverage has also positive relation with growth 

and liquidity. Tangibility, operating leverage and size have negative relation with leverage. 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

52 
 

 

P value is one of the most important determinants in the regression model. If P value is lower than or equal 0.05 

indicates, there is a strong relationship between dependent and independent variable. In this table, only 

tangibility and liquidity P value is lower than 0.05. So these variables are considered significant. 

T-stat is a statistic that indicates the size of an effect, from the standpoint of a bell curve (a probability 

distribution). The further away from Zero (0) the more likely that the effect is "statistically significant". In this 

table, only tangibility variables t stat value is greater than 2. So this variable is significant. 

Coefficient represent the beta which refers risk. The first intercept coefficient represents the constant value of 

the regression model. 

So the regression model is: 

 

Yi,t= α + βXi,t + εi,t 

If we elaborate the model: 

Yi= α + β*profitability + β*tangibility + β*growth + β*operating leverage + β*liquidity + β*size 

Yi= 0.998598508+0.126890261 * profitability+(-0.564312855) * tangibility+0.044125089 * growth+(- 

0.494013774) * operating leverage+ 0.001445136* liquidity+( -0.01107319) *size 

 

11.4 Testing of Firm Leverage theories 

Theories showed the relation between the determinants and leverage ratios. They should be positive and 

negative. According to the different statistical analysis we find the relation between the determinants and the 

leverage ratio. Now we find out which theories fit for the determinants of Firm Leverageand leverage ratio of food 

and allied companies in Bangladesh. 

In this table below, showed the relation between the determinants and leverage ratio according to theories and in 

terms of the data analysis. 

 

Table 7. Determinants findings and supporting theories. 

 

Theoretical Expectation Findings Supporting theory 

Independent 

variables 

Agency 

cost 

Trade- 

off 

Signaling Pecking 

order 

  

Profitability  + + - + Trade-off, Signaling 

Tangibility +/- +  - - Pecking order 

Growth - - + + + Signaling & pecking order 

Operating 

leverage 

 +  - - Pecking order 

Liquidity  +  - + Trade-off 

Size  + + - - Pecking order 

 

The finding is that tangibility, growth, operating leverage and size follow pecking order theory. They have also 

negative relation with leverage except growth. The rest two profitability and liquidity follow trade off theory. 

Profitability and growth also follow signaling theory. They both are positive that means they provide the 

investors a positive signal. 

 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

53 
 

 

 

12. Findings of the study 

According to correlation matrix there is a positive relation between profitability and leverage ratio. The 

coefficient of profitability is also correct. That means high profitable firms prefer debt finance for their business 

operations. Because of high profitability they have the ability to pay the debt and also excess of loan. 

Tangibility is the only determinants which has significant value in regression model and also show strong 

relation in correlation matrix. In hypothesis, tangibility H0 also accepted. There is a negative relation between 

tangibility and leverage which indicates firms with high fixed asset tend to use internal finance. Though, they 

have easy access of loan because of large amount of fixed asset. 

The relation between growth and leverage is not so significant. The correlation value is very low but correlation 

and coefficient value is positive. 

Operating leverage has a strong negative relation with leverage. That means companies with high income prefer 

to use their internal finance like retain earnings rather than external finance. 

Liquidity has very low value in correlation and insignificant in regression model. Though the value is very low 

but the relation is positive. 

Size has a negative correlation with leverage. That refers that, large size companies use more internal finance 

and less external finance. 

Packing order theory and trade-off theory have great impact on food and allied companies in Bangladesh. 

Packing order theory is followed because of internal financing like retain earnings and trade off theory followed 

because manager tend to take less risk that’s why they try to avoid external financing. Signaling theory also play 

important role in this sector. 

13. Conclusion 

The determinants of capital are not strongly influence the leverage decision of food and allied sector in Bangladesh 

except tangibility. Tangibility is the determinants which has significant value and relation with leverage. There is a 

negative relation between leverage and tangibility. Companies high fixed asset have high tangibility ratio prefer 

internal finance compare to external finance for their business operations. In the theories of capital structure, 

packing order theory and trade-off theory have great impact on our food and allied companies in Bangladesh. 

Packing order theory suggest to use internal finance like retain earnings due to its zero cost and in trade off theory 

manager taking firm debt-equity decision based on a trade-off between cost of financial distress and interest tax 

shields. 

References 

Chowdhury, M. U. (2004); Firm Leverage Determinants: Evidence from Japan & Bangladesh; Journal of Business 

Studies, xxv (1), 23-45. 

Jensen, M., & Meckling, W. (1976); Theory of the firm: Managerial behavior, agency costs and ownership structure; 

Journal of Financial Economics, 3(4), 305-360. 

Lima, M. (2010); An insight into the Firm Leverage determinants of the pharmaceutical companies in 

Bangladesh; GBMF Conference, 2010. 

Rajan, R. G., & Zingales, L (1995); What do we know about capital structure? Some evidence from international data; 

Journal of Finance, 50, 1421-1460. 

Sayeed, A. M. (2012). The Determinants of Firm Leverage for Selected Bangladeshi listed companies; International 

Review of Business Research Papers, 7(2), 21-36. 

 

 

 

 

 

 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

54 
 

 

 

Appendix 

Nine companies last seven years data 

 

 

 

Year 

 

Company 

name 

 

Total debt 

Total 

current 

liabilities 

 

Total asset 

 

Fixed asset 

Total 

current 

asset 

Operating 

revenues 

 

 

EBIT 

 

2017 

 

 

 

 

 

Apex food ltd 

1102179 

663 

1077907 

226 

1758501 

536 

3855338 

16 

1372967 

720 

16427721 

07 

 

4469543 

 

2016 

9261507 

63 

8831010 

97 

1545510 

181 

3599302 

52 

1185579 

929 

20319469 

45 

 

-20800413 

 

2015 

1157463 

237 

1104763 

634 

1779946 

562 

3307064 

94 

1449240 

068 

27517798 

85 

 

-53525355 

 

2014 

1130977 

648 

1040962 

126 

1693029 

263 

3726989 

73 

1320330 

290 

38446812 

56 

 

31319044 

 

2013 

1240793 

403 

1128293 

403 

1758652 

867 

3500994 

01 

1408553 

466 

33057172 

80 

 

20664243 

 

2012 

1019973 

962 

8774739 

62 

1571415 

244 

3490459 

84 

1222369 

260 

39333461 

04 

 

18734510 

 

2011 

1079963 

920 

9302018 

88 

1485155 

738 

2169777 

00 

1268176 

843 

32073147 

33 

 

9059599 

 

2010 

  1136280 

606 

    

 

2017 

British 

American 

Tobacco 

1646500 

1 

1363696 

5 

3534758 

3 

1541187 

3 

1993571 

0 

16563376 

0 

 

13926734 

 

2016 

1498131 

2 

1245028 

6 

2959083 

1 

1366501 

5 

1592581 

6 

14371166 

4 

 

13200527 

 

 

 

2015 

 1561150 

9 

1410283 

5 

2707501 

9 

1201857 

6 

1505644 

4 

12680460 

2 

 

11534652 

 

2014 

 

9562208 

 

8314769 

1846379 

8 

 

8513167 

 

9950631 

10958171 

0 

 

9504368 

 

2013 

 

8001553 

 

7029777 

1503449 

3 

 

5861627 

 

9172866 

 

90174080 

 

6912702 

 

2012 

 

7239749 

 

6300705 

1315104 

9 

 

5376634 

 

7774415 

 

75357351 

 

5246089 

 

2011 

 

7128724 

 

6323404 

1336943 

3 

 

5315562 

 

8053871 

 

65986503 

 

3145629 

 

2010 

  1201956 

5 

    

 

2017 

 

 

 

 

4802167 

54 

3841025 

20 

1581852 

767 

5640893 

36 

9767634 

31 

58678768 

7 

 

101924432 

 

2016 

4432930 

62 

3866021 

33 

1482203 

822 

5585534 

62 

8736503 

60 

76710939 

2 

 

134364942 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

55 
 

 

 

2015 

 

Fu-Wang foods 

ltd. 

3914561 

48 

3254515 

90 

1343232 

984 

5122796 

20 

7809533 

64 

81985185 

0 

 

169903795 

 

2014 

3406547 

10 

2625633 

29 

1179301 

123 

4799823 

40 

6493187 

83 

79440601 

4 

 

104922031 

 

2013 

2926293 

79 

2617136 

38 

1070394 

684 

4834268 

76 

5369678 

08 

78512652 

5 

 

107712285 

 

2012 

2601093 

46 

2601093 

46 

9998698 

91 

4751656 

49 

4747312 

42 

75845905 

0 

 

114100545 

 

2011 

2451310 

79 

2451310 

79 

8795389 

42 

3879200 

56 

4718147 

28 

70916856 

8 

 

117527552 

 

2010 

  5428772 

82 

    

 

2017 

 

 

 

 

Pran(Agric 

ultural 

marketing com. 

Ltd.) 

8892357 

03 

7258336 

66 

1463022 

240 

4741943 

53 

9888278 

87 

23803354 

93 

 

193375561 

 

2016 

9148193 

65 

6975322 

12 

1459268 

485 

5446370 

29 

9146314 

56 

20915538 

54 

 

190285679 

 

2015 

9886606 

91 

5398162 

78 

1505711 

652 

6580816 

31 

8476300 

21 

18865053 

85 

 

73888029 

 

2014 

6088439 

75 

5412394 

63 

1095910 

217 

3418084 

93 

7541017 

24 

17272176 

69 

 

74278680 

 

2013 

6510617 

87 

5655367 

87 

1137169 

643 

3389773 

11 

7981923 

32 

15544468 

36 

 

70621379 

 

2012 

7112438 

21 

5762903 

21 

1167556 

801 

3896744 

99 

7778823 

02 

14790834 

63 

 

69884451 

 

2011 

7424684 

82 

5917684 

82 

1172667 

837 

4158256 

88 

7568421 

49 

13163455 

76 

 

58060062 

 

2010 

  1115683 

180 

    

 

2017 

Olympic 3707466 

711 

3408642 

811 

9120317 

797 

2363826 

358 

6756491 

439 

11290557 

541 

215312959 

4 

 

 

 

2016 

 3109495 

848 

2859716 

979 

7640768 

208 

1963251 

175 

5677517 

033 

10965042 

877 

211644008 

0 

 

2015 

2382025 

686 

1988098 

981 

5763679 

785 

1909946 

076 

3853733 

709 

89961485 

94 

143117004 

7 

 

2014 

2526239 

640 

1977232 

044 

5048637 

186 

1869464 

492 

3179172 

694 

79223538 

76 

118491576 

9 

 

2013 

1767679 

547 

1517602 

918 

3693672 

553 

1432816 

473 

2260856 

080 

70931793 

69 

 

931270071 

 

2012 

1294469 

294 

1037540 

875 

2591236 

306 

1201849 

350 

1389386 

956 

60033420 

18 

 

697570228 

 

2011 

1005533 

832 

8622446 

37 

1850322 

260 

7742549 

33 

1076067 

327 

38851018 

24 

 

392222519 

 

2010 

  1361913 

744 

    



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

56 
 

 

 

2017 

 

 

 

Golden 

harvest agro 

industries ltd. 

1026466 

518 

7055677 

43 

5044390 

614 

3573568 

441 

1470822 

173 

62443865 

7 

 

221338024 

 

2016 

9917837 

36 

4796108 

99 

4006564 

213 

2750054 

728 

1256509 

485 

52056381 

3 

 

214765123 

 

2015 

9575501 

12 

4692200 

55 

3440355 

786 

2112805 

705 

1327550 

081 

47207772 

9 

 

124412913 

 

2014 

6034123 

35 

4618579 

23 

2614274 

832 

1293112 

465 

1321162 

367 

41869057 

5 

 

156521438 

 

2013 

4279623 

35 

3600029 

68 

1549432 

414 

1024677 

371 

3752263 

05 

35071920 

2 

 

113056661 

 

2012 

2583723 

00 

1872380 

64 

1151988 

069 

9276869 

81 

2243010 

88 

30435398 

2 

 

136840856 

 

2011 

2658794 

15 

2016846 

78 

1283278 

696 

9112658 

41 

3256482 

05 

28365487 

9 

 

125846782 

 

2010 

  1020135 

468 

    

 

2017 

 

 

 

 

 

Gemini sea 

food ltd. 

7290579 

44 

7224131 

98 

7720125 

28 

3607012 

3 

7359414 

05 

13551241 

37 

 

70247040 

 

2016 

3389941 

59 

3323932 

27 

3625919 

31 

3765275 

5 

3249391 

76 

11121376 

64 

 

56276303 

 

2015 

3715539 

50 

3648100 

30 

3740189 

41 

4041399 

0 

3336049 

51 

90523889 

5 

 

43953578 

 

2014 

2197907 

05 

2121941 

05 

2150519 

08 

4077736 

4 

1742745 

44 

95454056 

8 

 

45400224 

 

2013 

3012788 

79 

2933009 

19 

2950073 

07 

4272013 

0 

2522871 

87 

76697116 

2 

 

34228981 

 

2012 

2065428 

23 

 

2208579 

2171978 

48 

4683320 

5 

1703646 

43 

12162930 

05 

 

47546426 

 

2011 

1878526 

40 

1523589 

72 

2015683 

95 

4827785 

6 

2315680 

54 

10050265 

43 

 

42356847 

 

2010 

  2348855 

64 

    

 

 

 

2017 

 

 

 

 

National tea 

company 

1189238 

971 

5928652 

70 

2132951 

221 

1730819 

005 

4021322 

16 

98566997 

4 

 

104392614 

 

2016 

1170799 

425 

6565240 

21 

2072299 

643 

1621391 

111 

4509085 

33 

95934410 

4 

 

163120468 

 

2015 

9999104 

50 

4949059 

54 

1930693 

798 

1574521 

010 

3561727 

88 

34965317 

0 

 

20011608 

 

2014 

9714636 

34 

5124318 

34 

1804403 

178 

1448875 

981 

3555271 

97 

83773240 

1 

 

61597345 

 

2013 

9052079 

34 

4460937 

22 

1730513 

915 

1325131 

628 

4053822 

87 

85681691 

0 

 

181875020 

 

2012 

8023525 

34 

3551234 

63 

1528704 

254 

1215198 

919 

3135053 

35 

89197157 

3 

 

263175480 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

57 
 

 

 

2011 

7563258 

91 

2495284 

31 

1417909 

243 

1195648 

702 

2536954 

84 

92158467 

5 

 

285648206 

 

2010 

  1323930 

070 

    

 

2017 

 

 

 

 

RD & food 

products ltd. 

1236094 

41 

1071474 

00 

1104929 

064 

7048319 

77 

4000970 

87 

53243092 

4 

 

52549104 

 

2016 

9930816 

6 

8712380 

6 

1045252 

046 

6885111 

74 

3567408 

72 

49443387 

1 

 

42863417 

 

2015 

8319358 

6 

7322633 

9 

1012279 

083 

6745009 

76 

3377781 

07 

46858950 

7 

 

41440980 

 

2014 

5476659 

6 

4776429 

8 

9493098 

64 

6290847 

28 

3202251 

36 

46779555 

8 

 

48223587 

 

2013 

4296593 

9 

3733873 

3 

8963089 

20 

5888036 

02 

3075053 

18 

43242251 

3 

 

49893432 

 

2012 

5677442 

3 

5257078 

0 

8864774 

35 

5880305 

02 

2984469 

33 

39309637 

3 

 

44795983 

 

2011 

6052823 

5 

4275896 

7 

9789004 

61 

5236984 

70 

2754478 

26 

35401295 

8 

 

40198752 

 

2010 

  8834958 

73 

    

 

Ratios 

No 

. 

 

Year 

Company name  

Leverage 

Profitab 

ility 

 

Tangibility 

 

Growth 

Operating 

leverage 

Liquid 

ity 

 

Size 

1 2017  

 

Apex food ltd 

0.63 0.00 0.22 0.14 0.00 1.27 21.3 

2 2016 0.60 -0.01 0.23 -0.13 -0.01 1.34 21.2 

3 2015 0.65 -0.03 0.19 0.05 -0.02 1.31 21.3 

4 2014 0.67 0.02 0.22 -0.04 0.01 1.27 21.2 

5 2013 0.71 0.01 0.20 0.12 0.01 1.25 21.3 

6 2012 0.65 0.01 0.22 0.06 0.00 1.39 21.2 

7 2011 0.73 0.01 0.15 0.31 0.00 1.36 21.1 

8 2010  0.47 0.39 0.44 0.19 0.08 1.46 17.4 

 

9 2017  

British 

American 

Tobacco 

0.51 0.45 0.46 0.09 0.09 1.28 17.2 

10 2016 0.58 0.43 0.44 0.47 0.09 1.07 17.1 

11 2015 0.52 0.51 0.46 0.23 0.09 1.20 16.7 

12 2014 0.53 0.46 0.39 0.14 0.08 1.30 16.5 

13 2013 0.55 0.40 0.41 -0.02 0.07 1.23 16.4 

14 2012 0.53 0.24 0.40 0.11 0.05 1.27 16.4 

15 2017  

 

Fu-Wang foods 

ltd. 

0.30 0.06 0.36 0.07 0.17 2.54 21.2 

16 2016 0.30 0.09 0.38 0.10 0.18 2.26 21.1 

17 2015 0.29 0.13 0.38 0.14 0.21 2.40 21 

18 2014 0.29 0.09 0.41 0.10 0.13 2.47 20.9 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

58 
 

 

19 2013 0.27 0.10 0.45 0.07 0.14 2.05 20.8 

20 2012 0.26 0.11 0.48 0.14 0.15 1.83 20.7 

21 2011 0.28 0.13 0.44 0.62 0.17 1.92 20.6 

22 2017  

Pran(Agricul 

tural marketing 

com. Ltd.) 

0.61 0.13 0.32 0.00 0.08 1.36 21.1 

23 2016 0.63 0.13 0.37 -0.03 0.09 1.31 21.1 

24 2015 0.66 0.05 0.44 0.37 0.04 1.57 21.1 

25 2014 0.56 0.07 0.31 -0.04 0.04 1.39 20.8 

26 2013 0.57 0.06 0.30 -0.03 0.05 1.41 20.9 

27 2012 0.61 0.06 0.33 0.00 0.05 1.35 20.9 

28 2011 0.63 0.05 0.35 0.05 0.04 1.28 20.9 

29 2017  

 

 

Olympic 

0.41 0.24 0.26 0.19 0.19 1.98 22.9 

30 2016 0.41 0.28 0.26 0.33 0.19 1.99 22.8 

31 2015 0.41 0.25 0.33 0.14 0.16 1.94 22.5 

32 2014 0.50 0.23 0.37 0.37 0.15 1.61 22.3 

33 2013 0.48 0.25 0.39 0.43 0.13 1.49 22 

34 2012 0.50 0.27 0.46 0.40 0.12 1.34 21.7 

35 2011 0.54 0.21 0.42 0.36 0.10 1.25 21.3 

36 2017  

Golden harvest 

agro industries 

ltd. 

0.20 0.04 0.71 0.26 0.35 2.08 22.3 

37 2016 0.25 0.05 0.69 0.16 0.41 2.62 22.1 

38 2015 0.28 0.04 0.61 0.32 0.26 2.83 22 

39 2014 0.23 0.06 0.49 0.69 0.37 2.86 21.7 

40 2013 0.28 0.07 0.66 0.35 0.32 1.04 21.2 

41 2012 0.22 0.12 0.81 -0.10 0.45 1.20 20.9 

42 2011 0.21 0.10 0.71 0.26 0.44 1.62 21 

43 2017  

 

Gemini sea food 

ltd. 

0.94 0.09 0.05 1.13 0.05 1.02 20.5 

44 2016 0.93 0.16 0.10 -0.03 0.05 0.98 19.7 

45 2015 0.99 0.12 0.11 0.74 0.05 0.91 19.7 

46 2014 1.02 0.21 0.19 -0.27 0.05 0.82 19.2 

47 2013 1.02 0.12 0.14 0.36 0.04 0.86 19.5 

48 2012 0.95 0.22 0.22 0.08 0.04 77.14 19.2 

49 2011 0.93 0.21 0.24 -0.14 0.04 1.52 19.1 

 

50 2017  

 

National tea 

company 

0.56 0.05 0.81 0.03 0.11 0.68 21.5 

51 2016 0.56 0.08 0.78 0.07 0.17 0.69 21.5 

52 2015 0.52 0.01 0.82 0.07 0.06 0.72 21.4 

53 2014 0.54 0.03 0.80 0.04 0.07 0.69 21.3 

54 2013 0.52 0.11 0.77 0.13 0.21 0.91 21.3 

55 2012 0.52 0.17 0.79 0.08 0.30 0.88 21.1 

56 2011 0.53 0.20 0.84 0.07 0.31 1.02 21.1 

57 2017  0.11 0.05 0.64 0.06 0.10 3.73 20.8 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

59 
 

 

58 2016  

RD & food 

products ltd. 

0.10 0.04 0.66 0.03 0.09 4.09 20.8 

59 2015 0.08 0.04 0.67 0.07 0.09 4.61 20.7 

60 2014 0.06 0.05 0.66 0.06 0.10 6.70 20.7 

61 2013 0.05 0.06 0.66 0.01 0.12 8.24 20.6 

62 2012 0.06 0.05 0.66 -0.09 0.11 5.68 20.6 

63 2011 0.06 0.04 0.53 0.11 0.11 6.44 20.7 

Hypothesis 

 

t-Test: Paired Two Sample for Means   

   

 Leverage Profitability 

Mean 0.485113459 0.134335175 

Variance 0.063966837 0.016000565 

Observations 63 63 

Pearson Correlation 0.162528711  

Hypothesized Mean Difference 0  

df 62  

t Stat 10.55596582  

P(T<=t) one-tail 8.84586E-16  

t Critical one-tail 1.669804163  

P(T<=t) two-tail 1.76917E-15  

t Critical two-tail 1.998971517  

   

   

t-Test: Paired Two Sample for Means   

   

 Leverage Tangibility 

Mean 0.485113459 0.445406088 

Variance 0.063966837 0.045700274 

Observations 63 63 

Pearson Correlation -0.63700442  

Hypothesized Mean Difference 0  

 

df 62  

t Stat 0.745867839  

P(T<=t) one-tail 0.229282948  

t Critical one-tail 1.669804163  

P(T<=t) two-tail 0.458565896  

t Critical two-tail 1.998971517  

   



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

60 
 

 

t-Test: Paired Two Sample for Means   

   

 Leverage Growth 

Mean 0.485113459 0.159227798 

Variance 0.063966837 0.052554099 

Observations 63 63 

Pearson Correlation 0.089690154  

Hypothesized Mean Difference 0  

df 62  

t Stat 7.940284723  

P(T<=t) one-tail 2.51173E-11  

t Critical one-tail 1.669804163  

P(T<=t) two-tail 5.02347E-11  

t Critical two-tail 1.998971517  

   

t-Test: Paired Two Sample for Means   

   

  

Leverage 

Operating 

leverage 

Mean 0.485113459 0.12705305 

Variance 0.063966837 0.012578328 

Observations 63 63 

Pearson Correlation -0.5237648  

Hypothesized Mean Difference 0  

df 62  

t Stat 8.718548815  

P(T<=t) one-tail 1.13167E-12  

t Critical one-tail 1.669804163  

P(T<=t) two-tail 2.26333E-12  

t Critical two-tail 1.998971517  

   

t-Test: Paired Two Sample for Means   

   

 Leverage Liquidity 

 

 

Mean 0.485113459 3.132551199 

Variance 0.063966837 92.02192553 

Observations 63 63 

Pearson Correlation 0.12614236  



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

61 
 

 

Hypothesized Mean Difference 0  

df 62  

t Stat -2.19708905  

P(T<=t) one-tail 0.015880062  

t Critical one-tail 1.669804163  

P(T<=t) two-tail 0.031760124  

t Critical two-tail 1.998971517  

   

t-Test: Paired Two Sample for Means   

 Leverage Size 

Mean 0.485113459 20.58751243 

Variance 0.063966837 2.379115398 

Observations 63 63 

Pearson Correlation -0.25279376  

Hypothesized Mean Difference 0  

df 62  

t Stat -98.1951863  

P(T<=t) one-tail 4.70512E-70  

t Critical one-tail 1.669804163  

P(T<=t) two-tail 9.41024E-70  

t Critical two-tail 1.998971517  

Regression 

Summary Output 

  Regression Statistics  

 

Multiple R 0.675622233 

R Square 0.456465402 

Adjusted R Square 0.398229552 

Standard Error 0.001961972 

  Observations 63  

 

ANOVA  

  

df 

  

SS 

 

MS F 

Significance 

F 

Regression  6 1.810316186 0.301719364 7.838219976 3.79532E-06 

Residual  56 2.155627738 0.038493352  

Total  62 3.965943924   

 

 

  

Coefficients 

Standar 

d Error 

 

t Stat 

 

P-value 

Lower 

95% 

Upper 

95% 

Lower 

95.0% 

Upper 

95.0% 

Intercept 0.9986 0.5218 1.9137 0.0608 -0.0467 2.0439 -0.0467 2.0439 



 
 

www.cribfb.com/journal/index.php/asfbr          Asian Finance & Banking Review         Vol. 2, No. 2; 2018 

62 
 

 

Profitability 0.1269 0.2816 0.4506 0.6540 -0.4372 0.6910 -0.4372 0.6910 

Tangibility -0.5643 0.1580 -3.5717 0.0007 -0.8808 -0.2478 -0.8808 -0.2478 

Growth 0.0441 0.1186 0.3721 0.7112 -0.1934 0.2817 -0.1934 0.2817 

Operating 

leverage 

 

-0.4940 

 

0.3214 

 

-1.5369 

 

0.1299 

 

-1.1379 

 

0.1499 

 

-1.1379 

 

0.1499 

Liquidity 0.0014 0.0026 0.5503 0.5843 -0.0038 0.0067 -0.0038 0.0067 

Size -0.0111 0.0241 -0.4591 0.6480 -0.0594 0.0372 -0.0594 0.0372 

 

 

 

 

 

 

Copyrights 

Copyright for this article is retained by the author(s), with first publication rights granted to the journal. 

This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 

license (http://creativecommons.org/licenses/by/4.0/) 

 


