




































American Interdisciplinary Journal of Business 

and Economics 
ISSN: 2837-1909| Impact Factor : 4.6 

Volume. 9, Number 4; October-December, 2022; 

Published By: Scientific and Academic Development Institute (SADI) 

8933 Willis Ave Los Angeles, California 

https://sadipub.com/Journals/index.php/aijbe 

 

 

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THE SIGNIFICANCE OF REPUTATION IN CORPORATE FINANCING: 
STUDY OF NON-FINANCIAL FIRMS IN PAKISTAN 

 
 

Bilal Wei 
School of Economics and Finance, Xi’an Jiaotong University, Xi’an, Shaanxi, P.R. China 

 

Abstract: This study investigates the impact of firm reputation on financing decisions in the non-financial 

sector of Pakistan. It employs a fixed effect model to estimate the regression among variables and finds a 

positive and significant effect between price-earnings (P/E) ratio and firm financial leverage. In contrast, the 

study reveals a negative association between firm age and financial leverage, as older and better-reputed firms 

choose not to use trade credit during financial crises. The study also highlights the importance of tangible 

assets as loan collateral to obtain trade credit. The authors suggest that managers should consider the 

sensitivity of firm reputation when making financing decisions, as it can be used as an instrument of financing. 

The paper recommends that future studies should explore the effects of firm reputation on other business 

decisions such as investment and borrowing capacity. The study theoretically, empirically, and practically 

highlights the contribution of firm reputation in firm financing decisions, providing new understanding 

through different theories such as pecking order theory, trade-off theory, and agency cost theory. 

Keywords: firm reputation, financing decisions, non-financial sector, Pakistan, fixed effect model, price-

earnings ratio, financial leverage, trade credit, tangible assets, loan collateral, investment, borrowing capacity. 

 

Introduction 

Firm reputation is a key factor that influences financing decisions, particularly during financial crises. It 

affects the availability and cost of funds for firms to finance their operations. While prior research has 

examined the relationship between firm reputation and financing decisions, the literature lacks comprehensive 

studies in developing countries such as Pakistan. The purpose of this study is to investigate the impact of firm 

reputation on financing decisions in the non-financial sector of Pakistan. Specifically, this study aims to 

examine the relationship between firm reputation and financial leverage, trade credit, and tangible assets. 

The study employs a fixed effect model to estimate the regression among variables using ten years of data 

from 2010 to 2019. The sample consists of 337 listed firms of the non-financial sector of Pakistan. The annual 

data were collected from Thomson Reuter DataStream and financial reports that were published by State Bank 

of Pakistan. 

This study finds that firm reputation has a significant impact on financing decisions in the non-financial sector 

of Pakistan. The study reveals a positive and significant effect between price-earnings (P/E) ratio and firm 

financial leverage. In contrast, firm age has a negative association with financial leverage, as older and better-

reputed firms choose not to use trade credit during financial crises. The study also highlights the importance 

of tangible assets as loan collateral to obtain trade credit. 

The study contributes to the literature by providing a comprehensive understanding of the effects of firm 

reputation on financing decisions in developing countries. It provides insights for managers to consider the 

sensitivity of firm reputation when making financing decisions. The study recommends that future research 

should consider all proxies of firm reputation's effects on other business decisions such as investment and 



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borrowing capacity. The significance of this study is not only theoretical but also practical. It provides new 

insights into the contribution of firm reputation in firm financing decisions, which may help firms to make 

informed financing decisions in Pakistan.   

The decision regarding investment is considered a fundamental decision by the businesses and this decision 

is attached with upcoming growth and long-lasting success of the businesses (Kannadhasan & Aramvalarthan, 

2011). The corporate sector plays a significant role in economic development because it introduces new 

opportunities and new avenues for investment. Due to high world-wide competition, investors invest heavily 

in new machinery, infrastructure, product development, product management to meet their development 

needs. However, investment needs obtaining and utilization of resources from appropriate sources. Hence, 

companies either use inner funds or go for outer financing by issuing shares or debt. The fresh and young 

companies build unique features that separate them from older and recognized firms. The firm age is the proxy 

of firm reputation. The firms tend to learn over the years, they gain skills in different fields and try to build a 

strong network of relationships with their stakeholders to gain legitimacy in front of them.   

This work contributes theoretically, practically, and empirically. Theoretically, this study highlights the 

contribution of firm reputation in firm financing decisions by giving new understanding through different 

theories i.e., pecking order theory, trade-off theory, and agency cost theory. Practically, study helps managers 

to choose an economic way of financing by considering firm reputation as a significant determinant of the 

firm financing. The study quantifies the reputation by using different proxies of firm reputation. A well-known 

firm may help a firm to arrange funds with minimum obstacles. Empirically, this study has justified the impact 

of firm reputation impact on firm financing decisions by hypothesizing and applying different statistical 

techniques i.e., fixed effect model. The firm’s reputation helps us to choose the financing methods which may 

help to take the efficient financing decision for the firms. Fortune magazine (international agency for 

evaluation of reputation) segregates a world-wide yearly score which is termed as the ‘world’ most venerated 

companies. The benchmark of Fortune magazine to give rank to the companies include renovation, 

management efficiency, people management, financial dependability, social obligation, product & services 

quality and world-wide competitivness. Fortune magazine often uses different criterias and methods. This 

study uses different proxies to measure the firm reputation. Fortune magazine collects data from top 500 

companies all over the world and issues reports annually by using these proxies (Fortune Magazine, 2019).  

This study attempts to find the impact of firm reputation on firm financing decisions. For this purpose, we 

have employed a fixed effect model to run the regression throughout 2010-2019 by considering the 

nonfinancial sector of Pakistan. The statistical findings describe that the firm reputation is the significant 

determinant of the firm financing pattern. More specifically, there is a significant and negative liaison between 

firm age and firm financial leverage. However, there is a significant and positive link between price earnings 

ratio and decisions regarding firm financing. In brief, firm reputation plays an essential role in firm financing 

decisions. It has a very important role in firm financing decisions. Moreover, the firms do not include the firm 

reputation in the form of tangible financial benefit and cannot take rational decisions about firm financing and 

thus bear high cost of financing and the problem of stringent covenants. By keeping the view of this, this 

study has identified the impact of firm reputation on firm financing decisions. The arrangement of the 

variables has never been arranged before in the prior literature.  

The section two highlights review of literature, theory and theorization, and theoretical framework. The 

section three discusses data, methodology, econometric equations, and variable specifications. The section 

four reports results in the Tables i.e., descriptive statistics, correlation analysis, and regression analysis. 

Similarly, Section five explains the reported results. 

The section six depicts conclusion and policy recommendations.  

Literature Review  

The firm reputation is generally defined as the observations, emotions and feelings of multiple stakeholders 

about an organization (Fombrun et al., 1997).  The well reputed firms can accept more debt at lower costs 

because of their better reputations in the debt market. The work of Kaur and Sing (2018) used firm reputation 

as an independent variable in their study. Most organizations use the importance of good corporate reputation 



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through building a thought in the minds of stakeholders when they face an emergent situation (Fombrun et 

al., 1997). The corporate reputation describes stakeholder’s hopes and future actions of an organization which 

occurred from past experience and perceptions. Being trustworthy, a firm reputation can help to reduce the 

transaction cost. In this competitive era, firm reputation is an essential part of every business. According to 

our knowledge, there is a vast discussion of firm reputation practically but in literature, firm reputation is 

discussed a little bit. Previous literature has conducted studies on different topics i.e., Kaur and Singh, (2018) 

worked on the topic “measuring the immeasurable corporate reputation”. Pfister (2019) worked on the topic 

“Corporate reputation and the future cost of equity”. Anginer (2015) also worked on the topic “Firm reputation 

and cost of debt capital”. Chandler et al.(2013) described a positive relationship between firm reputation and 

status on inter organizational network structure. In contrast to common, there are few studies which have 

taken a firm reputation as a helping hand of financing. Moreover, limited studies have taken the firm reputation 

as critical assets and instruments of financing. So, to eliminate the gap, this research will find out the 

connection between firm reputation and firm financing decisions.       

The firm reputation is measured with different proxies. The research of Kaur and Singh, (2018) used several 

proxies (price earnings ratio, market capitalization and firm age) to represent firm reputation. The work of 

Chandler et al. (2013) showed financial soundness and long-term investment as proxies of firm reputation. 

The prior studies used these proxies i.e., price earnings ratio, market capitalization, firm age and longterm 

investment. The Fortune magazine categorized firms on the basis of these proxies (firm age, market cap, long-

term investment and price-toearnings ratio). The study of Rashid (2014) used financial leverage as an external 

financing decision which is considered as a dependent variable and furthermore discussed that the external 

source of financing is firm financial leverage. Ferrando et al. (2013) examined that the other external source 

of financing is equity financing and trade-credit, and it is an important secondary source of external financing. 

The finance managers give preference to other techniques that help to decide how, where, and when, to get 

finance to meet investment (Bei & Wijewardana, 2012). The reputation of the firm shows a very important 

role in firm financing decisions, and it mitigates agency problems between principal and agent. Cao et al. 

(2015) documented adverse affiliation between firm reputation and the equity cost. The high reputations 

companies have minimum chances to error their financial annual statements. They agree to pay high audit 

fees and produce higher quality financial statements. Karpoff at el. (2008) documented that high reputed firms 

avoid deceitful behaviour and thus have low cost of borrowing. The opinion and perception about a company 

is shaped on behalf of prior experience with the company, peer views, media coverage of a company, 

predictor’s comments and professional opinions about the company. The price-earnings ratio is an assessment 

method which prescribes the company’s existing financial position and informs about the company's 

upcoming growth prospects. Afza and Tahir (2012) examined that firm financial leverage is positively 

associated with price earnings ratio. There is a positive effect of financial leverage on price earnings ratio 

(Arslan et al., 2017). Investors are willing to invest and feel positive to invest their funds in high price earnings 

ratio companies.  

The firm reputation (measured by Fortune’s reputation ratings) to be a significant factor in explaining 

variation in price-earning ratio. The two firms are parallel in all aspects and steps but they show several 

priceearnings ratios because variance in price-earning ratio was due to the control of some unique, inimitable, 

non-substitutable resources by the company and those resources revealing a high price-earning ratio. 

Therefore, it was decided that a good reputation firm ranking leads to high price-earning ratio (Little & Little, 

2000). Price-earnings ratio has been used as a determinant of firm reputation in Italy. The price-earnings ratio 

is adversely linked with financial leverage and firm size (Afza & Tahir, 2012). The study of Tai (2017) showed 

that the market capitalization has positive association with debt rate in capital structure. The high market 

capitalization or high market value is connected to a good reputation. The investors prefer the large 

capitalization companies because those companies are attractive, suitable, having minimum hazard and having 

more liquidity. These companies are estimated to show performance far better in the near future as they are 

temporary to the market risk, give more dividends to stakeholders, and assure safety and liquidity of funds 



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with a good outcome to investors (Kaur & Singh, 2018). There is a positive impact of market capitalization 

on capital structure (Tai, 2017).  

The previous findings showed that the market capitalization is a crucial determinant of firm reputation 

(McGuire et al., 1990). There is enough empirical and theoretical proof that associates market capitalization 

to firm reputation and due to good reputation, the firms finance their assets easily. It can be conferred that 

market capitalization is a proxy for firm reputation. The managers try to select a minimum cost of financing 

for gaining more profit and in this way the managers can maximize the capital structure by minimizing the 

cost of financing (Tang et al., 2012). Some companies raise the cash inflow by over producing the goods, due 

to this strategy the price per unit will decrease in the market (Fosu, 2013).  Parsons (2009) examined that it is 

not difficult for more tangibility firms to gain debt because they can easily use tangible assets as loan 

collateral. The relationship is not surprising between tangible assets and debt because mostly tangible assets 

may be used easily as loan collateral. Myers (1977) noted that the loan taking ability of a firm may affect the 

investment. The research of Singhania and Seth (2010) explored adverse affiliation of firm financial leverage 

with investment. There is a negative association between firm financial leverage and firm long-term 

investment. John and Muthusamy (2011) depicted significantly and positively the association of firm financial 

leverage with firm investment for greater growth firms.   

Hence, research assumes both positive and adverse association of firm financial leverage with firm long-term 

investment. Mukhtar et al. (2016) suggested firm financial leverage could have either negative or positive 

impact on long-term investment of firms. Verwijmeren and Derwall (2010) have shown that the employee 

well-being is positively affiliation with high credit ratings. There is an ambiguity between theoretically 

affiliation of firm capital structure and firm age. The age of the firm matters because with the passage of time 

mostly firms can stabilize themselves. There is a negative relation of firm age with short-term firm financing 

(Hall et al., 2004). There is significant and empirical evidence of firm age and firm financing relations. The 

study of Ezeoha and Botha (2012) found a significant relationship between firm age and financial leverage. 

The aged companies have better access to finance their assets and have good connections with money 

financiers who always keep focus on companies’ reputation and financial record. The size of the firm, 

tangibility of total assets, profitability, and age of the firm are positively associated to total leverage 

(Ikechukwu & Cyril, 2017). The study further found negative effect of firm age on firm financial leverage. 

Moreover, there is adverse and significant affiliation between age of the firm and SMEs financing. The firm 

age is significantly negatively related to the firm financial leverage. The study of Hall et al. (2004) noted that 

firm age is linked with short-term debt. The market capitalization is positively allied with the percentage of 

debt in capital structure because the developed stock market guides the investors that they can spread the 

investments and, in this way, they can mitigate the hazard and asymmetric info which resulted in minimum 

lending cost. This will request the owners of the firms’ for increasing debt usage in capital structure (Tai, 

2017).   

The study of Keshtkar (2012) used price-to-earnings ratio (PE) as a proxy of growth opportunities and showed 

an adverse affiliation between growth opportunities and firm financial leverage. The study concluded a 

negative relation between growth opportunities and short-term debt because high growth companies have high 

uncertainty and firms will not take high short-term debt. These studies have the same results i.e., (Myers, 

1977). There is an adverse link between price-earnings ratio and firm financial leverage. García- Terue et al., 

(2010) found that the larger firms with greater growth opportunities and big investment in assets, get more 

finance from their suppliers, where firms have substitute sources of funding. The investment is a positive 

element of new debt financing which depicts the positive link of long-term investment with debt financing. 

The market value has a positive and significant relationship with trade credit (Tai, 2017). Li et al. (2019) noted 

that account payable and price earnings ratio are significantly and positively correlated. The bigger firms, 

with larger development opportunities and greater investment in assets, acquire more investment from their 

suppliers (Teruel & Solano, 2010). The investment decision has a positive effect on financing decision with 

less uncertainty whether financing is short-term or long-term. The SMEs financing has adverse and significant 



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association with age of the firm. There is an adverse and significant connection between firm age and trade 

credit because aged firms have enough resources to finance their assets (Kim, 2016).  

The study of Nazir (2012) used market capitalization and size at the same time in the paper. Large size firms 

can acquire funds from creditors, and a positive mark is anticipated between size of the firm and firm financial 

leverage (Qureshi at al., 2012). According to pecking-order theory, the highly profitable company tends to 

minimize their exterior finance which gives indications of low bankruptcy risk to creditors (Sheikh, 2011). 

The liquidity presents the aptitude of a firm to complete their current liabilities after maturity. The undue 

amounts of current assets possessed by a firm would maybe escalate the probabilities of interior financing 

resulting in an association between firm financial leverage and liquidity (Qureshi at al., 2012). Additionally, 

the abundant liquidity has an important effect on the financial strength of a firm (Bei & Wijewardana, 2012). 

The large volume firms of tangible assets are more able to guarantee their assets to develop additional funds 

with minor hazards due to the investment portfolio which shrinks the risk of insolvency (Qureshi at al., 2012). 

Hence, a positive signal is projected between firm financial leverage and tangibility of total assets. This study 

develops hypotheses between dependent variable and independent variable which is given below.  

H1: There is significant association between firm reputation and firm financing decision.   

Theories and Theorization  

The capital structure theories are related to firm reputation and reputation explains the impact of firm 

reputation on firm financing decisions. The size of the firm is associated with firm financing via agency cost 

theory because large size firms need more information and this info minimizes information asymmetries, and 

it makes it possible to acquire funds from money lenders (Marete, 2015). The market capitalization is affiliated 

with firm financing via agency cost theory because in developing countries, development and an improvement 

in stock market helps the investors that they can diversify the investment. In this way they can reduce risk and 

information asymmetric and transaction cost (Tai, 2017). The profitability of a firm is negatively associated 

with firm financing because firm profitability increases then the ratio of debt decreases. The pecking order 

theory shows adverse association between firm financial leverage and firm profitability, which gives high 

preference to retained earnings. The similar results in Pakistani firms are also found by (Rahman, 2016). De 

Jong, (2008) examined that high tangibility firms give preference to debt financing over equity financing. 

According to agency cost theory, tangibility is used as loan guarantee, and it reduces the information 

asymmetries and clears the business matter which helps to get the debt easily. Trade-off and agency cost noted 

positive relationship between leverage and assets tangibility (Olakunle & Oni, 2014).  

Conceptual Framework    

This framework shows explanatory and expliained 

variables.  

Figure 1.  

Conceptual Framework  

Financial Leverage  

Trade-credit  

  

Data and Methodology  

A research methodology is the process of collecting 

and analysing the information to test the hypotheses. 

This study took 10 years of data from 2010 to 2019. The research size consists of 337 listed firms of the 

nonfinancial sector of Pakistan. The annual data were collected from Thomson Reuter DataStream and 

financial reports which were published by State Bank of Pakistan. Firms having missed financial information 

for five years were removed from final analysis. Data availability statement lies as1  

                                                 
1 Data Availability Statement  

Firm specific financial data that have been used in this study retrieved from The Statement Bank of Pakistan (official data site 
management by Government of Pakistan).  



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Methodology  

Panel data estimation technique was used because the sample consists of both time series and cross sectional. 

It removes the problem of multi-colinearity. The data were analysed by using the fixed effect model (FEM) 

due to possible problems of multi-co-linearity. The statistical test i.e., Hausman test signifies the implication 

of a fixed effect model. When there is a high variance among the variables, then the study goes to use a fixed 

effect model. Moreover, Anginer (2015) used the fixed effect model to check the regression between firm 

reputation and debt cost. To hypothetically analyse which test is more appropriate, two hypotheses were 

developed.  

H1: The fixed effect model is more suitable.  

H0: The random effect is more appropriate.  

Table 1  

Haussmann Test  

Test summary  Chi-sq. Statics  Chi-sq. df  Prob.  

Cross-section Chi-square 

Model(1)  
671.382078  189  0.000  

Cross-section Chi-square 

Model(2)  
690.874286  265  0.000  

Note. Authors own calculations  

As the probability value is less than 0.05 which nullifies the null hypothesis and accepts the alternate 

hypothesis that fixed effect model is more appropriate. So, both literature and empirical findings support that 

fixed effect models should be applied. Econometric equation between the variables can be expressed as    

𝑛�𝑛� 
𝑌�𝑌�𝑖�𝑖�𝑖�𝑖� =  𝛽�𝛽�° + 𝛽�𝛽�1 𝑋�𝑋�𝑖�𝑖�𝑖�𝑖� +∪𝑖�𝑖�𝑖�𝑖�                                                                              (1)  

𝑗�𝑗�=1 

Where, 𝛽�𝛽�1𝑋�𝑋�𝑖�𝑖�𝑖�𝑖� = Vector of IV, s. Yit= dependent variable             

𝐹�𝐹�𝐹�𝐹�𝑖�𝑖�𝑖�𝑖� = 𝛽�𝛽�° + 𝛽�𝛽�1𝑃�𝑃�𝑃�𝑃�𝑃�𝑃�𝑖�𝑖�𝑖�𝑖� + 𝛽�𝛽�2𝑀�𝑀�𝑀�𝑀�𝑖�𝑖�𝑖�𝑖� + 𝛽�𝛽�3𝐹�𝐹�𝐿�𝐿�𝐿�𝐿�𝑖�𝑖�𝑖�𝑖� + 

𝛽�𝛽�4𝐴�𝐴�𝐴�𝐴�𝑃�𝑃�𝑖�𝑖�𝑖�𝑖� + 𝛽�𝛽�5𝑆�𝑆�𝐿�𝐿�𝑆�𝑆�𝑃�𝑃�𝑖�𝑖�𝑖�𝑖�  

+ 𝛽�𝛽�6𝐿�𝐿�𝐿�𝐿�𝐴�𝐴�𝑖�𝑖�𝑖�𝑖� + 𝜀�𝜀�𝑖�𝑖�𝑖�𝑖�                                                                       (2)  

𝐿�𝐿�𝑀�𝑀�𝑖�𝑖�𝑖�𝑖� 
= 𝛽�𝛽�° + 𝛽�𝛽�1𝑃�𝑃�𝑃�𝑃�𝑃�𝑃�𝑖�𝑖�𝑖�𝑖� + 𝛽�𝛽�2𝑀�𝑀�𝑀�𝑀�𝑖�𝑖�𝑖�𝑖� + 𝛽�𝛽�3𝐹�𝐹�𝐿�𝐿�𝐿�𝐿�𝑖�𝑖�𝑖�𝑖� + 𝛽�𝛽�4𝐴�𝐴�𝐴�𝐴�𝑃�𝑃�𝑖�𝑖�𝑖�𝑖� 

+ 𝛽�𝛽�5𝑃�𝑃�𝑃�𝑃�𝑃�𝑃�𝐹�𝐹�𝑖�𝑖�𝑖�𝑖� + 𝛽�𝛽�6𝐹�𝐹�𝐿�𝐿�𝐿�𝐿�𝑖�𝑖�𝑖�𝑖�  

+ 𝜀�𝜀�𝑖�𝑖�𝑖�𝑖�                                                                                                                      (3)  

FL stands for financial leverage, and it is used as a dependent variable, TC represents trade credit, and it is 

also used as a dependent variable. PER means price earnings ratio and this is considered as an independent 

variable, MC shows market capitalization, LTI abbreviations as long-term investment. TTA shows tangibility 

of total assets, LIQ means liquidity, PROF represents profitability, and AGE describes firm age.    

Table 2  

Overview of Variables  

Variables name  
Used 

as  
Measurement  References  

Price earnings 

ratio  
IV  

Market price per share/ 

earnings per share  

(Kaur & Singh, 

2018)  

Market 

capitalization  
IV  

Market price * total number 

of shares outstanding  

(Kaur & Singh, 

2018)  

Long term 

investment  
IV  Log of LTI  

(Chandler et al. 

2013)  



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Firm age  IV  
Current year – incorporation 

year  
(Kaur, 2018)  

Firm size  CV  Log of total assets  (Alkhatib, 2012)  

Profitability  CV  
Net profit after tax/total 

assets  
(Alkhatib, 2012)  

Liquidity  CV  
Current assets/current 

liabilities  
(Alkhatib, 2012)  

Financial leverage  
DV  Total debt / total assets  (Gill, 2012)  

Variables name  
Used as  

Measurement  References  

Trade credit  DV  
Account payable/total 

assets  

(Ahmed, et al., 

2016)  

Tangibility of total 

assets   
CV  Fixed assets/total assets  (Alkhatib, 2012)  

Note. FL= financial leverage, TC= Trade-credit, LTI= Long-term investment, MC= Market cap, PER= Price-

earnings ratio, TTA= Tangibility of total assets, LIQ= Liquidity, PROF= Profitability Source: Previous  

Literature  

Results and Discussion Table 3  

Descriptive Statistics  

Variables  Mean  Median  Max  Min  Std. 

Dev.  

Skewness  Kurtosis  

FL  0.465  0.475  0.692  0.011  0.107  0.014  2.146  

TC  0.336  0.230  0.599  0.010  0.207  0.830  0.410  

LTI  7.384  7.602  10.18  4.000  1.475  -0.206  2.514  

MC  5.433  5.257  8.777  2.755  1.111  0.332  2.739  

AGE  35.66  30.00  138.0  3.000  18.80  1.640  4.704  

PER  2.816  2.524  7.389  0.108  0.082  0.548  2.429  

SIZE  6.512  6.454  8.743  4.715  0.196  0.291  3.228  

TTA  0.540  0.567  0.684  0.051  0.161  0.871  3.593  

LIQ  0.226  0.242  0.517  0.089  0.106  1.116  4.550  

PROF  0.035  0.035  0.824  -0.407  0.108  0.741  3.343  

Note. FL= Financial leverage, TC= Trade-credit, LTI= Long-term investment, MC= Market cap, PER= Price-

earnings ratio, TTA= Tangibility of total assets, LIQ= Liquidity, PROF= Profitability Source: Author owns 

calculation  

The descriptive statistics portrays the overall image of firm responses. These responses are in the form of 

mean, median, and standard deviation which have been discussed in Table 3. The mean value of financial 

leverage is 46.5 which shows about the average replies of the respondent firms. It also means that the average 

firms use 46.5 percent financial leverage to finance their assets. The median value of FL is 47.5 which means 

that mostly under analysis firms use 47.5 percent debt to finance their assets. This is good for the firms that 

use less debt, and they don’t have a lot of debt. The maximum value of FL is 69.2 and minimum value of FL 

is 1.1 percent which shows that there is a firm which uses 1.1 percent financial leverage to finance its assets, 

and this is good. The standard deviation value is 0.107 which shows the degree of variation from mean value. 



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The value of skewness and kurtosis is 0.014 and 2.14 which show that the data are in normal shape. The mean 

value of TC is 33.6 percent which shows that average firms use 33.6 percent trade credit to finance their assets 

for the firms because it’s below than 50 percent. The median value of TC is 23 percent which means that most 

firms use 33.6 percent of trade credit to finance their assets which is less than 50 percent and it's good. The 

maximum value is 59.9 percent and minimum value of TC is 1 percent which means that one firm uses 1 

percent trade credit. The value of standard deviation is 20.7 percent which means that the usage of trade credit 

can be increased 20.7 percent from mean value or 20.7 percent can be decreased from mean value. The value 

of skewness and kurtosis is 0.83 and 0.41 which show that the shape of the data is normal.   

Table 4  

Correlation Analysis  

Variables  FL  TC  LTI  MC  AGE  PER  SIZE  TTA  LIQ  PROF  

FL  -                

TC  -

0.31  

-              

LTI  0.41  -

0.21  

-            

MC  0.45  -

0.37  

-

0.16  

-          

AGE  -

0.41  

-

0.45  

0.54  0.20  -        

PER  -

0.64  

0.51  -

0.46  

0.11  0.47  -      

SIZE  0.59  -

0.10  

-

0.34  

0.22  0.37  0.21  -     

TTA  -

0.51  

0.23  0.24  -

0.34  

-

0.20  

0.32  -0.31  -      

LIQ  0.35  0.30  0.16  0.44  0.14  0.16  0.26  -

0.23  

-    

PROF  -

0.36  

-

0.40  

-

0.26  

-

0.27  

0.19  0.44  0.14  -

0.17  

0.10  -  

Note. FL= Financial leverage, TC= Trade-credit, LTI= Long-term investment, MC= Market cap, PER= Price-

earnings ratio, TTA= Tangibility of total assets, LIQ= Liquidity, PROF= Profitability Source: Author owns 

calculation   

This correlation analysis describes the strength of association among the variables. The values of variables 

show the correlation strength. The correlation value of TC is -0.310 which means that there is weak association 

of TC with FL, but TC has an inverse relationship which means that when trade-credit will increase then the 

financial leverage will decrease and viceversa. The LTI has correlation value 0.410 which means that there is 

moderate association of long-term investment with firm financial leverage. The correlation value of MC is 

0.450 which shows that there is moderate correlation with financial leverage. The correlation value of age is 

-0.410 which describes that there is 41 percent degree of association of AGE with FL and its inverse affiliation.   

Table 5   

Regression between Firm Reputation and Firm Financing Decision  

Model 1  Model 2  

 Coefficient  t  p  Coefficient  t  p  

Models  FL   TC   



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C  -0.662  -2.165  0.0311  0.158  0.313  0.754  

LTI  0.017  2.439  0.015  0.013  1.223  0.221  

MC  0.031  3.261  0.001  -0.022  -1.373  0.170  

AGE  -0.009  -3.370  0.000  -0.028  -5.572  0.000  

PER  0.008  1.913  0.056  0.001  0.138  0.889  

SIZE  0.179  3.468  0.000  0.173  2.084  0.037  

TTA  -0.007  -0.176  0.859  0.101  2.270  0.023  

LIQ  0.007  0.368  0.712  0.041  1.400  0.162  

PROF  -0.333  -4.770  0.000  0.209  1.534  0.125  

Adj. R2   0.714    0.398   

D.W  

statistics  

 
1.806  

  
1.587  

 

Prob. 

Fstat  

 
0.000  

  
0.000  

 

The regression shows the relationship between independent variables and dependent variables. It also briefs 

the nature of relationship between the explained and explanatory variables. The t-value of size is 3.46 which 

shows a positive and significant impact on financial leverage. Big firms may have minimum deviations in 

earnings which leads to financial leverage as good selection of financing (Baloch et al., 2015). The large firm 

needs more information which minimizes the information asymmetries in the market which indicates the 

possibility of obtaining resources from lenders (Marete, 2015). The t-value of long-term investment is 2.439 

which depicts a significant positive relationship with financial leverage. There is significant positive 

relationship long-term investment and leverage. The t-value of liquidity is 0.368 which describes 

insignificantly association between liquidity and firm financial leverage. The financial managers are worried 

about investment and do not consider liquidity in determining their capital structure (Rizki et al., 2018). The 

t-value of tangibility of total assets is 0.176 which shows insignificant relationship with financial leverage. It 

was also noted that tangibility of total assets is adversely associated with the firm financial leverage (Baloch 

et al., 2015).    

The t-value of market capitalization is 3.261 which shows significant and positive relationship with financial 

leverage (Tai, 2017). The t-value of price earnings ratio is 1.913 which describes significant and positive 

association with financial leverage (Tahir et al., 2017). This study hypothesized adverse affiliation between 

P/E ratio and firm financial leverage but according to results, there is positive affiliation between them. The 

cause behind this is that some managers are risk takers, and they believe in the agenda “High risk and high 

return”. The t-value of age is -3.379 which illustrates negatively significant affiliation between firm age and 

firm financial leverage. The t-value of profitability is -4.770 which depicts a significant and negative 

relationship with financial leverage (Rahman, 2016).  

The t-value of firm age is -5.572 which shows significant and negative associated with trade credit (Kim, 

2016). The t-value of firm size is 2.084 which is significantly positively related with trade-credit. The t-value 

of tangibility of total assets is 2.270 which examines positive and significant relation with trade credit 

financing (J.O & Olowoniyi, 2014). The t-value of profitability is 1.534 which means that there is insignificant 

relationship with trade-credit (Khan, 2018). The liquidity has 1.40 its t-value which shows insignificant 

relationship with trade credit. The value of Adj. R2 of model 1 is 71.40 which means that the dependent 

variable is 71.40 percent associated with independent variables. The value of Durbin-Watson Stat is 1.80 

which is greater than 1.7; it means that there is no serial correlation between the error terms and independent 

variables. The value of F-statistic is 0.000 which tells about the overall significance of the model. The value 

of adjusted R-squared of model 2 is 39.81 which explains that there is 39.81 percent affiliation among 



Bilal Wei (2022) 
 

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independent variables and dependent variables. The value of Durbin-Watson stat is 1.58 which shows that 

there is no serial correlation between the error terms. The value of F-statistic is 0.000 which shows the overall 

significance of the model.     

Conclusion and Policy Recommendations  

The study finds that how firm reputation relieves firm financing decisions. The corporate reputation is a non-

financial aspect, but it is linked with several types of business decisions. This study has demonstrated the 

affiliation of firm reputation with firm financing decisions. The outcomes point out that alternate hypothesis 

(H1) was accepted. The study signifies that there is significant affiliation between corporate reputation and 

firm financing decision. The well reputed firms fund their assets with economic financing and have easy 

access to financing institutions. The outcomes of the study answer all research questions by fulfilling the study 

gap. But there were some limitations which were time constraints and data shortage. Some companies missed 

information about variables from balance sheets and income statements. In future, the researchers can be 

conducted by taking all proxies of firm reputation of FMAC (Fortune Magazine’s Most Admired Companies) 

list and their effect on other business decisions i.e., investment and borrowing capacity.  The outcomes of the 

study mention financing policy for finance managers to ponder firm reputation when deciding about firm 

financing decisions. The results of research emphasised on cheap financing. Mostly, the firms in under-

developed areas need to consider their reputation while taking some crucial business decisions i.e., financing 

decisions. This research will help to use the firm reputation in monetary terms. Overall, the corporate 

reputation will help to diminish financing cost.  

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