This paper scrutinizes Determinants of Capital Structure: A study on some selected corporate firms in Bangladesh. We have taken 10 out of 37 listed companies of DSE dividing into two sectors i.e. Pharmaceuticals and chemicals and Tannery sector, five years data from 2013 to 2017 has been collected from respective annual reports. Total number of observations was 50. There are different factors that affect a firm's capital structure decision. We use leverage (D/E ratio) as dependent variable and independent variables are profitability, tangibility, tax, size, growth, non-debt tax shield (NDTS) and financial costs. By using Descriptive Statistical Analysis, Correlation Analysis and Regression Analysis tools we find that Tangibility, size, NDTS, and financial costs are positively related with leverage and Profitability, tax, and growth are negatively related with leverage. In our analysis we see profitability, tangibility of asset, growth and non-debt tax shield have significant association. So when we take capital structure decision of the above firms we should consider profitability, tangibility of asset, growth and non-debt tax shield because other independent variables are insignificant in the context of Bangladesh economy.
The purpose of this research was to empirically investigate the effect of capital structure on financial sustainability
of deposit-taking micro finance institutions (DTMs) in Kenya. The specific objectives were to determine the impact
of debt on the financial sustainability of DTMs in Kenya, to assess the influence of retained earnings on the financial
sustainability of DTMs in Kenya, to examine the effect of ordinary share capital on the financial sustainability of
MFIs in Kenya, and to investigate the impact of preferred share capital on the financial sustainability of DTMs in
Kenya. The target population of the study was all the 13 DTMs in Kenya registered with the Central Bank of Kenya.
Secondary data was collected on all the DTMs financial data from the Central Bank of Kenya reports. Data was
analyzed using multiple regression model using SPSS and R as the data analysis tool. Based on the findings 76.9%
of the DTMs did not earn enough revenue to cover the actual financing direct costs, which include the total operating
costs, loan loss provisions and the financing costs but excluding the cost of capital. The analysis of variance
(ANOVA) table indicated that the predictor variables influenced the predictor variable significantly at 5%
significance level. Among the four variables; debt and retained earnings were statistically significant variable at 5%
significance level with 1.265 and 1.630 coefficient respectfully. Whereby the financial sustainability change by
1.265 and 1.630 for every unit change of debt or retained earnings respectfully. Therefore, for the deposit-taking
microfinance institutions to remain afloat in the lending business, they should utilize any borrowing opportunity,
plough back profits to the business, and low proportion of preferred share capital. Deposit-taking microfinance
institutions should avoid usage ordinary share capital as it negatively affected financial sustainability
This paper scrutinizes Determinants of Capital Structure: A study on some selected corporate firms in Bangladesh. We have taken 10 out of 37 listed companies of DSE dividing into two sectors i.e. Pharmaceuticals and chemicals and Tannery sector, five years data from 2013 to 2017 has been collected from respective annual reports. Total number of observations was 50. There are different factors that affect a firm's capital structure decision. We use leverage (D/E ratio) as dependent variable and independent variables are profitability, tangibility, tax, size, growth, non-debt tax shield (NDTS) and financial costs. By using Descriptive Statistical Analysis, Correlation Analysis and Regression Analysis tools we find that Tangibility, size, NDTS, and financial costs are positively related with leverage and Profitability, tax, and growth are negatively related with leverage. In our analysis we see profitability, tangibility of asset, growth and non-debt tax shield have significant association. So when we take capital structure decision of the above firms we should consider profitability, tangibility of asset, growth and non-debt tax shield because other independent variables are insignificant in the context of Bangladesh economy.
The purpose of this research was to empirically investigate the effect of capital structure on financial sustainability
of deposit-taking micro finance institutions (DTMs) in Kenya. The specific objectives were to determine the impact
of debt on the financial sustainability of DTMs in Kenya, to assess the influence of retained earnings on the financial
sustainability of DTMs in Kenya, to examine the effect of ordinary share capital on the financial sustainability of
MFIs in Kenya, and to investigate the impact of preferred share capital on the financial sustainability of DTMs in
Kenya. The target population of the study was all the 13 DTMs in Kenya registered with the Central Bank of Kenya.
Secondary data was collected on all the DTMs financial data from the Central Bank of Kenya reports. Data was
analyzed using multiple regression model using SPSS and R as the data analysis tool. Based on the findings 76.9%
of the DTMs did not earn enough revenue to cover the actual financing direct costs, which include the total operating
costs, loan loss provisions and the financing costs but excluding the cost of capital. The analysis of variance
(ANOVA) table indicated that the predictor variables influenced the predictor variable significantly at 5%
significance level. Among the four variables; debt and retained earnings were statistically significant variable at 5%
significance level with 1.265 and 1.630 coefficient respectfully. Whereby the financial sustainability change by
1.265 and 1.630 for every unit change of debt or retained earnings respectfully. Therefore, for the deposit-taking
microfinance institutions to remain afloat in the lending business, they should utilize any borrowing opportunity,
plough back profits to the business, and low proportion of preferred share capital. Deposit-taking microfinance
institutions should avoid usage ordinary share capital as it negatively affected financial sustainability
This report is aimed at finding the relationship between the net income and the current asset, current liability, working capital, debt ratio, current ratio, quick ratio, taking cement companies of Bangladesh into consideration. It overviews some theoretical literature on these financial factors and presents the regression outputs and their interpretation.
The findings of the study are:
1. Position of the various financial performances of these companies.
2. The regression output has components:
o Regression statistics table
o Correlation table
o Model summery
o ANOVA table
o Regression coefficients table
o Excluded Variables table.
3. And their interpretation.
Quantitative data is taken from company’s annual reports, business research companies’ archives and financial websites. The findings from the study can either have a positive or negative impact on financial performance.
The aims of the paper are to study the financial performance between the independent finance companies and the
integrated finance companies over the period 2001-2011.
The Effect of Capital Structure on Company's PerformanceHendra Gunawan
The research determine the effect of capital structure on company performance. The population in this study is the Indonesian Stock Exchange listed company. The final sample was obtained 756 companies over three years. The sample was selected using purposive sampling technique with some criteria. The independent variable measured of capital structure with long term debt and short term debt and dependent variable measured of company performance with ROA and ROE. Research hypotheses were tested by multiple linear regression analysis. Based on test results, it was found that the long term debt and short term debt has a significant to company performance. The limitations of this research was only three years the company's data, does not include other variables that have a significant effect the dependent variable.
Determinants of Capital Structure in Indonesian Banking Sector inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
The Impact of Capital Structure on the Performance of Industrial Commodity an...IJEAB
This paper investigates the impact of capital structure on the performance of commodity and service firms listed on the Vietnamese Stock Exchange. Data used in the paper were collected from the 142 firms listed on Ho Chi Minh and Ha Noi Stock Exchange during time 2009-2015. By using the descriptive statistics and linear regression model, the findings shows that there is negative relationship between capital structure (e.i. STD. LTD and DA) and peformance of the firms (i.e. ROE) for the commodity and services firms listed on two given Stock Exchange Market of Vietnam. Following are possible implications for the study.
A Comparative Analysis of Capital Structure between Banking and Non-Banking F...iosrjce
This research aims to compare the capital structure of Bangladeshi banking and non-banking
financial institutions through some measurements. The annual financial statements of 10 commercial banks and
10 non-bank financial institutions were used for this study which covers a period of five (5) years from 2009-
2013. The study assesses the capital structure of the banking and non-banking sectors measured by total debt
to equity ratio (DER), total debt to total funds ratio and performance by ROE, ROA, EPS.Descriptive statistics,
t-test have been used to show the differences between banking and non-banking capital structure and
performance. However this study concludes that there is no significant difference between Bank and non-bank’s
EPS but there is a significant difference between Bank and non-bank’s D/A ratio and D/E ratio and ROA and
ROE.
This paper analyzes the relationship between financial leverage and investment in the
Cameroonian context. To this end, using a sample of 1362 firms observed over the period 2015-2017, a
fixed-effect panel data instrumental variable regression model is estimated using the G2SLS method. The
results show that leverage positively influences investment. However, in the sample as a whole, and in the
individual SMEs, this relationship is not linear. It takes the form of an inverted "U". Specifically, at a low
level of debt, the relationship between financial leverage and corporate investment is positive. It becomes
negative at higher levels of leverage. Moreover, in turn, financial leverage is positively and significantly
determined by investment.
This report is aimed at finding the relationship between the net income and the current asset, current liability, working capital, debt ratio, current ratio, quick ratio, taking cement companies of Bangladesh into consideration. It overviews some theoretical literature on these financial factors and presents the regression outputs and their interpretation.
The findings of the study are:
1. Position of the various financial performances of these companies.
2. The regression output has components:
o Regression statistics table
o Correlation table
o Model summery
o ANOVA table
o Regression coefficients table
o Excluded Variables table.
3. And their interpretation.
Quantitative data is taken from company’s annual reports, business research companies’ archives and financial websites. The findings from the study can either have a positive or negative impact on financial performance.
The aims of the paper are to study the financial performance between the independent finance companies and the
integrated finance companies over the period 2001-2011.
The Effect of Capital Structure on Company's PerformanceHendra Gunawan
The research determine the effect of capital structure on company performance. The population in this study is the Indonesian Stock Exchange listed company. The final sample was obtained 756 companies over three years. The sample was selected using purposive sampling technique with some criteria. The independent variable measured of capital structure with long term debt and short term debt and dependent variable measured of company performance with ROA and ROE. Research hypotheses were tested by multiple linear regression analysis. Based on test results, it was found that the long term debt and short term debt has a significant to company performance. The limitations of this research was only three years the company's data, does not include other variables that have a significant effect the dependent variable.
Determinants of Capital Structure in Indonesian Banking Sector inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
The Impact of Capital Structure on the Performance of Industrial Commodity an...IJEAB
This paper investigates the impact of capital structure on the performance of commodity and service firms listed on the Vietnamese Stock Exchange. Data used in the paper were collected from the 142 firms listed on Ho Chi Minh and Ha Noi Stock Exchange during time 2009-2015. By using the descriptive statistics and linear regression model, the findings shows that there is negative relationship between capital structure (e.i. STD. LTD and DA) and peformance of the firms (i.e. ROE) for the commodity and services firms listed on two given Stock Exchange Market of Vietnam. Following are possible implications for the study.
A Comparative Analysis of Capital Structure between Banking and Non-Banking F...iosrjce
This research aims to compare the capital structure of Bangladeshi banking and non-banking
financial institutions through some measurements. The annual financial statements of 10 commercial banks and
10 non-bank financial institutions were used for this study which covers a period of five (5) years from 2009-
2013. The study assesses the capital structure of the banking and non-banking sectors measured by total debt
to equity ratio (DER), total debt to total funds ratio and performance by ROE, ROA, EPS.Descriptive statistics,
t-test have been used to show the differences between banking and non-banking capital structure and
performance. However this study concludes that there is no significant difference between Bank and non-bank’s
EPS but there is a significant difference between Bank and non-bank’s D/A ratio and D/E ratio and ROA and
ROE.
This paper analyzes the relationship between financial leverage and investment in the
Cameroonian context. To this end, using a sample of 1362 firms observed over the period 2015-2017, a
fixed-effect panel data instrumental variable regression model is estimated using the G2SLS method. The
results show that leverage positively influences investment. However, in the sample as a whole, and in the
individual SMEs, this relationship is not linear. It takes the form of an inverted "U". Specifically, at a low
level of debt, the relationship between financial leverage and corporate investment is positive. It becomes
negative at higher levels of leverage. Moreover, in turn, financial leverage is positively and significantly
determined by investment.
Study of the Static Trade-Off Theory determinants vis-à-vis Capital Structure...inventionjournals
This paper investigates the application of the Static Trade-Off theory regarding the capital structure of the Pakistani Chemical Industry. We have used panel data analysis for the sample of 31 listed chemical firms from the period 2005 to 2013. The study is unique in its type as unlike to Shah & Hijazi (2005) who studied many industrial sections, this study only focuses on the listed Chemical Firms. We used five independent variables such as Profitability (P), Tangibility (T), Liquidity (L), Firm Size (FS) and Total Assets Growth (TAG) to study the effect on independent variable Financial Leverage (FG). The results confirmed the relationship of Profitability, Liquidity and Firm Size. However the results were not confirmed for Tangibility and Firm Assets Growth. Even though the results for Tangibility were positive, however the significance of the coefficients failed to support the hypothesis. This study hold a unique position for researchers for future research and also has significance for the investors helping them to make wise investment decisions when investing in Pakistani Chemical Industry since this industry holds a major portion of industrial GDP of the country
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online
The Effect of Capital Structure on Profitability of Energy American Firms:inventionjournals
International Journal of Business and Management Invention (IJBMI) is an international journal intended for professionals and researchers in all fields of Business and Management. IJBMI publishes research articles and reviews within the whole field Business and Management, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This paper investigates the relationship between working capital management and financial performance of Pharmaceuticals and Textile firms listed at the Dhaka Securities Exchange in Bangladesh. The data analysis was carried on ten Pharmaceuticals and Textile firms for a period of 2013 to 2017. Secondary Data was analyzed by applying Descriptive Statistics, Regression and Correlation analysis to findthe relationship of current ratio, inventory conversion period and average payment period with Return on Asset. The findings indicate that the Pharmaceuticals and Textile firms’ performance is influenced by the variables relating to working capital. There is a positive relationship between profitability and current ratioand Inventory Turnover period shows a negative relationship with profitability but Average payment period shows insignificant impact on profitability. The study concludes that there exists a relationship between working capital managementand financial performance of Pharmaceuticals and Textile firms in Bangladesh. The study recommends that for the Pharmaceuticals and Textile firms to remain profitable, they should employ working capital management practice that will help in making decisions about investment mix and policy, matching investment to objective, asset allocation for institution and balancing risk against profitability.
An Empirical Analysis on the Nature of Relationship between Capital Structure...iosrjce
The financing decision with regard to capital structure theory of finance has been a topic of many
theories and their conflicting output for past many years. This paper aims to analyse the nature of relationship
between the capital structure of a firm and its performance. The data of 40 firms excluding financial services
firms listed on Nifty indices on National Stock Exchange is studied (The composition of 50 firms on Nifty
represents a well branch out index reflecting precisely the overall market conditions). Financial services firms
have been excluded from purview of this paper, as they are in the business of collecting money and investing in
financial assets rather than producing goods, hence follow a unique business valuation model. Further financial
services sector being one of the most sensitive sectors. This paper analyzes a period of 13 years (2001-2014)
covering the phases of a business cycle starting from boom (2001/02-2006/07), recession (2007/08-2008/09)
and then recovery (2009/10-2013/14). The complete business cycle will aid to demonstrate the results more
accurately. This paper also surveys the topical developments in the empirical capital structure research. The
data for a period of 13 years is analysed using descriptive statistics, correlation and multiple regression
techniques. For research purpose, the ratios such as debt-equity ratio, debt-asset ratio and long term debt are
taken as independent variables whereas Net Profit, Net Profit Margin, ROCE, ROE and ROA are the ratios
taken as dependent variables.
Turin Startup Ecosystem 2024 - Ricerca sulle Startup e il Sistema dell'Innov...Quotidiano Piemontese
Turin Startup Ecosystem 2024
Una ricerca de il Club degli Investitori, in collaborazione con ToTeM Torino Tech Map e con il supporto della ESCP Business School e di Growth Capital
Falcon stands out as a top-tier P2P Invoice Discounting platform in India, bridging esteemed blue-chip companies and eager investors. Our goal is to transform the investment landscape in India by establishing a comprehensive destination for borrowers and investors with diverse profiles and needs, all while minimizing risk. What sets Falcon apart is the elimination of intermediaries such as commercial banks and depository institutions, allowing investors to enjoy higher yields.
where can I find a legit pi merchant onlineDOT TECH
Yes. This is very easy what you need is a recommendation from someone who has successfully traded pi coins before with a merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi network coins and resell them to Investors looking forward to hold thousands of pi coins before the open mainnet.
I will leave the telegram contact of my personal pi merchant to trade with
@Pi_vendor_247
Introduction to Indian Financial System ()Avanish Goel
The financial system of a country is an important tool for economic development of the country, as it helps in creation of wealth by linking savings with investments.
It facilitates the flow of funds form the households (savers) to business firms (investors) to aid in wealth creation and development of both the parties
how can I sell pi coins after successfully completing KYCDOT TECH
Pi coins is not launched yet in any exchange 💱 this means it's not swappable, the current pi displaying on coin market cap is the iou version of pi. And you can learn all about that on my previous post.
RIGHT NOW THE ONLY WAY you can sell pi coins is through verified pi merchants. A pi merchant is someone who buys pi coins and resell them to exchanges and crypto whales. Looking forward to hold massive quantities of pi coins before the mainnet launch.
This is because pi network is not doing any pre-sale or ico offerings, the only way to get my coins is from buying from miners. So a merchant facilitates the transactions between the miners and these exchanges holding pi.
I and my friends has sold more than 6000 pi coins successfully with this method. I will be happy to share the contact of my personal pi merchant. The one i trade with, if you have your own merchant you can trade with them. For those who are new.
Message: @Pi_vendor_247 on telegram.
I wouldn't advise you selling all percentage of the pi coins. Leave at least a before so its a win win during open mainnet. Have a nice day pioneers ♥️
#kyc #mainnet #picoins #pi #sellpi #piwallet
#pinetwork
Poonawalla Fincorp and IndusInd Bank Introduce New Co-Branded Credit Cardnickysharmasucks
The unveiling of the IndusInd Bank Poonawalla Fincorp eLITE RuPay Platinum Credit Card marks a notable milestone in the Indian financial landscape, showcasing a successful partnership between two leading institutions, Poonawalla Fincorp and IndusInd Bank. This co-branded credit card not only offers users a plethora of benefits but also reflects a commitment to innovation and adaptation. With a focus on providing value-driven and customer-centric solutions, this launch represents more than just a new product—it signifies a step towards redefining the banking experience for millions. Promising convenience, rewards, and a touch of luxury in everyday financial transactions, this collaboration aims to cater to the evolving needs of customers and set new standards in the industry.
Empowering the Unbanked: The Vital Role of NBFCs in Promoting Financial Inclu...Vighnesh Shashtri
In India, financial inclusion remains a critical challenge, with a significant portion of the population still unbanked. Non-Banking Financial Companies (NBFCs) have emerged as key players in bridging this gap by providing financial services to those often overlooked by traditional banking institutions. This article delves into how NBFCs are fostering financial inclusion and empowering the unbanked.
how to sell pi coins effectively (from 50 - 100k pi)DOT TECH
Anywhere in the world, including Africa, America, and Europe, you can sell Pi Network Coins online and receive cash through online payment options.
Pi has not yet been launched on any exchange because we are currently using the confined Mainnet. The planned launch date for Pi is June 28, 2026.
Reselling to investors who want to hold until the mainnet launch in 2026 is currently the sole way to sell.
Consequently, right now. All you need to do is select the right pi network provider.
Who is a pi merchant?
An individual who buys coins from miners on the pi network and resells them to investors hoping to hang onto them until the mainnet is launched is known as a pi merchant.
debuts.
I'll provide you the Telegram username
@Pi_vendor_247
BYD SWOT Analysis and In-Depth Insights 2024.pptxmikemetalprod
Indepth analysis of the BYD 2024
BYD (Build Your Dreams) is a Chinese automaker and battery manufacturer that has snowballed over the past two decades to become a significant player in electric vehicles and global clean energy technology.
This SWOT analysis examines BYD's strengths, weaknesses, opportunities, and threats as it competes in the fast-changing automotive and energy storage industries.
Founded in 1995 and headquartered in Shenzhen, BYD started as a battery company before expanding into automobiles in the early 2000s.
Initially manufacturing gasoline-powered vehicles, BYD focused on plug-in hybrid and fully electric vehicles, leveraging its expertise in battery technology.
Today, BYD is the world’s largest electric vehicle manufacturer, delivering over 1.2 million electric cars globally. The company also produces electric buses, trucks, forklifts, and rail transit.
On the energy side, BYD is a major supplier of rechargeable batteries for cell phones, laptops, electric vehicles, and energy storage systems.
US Economic Outlook - Being Decided - M Capital Group August 2021.pdfpchutichetpong
The U.S. economy is continuing its impressive recovery from the COVID-19 pandemic and not slowing down despite re-occurring bumps. The U.S. savings rate reached its highest ever recorded level at 34% in April 2020 and Americans seem ready to spend. The sectors that had been hurt the most by the pandemic specifically reduced consumer spending, like retail, leisure, hospitality, and travel, are now experiencing massive growth in revenue and job openings.
Could this growth lead to a “Roaring Twenties”? As quickly as the U.S. economy contracted, experiencing a 9.1% drop in economic output relative to the business cycle in Q2 2020, the largest in recorded history, it has rebounded beyond expectations. This surprising growth seems to be fueled by the U.S. government’s aggressive fiscal and monetary policies, and an increase in consumer spending as mobility restrictions are lifted. Unemployment rates between June 2020 and June 2021 decreased by 5.2%, while the demand for labor is increasing, coupled with increasing wages to incentivize Americans to rejoin the labor force. Schools and businesses are expected to fully reopen soon. In parallel, vaccination rates across the country and the world continue to rise, with full vaccination rates of 50% and 14.8% respectively.
However, it is not completely smooth sailing from here. According to M Capital Group, the main risks that threaten the continued growth of the U.S. economy are inflation, unsettled trade relations, and another wave of Covid-19 mutations that could shut down the world again. Have we learned from the past year of COVID-19 and adapted our economy accordingly?
“In order for the U.S. economy to continue growing, whether there is another wave or not, the U.S. needs to focus on diversifying supply chains, supporting business investment, and maintaining consumer spending,” says Grace Feeley, a research analyst at M Capital Group.
While the economic indicators are positive, the risks are coming closer to manifesting and threatening such growth. The new variants spreading throughout the world, Delta, Lambda, and Gamma, are vaccine-resistant and muddy the predictions made about the economy and health of the country. These variants bring back the feeling of uncertainty that has wreaked havoc not only on the stock market but the mindset of people around the world. MCG provides unique insight on how to mitigate these risks to possibly ensure a bright economic future.
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
If you are looking for a pi coin investor. Then look no further because I have the right one he is a pi vendor (he buy and resell to whales in China). I met him on a crypto conference and ever since I and my friends have sold more than 10k pi coins to him And he bought all and still want more. I will drop his telegram handle below just send him a message.
@Pi_vendor_247
1. International Journal of Accounting and Financial Reporting
ISSN 2162-3082
2017, Vol. 7, No. 1
86
Capital Structure as Driving Force of Financial
Performance: Case of Energy and Fuel Sector of
Pakistan
Idrees Liaqat
MS Finance Scholar Riphah International University, Islamabad, Pakistan
Shamila Saddique
Huazhong University of Science and Technology, Wuhan, P.R. China
Tanveer Bagh
Independent Researcher, Pakistan
Muhammad Atif Khan
Department of Commerce, UMSIT Pakistan
Mirza Muhammad Naseer
MS Finance Scholar Riphah International University, Islamabad, Pakistan
Muhammad Asif Khan (Corresponding Author)
PhD Finance Scholar, School of Economics
Huazhong University of Science and Technology, Wuhan, 430074, P.R. China
E-mail: khanasif82@hotmail.com
Received: January 20, 2015 Accepted: February 18, 2017 Published: March 07, 2017
doi:10.5296/ijafr.v7i1.7722 URL: http://dx.doi.org/10.5296/ijafr.v7i1.7722
Abstract
Choosing the appropriate mix of various short and long-term sources of funds, stands among
2. International Journal of Accounting and Financial Reporting
ISSN 2162-3082
2017, Vol. 7, No. 1
87
the acute decisions to be taken by management of the firms to form elementary suitability for
investment and other decisions. Literature is lacking in consensus pertinent to impact of
capital structure on financial performance of the firms. This study intends to investigate the
impact of capital structure on financial performance of fuel and energy sector of Pakistan
taking into account secondary data from 2006-14. Empirical results of renowned econometric
model multiple regression revealed that there is a significant negative impact of capital
structure on ROA and ROE of firms in fuel & energy sector of Pakistan, while EPS is least
driven by capital structure parameters, only the size has significant positive bearing on EPS.
The research findings provide suggestions to policy makers and administrators to rely on
equity financing rather debt ethos in order to mitigate the default risk exposure.
Keywords: Capital structure, Financial performance, Multiple regression, Return on assets,
Return on equity, Earnings per share
1. Introduction
1.1 Background
Choosing the appropriate mix of various sources of short and long term funds, is among one
of the critical decision needs to be taken by governing body of an organization. Financing
decision serves as basis for investment decision and firm’s financial performance is greatly
affected by the proposition of financing mix. The mix of long-term financing termed as
Capital structure that got great importance after the seminal views of Miller and Modigliani
(MM). Prior to this study, organizations usually depend upon sole source of financing but
paradigm has shifted towards the appropriate combination of both the equity and debt capital
as each bears varying cost of acquiring and other considerations. Debt financing though least
costly because of tax exemption but subject to some obtaining constraints as well as expose
unit to default risk. Equity financing at other end is most relying source with high service
charges than debt, while creating challenges to administration due to voting rights, residual
claims and proxy fights.
Capital structure implies propositional bearing on firm’s financial performance of decision-
making units. Including debt as major part, magnify financial performance while equity
enhances solvency although it is comparatively costly. Cost reduction and assurance of
appropriate solvency have always been the key challenges to the organizations. Considering
this phenomena the study aims at exploring the magnitude by which capital structure drives
the financial performance.
The results of the study will extend the literature and expected to provide insight to many
organizations in developing their best fitted capital structures policies. Furthermore, the study
will assist the researchers and interested students in understanding the relationship of capital
structure with financial performance.
This study intends to investigate the impact of capital structure on financial performance of
fuel and energy sector of Pakistan.
3. International Journal of Accounting and Financial Reporting
ISSN 2162-3082
2017, Vol. 7, No. 1
88
2. Literature Review
The roots of capital structure theory refers to more than fifty decades back, since the seminal
work which presented by Modigliani and Miller (1958). They proved, under restrictive
assumptions (no taxes and transactions costs) that cost of capital does not effect on capital
structure, particularly debt then not effect on firm value where this theory called irrelevancy
preposition. In other words, the value of levered firm equals the value of unlevered firm.
Latterly Modigliani and Miller (1963) came with a new proof that cost of capital do effect on
any firms capital structure and therefor effect on the value of firm with assumption that
borrowing gives tax advantages. According to Brigham and Daves (2012) capital structure is
a way through which a firm finances its operations.
Holz (2002) examined that capital structure positively correlated with firm performance.
Berger and Patti (2002) concluded that the better a company’s operating performance the
higher the debt equity. Dessi and Robertson (2003) highlighted that financial leverage results
positively on the expected performance. They explained this result to that low growth firms
tries to depend on borrowing for utilizing expected growth opportunities and investing
borrowing money at the profitable projects. Mwangi (2010) proposed that there is a strong
positive relationship between leverage and ROE, liquidity, and return on investment. Nirajini
and Priya (2013) claimed that there is a significant positive relationship between capital
structure and financial performance.
Gleason, Mathur and Mathur (2000) came with the results that capital structure is negatively
co-related with financial performance. Majumdar and Ghosh (2007) reached the conclusion
that level debt (capital structure) affects negatively on firms performance. They describe that
creditor impose restrictions on firm as in distributing earnings among shareholders or
increasing interest rates imposing sufficient collaterals on loans, thus these restrictions will
lead firm to focus on how pay the burden of debt concerning in achieving earning and reflect
adversely on firm performance. Abor (2005) pointed that long-term debt associated
negatively and statistically with firm performance. The conclusion refers to that firms rely on
borrowing extremely, it will not achieve tax shields and then it lead to increase borrowing
cost of which the firm exposes to the bankruptcy risks and reduce the return. Zaitun and Tian
(2007) explored that capital structure puts negative impact of any firm’s financial
performance and if any firm underestimates to bankruptcy cost then it will force the firm to
borrow excessively and carry high debt in their capital structure. Ebaid (2009) deduced by
using regression model taking ROA, ROE, GPM as dependent proxies that capital structure is
negatively correlated with financial performance.
Azhagaiah and Gavoury (2011) narrated that too much debt in capital structure may result in
high gearing ratio, high risk of bankruptcy and may be worse for profit. Salim and Yadav
(2012) investigated by using multiple regression model that capital structure has a significant
negative relationship with financial performance. Marobhe (2014) narrates through using
regression model that there is a significant negative relation between capital structure and
ROA and weak relation with ROE and EPS. Mwangi, Makau and Kosimbei (2014) examined
that increased leverage results negatively in financial performance by using ROE as an
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accounting measure.
McConnell and Servaes (1995) reached at a decision that capital structure has a negative co-
relation with the performance of high growth firms while positive relationship with low
growth firms. Weill (2008) tested financial leverage’s effect on financial performance in
seven countries of Europe. He investigated that in Spain and Italy financial leverage has a
significant positive relation with financial performance while in Germany, France, Balgium,
and Norway is negatively co-related. Cheng, Liu and Chien (2010) suggested that when debt
ratio in capital structure is 53% to 70%, it puts positive impact on financial performance but
more than 70% contribution of debt relates capital structure with performance negatively.
After a long time, Li et al. (2008) reached at a decision that financial leverage has negative
impact on return on assets and positive on return on equity.
Thus we conclude that literature is contradicting and more evidence are desirable at this
proposition of capital structure and its bearings upon financial performance of manufacturing
sector of Pakistan.
3. Methodology
3.1 Model of the Study
ROA= β0 + β1LTD + β2T + β3S + β4TD + β5STD + €
ROE= β0 + β1LTD + β2T + β3S + β4TD + β5STD + €
EPS=β0 + β1LTD + β2T + β3S + β4TD + β5STD + €
Where, ROA= Return on assets; ROE = Return on equity; EPS =Earnings per share; LTD =
Long term debt; T =Tangibility; S=size; TD =Total debt and STD =Short term debt. In figure
1 relationship of IV and DV with respective proxies are portrayed. In our model Capital
Structure (CS) is independent variable having LTD, T, S, TD and STD its measures to
observe the relationship on dependent variable Financial Performance (FP) that is measured
through ROA, ROE and EPS.
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Figure 1 Graphical presentation of IV and DV with proxies
3.2 Significance of Model
Multiple regression model has been used to estimate the cause and effect relationship. This
model is a powerful technique through which impact on financial performance of capital
structure has been examined and used by many researchers like; Salim, 2012; Memon et al.,
2012; Salim, 2012; and Marobhe, 2014.
3.3 Population and Sample
The population of the study comprised upon all manufacturing sector companies listed with
Karachi stock exchange out of which 15 fuel and energy sector companies have accounted for
the sample on the basis of market capitalization and size.
3.4 Data Source and Analysis
The study used secondary data reported in audited annual financial statements of the sample
companies that is analyzed using inferential and descriptive statistics along with SPSS.
4. Results and Discussion
In this section the results of the study are discussed below.
4.1 Results of Correlation
Table 4.1 portrayed inter and intra relationship of all proxies. Return of asset has significant
positive relationship with Return on Equity, Earnings per Share and size but insignificant
positive relationship with tangibility. However, ROA is negatively significantly correlated
with short term debt and negatively insignificantly with long term debt and total debt. ROE is
positively significantly correlated with EPS. Earnings per share have positive significant
association with size. Long term debt has significant positive affiliation towards size, short
term debt and total debt while size reveals significant positive relationship with short term
and total debt. The strongest significant positive association is observed between short term
debt and total debt.
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4.2 Regression Analysis
This study was conducted to check the impact of capital structure on financial performance of
the firms in fuel and energy sector of Pakistan. The findings of the study are tabulated and
discussed below:
4.2.1 Econometrics for ROA
Following econometrics model for ROA was tested:
[ROA= β0 + β1LTD+ β2T+ β3S+ β4TD+ β5STD+€]
The results of econometrics model for ROA are reported in table 4.2 to 4.4 and indicate a
significant positive translation in ROA by translating proxies of capital structure as adjusted
R-square is .441 with significant P-value (.000) that infers 44% of financial performance of
the firms in the fuel and energy sector of Pakistan can be explained by capital structure.
Positive effect was reported for tangibility (1.825), size (6.561), long term debt (1.623), while
negative results for short term debt (-8.525) and total debt (-13.102). P-value size, short term
debt and total debt are within significant level range whereas, long term debt and tangibility
do no influence the financial performance (ROA).
4.2.2 Econometrics for ROE
The following model was used to check the impact of capital structure on ROE:
[ROE= β0 + β1LTD+ β2T+ β3S+ β4TD+ β5STD+€]
The findings of the model regarding ROE econometrics are respectively presented in table
4.5, 4.6 and 4.7, expressed positive but only 17 % change is translated by the model. The
positive effect was observed pertaining to size (7.823), tangibility (1.172), and total debt
while negative results for short term debt (-13,123) and long term debt. Adjusted R square is
.112 that indicates that 11% variability in dependent variable ROE is explained by the model.
P value in ANOVA table is .009 that signifies that model has predicting power to measure the
effect of size, tangibility, long term debt, short term debt ant total debt. In coefficient table, B
reports that one unit increase in long term debt brings negative -88.469 changes in ROE and P
value (.013) that is lesser than (.05) indicates a statistically significant Impact. Size brings a
positive change of 7.833 and its P value .02<.05 has a significant impact. Tangibility has
shown a positive impact of 1.172 but its P value .932 >.05 and has an insignificant impact.
One unit change in short term debt decrease ROE by 13.123 and corresponding P value is
.164 that is greater than .05 puts an insignificant impact. One unit increase in total debt has a
positive but it is statistically insignificant as its P value is greater than .05.
4.3 Econometrics for EPS
To examine the effect of capital structure on EPS below model was used.
[EPS= β0 + β1LTD+ β2T+ β3S+ β4TD+ β5STD+€]
The findings of the study about what impact capital structure has on EPS are discussed in
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table no. 4.8, 4.9 and 4.10 as under.
Adjusted R-square is .138 that shows that model has the predicting power to measure the
effect of independent variables on EPS as P-value is significant. In coefficients table under
un-standardized coefficients B value of long term debt shows that an increase of 1 unit in
long term debt decrease EPS by 4.50 and corresponding P-value is .80>.05. If we look at size
it positively increases in EPS and its P-value is 000 that is statistically significant.
5. Conclusion and Recommendations
5.1 Conclusion
The study has concluded that there is a significant negative impact of capital structure on
ROA of firms in fuel & energy sector of Pakistan that is consistent to the Salim (2012);
Zingales (1995); and Abor (2005) findings that capital structure has significant negative
impact on ROA. From ROE equity point of view capital structure also has significant
negative impact on it as long term debt and short term debt decreases the financial
performance. Refer to capital structure and EPS only the size has positive impact on it while
rest of the independent proxies place insignificant impact. Aggregately capital structure
poses significant negative impact upon two major proxies of financial performance that
negates the research findings of Ross (1977); and Holz (2002) which claimed that capital
structure has positive impact on financial performance.
5.2 Policy Recommendations
Debt does not always result in an improvement in financial performance. Our findings are
least supportive to debt financing ethos. It has many complications like; openness to default
risk; high service charges; and adverse impact upon financial performance. It creates agency
problems between stockholders and creditors. This study suggests that Pakistan fuel and
energy sector firms may prefer internal financing rather than increasing more leverage in
capital structure that consumes high cost of capital because of default risk. Equity financing
also safeguards firms from bankruptcy to great extent.
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Appendices
Table 4.1 Correlations
Return
on
Assets
Return
on
Equity
Earnings
Per Share
Long
Term
Debt Size
Tangibili
ty
Short
Term
Debt
Total
Debt
Return
on
Assets
Pearson
Correlation
1 .441**
.594**
-.051 .449**
.027 -.368**
-.156
Sig. (2-tailed) .000 .000 .560 .000 .753 .000 .072
N 134 134 134 134 134 134 134 134
Return
on
Equity
Pearson
Correlation
1 .329**
-.212*
.156 -.036 -.151 -.078
Sig. (2-tailed) .000 .014 .071 .676 .082 .371
N 134 134 134 134 134 134 134
Earning
s Per
Share
Pearson
Correlation
1 -.113 .269**
.010 -.199*
-.117
Sig. (2-tailed) .195 .002 .910 .021 .179
N 134 134 134 134 134 134
Long
Term
Debt
Pearson
Correlation
1 .273**
.145 .325**
.557**
Sig. (2-tailed) .001 .094 .000 .000
N 134 134 134 134 134
Size Pearson
Correlation
1 .054 .236**
.502**
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Sig. (2-tailed) .534 .006 .000
N 134 134 134 134
Tangibil
ity
Pearson
Correlation
1 .113 .011
Sig. (2-tailed) .193 .902
N 134 134 134
Short
Term
Debt
Pearson
Correlation
1 .698**
Sig. (2-tailed) .000
N 134 134
Total
Debt
Pearson
Correlation
1
Sig. (2-tailed)
N 134
**. Correlation is significant at the 0.01 level
(2-tailed).
*. Correlation is significant at the 0.05 level (2-
tailed).
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Table 4.2 Model Summary
Model R
R
Square
Adjusted
R Square
Std. Error of
the Estimate
Change Statistics
R Square
Change F Change df1 df2 Sig. F Change
1 .680a
.462 .441 14.23406 .462 21.990 5 128 .000
a. Predictors: (Constant), Total Debt, Tangibility, Size, Long Term Debt,
Short Term Debt
Table 4.3 ANOVAb
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression 22276.616 5 4455.323 21.990 .000a
Residual 25933.896 128 202.609
Total 48210.512 133
a. Predictors: (Constant), Total Debt, Tangibility, Size, Long Term Debt, Short
Term Debt
b. Dependent Variable: Return on Assets
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Table 4.4 Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) -25.072 4.821 -5.201 .000
Long Term
Debt
1.825 8.205 .018 .222 .824
Size 6.561 .777 .647 8.444 .000
Tangibility 1.623 3.232 .034 .502 .616
Short Term
Debt
-8.525 2.200 -.365 -3.876 .000
Total Debt -13.102 6.559 -.236 -1.997 .048
a. Dependent Variable: Return on Assets
Table 4.5 Model Summary
Model R
R
Square
Adjuste
d R
Square
Std. Error
of the
Estimate
Change Statistics
R Square
Change F Change df1 df2 Sig. F Change
1 .334a
.112 .077 60.65584 .112 3.216 5 128 .009
a. Predictors: (Constant), Total Debt, Tangibility, Size, Long Term Debt,
Short Term Debt
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Table 4.6 ANOVAb
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression 59165.302 5 11833.060 3.216 .009a
Residual 470928.696 128 3679.130
Total 530093.998 133
a. Predictors: (Constant), Total Debt, Tangibility, Size, Long Term Debt, Short
Term Debt
b. Dependent Variable: Return on Equity
Table 4.7 Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) -22.875 20.543 -1.113 .268
Long Term
Debt
-88.469 34.964 -.260 -2.530 .013
Size 7.823 3.311 .233 2.363 .020
Tangibility 1.172 13.774 .007 .085 .932
Short Term
Debt
-13.123 9.373 -.170 -1.400 .164
Total Debt 12.649 27.952 .069 .453 .652
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Table 4.6 ANOVAb
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression 59165.302 5 11833.060 3.216 .009a
Residual 470928.696 128 3679.130
Total 530093.998 133
a. Predictors: (Constant), Total Debt, Tangibility, Size, Long Term Debt, Short
Term Debt
a. Dependent Variable: Return on Equity
Table 4.8 Model Summary
Model R
R
Square
Adjusted R
Square
Std. Error of
the Estimate
Change Statistics
R Square
Change
F
Change df1 df2 Sig. F Change
1 .413a
.171 .139 9.35640 .171 5.277 5 128 .000
a. Predictors: (Constant), Total Debt, Tangibility, Size, Long Term Debt,
Short Term Debt
Table 4.9 ANOVAb
Model
Sum of
Squares df
Mean
Square F Sig.
1 Regression 2309.810 5 461.962 5.277 .000a
Residual 11205.407 128 87.542
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Total 13515.217 133
a. Predictors: (Constant), Total Debt, Tangibility, Size, Long Term Debt, Short
Term Debt
b. Dependent Variable: Earnings Per Share
Table 4.10 Coefficientsa
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) -5.572 3.169 -1.758 .081
Long Term
Debt
-4.501 5.393 -.083 -.834 .406
Size 2.217 .511 .413 4.340 .000
Tangibility .471 2.125 .018 .222 .825
Short Term
Debt
-1.867 1.446 -.151 -1.292 .199
Total Debt -5.070 4.312 -.173 -1.176 .242
a. Dependent Variable: Earnings Per Share
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