Dr. Manisha Goel^{ }, ^{}
Associate Professor, Department of Management Studies,
J. C. Bose University of Science and Technology, YMCA
Faridabad, Haryana, India.
Ruchi Mangla,
Research scholar,
Department of Management Studies,
J. C. Bose
University of Science and Technology, YMCA
Faridabad,
Haryana, India
Abstract
With the privatization and entry of
private banks in this sector, the banking scenario is changing. Banks are also
under the pressure to pay dividend to their shareholders. In this scenario, it
becomes very important to know if there is any difference in dividend paid by
nationalised banks and private banks. In this study efforts have been made to
find out the impact of financial leverage on dividend paid by private banks in
India. This is a quantitative research in which the relationships have been
developed in the form of statistical model. A co relational research design has
been adopted to find out whether there exists any corelation between dividend
and financial leverage of private banks in India or not.
Keywords: Financial
Leverage, Dividend, Earnings, Corelation, Linear Regression, Non linear
Regression
Introduction
Dividend policy is defined as the set of instructions a
company follows to decide the share of the earnings of the company to be paid
out to its shareholders as dividends (Aggarwal 2013). It is the policy of distributing the earnings of the
company among the shareholders with respect to the ownership they possess in
the company. There is an inverse relationship between the retained earnings and
the dividend paid to shareholders. So the decision involves the choosing
between distributing the profits earned to the shareholders and keeping them
back with the company for further investment. Financial leverage can be used by
a firm to alter the cash flows and the position of the firm in the market. A little
leverage is required for funding the business as the debts are not taxed, so
using apropriate amount of debts lowers the overall cost of the borrowing as
the rate on return compensates for the funds borrowed. The fixed compensation
linked with the earnings of the company leads to the financial leverage of the
firm, through the usage of funds that the company has borrowed at a fixed cost
to attain profits in the future (KHAN, n.d.).
Financial leverage is related to the extent to which business
utilizes borrowed money for the business, indicating the existence of debt in
the capital structure of the company. The estimation of financial leverage is
usually expressed in terms of book values or market values. The present
attitude of shareholders is depicted by market values in a more suitable way.
The most accepted way to measure the financial leverage in firms and banks is
debt to equity ratio. Financial leverage increases the risk quotient of the
firm, due to which the firm pays out less dividends to its investors and
retains a higher portion of the profits to reinvest in the investment projects
that would eventually decrease the debts of the company, so making the dividend
payouts lesser in value. Banking sector in India has undergone major growth in
multiple areas. Banks help various sectors of the economy to become more
profitable and productive which in turn demands the need of a stronger and
sustainable banking industry. The present study is aimed to study the impact of
financial leverage on dividend paid by private banks in India.
Literature Review
Many studies have included leverage as one of the
determinants of dividend. There are very few studies available which explore
the impact of financial leverage on dividend of private banks in India.
Uwuigbe (2013)
attempted to examine the effect of financial leverage and ownership structure
on dividend payment by Nigerian firms. He used the judgemental sample of 50
companies from Nigerian Stock Exchange. Using regression analysis he observed a
negative relationship of financial leverage and dividend payout while positive
between ownership structure and dividend payout. More over the negative impact
of financial leverage was quite significant in Nigerian firms.
Tamimi et al. (2014) in their research investigated the
impact of age and financial leverage on dividend policies of manufacturing
firms which have been listed on Tehran Stock Exchange over the period from 20052011. They used the systematic sample of 92
companies. For the manufacturing companies of Tehran they found a significant
but negative relationship between financial leverage and dividend payment.
Ikechukwu et al. (2015) assessed the 9 Nigerian
conglomerates for their impact of financial leverage on dividend policy. They
used the panel data for the period 20102015. The study was based majorly on
consumer goods firms. They concluded that leverage measured by short term debt,
long term debt and total debt had a significant effect on DPS, dividend payout
ratio and dividend yield , thus having an overall impact on dividend policy.
Most of these
researches showed that there exist a relationship between financial leverage
and dividend payment. As far as the impact is concerned few of the researchers
found a positive impact of financial leverage on dividend(Mayer and Bacon,2004;
Alam and Hosain,2012; Gul et al.,2012), some other found a negative impact
(Kumar,2003; AlMalkawi,2007; Kuwari,2009; Moradi et al.2010; Alam and Hosain,2012)
while few of them found it to be insignificant (Ben Naceur,2006; Rafique,2012).
In totality there was no consensus as to the impact of financial leverage.
Gupta (2012) examined
the selected private and public sector banks in India and measured the effect
of financial leverage on these selected banks. This study has been carried over
the period from 2007 to 2011. For analysing the results, the balance sheets of
the respective banks were observed and also the effects of leverage ratio were
deduced from the same. It has been observed that the financial leverage in the
commercial banks did not experience a rise in consecutive years following the
year 2007 rather showed a decline in this area. Whereas, the government banks
in the country showed a stable leverage ratio over the years and also
experienced a movement towards an increased financial leverage ratio within the
banks. On the other hand, public sector banks experienced a decline in the
owner funds which were measured as a percentage of total sources of public and
private sector banks, whereas on the other side, the commercial banks showcased
a significant increase in the funds of the owners in the bank. The fixed asset
turnover ratio has been also estimated for the public and private sector banks
from 2007 to 2011 and it has been found that fixed assets turnover ratio
increased in both the sectors of the banks but with the public sector
experiencing a higher turnover of the fixed assets compared to that
experienced by the commercial banks in the country.
Another research (Sri Hari et al., 2012) concluded that
nationalised sector banks paid more dividends than private sector banks.
Research Design
The present study is quantitative in nature to analyze
the properties of the past records of 15 years related to financial leverage
and dividend of private banks in India and to make predictions for the future
by developing mathematical models. The values for the years where banks have
paid no dividend have been ignored. Inferences have been drawn from the values
collected for 15 scheduled private Indian banks which have been listed on
Bombay stock Exchange as on 2012. The focus of the study has been to explore the
effect of financial leverage and earnings on dividend of private banks.
Correlation and regression models have been developed for the leverage and
dividend of private commercial banks in India. Analysis has been performed with
the help of the software i. e. Microsoft Excel 2007 and SPSS 21.0.
Data Analysis and Interpretation:
The regression has been used as a tool to find out the
impact of financial leverage on DPS of scheduled private banks in India. Taking
DPS as a dependent variable and financial leverage as independent variable, the
regression has been run been on data.
IMPACT OF FINANCIAL LEVERAGE ON EQUITY
DIVIDEND OF PRIVATE INDIAN BANKS
To find out the impact of financial leverage on DPS of
banks in India regression has been used as a tool.
LINEAR REGRESSION OF DPS AND FL FOR
PRIVATE INDIAN BANKS
The linear regression was run the data
related to private Indian banks to find out the impact.
Table 1 Regression of DPS and FL of
Private Banks

DPS 
Financial Leverage 

Pearson Correlation 
DPS 
1.000 
.164 
Financial Leverage 
.164 
1.000 

Sig. (1tailed) 
DPS 
. 
.031 
Financial Leverage 
.031 
. 
Table 2
Model Summary of Regression of
DPS and FL of Private Banks
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
DurbinWatson 
.164^{b} 
.027 
.019 
9.06857 
.499 
Table 3 Coefficients of DPS and FL of
Private Banks

Unstandardized Coefficients 
Standardized Coefficients 
t 
Sig. 

B 
Std. Error 
Beta 


(Constant) 
13.573 
2.539 

5.345 
.000 
Financial
Leverage 
.404 
.215 
.164 
1.876 
.063 
From the above tables it has been observed that
the relationship between DPS and Financial Leverage of private Indian banks is
significantly negative. Financial
Leverage has a negative impact on DPS i.e. with the increase in financial
leverage, DPS decreases in case of private Indian banks. The regression
coefficient is 0.404 with a constant of 13.573.
REGRESSION MODEL
With the help of coefficients the regression
model can be written as
DPS = 13.573  0.404(Financial
Leverage)
As the value of^{ }R^{2} is 0.027, it means that only 3% of Variations in
DPS are explained by financial leverage for private Indian banks which is very
low. Since the p value is less than 0.05 the null hypothesis that there is no
significant impact of financial leverage on equity dividend of private Indian
banks, has been rejected and it is found that there is significant impact of
financial leverage on equity dividend of private Indian banks.
VALIDITY OF REGRESSION RESULTS FOR DPS AND FL
OF PRIVATE INDIAN BANKS
Before we reach any conclusion regarding this
model it is necessary to check the validity of regression results. To check
validity of regression results few basic assumptions of classic linear
regression model are checked with . tests of linearity, normality, stationarity,
auto collinearity and homoscedasticity.
a)
Assumption of Linearity
This has been checked with the help of
Scatter diagram. The scatter diagram of the above said data is represented in
figure 1.
Figure 1
Scatter Plot of DPS and FL for Private
banks
As there are number of outliers present, it
has been observed that the relationship is not linear between Financial
Leverage and DPS of private Indian banks.
b)
Assumption of Normality
ShapiroWilk test along with QQ plot has
been used to test the normality of data.
i.
ShapiroWilk Test
the results of the test are as below:
ii.
Table 4 Test of Normality of DPS and FL
of Private Banks

KolmogorovSmirnov^{b} 
ShapiroWilk 

Statistic 
df 
Sig. 
Statistic 
Df 
Sig. 

DPS 
.178 
129 
.000 
.779 
129 
.000 
Financial Leverage 
.065 
129 
.200^{*} 
.986 
129 
.202 
As we are able to see that level of
Significance for ShapiroWilk test for DPS
is below 0.05, so the data don’t hold the assumption of normality and
regression results of the data which is not normal, are not valid.
iii.
QQ Plot –On the observation of the data of FL on QQ plots, it
is found that it is quite along the
expected line but this is not the case of DPS.
Figure
2 QQ plot of DPS of
Private Banks
Figure 3 QQ plot of FL of
Private Banks
c)
Assumption of Stationarity and auto
correlation
Stationarity
has been checked using auto correlation test in SPSS and DurbinWatson
statistics.
i.
Autocorrelation test Auto correlation
test results show that data is not stationary
Figure 4 ACF Chart of FL of private Figure 5 ACF Chart of DPS of Private
ii.
Durbin –Watson Statistics
As per the model summary, the DurbinWatson
value is 0.499 which very far off from the expected value of 2, for that to
fulfil the assumption. So the data is having auto collinearity.
d)
Assumption of Homoscedasticity
To check this assumption the scatter plot of
residuals has been observed.
Figure 6 Scatter Plot of Regression
Standardized
Residuals of FL and DPS of Private Banks
The scatter plot of residuals is not equally
distributed and depicts a cluster, which suggests the presence of
hetroscedasticity
e) Assumption
of Correct Regression
This assumption is checked with the help of
PP plot of observed and expected residuals. As per the observed PP plot the
residuals are near to but not exactly on the expected line. So the egression is
not a good fit.
Figure
7 Normal PP Plot of Regression Standardized
Residuals
of FL and DPS of Private Indian banks
It
has been analysed that the majority of assumption of linear regression model
are not satisfied in the case of private Indian banks also, so some kind of
transformation is needed to make the data normal and fit the regression line. This
transformation has been done by taking log values.
LINEAR REGRESSION WITH LOG OF DPS AND FL FOR PRIVATE
INDIAN BANKS
The transformation has been done with the
help of taking log of all the values. After transformation the model has been
developed in the form of:
Log
DPS = a + b (Log Financial Leverage)
The
regression has been run on the data related to private Indian banks and the
details are as follows:
Table 5 Linear Regression with Log of DPS and FL of
Private Banks in India
Correlations 


Log DPS 
Log Financial Leverage 

Pearson Correlation 
Log DPS 
1.000 
.065 
Log Financial Leverage 
.065 
1.000 

Sig. (1tailed) 
Log DPS 
. 
.233 
Log Financial Leverage 
.233 
. 
Table 6 Model Summary of Linear Regression
with Log of DPS and FL of Private Banks
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
DurbinWatson 

.065 
.004 
.004 
.45480 
.348 

Table 7 Coefficients of Linear Regression
with Log of DPS and FL of Private Banks 



Unstandardized Coefficients 
Standardized Coefficients 
t 
Sig. 


B 
Std. Error 
Beta 



(Constant) 
.935 
.256 

3.648 
.000 


Log Financial Leverage 
.181 
.248 
.065 
.731 
.466 


From the above tables it has been concluded
that there is a negative relationship between Log DPS and Log Financial
Leverage of private Indian banks which is not significant as the p value is
more than 0.05. Financial Leverage has a
negative impact on DPS i.e. with the increase in leverage DPS decreases in case
of private Indian banks in India. The regression coefficient is 0.181 with a
constant of 0.935.
REGRESSION MODEL
The equation can be written as a model fit
equation between two variables as
Log DPS = 0.935 – 0.181(Log Financial
Leverage)
As
the value of^{ }R^{2} is 0.004, it
means that variations in DPS are not explained by Financial Leverage for the
private Indian banks. But before we reach any conclusion regarding this model
it is necessary to check the validity of regression results.
VALIDITY OF REGRESSION RESULTS WITH LOG DPS AND LOG FL
FOR PRIVATE INDIAN BANKS
To check validity of regression results few
basic assumptions of classic linear regression model are checked with . tests
of linearity, normality, stationarity, auto collinearity and
homoscedasticity.
a)
Assumption of Linearity
This has been checked with the help of
Scatter diagram. The scatter diagram of the above said data is represented in
figure 8.
Figure 8
Scatter Plot of Log DPS and Log
FL for Private Banks
As there are number of outliers present, it
has been observed that the relationship is not linear between Log Financial
Leverage and Log DPS of private Indian banks.
b)
Assumption of Normality
ShapiroWilk test along with QQ plot has
been used to test the normality of data.
i.
ShapiroWilk
Test the results of
the test are as below:
Table 8
Test of Normality of Log DPS
and Log FL of PrivateBanks

KolmogorovSmirnov^{a} 
ShapiroWilk 

Statistic 
df 
Sig. 
Statistic 
Df 
Sig. 

Log DPS 
.089 
129 
.014 
.978 
129 
.031 
Log Financial Leverage 
.112 
129 
.000 
.948 
129 
.000 
As we
are able to see that level of Significance for ShapiroWilk test is below 0.05
for Log financial leverage and Log DPS, so the data don’t hold the assumption
of normality and regression results of the data which is not normal, are not
valid.
ii.
QQ Plot –.
On
the observation of the data on QQ plots, it is found that it is not normal.
Figure 9 QQ plot
of Log DPS of Private Banks Figure 10 QQ plot of Log FL of Private
Banks
c)
Assumption of Stationarity and auto correlation
Stationarity
has been checked using auto correlation test in SPSS and DurbinWatson
statistics.
i.
Autocorrelation test Auto correlation
test results show that data is not stationary
Figure 11 ACF Chart of Log FL of Private Figure 12 ACF Chart
of Log DPS of Private
ii.
Durbin –Watson Statistics
As per the model summary, the DurbinWatson
value is 0.348 which very far off from the expected value of 2, for that to
fulfil the assumption. So the data is having auto colinearity.
d) Assumption
of Homoscedasticity
To check this assumption the scatter plot of
residuals has been observed.
Figure 13 Scatter Plot of Regression Standardized
Residuals
of Log FL and Log DPS of Private Banks
The scatter plot of residuals equally distributed, which
suggest the presence of homoscadedticity.
e) Assumption
of Correct Regression
This
assumption is checked with the help of PP plot of observed and expected
residuals.
Figure
14 Normal PP Plot of Regression
Standardized
Residuals
of Log FL and Log DPS of Private banks
As
per the observed PP plot the residuals are very much near to the expected line
but not exactly on it.. So this assumption is not fulfilled.
It has been analysed that in this case also
all of assumption of linear regression model are not satisfied. Though the
results have improved as compared to simple regression but regression line
cannot be taken as a good fit. Now the efforts have been made to find the non
linear regression between the variables.
NONLINEAR REGRESSION OF DPS AND FL OF PRIVATE INDIAN
BANKS
As the linear regression model even after
transformation with log is not a good fit to explain the impact of financial
leverage on dividend of private Indian banks, Nonlinear regression model has
been applied. The correlation between dividend paid and financial leverage is
negative, therefore decay model has been chosen. The model is in the form as
below:
DPS=
A(B*(C*Financial Leverage))
When the same model has been
run on the data related to private Indian banks the results are as
below:
Table 9 Parameter Estimate for NonLinear Regression of
DPS and FL for Private Banks
Parameter 
Estimate 
Std. Error 
95% Confidence Interval 

Lower Bound 
Upper Bound 

A 
13.573 
2.549 
8.528 
18.618 
B 
.506 
9070461.159 
17950176.487 
17950175.474 
C 
.799 
14258716.429 
28217581.434 
28217579.837 
From the above tables it has been concluded
that there is a negative relationship between DPS and Financial Leverage of
private Indian banks i.e. with the increase in leverage DPS decreases in case
of private Indian banks.
NONLINEAR
REGRESSION MODEL
The equation can be written as a model fit
equation between two variables as
DPS= 13.573 
(0.506*(0.799*Financial Leverage)) i.e.
DPS= 13.573 
(0.506*(0.799*Financial Leverage))
As
the value of^{ }R^{2} is 0.027, it
means that 3 % of variations in DPS are explained by Financial Leverage for the private Indian banks.
Conclusion:
The results of
the study show that there exist a negative relationship between Financial
Leverage and Dividend of nationalized banks in India. Linear regression models
after transformation with Log have also
been developed depicting the significant impact of FL on DPS for banks. Though
the models cannot be used to predict DPS on the basis of FL yet the results of
the study can be used by the financial experts to formulate strategies related
to capital structure.
References
Aasia Asif, Waqas Rasool, and Yasir Kamal,
"Impact of financial leverage on dividend policy: Empirical evidence from
Karachi Stock Exchangelisted companies." African Journal of Business
Management, vol. 5, no.4, 2011, pp. 1312.
C. Bryan Cloyd, John Robinson, and Connie
Weaver, "Does Ownership Structure Affect Corporations' Responses to Lower
Dividend Tax Rates? An Analysis of Public and Private Banks." 2005.
Dinesh Kumar Sharma and Ritu Wadhwa,
"Determinants of Dividend Policy Decision: An Analysis of Banks in
India." Proceedings of International Conference on Strategies in
Volatile and Uncertain Environment for Emerging Markets, 2017.
Duha AlKuwari, "Determinants of the Dividend
Policy of Companies Listed on Emerging Stock Exchanges: The Case of the Gulf
Cooperation Council (GCC) Countries." 2009.
Eugene F Fama and Harvey Babiak,
"Dividend policy: An empirical analysis." Journal of the American
statistical Association, Vol. 63, no.324, 1968, pp.11321161.
H. Kent Baker and Gary E. Powell,
"Determinants of corporate dividend policy: a survey of NYSE firms." Financial
Practice and education, vol.10, 2000, pp. 2940.
H. Kent Baker, E. Theodore Veit, and Gary E.
Powell. "Factors influencing dividend policy decisions of Nasdaq
firms." Financial Review, vol. 36, no.3, 2001, pp.1938.
Hashim Zameer, Shahid Rasool, Sajid Iqbal,
and Umair Arshad."Determinants of dividend policy: A case of banking
sector in Pakistan." MiddleEast Journal of Scientific Research, Vol.18,
no. 3, 2013, pp. 410424.
HusamAldin Nizar AlMalkawi, "Factors
influencing corporate dividend decision: Evidence from Jordanian panel
data." International Journal of Business, vol.13, no.2, 2008,
pp.177.
Jorge Farinha, "Dividend policy,
corporate governance and the managerial entrenchment hypothesis: an empirical
analysis." Journal of Business Finance & Accounting, Vol.30,
no.9‐ 10,
2003, pp.11731209.
Lee Wei Sim, "A study on leading
determinants of dividend policy in Malaysia listed companies for food industry
under consumer product sector." Conference Master Resources, 2011.
M. Sudhahar and T. Saroja, "Determinants
of dividend policy in Indian banks: An empirical analysis." IUP Journal
of Bank Management, Vol.9, no.3, 2010, pp. 63.
M. Z Alam and Mohammad Emdad Hossain,
"Dividend policy: a comparative study of UK and Bangladesh based
companies." IOSR Journal of Business and Management, vol.1,no.1,
2012, pp.5767.
Manoj Anand, "Factors influencing
dividend policy decisions of corporate India." 2004.
Mohammad Tamimi and Nasrollah Takhtaei,
"Relationship between Firm Age and Financial Leverage with Dividend
Policy." Asian Journal of Finance & Accounting, Vol. 6, no.2,
2014, pp. 53.
Mokhtar Emamalizadeh, Mousa Ahmadi, and
Jaffar Pouyamanesh, "Impact of financial leverage on dividend policy at
Tehran Stock Exchange: A case study of food industry." African Journal
of Business Management, Vol.7, no.34, 2013, pp. 3287.
Ross N Dickens, K. Michael Casey, and Joseph
A. Newman, "Bank dividend policy: explanatory factors." Quarterly
journal of Business and Economics,2002, pp. 312.
S. Jasvir Sura, Karam Pal, and B. S. Bodla,
"Factors Influencing Dividend Policy Decisions in Banking Sector: An
Indian Evidence." 2012.
Souvik Banerjee and K. T. Rangamani, "A
Comparative Analysis of Dividend Policy of Public and Private Sector Banks in
India." SAMVAD, vol. 11, 2016, pp. 5964.
Turki SF Alzomaia, and Ahmed AlKhadhiri,
"Determination of dividend policy: The evidence from Saudi Arabia." International
Journal of Business and Social Science, vol. 4, no.1, 2013.