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Capital Structure of Select Companies in Indian Automobile Industry:
A SEM Approach
Dr R SARAVANAN
Director, School of Management, Sri Krishna College of Technology
( V.L.B.Janakiammal College of Engineering & Technology )
Kovaipudur, Coimbatore- 641 042, India
K GOWRI
Ph.D Research Scholar, Bharathiar University, Coimbatore-46, India
ABSTRACT
Capital structure is one of the most complex areas of financial decision making due to inter
relationship with other financial decision variables. In finance, the capital structure is the most
debatable topic and continues to keep researchers pondering. A good capital structure helps to gain
attractive profit, and the absence of a proper capital structure affect the debt position as well as the
leverage which leads to great financial risk. A restructuring of capital will be all suggested for poor
profit generating Industries and loss making Industries. For sound capital structure, the companies
struggle while raising funds is whether to raise debts or equity, because the debt and equity are the two
principal sources of finance for a company. The tough problem facing companies which raising funds,
so there arises an inconclusive debate on this issue. Hence, an attempt is made in this study to ascertain
the impact of various determinants so that appropriate capital structure could be designed by the
companies in order to make themselves competitive and cost effective. The analysis of the Structural
Equation model suggests that the measured variables are influenced to determine the capital structure
of select companies in Indian Automobile industry except STDR NDTS and OPR.
KeyWords: Capital structure, Determinants of Capital structure, Automobile industry.
INTRODUCTION
Structural equation models (SEMs) report findings in three different ways. Understanding the
way statistical significance is reported requires understanding the terminology of the model itself.
Within the graphical display of the model there are boxes and arrows. Boxes represent observed data
and the arrows represent assumed causation. Within the model a variable that receives a one-way
directional influence from some other variable in the system is termed "endogenous", or is dependent.
A variable that does not receive a directional influence from any other variable in the system is termed
as "exogenous" or is independent. The capital structure decision is crucial for business organizations.
The capital structure decision is important because of the need to maximize returns of the firms, and
because of the impact, such a decision has on the firm’s ability to deal with its competitive
environment. Therefore, it is important to test the relationship between capital structure and the
profitability of the firm to make sound capital structure decisions. Hence, the capital structure
determinants have been used to analyse the capital structure of select companies in Indian Automobile
Industry under SEM approach.
REVIEW OF PREVIOUS STUDIES
One of the main factors that could influence the firm’s performance is capital structure. Since
bankruptcy costs exist, deteriorating returns occur with further use of debt in order to get the benefits
of tax deduction. Therefore, there is an appropriate capital structure beyond which increases in
bankruptcy costs are higher than the marginal tax-sheltering benefits associated with the additional
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substitution of debt for equity. Firms are willing to maximize their performance, and minimize their
financing cost, by maintaining the appropriate capital structure or the optimal capital structure. Harris
and Raviv (1991) argued that capital structure is related to the trade-off between costs of liquidation
and the gain from liquidation to both shareholders and managers. So firms may have more debt in their
capital structure than is suitable as it gains benefits for both shareholders and managers. However, as
stated in the previous literature, underestimating the bankruptcy costs of liquidation or reorganization,
or the aligned interest of both managers and shareholders, may lead firms to have more debt in their
capital structure than they should (see, for example, Harris and Raviv, 1991). Krishnan and Moyer,
(1997) found a negative and significant impact of total debt to total equity (TD/TE) on return on equity
(ROE). Another study by Gleason, Mathur and Mathur, (2000) found that firms capital structure has a
negative and significant impact on firms performance measures return on assets (ROA), growth in
sales (Gsales), and pre tax income (Ptax). Therefore, high levels of debt in the capital structure would
decrease the firm's performance.
Hunjra et al., (2011) in their study entitled “Patterns of Capital Structure and Dividend Policy
in Pakistani Corporate Sector and their Impact on Organization Performance”, analyzed the
determined of patterns of capital structure decisions and dividend policy as well as their level of
application in Pakistani corporate sector and also checked the impact of capital structure and dividend
policy on organization performance. The study concluded that capital structure decisions were being
properly practiced while dividend policy was a major concern in most of the organizations. The study
also concluded that there was a significant and positive relationship between capital structure decision,
dividend policy and organization performance.
San and Heng (2011) in their article entitled “Capital Structure and Corporate Performance of
Malaysian Construction Sector”, studied the relation of capital structure with performance of the firm
in the Malaysian construction industry in the aftermath of financial crises of 2007-08 that badly
affected most of the economies of the world including Malaysia. They found that the financial crises
do not show any major impact on the performance of construction industry because of the large scale
development work going on the country. Weak relation exists between leverage and performance
measured by assets returns, equity returns and profitability in the Malaysian construction industry
including small, medium and large size companies.
OBJECTIVE
To analyse the factors determining the capital structure of select companies in Indian
Automobile Industry under SEM approach.
SCOPE OF THE STUDY
The present study has been analyzed to design an appropriate capital structure to make
competitive and cost effective of select companies for a period of the study which was extended over
ten years from 2002-2003 to 2011-2012.
SELECTION OF SAMPLE
The Study takes into account of the following top ten Automobile companies in the year 2013 were
purposively selected.
1. Maruti Suzuki India Ltd
2. Hyundai Motors India Ltd
3. Tata Motors Ltd
4. Ashok Leyland
5. Mahindra & Mahindra Ltd
6. Toyota Ltd
7. General Motors India Private Ltd
8. Ford Motor Company
9. Honda Cars India Ltd.,
10. Nissan Motor India Private Ltd.
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DATA AND SOURCES OF DATA
The study was based mainly on secondary data. The following data needed for the study were
collected from the official Directory of the Bombay Stock Exchange and Corporate Data base
(PROWESS) of the Centre for Monitoring Indian Economy (CMIE).
ANALYSIS OF CAPITAL STRUCTURE
STRUCTURAL EQUATION MODELING (SEM)
Structural Equation Modeling is a very general statistical modeling technique, which is widely
used in the behavioural sciences. It can be viewed as a combination of factor analysis and regression or
path analysis. The interest in SEM is often on theoretical constructs, which are represented by the
latent factors. The relationships between the theoretical constructs are represented by regression or
path coefficients between the factors. The structural equation model implies a structure for the co-
variances between the observed variables, which provides the alternative name covariance structure
modeling. However, the model can be extended to include means of observed variables or factors in
the model, which makes covariance structure modeling a less accurate name.
RESEARCH MODEL AND HYPOTHESIS FORMULATION
The research hypotheses have been defined on the basis of the constructs outlined above and
using previous research on assessing the capital structure capital structure of select companies in
Indian Automobile Industry. The Chart No.1 is a graphic presentation of the developed hypothetical
model. On the basis of above presented model, the following hypotheses are proposed.
HYPOTHESIS OF THE STUDY
The following “selected variables are positively correlated with the capital structure of select
companies in Indian Automobile Industry”. The manifest and latent variables are exhibited in table
no.1.
CO-VARIANCE MATRIX
In probability theory and statistics, a covariance matrix (also known as dispersion matrix or
variance covariance matrix) is a matrix whose element in the i, j position is the covariance between the
i th
and j th
elements of a random vector (that is, of a vector of random variables). Each element of the
vector is a scalar random variable, either with a finite number of observed empirical values or with a
finite or infinite number of potential values specified by a theoretical joint probability distribution of
all the random variables. Intuitively, the covariance matrix generalizes the notion of variance to
multiple dimensions. As an example, the variation in a collection of random points in two-dimensional
space cannot be characterized fully by a single number, nor would the variances in the x and y
directions contain all of the necessary information; a 2×2 matrix would be necessary to fully
characterize the two-dimensional variation.The Co-variance matrix of select Automobile
manufacturing companies are presented in Table No.2.
DISCUSSION OF THE RESULT
Table No.3 and Chart No.3 infers that the following measured variables LTDR, TDR, CI,
PROF, AGE, SIZE, TANG, ROE, ROCE, RONW, GPR, NPR, OCR and CPR are influenced with
latent variable of successful operation and have positive relationship with the significant at 1 percent
and 5 percent level of determining the capital structure of select companies in Indian Automobile
industry and the negative relationship with STDR, NDTS and OPR. The analysis of the model
suggests that almost all the measured variables are influenced to determine the capital structure of
select companies in Indian Automobile industry except STDR, NDTS and OPR.
The table No.4 reveals that the regression coefficient of the exogenous variables. It is noted
that the critical ratio of the following LTDR, TDR, CI, PROF, AGE, SIZE, TANG, ROE, ROCE,
RONW, GPR, NPR, OCR and CPR manifest variables are above the table value 2.962 and it is
significant at 1 percent level. Among the selected variables, almost all the variables are influenced to
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determine the capital structure of select companies in Indian Automobile industry except three
variables named STDR, NDTS and OPR. These are not influenced to determine the capital structure of
the select companies.
Table no.5 indicates that the model fit indices of Automobile industry. The entire test has the
range of 0 to 1. The comparative fit index (CFI) scored 0.712, normed fit index (NFI) scored 0.823,
relative fit index (RFI) scored 0.769, incremental fit index (IFI) scored 0.825, parsimonious normed fit
Index (PNFI) scored 0.622, parsimony comparative fit index (PCFI) scored 0.789, Tucker Lewis index
(TLI) scored 0.597, and the Root Mean Squared Error of Approximation (RMSEA) secured 0.031 that
indicates a close fit of the model.
FINDINGS
The following LTDR, TDR, CI, PROF, AGE, SIZE, TANG, ROE, ROCE, RONW, GPR,
NPR, OCR and CPR manifest variables are above the table value 2.962 and it is significant at 1
percent level. Among the selected variables, these variables are influenced to determine the capital
structure of select companies in Indian Automobile industry. And the other variables STDR, NDTS
and OPR are not influenced to determine the capital structure of the select companies.
SUGGESTIONS
Based on the findings of this study, it is concluded that the capital structure of the firm influences
profitability. The results suggest that profitable firms depend more on debt as their main financing option.
Although interest on debt is tax deductable, a higher level of debt increases default risk, which in turn,
increases the chance of bankruptcy for the firm. Therefore, the firm must consider using an optimal capital
structure by including debt. It is “The best” debt / equity ratio for the firm, which in turn, will minimize the
cost of capital, i.e., the cost of financing the company’s operations. In addition, it will reduce the chances of
bankruptcy.
The prime objective of every firm is to maximize the profit to improve better returns to its
stakeholders and to increase faith in the intrinsic value of the firm. The company can find out the ratios
which consistently discriminate the more profitable companies from less profitable. The latter
companies shall take the necessary cost reduction measures to improve their profitability. Cost control
measures should be applied to control the cost. As cost decides the profit of the concern, different
elements of cost should be verified and find out which cost is going up and take remedial measures to
control cost.
CONCLUSION Capital structure/leverage level of the firm determined by several factors. Proper capital
structure leads the firm to achieve the better performance and ensures the sustainability in its
operation. Even though there are several factors contribute to the institutional performance,
determinants of the capital structure play an important role. If the suggestions given in this study are
properly carried out the concern can have a bright future. These concerns can concentrate more on cost
control and Economic Production. The study is a rewarding exercise to the researcher and he will be
delighted if the findings and suggestions are incorporated by the policy makers of these select
companies in Indian Automobile Industry.
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CHART N0.1
RESEARCH MODEL SPECIFICATION
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TABLE No.1
VARIABLES SPECIFICATION FOR CAPITAL STRUCTURE ANALYSIS
MANIFEST AND LATENT VARIABLES FOR SEM
Manifest variables Latent variables
Long-term Debt Ratio LTDR
Capital Structure(CS) Short-term Debt Ratio STDR
Total Debt Ratio TDR
Capital Intensity CI
Capital structure
determinants(CAPSD)
Profitability PROF
Age AGE
Size SIZE
Non-debt tax Shields NDTS
Tangibility TANG
Return on Equity ROE
Investment Ratios(IR) Return on Capital Employed ROCE
Return on Networth RONW
Gross Profit Ratio GPR
Profitability of the Firm (PROFT) Net Profit Ratio NPR
Operating Profit Ratio OPR
Operating Cost Ratio OCR
Cash Profit Ratio CPR
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CHART No.2
UNSTANDARDISED ESTIMATES
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CHART No.3
STANDARDISED ESTIMATES
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TABLE No.3
TESTING OF HYPOTHESES – STANDARDISED ESTIMATES
Hypotheses Hypothetical
Relationship
Result
H1: There is a positive impact of LTDR and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H2: There is a negative impact of STDR and the Capital
structure of Select Automobile companies in India. Negative
Not
Confirmed
H3: There is a positive impact of TDR and the Capital structure
of Select Automobile companies in India. Positive Confirmed
H4: There is a positive impact of CI and the Capital structure
of Select Automobile companies in India. Positive Confirmed
H5: There is a positive impact of PROF and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H6: There is a positive impact of AGE the Capital structure of
Select Automobile companies in India. Positive Confirmed
H7: There is a positive impact of SIZE and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H8: There is a positive impact of NDTS and the Capital
structure of Select Automobile companies in India. Negative
Not
Confirmed
H9: There is a positive impact of TANG and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H10: There is a positive impact of ROE and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H11: There is a positive impact of ROCE and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H12: There is a positive impact of RONW and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H13: There is a positive impact of GPR and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H14: There is a positive impact of NPR and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H15: There is a positive impact of OPR and the Capital
structure of Select Automobile companies in India. Negative
Not
Confirmed
H16: There is a positive impact of OCR and the Capital
structure of Select Automobile companies in India. Positive Confirmed
H17: There is a positive impact of CPR and the Capital
structure of Select Automobile companies in India. Positive Confirmed
Chi-square = 27752.9, Degrees of freedom = 113, Probability level = .000
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TABLE No.4
REGRESSION WEIGHTS FOR CAPITAL STRUCTURE ANALYSIS
LISREL MAXIMIM LIKELIHOOD ESTIMATES
Latent
Variables
Measured
Variables
Estimates
SE
R2
CR
P
CS <--- LTDR 10.773 .366 0.05 29.439 ***
CS <--- STDR 10.000 .255 -0.88 1.33 0.02
CS <--- TDR 12.103 1.879 0.82 6.441 ***
CAPSD <--- CI 5.409 .243 0.92 22.244 ***
CAPSD <--- PROF 6.719 1.010 0.87 6.656 ***
CAPSD <--- AGE 72.545 .772 0.95 93.952 ***
CAPSD <--- SIZE 3.864 .221 0.20 17.472 ***
CAPSD <--- NDTS 3.818 .182 -0.10 1.071 0.022
CAPSD <--- TANG 4.818 .243 0.32 19.831 ***
IR <--- ROE 6.682 1.790 0.39 3.732 ***
IR <--- ROCE 12.379 2.475 0.61 5.001 ***
IR <--- RONW 52.409 6.358 1.26 8.243 ***
PROFT <--- GPR 3.045 .290 0.21 10.488 ***
PROFT <--- NPR 2.591 .306 0.09 8.461 ***
PROFT <--- OPR 2.864 .249 -1.24 1.511 0.024
PROFT <--- OCR 85.545 1.659 0.24 51.566 ***
PROFT <--- CPR 4.091 .160 0.26 25.578 ***
***- Significant at 1% level
TABLE No.5
MODEL FIT INDICES
Sl.
No
Model Fit Indices Calculated
Value
Acceptable Threshold Levels
1 Comparative Fit Index(CFI) 0.721 0-1
2 Normed Fit Index (NFI) 0.823 0-1
3 Relative Fit Index (RFI) 0.769 0-1
4 Incremental Fit Index (IFI) 0.825 0-1
5 Parsimonious Normed Fit Index
(PNFI))
0.622 0-1
6 Parsimony Comparative Fit Index
(PCFI)
0.789 0-1
7 Tucker Lewis Index (TLI) 0.597 0-1
8 Root Mean Squared Error of
Approximation (RMSEA)
0.031 0.05 or less would indicate a close fit of
the model
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