Capital Structure Strategies and Its Effect on Sustainable Corporate Growth - A Study on Dr. Reddy's Laboratories

Dr. K.S. Sekhara Rao¹*, Dr. V. Venu Madhav²

¹Assistant Professor, KLU Business School, KL University, Andhra Pradesh, India

²Associate Professor, KLU Business School, KL University, Andhra Pradesh, India

*Corresponding Author E-mail: sekharks1@gmail.com; dr.v.v.madhav@kluniversity.in

ABSTRACT:

The search for optimal capital structure that maximizes firms’ value and shareholder wealth has received significant attention in the academic community and also in the real world. There are different opinions on optimal capital structure. However, capital structure is a proper mix of the debt and equity. If there is a proper ratio of debt to equity, the firm is able to survive in existing competitive environment. According to several studies, capital structure has an impact on the performance of an organization. So, every company should plan for the good mix of debt to equity in order to gain the growth in its value. This study mainly focused on to derive the facts related to the capital structure design, and its impact on the organization including the performance, by using various theories and tools. The study has the net profit as indicator of the overall performance of the organization. The result shows that, the capital structure has close relationship with company performance, and it is influencing the overall performance of the organization.

KEY WORDS: capital structure, debt equity ratio, leverage, corporate performance, organization.

INTRODUCTION:

An unmanageable number of publications and countless scientific studies have examined a wide range of theoretical and empirical aspects on understanding of how firms make financing choices and what determines corporate capital structure is still limited. The theory of capital structure is critical because, the financing mix of a company can have significant effects on it. The frequently-used trade-off theory suggests that, there is an optimal capital structure for each individual firm which can be reached by balancing both the benefits and the costs of debt (Myers 1984). The use of debt is only increase the returns to shareholders as long as the cost of debt is less than the return on assets (Perridon and Steiner, 2012).

But the shareholder value model is aimed to maximize the shareholder value. Rappaport (1998, p.) noted that “corporate boards universally embrace the idea of maximizing shareholder value [that] reflects the way rational participants in a market-based economy assess the value of an asset”. Fundamental idea behind this concept is to measure a company's success and to evaluate alternative courses of action (Rappaport, 1998). When people refer to capital structure, they are most likely referring to a firm’s debt-to equity ratio which provides insight into how risky a company is. However, the capital structure policy involves a trade-off between risk and return. Using more debt raises the riskiness of the firm’s earnings. Therefore, the optimal capital structure is one that strikes a balance between risk and return to achieve our ultimate goal of maximizing the price of the stock.

This study mainly focused on the capital structure strategies and its impact on organisation performance. This was studied on Dr. Reddy's Laboratories Ltd., which is a pharmaceutical company. The company manufactures and markets a wide range of pharmaceuticals in Hyderabad. Dr. Reddy’s Laboratories Limited (DRL) is an integrated global pharmaceutical company. The study has taken the components of shareholders equity and debt in capital structure and measured its impact on organisation performance. The result shows that, there is an impact of capital structure strategies on performance and growth of organisation.

REVIEW OF LITERATURE:

There are many variables in a capital structure choice and structure of debt maturity which can affect a company’s performance. Debt maturity can influence a company’s option in investing. Furthermore, tax rate can also affect company’s performance. In the case of this, examine the impact of capital structure’s variables base on company’s performance will present prove for a company’s performance due to the effect of capital structure (Tian & Zeitun, 2007). Abor (2005) found that there is significant positively interrelated between SDA and ROE and shows that firms which earn a lot, use more short-term debt to finance their business. In his study the regression output showed that, the positive relationship between debt and ROE which measure the relationship between total debt and profitability.

If wealth could be enhanced by getting the leverage decision right, managers need to understand the key influences. Its actual relevance and the consequences on a business have been questioned in past research (Modigliani and Miller, 1958) but more recent empirical evidences clearly points out that capital structure does matter (Myers and Majluf, 1984). Gleason, et.al (2000) on relationship between capital structure and organisation performance, using data from retailers in 14 European countries, showed that, capital structure has influence on organisation performance.

A study has been done by Akintoye (2008) on sensitivity of performance to capital structure on selected food and Beverage Companies in Nigeria. The result shows that, performance indicators to turnover (Earnings before Interest and Taxes, Earninig per Share and Dividend per Share) and the measures of leverage (Degree of Operating Leverage, Degree of Financial Leverage and Dividend per Share) are significantly sensitive.

In contrary, the other researches showed that, Capital structure doesn't have influence on the market value of the company. Puwanenthiren Pratheepkanth (2011) constitute an attempt to identify the impact of capital structure on companies performance, by taking into consideration the level of company’s financial performance. The result shows that, the relationship between the capital structure and financial performance has negative association at -0.114. Co-efficient of determination is 0.013. F and t values are 0.366, -0.605 respectively. It also reflected in the business companies in Sri Lanka. Ahmed Al Ajlouni, (2013) study also affirmed that, the capital structure doesn't have influence on the market value of the company, which can be settled by the composition of its assets.

To improve the organisational performance an optimal capital structure is required. According to Muritala Taiwo Adewale et.al (2013) an optimal capital structure exists which balances the risk of bankruptcy with the tax savings of debt. Once established, this capital structure should provide greater returns to stockholders than they would receive from an all-equity firm. Modigliani and Miller (1963) argued that, due to tax deductibility of interest payments, the appropriate capital structure for a firm is composed entirely of debt. Brigham and Gape ski (1996), however, assert that the Miller and Modigliani (MM) model is probably true in theory, but in practice, bankruptcy costs exist and they increase when equity is traded off for debt.

NEED FOR THE STUDY:

The main purpose of this study is to identify the affect of capital structure on profitability, by analyzing various factors which are involved in the capital structure. This study mainly focuses on the capital structure strategies of Dr. Reddy Labs. This study believes that, the growth of the organisation influenced by the capital structure of that organisation. So, to analyse and establish the relationship between capital structure and the profitability of the company this research has been undertaken.

PROBLEM STATEMENT:

The study encompasses an analysis of capital structure and its impact on the performance of the company. If wealth could be enhanced by getting the leverage in capital structure, its actual relevance and the consequences on a business performance have been questioned in past researches. Some researches made an attempt but not find out clearly. So the clarity is required on leverage in capital structure and its consequences on a business performance to decide proper mix of debt and equity. Therefore, this study wants to make an attempt to find out the impact of capital structure on the performance of the Indian organisation.

OBJECTIVES OF STUDY:

Following are the objectives of the present study.

Primary Objectives:

The primary objective of the study is to analyze the capital structure strategies of Dr. Reddy's Laboratories and its impact on the performance of the company.

Secondary Objectives

The study is specially aimed to attain the following objectives.

1. To assess the capital structure of the company.

2. To determine the impact of long-term debt on profitability of the company.

Hypotheses:

H1: The proportion of share holders’ equity in capital structure influences the net profit of the company.

H2: The proportion of total long term debt in capital structure influences the net profit of the company.

H3: The total capital structure influences the net profit of the company.

Research Design:

As the study aims at narrating the existing facts and figures regarding financial position of the company, it is descriptive in nature. The study focuses on the secondary sources (includes annual reports and other documents of the company) for data analysis. To prove the impact of capital structure on the performance of the organisation the study has framed some objectives and hypotheses (above mentioned). The SPSS 17.0 version has been used to analyse the data, for proving hypotheses of the study.

Data Analysis

The study has taken the capital structure components of stockholders equity and the total long term debt. It is also taken the performance indicators such as: revenue, gross profit and net profit for the analysis. The values of these from the year 2004 to 2013 are given below.

Table 1: Table consisting of capital structure components and performance indicators of Dr. Reddy‘s Laboratories. (Rs in lakhs)

VARIABLES	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013
Revenues	49,255	19,519	24,267	65,095	50,006	69,441	70,277	74,693	96,737	116,266
Stockholders’ equity	3826	20,953	22,272	42,627	47,350	42,045	42915.00	45990.00	57,444	73,105
Total long term debt	21149	25	20,937	17,871	12,698	10,132	5385.00	5271.00	16,335	12,625
Total debt+equity	24975	20,978	43,209	60,498	60,048	52177.00	48300.00	51261.00	73,779	85,730
Gross profit	37507	10,134	11,850	30,876	25,408	36,500	36,340	40,263	53,305	60,579
NET PROFIT	-36911	201	1,629	9,323	3,836	(5168)	1,068	11,040	14,262	12,655

Source: Dr. Reddy’s lab limited Annual Report 2008–09, 2009-10, 2010-11, 2011-12, 2012-13.

The analysis of capital structure components and the performance indicators mentioned in the above table given with the help of the graphs.

Fig 1: Graph showing the relationship among revenue, gross profit and net profit.

The above diagram shows that, the revenue, gross profit and net profit of the company. Both are increased year by year except in the years 2005 and 2008. In the years 2005 and 2008 the company is used very less debt in its capital structure. From the year 2011 onwards the rate of growth in the profit is high. Because, the efficient capital structure policies used by the company.

Fig 2: Graph showing the relationship among gross profit, total debt equity and net profit.

The above graph shows that, the gross profit, net profit and total debt equity of the company. In the years 2004 and 2009 the company earned losses, and in 2005 it earned less profit. If we see in those years the amount of total debt equity is almost all equal to the other years debt equity, but the proportion of equity is more and the proportion of the debt is very less. Because of less debt usage in the capital structure the company performance is declined.

Fig 3: the relationship among gross profit, share holders equity and long term debt.

The above graph shows that, the relationship among gross profit, share holders equity and long term debt of the company. In the year 2004 the gross profit is high when it compared with other years because of high amount of debt used in the total capital structure. In the year 2005 the gross profit was very less because the company used very less amount of debt funds and high amount of equity funds. By observing the graph we can understand that, the proportion of capital mix in the capital structure affected the amount of the gross profit earned by the company.

Fig 4: Graph showing the relationship among net profit, share holders equity and long term debt.

The above graph shows that, the relationship among net profit, share holders equity and long term debt of the company. The company earned loss in the years 2004 and 2007. The reasons could be high interest rates on debt and high tax rates. In the rest of years the company earned adequate amount of net profits.

For this study the identified variables are: gross profit, net profit, share holders equity, long term debt .To analyze the relationship between these variables in terms of the impact of one variable on another the regression analysis is identified as a suitable statistical technique.

Before run the regression test to the given variables first we should draw the scatter diagram for the data to see the relationship between X and Y. Suppose the relationship between X and Y appear reasonably linear we can postulate a linear equation for the line which is the best fit of the sample data from the population. The mathematical equation to represent this relationship between X an Y is

Y=a+ bX

Where

a= the intercept, and b= the slope of the line.

The point on the scatter diagram represents a sample value of a controlled variable X and a random variable Y. The equation of a straight line which might best fit the population of point may be rewrite as

Y=α+ βx

From the equation to find out α and β we should use the criterion of least square. It means minimize the sum of squares of vertical distances from the sample point to the so called regression line. The method of least squares is a way of finding the line that best fit the data. This line of best fit is found by ascertaining the line from all of the possible lines that could be drawn, results in the least amount of difference between the observed data points and the line.

The estimated β- value is

α- values is

α = y- βx

The main purpose of determining the regression line is to find the true value of the slope β of the population. The regression line scattered in all cases, the regression line is estimated by using sample data.

Using the mean as model, it can be calculated the difference between the observed values, and the values predicted by the mean. We should square all these differences which are known as total sum of squares (SS_T) , this value represents how good the mean is as a model of the data. The differences squared before they are added up is known as sum of squared residuals (SS_R).this value represents the degree of inaccuracy when the best model is fitted to the data. The use of regression model improves the prediction of outcome rather than the mean is calculated.

The output of regression R² represents the amount of variance in the outcome explained by the model sum of squares (SS_M) relative to how much variance there was to explain in total sum of squares (SS_T). Therefore as a percentage of the variation in the outcome that can be explained by the model.

The other use of the sum of the squares in assessing the model is through the F-test. F is based upon the ratio of the the improvement due to the model (SS_M) and the difference between the model and the observed data (SS_R). However the F-ratio is a measure of how much the model has improved the prediction of the outcome compared to the level of inaccuracy of the model

H1: Total share holders’ equity influences the net profit of the company.

Table 2: Model Summary^b of regression between share holders’ equity and net profit.

The R-square of the regression model is the fraction of the variation in the dependent variable that is accounted for (or predicted by) independent variables. (In regression with a single independent variable, it is the same as the square of the correlation between dependent and independent variable) the summary of the model provided the value of R and R² for the model that has been derived. These data R has a value of .795 because there is only one predictor, this value represents the simple correlation between the net profit and share holders equity. The value of R² is .632 which tells us the total share holders’ equity can account for 63.2 percent variation in net profit. The remaining 37 percent of variation is not explained by this model because there might be other factors that can explain this variation, but this model which include only share holder’s equity.

The next part of the output reports an analysis of variance (ANOVA). The table below shows the various sums of squares and the degree of freedom associated with each. From these two values, the average sums of squares (mean squares) can be calculated by dividing the sums of squares by the associated degrees of freedom. The most important part of the table is the F-ratio, which is calculated using the above equation, and the associated significance value of the F-ratio. For these data, F is 13.723 which is significant at p >.001. The sig: value is .006. It shows there is an impact of Total share holders’ equity on net profit. So the above mentioned hypothesis can be accepted.

Table 3: ANOVA^b results of regression model between stock holders’ equity and net profit.

Table below provides complete information about the model i.e. coefficients. It indicates the significant values of predictors that affect the dependent variable. It is found that the impact of the total share holders’ equity on the net profit and it influences the performance of the company.

Table 4: Coefficients^a of regression between total stock holders’ equity and net profit.

a. Dependent variable: Q_3 Net profit

Based on the above regression model results, to know the impact of the share holders equity influence the net profit of the, it is clear the share holders’ equity significantly influencing the net profit.

Analysis of the relationship between total long term debt and net profit of the company

H2: Total long term debt influences the net profit of the company.

Table 5: Model summary^b of regression between term debt and the net profit.

The R-square of the regression model is the fraction of the variation in the dependent variable that is accounted for (or predicted by) independent variables. (In regression with a single independent variable, it is the same as the square of the correlation between dependent and independent variable) the summary of the model provided the value of R and R² for the model that has been derived. These data R has a value of .289 because there is only one predictor, this value represents the simple correlation between the net profit and total long term debt. The value of R² is .084 which tells us the total long term debt can account for 8.4 percent variation in net profit. The remaining 91.6 percent of variation is not explained by this model because there might be other factors that can explain this variation, but this model which include only long term debt.

The next part of the output reports an analysis of variance (ANOVA). The table below shows the various sums of squares and the degree of freedom associated with each. From these two values, the average sums of squares (mean squares) can be calculated by dividing the sums of squares by the associated degrees of freedom. The most important part of the table is the F-ratio, which is calculated using the above equation, and the associated significance value of the F-ratio. For these data, F is .139 which is significant at p >.001. The sig: value is. 719. It shows there is an impact of Long term debt on gross profit. So the above mentioned hypothesis can be accepted.

The next part of the output reports an analysis of variance (ANOVA). The table below shows the various sums of squares and the degree of freedom associated with each. From these two values, the average sums of squares (mean squares) can be calculated by dividing the sums of squares by the associated degrees of freedom. The most important part of the table is the F-ratio, which is calculated using the above equation, and the associated significance value of the F-ratio. For these data, F is .731 which is significant at p >.001. The sig: value is. 418. It shows there is an impact of long term debt on gross profit. So the above mentioned hypothesis can be accepted.

Table 6: ANOVA^b results of regression model between total long term debt and net profit.

a. Predictors: (Constant), Q_4 Total long term debt

b. Dependent Variable: Q_3 Net profit

Table below provides complete information about the model i.e. coefficients. It indicates the significant values of predictors that affect the dependent variable. It is found that the impact of the Total long term debt on the net profit and it influences the performance of the company.

Table 7: Coefficients^a regression model between total long term debt and net profit

a. Dependent variable: Q_3 Net profit

Based on the above regression model results, to know the impact of the long term debt influence the Gross profit of the, it is clear the long term debt significantly influencing the net profit.

H3: Total capital structure influences the net profit of the company

Table 8: Model summary^b of regression between total capital structure and net profit

a. Predictors: (Constant), Q_6 Total capital structure

b. Dependent variable: Q_3 Net profit

The R-square of the regression model is the fraction of the variation in the dependent variable that is accounted for (or predicted by) independent variables. (In regression with a single independent variable, it is the same as the square of the correlation between dependent and independent variable) the summary of the model provided the value of R and R² for the model that has been derived. These data R has a value of .687 because there is only one predictor, this value represents the simple correlation between the net profit and total capital structure. The value of R² is .472 which tells us the total long term debt can account for 47.2 percent variation in net profit. The remaining 52.8 percent of variation is not explained by this model because there might be other factors that can explain this variation, but this model which include only total capital structure.

Table 9: ANOVA^b results of regression model between total capital structure and net profit.

Table below provides complete information about the model i.e. coefficients. It indicates the significant values of predictors that affect the dependent variable. It is found that the impact of the total capital structure on the net profit and it influences the performance of the company.

Table 10: Coefficient^a of regression model between total capital structure and net profit.

Based on the above regression model results, to know the impact of the capital structure influence the net profit of the, it is clear the capital structure debt significantly influencing the net profit.

CONCLUSIONS:

It is observed that in the year 2004 and 2009 the company earned loss, even the company maintained an appropriate proportion of debt and equity in its capital structure. From the analysis of share holder equity vs. net profit, it is identified that the amount of equity considerably influencing the net profit of the company (R = 0.795). From the analysis of net profit and total long term debt the data R has a value of .289. The value of R² is .084 which tells us the total long term debt can account for 8.4 percent variation in net profit. From the above analysis it is concluded that the total long term debt does not affect the profits whereas the share holder equity have less affect on it.

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Received on 24.01.2015 Modified on 15.02.2015

Accepted on 25.03.2015 © A&V Publication all right reserved

Asian J. Management; 6(2): April-June, 2015 page 101-109

DOI: 10.5958/2321-5763.2015.00015.3