Editorial Board

A Refereed Monthly International Journal of Management

An Empirical Examination of Determinants of Financial Performance for Pharmaceutical Industry in India

Dr. T. Manjunatha

Professor,

Department of Management Studies (MBA)

Visvesvaraya Technological University

B D T College of Engineering, Davangere,

Karnataka, India

ORCID: 0000-0003-2322-0498

Keerthi S,

Faculty,

G M Institute of Technology, Davangere

and Research Scholar, Dept. of MBA

Visvesvaraya Technological University

B D T College of Engineering, Davangere,

Karnataka, India

Abstract

The paper aims at ascertaining the determinants of financial performance for pharmaceutical industry. We use the financial data of one hundred and forty-one pharmaceutical companies listed in the Indian stock exchanges. The result of the data shows that logarithm of dividend to paid up capital, liquid ratio and logarithm of PBIT by total assets as independent variables emerge as determinants of the financial performance of pharmaceutical industry of the study. The results of the study may be used to compare with other foreign pharmaceutical companies to understand the determinants of financial performance. Further studies can be undertaken for company wise analysis in pharmaceutical industry in India.

Key words: Net Profit Ratio, Net Profit to Assets, Return on Investment, Return on Equity, Operating profit to Total Asset, Operating Profit to Total Assets, pharmaceutical Industry companies.

Introduction

Indian Pharmaceutical industry supplies more than fifty percent of the global demand for various vaccines. In the global pharmaceuticals sector, India is a significant and rising player. India is the world's largest supplier of generic medications. The companies in Indian pharmaceutical industry are fairly doing well, hence promoters and investors in this industry need to financial pattern, profitability and determinants for financial pattern, profitability of these firms. The study on financial performance of companies and determinants for financial pattern, profitability has been undertaken by Frederick et.al (1984)studied the risk-return characteristics of the portfolios and compared them with fundamental performance measures and found that rankings are correlated with variability of returns.Titman and Wessel (1988) found that transaction costs are the important determinant of capital structure. Hasnath and Chatterjee (1990)analysed the patterns of public sector construction expenditure in the United States for the years 1957-1985. Their analysis of expenditure trend showed that demand and supply factors influence capital expenditure. Buckmaster and Saniga (1990), Osteryoung and Richard 1992) report that earnings on total assets and equity are important to understand the financial performance of an enterprise. Cornett and Tehrani an (1992) observed the benefits from merger and acquisition for a bank. This merger and acquisition seemed to bring about their expanded ability to pull in financial performance. Healy et.al. (1992) explored the post-acquisition performance of the companies’ resident in the US. The study evaluated the cash flow performance of the merger-initiated companies. Results demonstrated that the merged organizations enlisted improvements in the post-merger working execution in contrast with that of their industry peers. These increases emerged from enhancements in resource efficiency. Pilloff and Santomero (1998) analysed value of the banks with respect to merger and acquisition. Result shows that there is an increase in the performance because of the merger and acquisition. Karthikeyan (2000)found positive relationship between the financial performance and financial forecasting. Beena (2000) observed that merger and acquisition movement was dominant in the 1990s. Merger and acquisition has contributed lot to the companies’ financial performance. Yeh and Hoshino (2000) studied how mergers and acquisitions impact stock prices and financial performance of acquiring firms and reports that these have positive impact. Pawaskar (2001) observed the operating performance of the companies and found that asset turnover and profit margins have major impact on companies’ performance. Manoharan (2002)studied the performance of cement companies in India using age, size, and location. The study found that leverage and earnings are related. Lermack (2003) argues that financial ratios analysis is of immense use in assessing the performance of companies. Gugler et. al. (2003) report that although merger and acquision resulted in increased profits, they reduce the sales of merged entity. Sudarsana (2003)analysed the receivables of Andhra Pradesh Paper Industry and they suggested the preparation of frequent debtors aging schedule will lead to improvement in the performance of companies.  Ali et al (2004)studied BOT model in Turkey and found that there were problems related to coordination, land acquisition and use, water, operation time period, financing mix of the project, return on equity. Bardia (2004)applied Spearman’s rank correlation between liquidity and financial performance and found a positive association between the two. Narware and Sharma (2004)used ratios, correlations analysis and multiple regression analysis to study the relationship betweenworking capital and financial performance and the study reports that working capital and financial performance have both negative and positive association. Chen and Messner (2005) analysed BOT in water projects in China and found that many factors influence the capital structure and performance of these water projects.Thomas (2006)studied the risk probability and assessment framework and demonstrated in the context of critical risks in Indian BOT road projects. Dale et.al (2008) analysed infrastructure companies in the US and found that there are difficulties in understanding productivity growth because of the data revisions. Karadeniz et.al (2009) investigated the factors influencing capital structure decisions of the Istanbul Stock Exchange firms and found that a number of variables influence capital structure choice.Edward and Elizabeth (2009)observed corporate social responsibility and financial performance are positively related.  Gurbuzet.al(2010)observed the corporate governance and financial performance are positively related in Turkey.  Gnanavelu (1996) found that to increase financial performance there is a need for good financial performance and minimum borrowing. Cinca et.al. (2005) argue that size of a firm and the location of the firm impact the financial ratio structure.  Blessing and Onoja (2015) found thatcombined leverage and operating leverage have impact on financial performance.Saurabh and Sharma (2016) report that capital structure or financial leverage does not impact firm’s financial performance.Rakesh (2018) studied the determinants of capital structure and reported that financial performance, size, age, debt service capacity growth and tax shield variables are the significant firm-level determinants of capital structure. Manjunatha and Gujjar (2018a; 2018b) analyzed and found that net income of the organization is not enough to determine its efficiency unless profit margin, asset turnover, financial leverage is taken into consideration. In most of the developing countries there has been a debate on the level of efficiency of the state, public sector, and listed companies.  Kavitha and Mohanraj (2019) found that capital structure is negatively related with liquidity while it is positively related with cost of debt, size of the business, liquidity, financial performance and collateral value of asset. Manjunatha et.al (2020) found that return on equity is better in creating positive shareholders value and also found that return on sales, return on assets and assets turn over are positively correlated with ROE. Praveen and Manjunatha (2021) calculated return on equity for software and training services companies in India using three factors DuPont model and five factors DuPont model and found that there is a significant relationship between return on equity, asset turnover and profit margin. Manjunatha et.al (2020) found that found that return on equity is better in creating positive shareholders value and also found that return on sales, return on assets and assets turnover are positively correlated with return on equity.Manjunatha and Vikas (2021) found that there is a significant difference in the financing pattern and independent variables have inverse relationship with the financing pattern of selected infrastructure sectors in India.

While many studies have been conducted on determinants of financial performance of companies in the western countries, there are a few studies in the Indian context. Authors sample data used for their studies is also limited to one sector/few sectors.  Studies by Karthikeyan (2000) and Rakesh (2018) have generally supported the determinants of financial performance in India.  There is no robust conclusive evidence that whether we can use particular variables to know the determinants of financial performance in India and further Kavitha and Mohanraj (2019) suggested to use large sample for longer span of time to ascertain the relationship between financial performance of firms and liquidity, leverage, financial performance and efficiency ratios. Therefore, this study is undertaken on pharmaceutical industry of the infrastructure.  Further, the study also uses the ratios and regression analysis for getting the overall results for the pharmaceutical industry as in India.

Research Design

Objective:

We have set following objective based on the evidence of review of literature

• To test the determinants of financial performance for pharmaceutical industry in India

Data and Sample:

We use the financial data of one hundred forty-one companies in pharmaceutical industry which are listed in the Indian stock exchanges. The required secondary data of annual reports are collected from the capital market line data base and prowess data base. This study uses the annual reports and the various corporate news releases of the companies to assess the determinants of the profitability of pharmaceutical industry. The companies are selected based on two criteria: a) the companies selected should have been listed and traded in Indian stock exchanges and b) annual reports and financial statements should be available for the years 1999-2000 to 2017-2018.  The total number of companies included in this study, using the above criteria is one hundred forty-one. The profitability measures of ten dependent variables viz. a) Net Profit Ratio(NPR); b) Net Profit to Total Assets (NPTA); c) Operating Profit Ratio(OPR); d) Return on Investment (long term) ratio{ROI(LT)}; e) Return on Investment (total) ratio(ROI); f) Return on shareholders’ Equity(ROE); g) Return on Total Assets(ROTA); h) Return on Fixed Assets(ROFA); i) Retained Earnings to Total Assets(RETA) and j) Operating Profit to Total Assets(OPTA) and forty one independent variables viz. 1) current ratio; 2) liquid ratio; 3) inventory to working capital; 4) current liabilities to net worth; 5) current liabilities to total assets; 6) working capital to net sales; 7) working capital to operating expenditure; 8) cash flow to current liabilities; 9) inventory turnover ratio; 10) receivables turnover ratio; 11) creditors turnover ratio; 12) total assets turnover ratio; 13) fixed assets turnover ratio; 14) working capital turnover ratio; 15) current assets turnover ratio; 16) long term debt to equity (net worth ratio); 17) total debt-equity ratio; 18) total debt (exclusive current liabilities) to debt + equity; 19) total debt (exclusive current liabilities) to total assets ratio; 20) capital gearing ratio; 21) proprietary ratio (fixed assets/shareholders equity); 22) leverage ratio; 23) long term debt to total capitalization (book value); 24) long term debt to total asset; 25) short term debt to total debt( including current liabilities); 26) EPS ; 27) pay-out ratio; 28) price to earnings ratio; 29) book value per share: 30) price to book value ratio; 31) net fixed assets to total Assets; 32) working capital to total assets; 33) retained earnings to total assets; 34) market value of equity to book value of debt; 35) market equity or market capitalization; 36) market value of firm; 37) logarithm of sales; 38) logarithm of total assets; 39) dividend to paid up capital; 40) PBIT to total assets;  41) cash profits to sales are computed from financial statements of pharmaceutical  companies from the years 2000 to 2018 are aggregated for the pharmaceutical  industry.

Tools of analysis:

There are numerous factors both qualitative and quantitative, including the subjec­tive judgment of financial managers which conjointly determine the profitability of a firm. The main determinants of the profitability are many.  In this study we use forty-one different financial ratios to ascertain how these ratios influence the profitability of the pharmaceutical sector. We usefinancial statement analysis tools and regression for the paper. Ten ratios representing as profitability are dependent variables and forty-one ratios are taken as independent variables for pharmaceutical industry.  The following regression equations are designed to test the relationship and significance.

We usefinancial statement analysis tools and univariate regression model for the paper. We test the determinants of ten ratios represent financial performance of pharmaceutical industry as dependent variables and forty-one ratios as independent variables by following linear regressions.

         NPR        =  α_i + β_1* variable_i +e_i                                                 …1

         NPTA     =  α_i + β_1* variable_i +e_i                                  …2

OPR        =  α_i + β_1* variable_i +e_i                                             …3

         ROI(LT)  =  α_i + β_1* variable_i +e_i                                                 …4

ROI          =  α_i + β_1* variable_i +e_i                                           …5

         ROE         =  α_i + β_1* variable_i +e_i                                               …6

ROTA      =  α_i + β_1* variable_i +e_i                                            …7

         ROFA      =  α_i + β_1* variable_i +e_i                                                …8

         RETA         =  α_i + β_1* variable_i +e_i                            …9

OPTA      =  α_i + β_1* variable_i +e_i                                            …10

We present results of the regression co-efficient and their corresponding probability values (p-values) for pharmaceutical industry which results in 410 regression lines (41x10) inTables 1A & 1B.

Results and Analysis

The findings of the determinants of financial performance for pharmaceutical industry are presented in the following paragraphs.

The regression result reported in the Table 1A shows the determinants of NPR. Of the forty-one independent variables analyzed, twenty-six exhibit positive association with NPR and fifteen exhibit negative association. A positive association indicates that the independent variable has a direct relationship with NPR which means as the independent variable increases, NPR also increases. Of the forty-one independent variables analyzed, twenty exhibit a statistically significant association with NPR and thirteen exhibit statistically insignificant association. The coefficients of the six independent variables viz. working capital to net sales, working capital to operating expenditure, cash flow to current liabilities, inventory turnover ratio, logarithm of sales and logarithm of PBIT by total assets have positive and statistically significant relationship with the net profit ratio and therefore, we conclude that these variables are the determinants of the NPR.

Note: The above analysis is based on forty-one independent variables which are used as determinants of financial performance of the companies in pharmaceutical industry.  Since this is the first dependent variable taken for analysis, we have used all the forty-one variables and interpreted the results. We use only the coefficients of the independent variables which have positive and statistically significant relationship with the nine dependent variables that are taken for further analysis. The interpretation of all the independent variables is identical for the remaining nine dependent variables. Therefore, only the overall interpretation is given to save the space, ensure brevity and avoid monotony.  

Further, Table 1A shows that six independent variables viz. current liabilities to total assets, total assets turnover ratio, net fixed assets to total assets, working capital to total assets, logarithm of sales and logarithm of dividend to paid up capital are the determinants of the NPTA. The five independent variables viz. cash flow to current liabilities, inventory turnover ratio, retained earnings to total assets, logarithm of dividend to paid up capital and logarithm of PBIT by total assets are the determinants of the OPR.  The twelve independent variables viz. liquid ratio, current liabilities to total assets, working capital to net sales, working capital to operating expenditure, fixed assets turnover ratio, long term debt to equity, leverage ratio, long term debt to total asset, short term debt to total debt, retained earnings to total assets, logarithm of total assets and logarithm of dividend to paid up capital are the determinants of the ROI (LT).  The four independent variables viz. liquid ratio, fixed assets turnover ratio, leverage ratio and retained earnings to total assets are the determinants of the ROI.

Table 1B show that the nine independent variables viz. viz liquid ratio, capital gearing ratio, proprietary ratio, price to book value ratio, EPS, logarithm of sales, logarithm of total assets, logarithm of dividend to paid up capital and logarithm of cash profits by sales are the determinants of the ROE. The three independent variables viz. total debt to total assets ratio, logarithm of dividend to paid-up capital and logarithm of PBIT by total assets are the determinants of the ROTA. The six independent variables viz. liquid ratio, inventory turnover ratio, fixed assets turnover ratio, retained earnings to total assets, logarithm of total assets and logarithm of dividend to paid up capital are the determinant of the ROFA. The eight independent variables viz. liquid ratio, working capital to operating expenditure, fixed assets turnover ratio, long term debt to equity, leverage ratio, short term debt to total debt, logarithm of total assets and logarithm of dividend to paid up capital are the determinants of the RETA.The five independent variable viz. current liabilities to total assets, cash flow to current liabilities, current assets turnover ratio, retained earnings to total assets and logarithm of PBIT by total assets are the determinants of the OPTA.

Summary and Conclusion

This paper has attempted to test the determinants of financial performance for pharmaceutical industry in India. The summary and conclusions of these results are presented in this section.

1. a) We found that logarithm of dividend to paid up capital as an independent variable emerge as determinant for six dependent variables viz. NPTA, OPR, ROI (LT). ROTA, ROFA and RETA; b) liquid ratio and logarithm of PBIT by total assets independent variable emerge as determinant for four dependent variable viz. NPR, OPR, ROTA and OPTA; c) current liabilities to total assets, working capital to operating expenditure, cash flow to current liabilities, fixed assets turnover ratio, logarithm of sales, leverage ratioretained earnings to total assets as independent variable emerge as determinant for three dependent variable viz. ROI, ROFA and RETA and d) working capital to net sales, inventory turnover ratio, long term debt to equity, short term debt to total debt, logarithm of total assets as independent variable emerge as determinant for two dependent variable viz. NPR and ROTA. We conclude that logarithm of dividend to paid up capital, liquid ratio and logarithm of PBIT by total assets emerge as major determinants of the financial performance of pharmaceutical industry in India. The results of the study may be used by researchers to compare with other foreign infrastructure companies to understand the determinants of financial performance of the infrastructure industries. We have analysed only the listed companies and further studies can include unlisted companies. Further studies can be undertaken for company wise analysis and also bivariate, trivariate and multivariate regressions models may be designed for better understanding of the relationship and significance in construction industry in India and western countries.

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Tables

Table 1A: Determinants of Financial performance for Pharmaceutical Industry in India

Source:  Computed by the researcher using the ratios and fitting the simple linear regression.

Note 1: First row of the table 1 A serial number a to e represents dependent variables which are explained data and sample.

Note 2: First column of the table 1A serial number 1to 41 represents independent variables

Note 3: Second and third column of the table1A serial number i and ii indicates co-efficient and p values respectively.  Same explanation holds good for column fourth to eleventh.

Note 4: Forty second row of the table indicates the Number of positive coefficients (N+ve/  P>0.05).

Note 5: Forty third row of the table indicates the Number of negative coefficients (N –ve/  P<0.05).

Note 6: Forty fourth row of the table indicates the Number of positive coefficients (N +ve,  P>0.05).

Note 7: Forty fifth row of the table indicates the Number of negative coefficients (N -ve, P>0.05).

Note 8: Forty sixth row of the table indicates the Number of positive coefficients (N +ve,P>0.05).

Note 9: Forty seventh row of the table indicates the Number of negative coefficients (N -ve, P>0.05).

Note 10.N +ve/ P> 0.05 indicate the number of coefficients that are positive and not statistically significant, N +ve/ P< 0.05 indicate the number of coefficients that are positive and statistically significant, N -ve/ P> 0.05 indicate the number of coefficients that are negative and not statistically significant, N -ve/ P< 0.05 indicate the number of coefficients that are negative and statistically significant.  The mark * in the p-value column denotes that the corresponding coefficients of the independent variables are statistically significant at 5% level of significance. N at the top of the table represents the number of observations taken for fitting the regression and the number to the left of N represent the actual number that were taken. 

Table 1B: Determinants of Financial performance for Pharmaceutical Industry in India

Note 1: First row of the Table 1B serial number f to j represents dependent variables which are explained data and sample.

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