Eva versus Convenational Performance Measures – Empirical Evidence from India

Value based financial performance measures like Economic value added (EVA), Shareholder value added (SVA) has attracted the attention of investors, policy makers and researchers in the recent time due to their superiority and ability to reflect the true valuation of the companies. Investor’s in developing countries are shifting their attention from traditional mandated corporate performance measures like NOPAT, EPS to value based mainly to EVA in while analyzing the performance of the companies and making investment strategy. The main objective of this study is to examine whether Economic Value Added (EVA) can be used as a tool of performance measures while investing in Indian market and provide evidence about its superiority as a financial performance measure as compared to conventional performance measures in Indian companies. To achieve this, performance of the Indian listed manufacturing companies is compared with traditional mandated corporate financial performance measures used in investment analysis. Further, the present study ranks the performance Indian companies on the basis of various performance measures and suggests to investors which performance measures should be used to analyze the companies in order to make better investment decision. The results of our study revels that investor should use EVA alongwith traditional measures in firm valuation and making investment strategy INTRODUCTION The most important objective of Financial Management is the maximization of shareholders’ value. After reading this, the first question which comes to our mind is that how do shareholders know that the company to whom they have entrusted their hard earned money is efficiently utilizing it and thus, creating value for them. We have always read the annual reports of the companies to find out information about their ‘top line’ and ‘bottom line’. We also have various financial ratios for our aid like Return on Capital Employed (ROCE), Return on Net worth (RONW), Earning per Share (EPS), Dividend per Share (DPS) etc. In 1890, Alfred Marshall introduced the concept of Residual Income, which can be arrived at by subtracting the charge for the capital employed from the operating profit. In the beginning of the 1990’s, Stern Stewart & Co. came out with a modified way of calculating Residual Income suggesting accounting changes with respect to depreciation, inventory, research and development expenditure etc., for arriving at the figures of operating profit and capital employed. With this, the term – Economic Value Added (EVA) was introduced on which the firm has the copyright. Many studies have been carried out to find out whether these measures really contribute to the shareholders’ wealth. However, since EVA was introduced as an indicator for shareholders’ wealth maximization, it has been a focal point for majority of the studies. Also, many Indian companies like Infosys, Hindustan Lever, Tata Steel, Godrej etc. have adopted EVA and are disclosing it in their annual reports. This study is another attempt to find out whether EVA really explains the value accretion for the shareholders. Are we better off by removing the focus from EVA and concentrating on traditional measures like ROCE, RONW, EPS, DPS etc.? The another motivation of conducting this is to know whether should used EVA as tool of measuring financial performance while making investment based strategy or they should focus on traditional measures in valuation of Indian companies. Proceedings of ASBBS Volume 19 Number 1 ASBBS Annual Conference: Las Vegas February 2012 805 The structure of the study is as follows. First, we briefly review the literature regarding efficacy of various performance measures. The next section discusses the hypotheses developed and used in the study. Data and methodology constitute the next section. Analysis and Interpretation is discussed in the next section. Finally, we provide the research findings and discuss their managerial and theoretical implications. REVIEW OF LITREATURE Traditional performance measurement systems were developed at a time when decision-making was focused at the center of the organisation and responsibilities for decision-making were very clearly defined. According to Knight (1998, p.173) ‘these performance measurement systems were designed to measure accountability to confirm that people met their budget and followed orders’. However, during the last two decades it was widely argued that most of the performance measurement systems failed to capture and encourage a corporation’s strategy, producing mostly poor information leading to wrong decisions. They are often criticized for not taking into consideration the total cost of capital and for being unduly influenced by accrual-based accounting conventions .VBM approach, based mainly on NPV techniques, Free Cash Flow, and cost of capital, have its main objective the maximization of shareholder value. Value-based management emerged from the discipline of strategic management in the late 1970’s. Interest in value-based methods reflected disenchantment with traditional accounting earnings, although the objectives of each are different. Value-based management recognized that accounting data was no longer providing a robust insight into business performance. Valuebased methods are based on the concept that the underlying financial performance of a business is best represented by the change in its economic value. That is, the change in the net present value of its expected future cash flows. To overcome problems associated with earnings-based measures, several scholars proposed alternative theories and new (modern) performance measures. As a consequence, the Shareholder Value approach was developed in the late 1980s and early 1990s. Shareholder Value approach estimates the economic value of an investment by discounting forecasted cash flows by the cost of capital (Rappaport, 1998, p. 32). Proponents of shareholder value approach, either academics or consulting firms, grounded their analysis on free cash flows (FCF) and the cost of capital and produced a variety of such measures. The most common referred variants of those measures are: (a) Shareholder Value Added (SVA) by Rappaport and LEK / Alcar Consulting group (Rappaport, 1986; 1998), (b) Cash flow return on investment (CFROI®) by Boston Consulting Group (BCG) and HOLT Value Associates (Black, Wright and Bachman, 1998; Madden, 1999; Barker, 2001), (c) Cash Value Added (CVA) by Boston Consulting Group (BCG) and the Swedes Ottoson and Weissenrieder (Ottoson and Weissenrieder, 1996; Madden, 1999; Barker, 2001), and (d) Economic Value Added (EVA) by Stern Stewart & Co. (Stewart 1991; 1999; Ehrbar, 1998; 1999; Stern, 2001). One such model in the field of internal and external performance measurement is a trade-marked variant of residual income known as EVA (Economic Value-Added). EVA is financial performance measure that most accurately reflects company’s true profit (Stewart, 1991). EVA is the calculated after deducting the cost of equity capital and debt from the operating profits. EVA is a revised version of Residual Income (RI) with a difference the way the economic profit and the economic capital are calculated. Coined and popularized by New York based management consultancy firm Stern Stewart & Co. in 1991, EVA over the years has gained popularity as a reliable measure of corporate performance. In the later years, the concept has received recognition and support from various corporate houses; those adopted it as an internal control measure. The selling point of EVA is that it considers economic profits and economic capital in order to know the value created and destroyed by an organization during a particular period. Economic profit and economic capital is calculated by making certain adjustments into the accounting profits. The empirical studies such as Milunovich and Tsuei, 1996; O’Byrne, 1996; Uyemura et al., 1996; Biddle et al., 1997; Chen and Dodd, 1997, 2001; Bao and Bao, 1998; De Villiers and Auret, 1998; Turvey et al., 2000; Worthinton and West, 2001, 2004; Peixoto, 2002; DeWet(2005); Ismail, 2006; Kyriazis and Anastasis, 2007; Maditinos et al., 2009 have been conducted in the last two decades, initially in the developed markets like USA and later in the rest of the international market , to answer if “it is really better to use value-based than traditional accounting performance measures to measure the financial performance of corporations, or which financial performance measure best explains corporations’ change of value created and destroyed”. Recently researchers like Ismail (2008), Maditions et al. (2009) and Lee and Kim (2009) have examined the explanatory power of EVA and traditional measures. However, the results reported in the studies are quite mixed and controversial. Further in India, very less number of studies has been undertaken to test the efficacy of various performance measures particularly of value based measures. Present study aims to fulfill this gap and shall conclude whether EVA based performance measures should be used by investor while analyzing the performance of companies and designing investment strategy. Proceedings of ASBBS Volume 19 Number 1 ASBBS Annual Conference: Las Vegas February 2012 806 RESEARCH QUESTIONS This study is primarily intended to test whether a new value based measurement i.e. EVA better explains the variation in market value added (MVA) of Indian companies as compared to conventional accounting based corporate performance measures such as ROE, ROI, EPS, NOPAT, NI, OCF and RI. Also another objective is know whether investor should follow EVA based investment strategy or continues to use traditional performance measures while making investment decisions. In order to achieve this following research questions are empirically examined and analyzed:1. Does a statistical relationship between EVA and shareholder wealth exist, and if it does, how much of the variation of the shareholder value (as measured by stock returns or MVA) of Indian companies can be explained by EVA?. 2. Does EVA dominate traditional corporate performance measures such as ROE, ROI, EPS, NOPAT, NI, OCF and RI in explaining contemporaneous MVA or stock returns of Indian companies? 3. Do components unique to EVA, such as Cash flow from operations (CFO), Interest expenses (ATI), Accruals (ACC), Cost of capital (CC) and Adjustments (ADJ) help in explaining contemporaneous MVA (stock returns) beyond the explanation given by conventional performance measures? Following hypotheses are formulated to achieve the stated objective of the study:1. Economic Value Added (EVA) is significantly and positively associated with the firm's Market Value Added 2. EVA dominates conventional performance measures such as NOPAT, ROCE, ROE, and EPS etc. in explaining contemporaneous MVA. 3. Components unique to EVA help in explaining contemporaneous MVA beyond the explanation given by conventional financial performance measures such as ROCE, RONW, EPS, NOPAT, NI, OCF and RI. RESEARCH METHODS In this study panel data (or sometimes referred as pooled data) regression is used to test the research hypotheses. In the last decade or so, panel data analysis has became central in quantitative studies. Its popularity has been greatly increased among social and behavioral science researchers and it became one of the most active and innovative bodies of literature in econometrics. The main limitation of basic regression is that it is based on the assumption that parameters do not vary across sample observations. Whereas, pooled time series model (panel) allows parameters to vary in some systematic and / or random way across partitions of the sample data or even from observation to observation. The statistical models used in the study are based on the combination of earlier work of various researchers such as Biddle et al. (1997), Chen and Dodd (1997, 2000), Elali (2006), Erasmus (2008), Ismail (2006) and Kramer and Pushner (1997) etc. To achieve the various objectives of the study and to test the research hypotheses, two panel regression models are used. The data is analyzed with E-Views version 6 and SAS 9.1 software. In the present study, to test the relative and incremental information content of various performance measures, various univariate and multivariate econometric models are built and analyzed. The first model examines the association between the various corporate performance measures and the MVA. It also highlights the value relevance of the various competing corporate performance measures in explaining the firm values. To test hypothesis two and three, following models are formulated MVAit = β0+β1 EVAit+ eit MVAit = β0+β1 EPSit + eit MVAit = β0+β1 RONWit + eit MVAit = β0+β1 ROCEit + eit MVAit = β0+β1 OCFit + eit MVAit = β0+β1 NOPATit + eit MVAit = β0+β1 NIit + eit MVAit = β0+β1 RIit + eit MVAit = β0+β1 EVAit + β2 EPSit + β3 ROCEit + β4 RONWit+ β5 OCFit+ β6 NOPATit+ β7 NIit+ β8 RIit + eit The dependent variable in the above models is the Market Value Added (MVA) for the firm i and period t. The independent or explanatory variables are: economic value added (EVA), earnings per share(EPS), return on net worth (RONW), return on capital employed (ROCE), cash flow from operations (OCF), net operating profit after taxes (NOPAT), net income (NI), and residual income (RI). The entire variables in the above models are scaled by market capitalization to overcome the problem of heteroscedasticity. The Second set of models investigates whether EVA components can explain contemporaneous MVA beyond that explained by the others performance metrics. Following panel models are used and examined to find out whether EVA components can explain MVA beyond explained by other performance measures. Following Biddle et al. (1997);Worthington and West (2004) and Elali (2006), EVA is broken down into five components i.e., Cash flow from operations (OCF), Accounting Accruals (ACC), After tax interest cost (ATI), Capital Charge (CC) and Stern-Stewart Proceedings of ASBBS Volume 19 Number 1 ASBBS Annual Conference: Las Vegas February 2012 807 Accounting Adjustments (ADJ) in order to examine the contribution of each components towards explaining contemporaneous MVA as compared to other measures . The dependent variable is given as MVA. Along with this five components of EVA are used as independent variables. This model is also estimated by using the pooled ordinary least squares. MVAit = β0+β1 OCFit + eit MVAit = β0+β1ACCit + eit MVAit = β0+β1ATIit + eit MVAit = β0+β1CCit + eit MVAit = β0+β1ADJit + eit MVAit = β0+β1OCFit + β2 ACCit + β3 ATIit + β4 CCit+ β5 ADJit + eit The present study is based on secondary data. Data about various variables used in the study is mainly obtained from Prowess and Capitaline Plus databases. Since EVA figures are not published by Stern Stewart for Indian companies, the EVA values are calculated from the information available in the Prowess database using standardized financial statements. For this purpose Net operating profits after taxes (NOPAT) is used as available in the database and various adjustments as suggested in BTSS survey, 2001 about Indian companies are made in the NOPAT to arrive at economic profit figures. Economic capital of the sample companies for the period 2000-2009 is also calculated after making the adjustments suggested in the BT-SS survey about Indian companies. EMPIRICAL RESULTS Correlation Table 1 illustrates the relationship between MVA and the independent variables. The correlation coefficients thus reveal a significant association between MVA and EVA suggesting that EVA yield information that is perceived important by the stock market, a rightful claim made by EVA advocates. Nevertheless, the relationship between MVA and the EVA measure is far from perfect. A correlation of 0.4541 between MVA and EVA indicates that increasing EVA alone is not all that matters in the marketplace. As, it can be observed from the table that apart from EVA, RI and NOPAT and OCF are also highly correlated with MVA. An interesting observation from the table is that a weak correlation exits between MVA and NI and also between MVA and RONW. Highest correlation coefficient between MVA and independent variables can be observed between MVA and RI. TABLE 1: CORRELATION MATRIX MVA EVA EPS NOPAT OCF NI RI ROCE RONW MVA 1.0000