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Traditionally, the financial performance has been valued by matrices in financial statements, such as net profit, earning per share, return on investment, and return on assets, etc. This information is used by corporate managers, owners (shareholders), and investors to measure and predict current as well as future firm performance. But these traditional accounting-based performance measures are often criticized for not taking into consideration the total cost of capital and for also being unduly influenced by accrual-based accounting conventions. Due to the limits of the traditional matrices in measuring the performance, many new value based performance measures have been emerged to the performance evaluation systems since mid 80s in 20 century, such as EVA (Economic Value Added), MVA (Market Value Added), CVA (Cash Value Added), and CFROI (Cash Flow Return on Investment). EVA (Economic Value Added) emerged as the most popular value based performance measures as Peter Druker (1995) in the Harward Business Review suggest that EVA's growing popularity reflects, amongst other things the demand of the information age for a measurement of the total factor productivity.
The origin of EVA (Economic Value Added) has been tracked from Hamilton (1777), and Marshall (1890) work, who explained that to create wealth they must earn more than the cost of supplied funds. In 1920's General Motors (GM) applied this concept, and in 1950 General Electric (GE) labeled it "residual income" and applied it as performance measure to their decentralized divisions (Stewart, 1994). From the inception to till date there is growing concern debate about the validity, adoptability and superiority of the concept. The very first question arise that whether, it is internal performance measure or external performance measure. Solomon (1965) suggested that residual income be used as an internal performance measure and Anthony (1973, 1982, and 1982) suggested that it be an external performance measure.
In 1991 Stern Stewart & Company revised the computation of residual income through a series of accounting adjustments and relabeled it EVA. EVA is a measures whether operating profit is enough compared to the total cost of capital. Stewart defined (1990) EVA as net operating profit after tax (NOPAT) subtracted with capital charge.
REVIEWING the existing literature
Stewart (1991) claim that traditional measures as earning per share (EPS), return on equity (ROE), and return on investment (ROI) are misleading measures of corporate performance. But the evidence about superiority of EVA over traditional matrices is mixed and these studies can be divided in two groups: the studies carried out by EVA promoters and those carried out by academics. As stated in Lehen and Makhija (1997), "EVA is seen by its proponents as providing the most reliable year-to-year indicator of a market-based performance measure known as Market Value Added â€¦ Despite wide interest in EVA, little is known empirically about the efficacy of this measure versus other measures of performanceâ€¦ The evidence from these studies is mixed, however, and has not be resolved the debate over performance measures". Biddle (1998) suggested several reasons why EVA performs relatively poorly in comparison with earnings in explaining stock returns. The first reason is that EVA may not outperform the current realizations of other performance measures, such as earnings, in proxying for future equity, as against debt and equity, cash flows. Secondly, Stern Stewart's estimates of the charge for capital and accounting adjustments may contain measurement error relative to what the market is using to value firms. Further, most studies use Stern Stewart's publicly available database, which may not include many custom adjustments that are made for specific clients. The empirical results do not support the claim that EVA is better financial tool than traditional accounting measurement in explaining value. EVA did not significantly outperform traditional accounting measure in test of relative informational contents (Kim, 2006). Hence, both strands of this empirical literature are equally deserving of attention.
Stewart (1991), The literature relating to EVA, literally begins with the publication of the book The Quest for Value in which the author exposed his views about the usefulness of EVA as the basis of performance measurement of a company and its management at a total or a divisional level. In his empirical research he examined the informational content of EVA canvassing 613 American companies comparing two periods, namely 1984-85 and 1987-88. He found a strong correlation between EVA and MVA, which becomes more apparent when the changes in EVA and MVA are considered giving an R2 of about 97%. However, for companies with a negative EVA the association becomes less obvious, because of the increased probability of liquidation or acquisition, which sets a lower limit on the market value of these companies.
Stewart (1994) investigated the performance of the largest 1,000 American companies, he reported that the change in EVA explains 50% of the change in MVA (the remaining 50% is explained by the future EVA), whereas the change in sales explains only 10% of the change in MVA, comparing it with 15-20% of the change in earnings per share (EPS) and 35% of the change in ROE.
Peterson and Peterson (1996) analyzed traditional and value-added measures of performance and compared them with stock returns. According to their findings, traditional measures are not empirically less related to stock returns than return on capital: as result, traditional measures should be not eliminated as a means of evaluating performance, though these have no theoretical appeal. From this point of view, they rule out the possibility of value added measures not being worthwhile: since value added measures focus on economic rather than accounting profit, these play an important role in evaluating performance because managers will aim towards value creation rather than mere manipulation of short-sighted accounting figures.
Uyemura, Kantor, and Petit, (1996), a particularly interesting study for our purposes since it focuses on banking, analyzed the largest 100 U.S. bank holding companies over a period of ten years (1986- 95). By regressing changes in standardized MVA against changes in standardized EVA (defined as EVA divided by capital) and traditional performance measures, EVA was found to have the highest correlation with MVA (table 2.1).
Table 2.1 Uyemura et al., (1996) results
Source: Uyemura et al., (1996, p.99)
Chen and Dodd (1997) reported that not a single EVA measure (average EVA per share, change of standardized EVA, return on capital, capital growth and return on capital minus the cost of capital) is able to account for more than 26 percent of the variation in stock returns. Collectively the regression model containing the five EVA variables explained only some 41.5 percent of the variation in stock returns. They concluded that although EVA measures provide relatively more information than the traditional measures of accounting profit (including earnings per share, return on assets and return on equity) in terms of the strength of their associations with stock return, traditional accounting measures still have more significant information content. They also found that EVA and residual income variables are highly correlated and are almost identical in terms of association to stock return.
Biddle, Bowen and Wallace (1997), studied that whether EVA is more highly associated with stock returns and firm values than accrual earnings, and evaluated which components of EVA, if any, contribute to these associations. The results of their study of 773 large US firms indicated that earnings is more highly associated with market-adjusted annual returns than either residual income or EVA, and that all three of these measures dominate cash flows from operations . Thus, when considering the relative and incremental information content results together, neither EVA nor RI appears to dominate earnings in its association with stock market returns.
Banerjee (1997) has conducted an empirical research to find the superiority of EVA over the traditional financial performance measures. Ten industries have been chosen and each industry is represented by four/five companies. ROI and EVA have been calculated for sample companies and a comparison of both has been undertaken, showing the superiority of EVA over ROI. Indian companies are gradually recognizing the importance of EVA. Some of such companies are Ranbaxy Laboratories, Samtel India Ltd. and Infosys Technologies Ltd.
Banerjee and Jain (1998) carried out a research based on empirical data. Among the selected independent variables (EPS, EVA, Kp, Lp and ARONW) EVA has proved to be the most explanatory variable, when MVA was taken as the dependent variable and Backward Elimination Method was applied to find the most explanatory independent variable. For this purpose the time frame was of eight years and all the variables were calculated over this period for the sample companies.
Abdeen, and Haight (2000) the article compares the performance of EVA user companies with non-user Fortune 500 companies for the years 1997 and 1998. It shows that users' performance means profits as percentage of revenues, assets, and stockholders' equity were higher than the means of non-users. However, the means for 1998 earnings per share (EPS), EPS change from 1997 and EPS growth for the years 1988-1998 were lower for the EVA user companies. EVA will become less popular in its use as an instrument of control and performance evaluation. Therefore, the conclusion of this research is not in support of EVA use as a measure of value creation to stockholders.
Peixoto (2002) for a sample of 39 Portuguese companies for the period 1995-98, it was reported that the net income variable has a higher informational content than EVA and operating profits, when the dependent variable is the market value of the companies. However, EVA appeared to have a superior informational content when the dependent variable is the MVA. The latter finding implies that EVA may perform well as a measure of evaluation of management performance, when the goal is the maximization of shareholders' wealth.
Kim (2006) the sample for this study consisted of 89 publicly traded hospitality firms. Firms that did not have data for the entire period of 1995 to 2001 were eliminated from the analysis. Regression analysis tests the information content of EVA and indicates that earnings are more useful than cash flow in explaining the market value of hospitality firms. EVA itself has very little explanatory power. Incremental information content tests show that EVA makes only a marginal contribution to information content beyond earnings and cash flow. Overall, the results do not support the hypothesis that EVA is superior to traditional accounting measures in association with equity market value.
Ralph (2006) the paper is to test assertions that economic value added (EVA) is more highly associated with stock returns and firm values than accrual earnings, and evaluates which components of EVA, contribute to these associations. Thirty three non-EVA users and 75 EVA users were selected at random. Variables used in this study were revenues, profits, assets, stockholders' equity, market value, earnings per share, total return to investors, and percentage cost reduction over time. Data were collected on several metrics. The study suggests that the common and widely accepted metrics used by analysts and calculated for EVA users are not necessarily superior to that of non-EVA users. The evidence support that EVA is somewhat invalid, unreliable, and questionable.
Ismail (2006), the paper uses a sample of 2,252 firm-year observations from the UK market and applies panel data regressions to test the relative information content of EVA and other accounting measures and the incremental information content of EVA components in explaining stock return. It is found that net operating profit after tax and net income outperform EVA and residual income in explaining stock return; it was also found that accruals and operating cash flow have significant incremental information content, while the accounting adjustments of EVA proponents have significantly less contribution in explaining stock return. Yet the paper concludes that other variables must be considered in order to capture the unexplained variation in stock return models.
Dimitris and Christos (2007) studied for 121 non-financial publicly traded Greek firms covering a period of eight years, from 1996 to 2003 concluded that relative information content tests reveal that net and operating income appear to be more value relevant than EVA. Additionally, incremental information tests suggest that EVA unique components add only marginally to the information content of accounting profit. Moreover, EVA does not appear to have a stronger correlation with firms' Market Value Added than the other variables, suggesting that - for our Greek dataset - EVA, even though useful as a performance evaluation tool, need not necessarily be more correlated with shareholder's value than established accounting variables.
Maditinos, Zeljko, and Nikolaos (2009), The paper is to investigate the explanatory power of two value-based performance measurement models, Economic Value Added (EVA) and shareholder value added (SVA), compared with three traditional accounting performance measures: earnings per share (EPS), return on investment (ROI), and return on equity (ROE), in explaining stock market returns in the Athens Stock Exchange (ASE). The paper uses the Easton and Harris formal valuation model and employs both a relative and an incremental information content approach to examine which performance measure best explains stock market returns; and the explanatory power of the pair-wise combinations of one value-based performance measurement model and one traditional accounting performance measure in explaining stock market returns. For this purpose, pooled time-series, cross-sectional data of listed companies in the Athens Stock Exchange (ASE) over the period 1992-2001 have been collected and modeled. Relative information content tests reveal that stock market returns are more closely associated with EPS than with EVA or other performance measures. However, incremental information content tests suggest that the pair-wise combination of EVA with EPS increases significantly the explanatory power in explaining stock market returns.
Leong, Marco and Janis (2009), studies have shown that investment strategy using two popular metrics, the earnings price ratio (EP) and book-to-market ratio (BM) enable investors to reap abnormal returns. More recent development of another ratio, economic value-added-to-market value (EVAM) can be seen as a hybrid of EP and BM ratios. The purpose of this study is to examine whether portfolios created by utilizing the EVAM ratio will generate higher returns than portfolios formed with EP or BM ratios. There are three interesting findings. One, the EP portfolios depict results that have long been documented. That is, value stock (low price-to-earnings ratio firms) and growth stocks (high price-to-earnings ratio) exhibit the highest returns. Two, the ten BM portfolio performances are not statistically different. Three, the EVAM ratios indicate that the negative EVAM (lowest decile) portfolios exhibit the highest return and the second highest return is generated by the highest EVAM portfolio. The general results of the thirty portfolios show that the highest EVAM ratio (EVAM10) performs the best. However, the pair-wise mean differences between EP, BM and EVAM portfolios do not show statistical differences over the 1995-2004 period.
Tong, Chuang, and Xiaoke (2009), Motivated by the increased use and interest, we examine the value relevance of Economic Value Added (EVA) based on sample of Chinese logistics. Empirical evidence supports significant incremental information content of EVA compared with traditional performance measures, but the incremental information is not sufficient enough to support EVA dominating them. Nevertheless, the significant coefficients of the components of EVA give strong support for the application of EVA in logistics. So, logistics enterprises should include EVA in their evaluation system to reflect the real wealth creation for shareholders, while traditional measures still in use at the same time.
Paulo (2010), The purpose of the study is to investigate whether economic value added (EVA1) is a superior financial performance metric and creates market value added (MVA), as claimed by Stern Stewart and Company, and therefore is consistent with the purpose and intent of the UK Companies Act of 2006 and the Sarbanes-Oxley Act of 2002. If these claims can be sustained, then it could be argued that this valuation metric should form part of the Business Review, Section 417 of the UK Companies Act of 2006, and furthermore it could be an appropriate approach to the attainment of the corporate objective of the UK Companies Act of 2006, Section 172(1). There is insufficient supportive evidence to validate the claims of EVA1; furthermore, from the perspective of epistemology and sound research methodology it is not possible to make a robust case for the unqualified use of EVA in jurisdictions where the UK Companies Act of 2006 and the Sarbanes-Oxley Act of 2002 apply. Directors who make unqualified use of this financial performance metric place themselves at unnecessary risk.