Online from: 2003
Subject Area: Accounting and Finance
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|Title:||Further evidence on relative and incremental information content of EVA and traditional performance measures from select Indian companies|
|Author(s):||Satish Kumar, (Department of Management Studies, Indian Institute of Technology Roorkee, Roorkee, India), A.K. Sharma, (Department of Management Studies, Indian Institute of Technology Roorkee, Roorkee, India)|
|Citation:||Satish Kumar, A.K. Sharma, (2011) "Further evidence on relative and incremental information content of EVA and traditional performance measures from select Indian companies", Journal of Financial Reporting and Accounting, Vol. 9 Iss: 2, pp.104 - 118|
|Keywords:||Economic value added, Incremental information test, Market value added, Principal component analysis, Relative information content, Return on capital employed|
|Article type:||Research paper|
|DOI:||10.1108/19852511111173086 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – The main objective of this study is to examine the claim of economic value added (EVA) proponents about its superiority as a financial performance measure compared to five traditional performance measures, i.e. net operating profit after tax (NOPAT), cash flow from operations (OCF), earnings per share (EPS), return on capital employed (ROCE) and return on equity (ROE) in Indian manufacturing sector, and simultaneously provide its empirical evidences. To achieve this, relative and incremental information content of various performance measures and their relationship with market value added (MVA) is tested and examined.
Design/methodology/approach – Principal component analysis (PCA) is one of the important multivariate methods utilized in business research for data reduction, latent variable modeling, multicollinearity resolution, etc. The present sample consists of 608 firm-year observations from the Indian manufacturing sector for the period 2000-2007. Firstly, principal component analysis (PCA) is employed to determine the important variables that explain market value. Secondly, alongside PCA, multiple regression models (OLS) are used to examine the relative and incremental information content of EVA and traditional performance measures.
Findings – These results about PCA reveal that variables like NOPAT, OCF, ROE, ROCE and EVA have maximum influence on the market value (MVA) of the sample companies, whereas EPS has a negative loading, so, EPS is discarded for further analysis. Further, the PCA loading matrix reveals that NOPAT, OCF, ROE and ROCE outscore EVA. The regression results regarding the relative information content test reveal that NOAPT and OCF outperform EVA in explaining the market value of Indian companies. The incremental information content test shows that EVA makes a marginal contribution to information content beyond NOPAT, OCF, ROCE and ROE. Overall, these empirical results about Indian companies do not support the Stern Stewart hypothesis that EVA is superior to traditional accounting-based measures in association with market value of the firm.
Originality/value – The study concludes that along with financial variables, other non-financial variables such as employees, product quality, etc., should be considered in order to capture the unexplained variation in the market value of Indian companies.
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