Purpose-
This study to predict the association between earnings management and
EVA, evaluated it for accuracy.
Methodology-
This study through logistic regression model (excluding OLS
regression model), Support Vector Machines and Rough Set Theory
Findings-
Empirical results show that RST model exhibited
the highest accuracy in China and Africa
nations. SVM model exhibited the
highest accuracy in Latin-America nations.
Conclusion-
Our
results provide critical implications for managers, researchers, investors, and
regulators. Managers should analyze whether
EVA motivates managers to engage in earnings management behavior. For researchers, we adopted logit, SVM and RST model to
predict effect of earnings management on economic value added;
For investors, they can analyze the true value of enterprises, regardless of
whether enterprises have adopted earnings management. Regulators (e.g.,
governments) should establish stricter security measures and laws or rules for
listed firms to prevent earnings management following a financial tsunami and to encourage them to report their “real” true
value.
Earnings management economic value added logistics model support vector machines rough set theory
Primary Language | English |
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Journal Section | Articles |
Authors | |
Publication Date | September 30, 2018 |
Published in Issue | Year 2018 Volume: 5 Issue: 3 |
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