Corporate Governance and Earnings Management by Classification Shifting

被引:86
|
作者
Haw, In-Mu [1 ]
Ho, Simon S. M. [2 ]
Li, Annie Yuansha [3 ]
机构
[1] Texas Christian Univ, Ft Worth, TX 76129 USA
[2] Univ Macau, Taipa, Peoples R China
[3] Univ Massachusetts Lowell, Lowell, MA USA
关键词
INVESTOR PROTECTION; OWNERSHIP STRUCTURE; ACCOUNTING EARNINGS; CASH FLOWS; EAST-ASIA; INFORMATION; INCENTIVES; PRIVATE; MATTER; LEGAL;
D O I
10.1111/j.1911-3846.2010.01059.x
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This study examines earnings management through classification shifting and the monitoring role played by corporate governance mechanisms in curbing such misclassification in an international setting. Employing a sample drawn from eight East Asian economies, we find that managers opportunistically shift core expenses to special items to increase core earnings and that misclassification is magnified when such shifting enables the firm to meet analyst earnings forecasts, results that are consistent with those of prior U.S. research. More importantly, our study shows that misclassification increases with the degree of the separation of ownership and control by the ultimate owners of a firm, especially when they are family members, thus suggesting that controlling shareholders mask firm performance through less visible classification shifting. We also find that stronger legal institutions mitigate the expense shifting induced by the concentrated ownership structures in East Asia and enhance the effectiveness of Big 4 auditors in curbing misclassification. Finally, our market tests indicate that investors are temporarily fooled by classificatory management at the initial announcement stage, but then unravel the quality of manipulated core earnings over the course of the subsequent year. Although managers employ the earnings management tools of expense shifting and discretionary accruals as substitutes, they are more likely to shift core expenses than to manage discretionary accruals to increase core earnings. Our results are robust to a series of sensitivity tests, which suggests that our evidence is not driven by model bias.
引用
收藏
页码:517 / +
页数:38
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