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研究生： 邱品璇
Chiou, Pin-Hsuan
論文名稱： 盈餘管理對執行長薪酬之影響
Impacts of Earnings Management on CEO Compensation
指導教授： 黎明淵
Li, Ming-Yuan
學位類別： 碩士
Master
系所名稱： 管理學院 - 財務金融研究所
Graduate Institute of Finance
論文出版年： 2011
畢業學年度： 99
語文別： 英文
論文頁數： 38
中文關鍵詞： 盈餘管理 、執行長薪酬 、裁決性應計項目 、門檻迴歸
外文關鍵詞： earnings management, CEO compensation, discretionary accruals, threshold regression
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    • 盈餘管理向來被認為是一種可以增加執行長薪酬的工具，但是過度盈餘管理卻可能對公司產生不良影響，因此，本文探討不同程度的盈餘管理是否對執行長薪酬產生不同的影響，另外，也進一步研究不同薪資的執行長，在進行盈餘管理時對其薪酬的影響程度是否不同。本文利用門檻模型檢測出盈餘管理與執行長薪酬的確有非線性的關係，根據模型結果，一般薪資的執行長，進行適度的盈餘管理有助於增加其薪資，相反的，高薪執行長過度的操弄盈餘反而會對其薪資產生不良影響。

    Most studies indicate that earnings management contributes to increasing executive compensation. This study further examines the conditional relationship between earnings management and CEOs' compensation. By investigating whether the asymmetric impact of manipulation of discretionary accruals depends on different levels of earnings management and compensation. The contribution of this study is that we confirm the conditional effects of discretionary accruals on compensation by the threshold process, where discretionary accruals are proxies for the aggregate effects of accounting choices on income. The results show that the normal level of accruals earnings management by CEOs with ordinary compensation could increase their salary and bonus pay. In contrast, excessive earnings manipulation by CEOs with high salary and bonus pay would decrease their compensation.

    Contents Chapter 1 Introduction 1 Chapter 2 Literature review 4 2.1 Executive compensation and earnings management 4 2.2 The establishment of hypotheses 6 2.2.1 The asymmetry due to the level of earnings management 7 2.2.2 The asymmetry due to the level of CEO cash compensation 8 Chapter 3 Data and sample selection 11 3.1 Sample selection 11 3.2 Accruals estimation 12 Chapter 4 Empirical Model and Methodology 14 4.1 Model specification 14 4.1.1 The non-threshold model 15 4.1.2 The single-threshold model 16 4.1.3 The double-threshold model 17 4.2 Estimation procedure 18 4.3 Summary statistics 19 Chapter 5 Empirical results 21 5.1 The non-threshold panel data model 21 5.2 Panel data model with a single threshold variable and two regimes 22 5.3 Panel data model with double threshold variables and four regimes 25 Chapter 6 Conclusions 28 References 30 List of Tables Table 1 Variable definitions 33 Table 2 Basic statistics of variables 34 Table 3 Correlations among variables 34 Table 4 Estimates of the non-threshold model 35 Table 5 Estimates of the single threshold model applying discretionary accruals as the threshold variable 36 Table 6 Estimates of the single threshold model applying cash compensation as the threshold variable 37 Table 7 Estimates of the double threshold model with two threshold variables 38

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