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研究生：	余尚恩 Yu, Shang-En
論文名稱：	三篇關於高階經理人薪酬之研究 Three essays on CEO equity-based compensation
指導教授：	黎明淵 Li, Ming-Yuan Leon
學位類別：	博士 Doctor
系所名稱：	管理學院 - 財務金融研究所 Graduate Institute of Finance
論文出版年：	2010
畢業學年度：	99
語文別：	英文
論文頁數：	105
中文關鍵詞：	高階經理人股票薪酬、盈餘管理、門檻迴歸、分量迴歸
外文關鍵詞：	CEO stock-based pay, earnings management, panel threshold, quantile regression
相關次數：	點閱：76 下載：0
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本研究的第一部分使用門檻模型來再次檢驗處於不同的公司規模條件下高階經理人股票薪酬和公司盈餘之間的非單調關係。本文使用1993到2005年間的美國非財務公司來檢驗此模型的可行性。本文的實證結果指出，當公司規模較小時，高階經理人股票薪酬和公司盈餘之間呈現正向關係，然而當公司規模較大時，兩者之間呈現負向影響關係。此外，本研究的結果也能充分解釋在過去的研究中，高階經理人股票薪酬能否增進公司盈餘的長期爭論。
本研究的第二部分檢驗高階經理人股票薪酬是否能增進公司盈餘。雖然很多過去的研究已經檢驗此重要議題，但實證結果卻是具有爭議的。因此，最近的實證研究轉而研究存在於高階經理人股票誘因薪酬和公司盈餘間的不對稱效果。因使用武斷且外生的樣本分割準則使得過去研究的推論產生混淆的結果，本研究使用門檻迴歸模型，此模型允許內生產生不同的狀態，其準則決定於兩個門檻﹕公司獲利能力高、低和高階經理人適度、過度股票誘因薪酬。本文的實證結果顯示除了高階經理人股票誘因薪酬適度的公司其高階經理人薪酬對公司盈餘呈現正相關外，對於獲利不佳的公司，其兩者的關係也是正相關。
最後，由於過去的研究對於高階經理人股票薪酬與盈餘管理之間的關係並未有一致的結論。因此，本研究的第三部份使用分量迴歸探討從1995至2006年間2463筆S&P500美國非財務公司。實證結果顯示當裁決性應計項目與取絕對值後的裁決性應計項目處於高分量狀態下，高階經理人的股票薪酬與其兩者皆呈現正相關。相較之下，當裁決性應計項目與取絕對值後的裁決性應計項目處於低分量狀態下，高階經理人的股票薪酬與取絕對值後的裁決性應計項目之間為正相關，但與裁決性應計項目之間則無顯著相關。此結果顯示若公司的財報品質不佳，高階經理人的股票薪酬越高越促成其盈餘管理的動機。然而在公司的財報品質越好情況下，給與高階經理人的股票薪酬越高的確能有效減少其盈餘管理的操作。

Firstly, the first part of my dissertation employs the panel threshold model to reexamine the non-monotonic relationship between CEO stock-based compensation and firm earnings across various firm size conditions. The feasibility of the model is tested using data for U.S. non-financial firms from 1993 to 2005. The empirical results indicate that while a positive relationship between CEO stock-based pay and earnings is presented for small-size firms, a negative impact of CEO stock-based compensation on earnings is shown when large-size firms are concerned. Further, the longstanding puzzle of whether CEO stock-based pay could enhance earnings among earlier studies could be satisfactorily explained by the empirical results.
Secondly, the second part of this study examines whether Chief Executive Officer (CEO) equity-based compensation enhance firm earnings. While lots of prior studies have examined this important issue, the empirical evidence is mixed. Consequently, recent empirical studies turn to investigating the presence of asymmetric effects involved in the link between CEO equity incentives and firm earnings. Since inferences from earlier studies may be confounded by the use of arbitrary and exogenous sample segmentation criteria, this study employs threshold regression models that allow to endogenously generate different regimes identified by the thresholds more/less profitability and moderate/excessive equity incentives. The empirical results show that not only is the positive impacts of CEO equity incentives on firm earnings more pronounced for company with the moderate level of stock incentives but this effect is also higher for those profitless firms.
Finally, prior research has not provided conclusive evidence on the association between executive equity compensation and earnings management. Accordingly, in final part of this study I investigate a sample of 2,463 observations of non-financial S&P 500 firms for the 1995-2006 period using the quantile regression (QR) approach. The empirical results show that equity compensation is positively associated with absolute and signed values of discretionary accruals when the latter two values are in high quantiles. In contrast, when the absolute and signed values of discretionary accruals are in low quantiles, equity compensation is negatively associated with absolute discretionary accruals but not associated with signed values of discretionary accruals. These results suggest that equity compensation is more likely to motivate earnings management if the firm has lower financial reporting quality. When financial reporting quality is sufficiently high, equity compensation indeed mitigates earnings management.

Table of Contents

Chapter 1 Introduction of research issues and methodologies	1
1.1 A summary of literature review	2
1.1.1 The impact of CEO equity compensation on firm performance	2
1.1.2 The impact of CEO equity compensation on earnings management	4
1.2. Methodology	5
1.2.1 The limitations of the traditional linear regression analyses	5
1.2.2 A two-step procedure	6
1.2.3 The threshold models	6
1.2.4 The quantile regression (QR) approaches	7
Chapter 2 Do large firms overly use stock-based incentive compensation?	12
2.1. Introduction	13
2.2. Empirical methods	15
2.2.1 Non-threshold model	15
2.2.2 Panel threshold model	15
2.3. Data and empirical results	19
2.3.1 Data	19
2.3.2 Threshold testing	21
2.3.3 Could CEO stock-based incentive pay enhance firm earnings?	22
2.3.4 Robustness test	26
2.4. Conclusions	27
Chapter 3 Asymmetric effects of CEO equity incentive compensation on firm earnings	37
3.1. Introduction	38
3.2. Data	39
3.3. Single threshold model with two regimes	40
2.3.1 Model specification	40
3.3.1.1 The non-threshold model	41
3.3.1.2 Panel data model with a single threshold variable and two regimes	42
3.3.2 Hypotheses establishments	42
3.3.2.1 The asymmetry due to the level of CEO stock-based pay	42
3.3.2.2 The asymmetry due to the magnitude of firm earnings	43
3.3.3 Estimation procedure	44
3.3.4 Empirical results	44
3.4. Panel data model with two threshold variables and four regimes	47
3.4.1. The model	47
3.4.2. Empirical results	48
3.5. Conclusions	50
Chapter 4 Executive equity compensation and earnings management: A quantile regression analysis	55
4.1. Introduction	56
4.2. Related Studies and research questions	60
4.2.1 Studies on equity incentives and earnings management	60
4.2.2 Development of research questions	61
4.3. Theoretical models	62
4.3.1 OLS and LAD models	62
4.3.2 QR Model	63
4.4. Sample, variables, and empirical model	66
4.4.1 Sample	66
4.4.2 Measures of financial reporting quality and equity compensation	66
4.4.3 Empirical model	68
4.5. Empirical results	69
4.5.1 Descriptive statistics	69
4.5.2 Equity compensation and absolute discretionary accruals	69
4.5.3 Equity compensation and signed values of discretionary accruals	71
4.6. Robustness tests	73
4.6.1 An alternative measure for discretionary accruals	73
4.6.2 An alternative measure for incentive compensation	74
4.6.3 Model specification with additional control variables and year dummies	74
4.6.4 The issue of endogeneity	75
4.6.5 The issue of level equation vs. first difference equation	76
4.7 Conclusions	76
References	78










List of Tables

Table 1.1 Summary of the literature on the incentive of stock-based compensation	9
Table 1.2 Summary of the literature in the impact of CEO equity compensation on earnings management	11
Table 2.2 Descriptive statistics dependent/independent variables	31
Table 2.3 Tests for threshold effects and threshold estimates	32
Table 2.4 Estimated threshold estimates and their confidence intervals	32
Table 2.5 Percentage of firms in each regime by year	32
Table 2.6 Impact of stock-based/total variable on earnings across various firm size regimes	32
Table 2.7 The test of equal mean values of the ratio and level of stock-based pay across various firm size regimes	33
Table 2.8 Tests for threshold effects and threshold estimates	33
Table 2.9 Impact of stock-based/total variable on earnings	34
Table 3.1 Definition of dependent/independent variables	51
Table 3.2 Descriptive statistics of dependent/independent variables	51
Table 3.3 Estimates of the panel data model with a single threshold variable and two regimes	52
Table 3.4 Estimates of the panel data model with two threshold variables and four regimes	53
Table 4.1 Definition of variables	88
Table 4.2 Descriptive statistics of variables	88
Table 4.3 Results from regression of absolute discretionary accruals (|DA|) on equity compensation and control variables – OLS and QR regressions at various quantile levels of |DA|	89
Table 4.4 Results from regression of signed values of discretionary accruals (DA) on equity compensation and control variables – OLS and QR regressions at various quantile levels of DA	90

 
List of Figures

Figure 2.1 Single threshold model	34
Figure 2.2 First threshold in double threshold mode	35
Figure 2.3 Second threshold in double threshold model	35
Figure 2.4 Structure of CEO compensation: Stock-based versus cash-based pay	36
Figure 2.5 Regression lines: Threshold versus non-threshold	36
Figure 3.1 Regression lines: Non-threshold vs. single threshold vs. double threshold	54
Figure 4.1 Impact of EQCOM on absolute discretionary accruals (i.e., |DA|): QR estimates with 95% confidence intervals versus OLS estimate	91
Figure 4.2 Impact of EQCOM on signed discretionary accruals (i.e., DA): QR estimates with 95% confidence intervals versus OLS estimate	91
Figure 4.3 Regression lines: Quantile versus non-quantile	92
Figure 4.4 Impact of EQCOM on discretionary accruals calculated by the Jones model: QR estimates with 95% confidence intervals versus OLS estimate	93
Figure 4.5 Impact of option/total ratio on discretionary accruals: QR estimates with 95% confidence intervals versus OLS estimate	94
Figure 4.6 Impact of EQCOM on discretionary accruals for the model with the four additional control variables and the thirteen year dummies: QR estimates with 95% confidence intervals versus OLS estimate	95
Figure 4.7 Impact of lagged EQCOM on discretionary accruals: QR estimates with 95% confidence intervals versus OLS estimate	96
Figure 4.8 Impact of EQCOM on discretionary accruals for the model in first difference: QR estimates with 95% confidence intervals versus OLS estimate	97

                                    

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